decentralized finance master thesis

Decentralized Finance—A Systematic Literature Review and Research Directions

ECIS 2022 Research Papers. 25. https://aisel.aisnet.org/ecis2022_rp/25

21 Pages Posted: 28 Jan 2022 Last revised: 16 May 2022

Technische Universität München (TUM)

Isabell M. Welpe

Technische Universität München (TUM) - School of Management

Philipp G. Sandner

Frankfurt School of Finance & Management

Date Written: 2022

Decentralized Finance (DeFi) is the (r)evolutionary movement to create a solely code-based, intermediary-independent financial system—a movement which has grown from $4bn to $104bn in assets locked in the last three years. We present the first systematic literature review of the yet fragmented DeFi research field. By identifying, analyzing, and integrating 83 peer-reviewed DeFi-related publications, our results contribute fivefold. First, we confirm the increasing growth of academic DeFi publications through systematic analysis. Second, we frame DeFi-related literature into three levels of abstraction (micro, meso, and macro) and seven subcategories. Third, we identify Ethereum as the blockchain in main academic focus. Fourth, we show that prototyping is the dominant research method applied whereas only one paper has used primary research data. Fifth, we derive four prioritized research avenues, namely concerning i) DeFi protocol interaction and aggregation platforms, ii) decentralized off-chain data integration to DeFi, iii) DeFi agents, and iv) regulation.

Note: The paper is work in progress.

Keywords: Decentralized Finance, DeFi, Literature Review, Research Directions, Blockchain

JEL Classification: G23, O31

Suggested Citation: Suggested Citation

Eva Meyer (Contact Author)

Technische universität münchen (tum) ( email ).

Arcisstrasse 21 Munich, DE 80333 Germany

Technische Universität München (TUM) - School of Management ( email )

Leopoldstrasse 139 Munich, 80804 Germany ++49/89/289-24800 (Phone) ++49/89/289-24805 (Fax)

HOME PAGE: http://www.strategie.wi.tum.de

Philipp Sandner

Frankfurt school of finance & management ( email ).

Adickesallee 32-34 Frankfurt am Main, 60322 Germany

HOME PAGE: http://www.philipp-sandner.de

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A multivocal literature review of decentralized finance: Current knowledge and future research avenues

• Research Paper
• Open access
• Published: 27 April 2023
• Volume 33 , article number  11 , ( 2023 )

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While decentralized finance (DeFi) has the potential to emulate and, indeed, outperform existing financial systems, it remains a complex phenomenon yet to be extensively researched. To make the most of this potential, its practitioners must gain a rigorous understanding of its intricacies, as must information systems (IS) researchers. Against this background, this study uses a multivocal literature review to capture the state of research in DeFi. Thereby, we (1) present a consolidating definition of DeFi as we (2) analyze, synthesize, and discuss the current state of knowledge in the field of DeFi. We do so while adapting the blockchain research framework proposed by (Risius and Spohrer, Business & Information Systems Engineering 59:385–409, 2017 ). Furthermore, we (3) identify gaps in the literature and indicate future research directions in DeFi. Even though our findings highlight several shortcomings in DeFi that have prevented its widespread adoption, our literature review shows a large consensus on DeFi’s many promising features and potential to complement the traditional financial system. To that end, this paper is presented to encourage further research to mitigate the current risks of DeFi, the payoff of which will be an enriched financial ecosystem.

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Introduction

Recently, the domain of blockchain-based crypto assets and currencies has seen an increase in both attention and acceptance. Almost half of the market participants were novices when they purchased these assets in 2021, leading to a rapid and massive rise in user adoption (Lang, 2022 ). In general terms, 2021 proved to be a blockbuster with substantial growth in the crypto asset and currency market, demonstrated by the all-time high of Bitcoin (Chainalysis, 2021a ). More specifically, the past years have seen blockchain-based financial services that empower a decentralized finance (DeFi) system which gained strong momentum, so much so that the use of DeFi-based services has grown tremendously (Behrens, 2022 ; Chainalysis, 2021b ; Gramlich et al., 2022 ). This growth is reflected in, among other things, the total value of crypto assets locked in DeFi-based applications since that value quadrupled to $80 billion in early 2022 (DeFi Pulse, 2022 ). DeFi encompasses a new field that emulates traditional financial services and products in the crypto domain, such as lending and borrowing services (Buterin, 2014 ; Schär, 2021 ; Zetzsche et al., 2020 ).

It is high time, then, that DeFi is recognized as a new and rapidly growing research field at the intersection of multiple disciplines as varied as finance, law, and technology (Grigo et al., 2020 ; Zetzsche et al., 2020 ). By means of integrating decentralized infrastructure and financial applications, DeFi seeks to ensure the functionality of a financial system in a digital and decentralized manner (Schär, 2021 ; Schueffel, 2021 ). DeFi is perceived to have significant disruptive potential concerning the ways in which financial activities will be conducted in the future (Chen & Bellavitis, 2020 ; Grigo et al., 2020 ). While traditional financial activities often require trusted intermediaries, such as brokers or banks, DeFi aims to replace them with deterministic code, which is to say code embedded in such things as blockchains and smart contract protocols. This is expected to facilitate disintermediation and create a trustless environment (Buterin, 2016 ; Dai, 1998 ; Feulner et al., 2022 ; Schär, 2021 ).

However, the broad adoption of DeFi is still facing substantial challenges. Specifically, there are remaining concerns about institutional embeddedness, scalability, and general safety due to technical risks, illicit activities, and regulatory uncertainty (Chen & Bellavitis, 2020 ; Derviz et al., 2021 ; Meegan & Koens, 2021 ). Although DeFi has significant merits, it also possesses a certain complexity that can make it difficult to grasp, given its high degree of innovation, rapid development, novel technological components, and as yet unknown socioeconomic impact (Gramlich et al., 2022 ; Meyer et al., 2022 ; Zetzsche et al., 2020 ). Also worth considering is the flipside of less intermediation, i.e., the fact that individual users are burdened with more responsibility when using DeFi-based services, for example the need to store their private keys that provide access to their funds. For some users of DeFi, this increase in responsibility can mean a decrease in the convenience of using financial services (Lockl & Stoetzer, 2021 ). To mitigate this potential effect, end-users must thoroughly understand DeFi to avoid application errors or dangers. Indeed, as traditional financial institutions like asset management firms and financial technology companies (FinTechs), such as those specializing in crypto asset exchanges, embrace this emerging ecosystem, they not only provide access to DeFi-based services and instruments. They also bear significant risks (Ehrlich, 2022 ; Gramlich et al., 2022 ; OECD, 2022 ). The need for risk awareness became apparent dramatically with the recent collapse of UST, one of the largest stablecoins, valued at approximately USD 19 billion pre-crash. This shocking event resulted from a market downturn which caused a failure in the algorithm designed to keep the price pegged to the US Dollar. Due to this failure, individual and institutional investors incurred severe financial losses (Barthere et al., 2022 ). The case of UST is a prime example of the complex risks associated with DeFi and its interplay of regulatory, financial, and technical aspects. It stands to reason, therefore, that any parties engaging in DeFi-based services ought to have a keen awareness and thorough understanding of these complex interrelationships, challenges, and opportunities. Indeed, this ought to be seen as a necessity for organizations, policymakers, regulatory authorities, and individuals who wish to harness the full potential of DeFi (Gramlich et al., 2022 ; Schär, 2021 ).

While the research on DeFi is still in the early stages, particular articles published to date have done crucial pioneering work. For example, Chen and Bellavitis ( 2020 ), Zetzsche et al. ( 2020 ), Amler et al. ( 2021 ), Schär ( 2021 ), Gramlich et al. ( 2022 ), and Schueffel ( 2021 ) have focused on providing a fundamental understanding of DeFi by conceptualizing the core challenges, opportunities, applications, and functionalities of DeFi. Although this research has made a valuable contribution to the current body of knowledge, no holistic understanding of the DeFi phenomenon can be achieved without a systematic synthesis of the literature. While both Werner et al. ( 2021 ) and Bartoletti et al. ( 2021c ) have used systematizations of knowledge to collect, synthesize, and present findings on lending pools and security challenges in DeFi and draw on rigorous methodologies, they focus on specific application fields of DeFi. In so doing, however, they do not cover the full range of the literature to date and, therefore, do not provide a holistic concept of DeFi. Meanwhile, Meyer et al. ( 2022 ) have tried to provide a systematic overview of the peer-reviewed academic literature on DeFi. Yet, their exclusion of the so-called grey literature meant that they could not fully account for community-driven phenomena such as DeFi (Brennecke et al., 2022b ) and blockchain-based systems in general (Brennecke et al., 2022a ; Reijers et al., 2021 ).

Moreover, DeFi has yet to be conceptualized from multiple perspectives, particularly from a technical, regulatory, and organizational point of view (Matsuo, 2020 ). In addition, no consensus has been established in the literature regarding a common understanding of DeFi, which is to say that there is a clear need for a concise and comprehensible definition (Katona, 2021 ). Practitioners and IS researchers should be able to look to the current literature to refine their as yet partial understanding of DeFi. For example, organizations should be able to learn how to take strategic actions to adopt and develop new DeFi-enabled business models, use cases, services, and products. In doing so, they should benefit from greater efficiency and automation, as from the considerable trust promises of blockchain and smart contracts (Schär, 2021 ). Meanwhile, policymakers and regulators stand to benefit from understanding the complexities and interwoven constructs of DeFi as it should help them make the necessary decisions to create suitable regulatory frameworks that promote DeFi-based applications. Accordingly, our research draws on these premises and raises the following research questions:

RQ1: How can DeFi be defined?

RQ2: What is the state of research regarding DeFi, and how can it be conceptualized?

RQ3: Where might one find worthy future research avenues in the field of DeFi?

We conduct a multivocal literature review in response to these research questions (Garousi et al., 2016 , 2019 ). Informed by its multiple findings, we propose a concise and comprehensive definition of DeFi. This definition consolidates all prior definitions proposed in the literature, thus providing researchers and practitioners with a shared understanding when referring to DeFi. We also present a structured synthesis of the current state of research on DeFi. We analyze 79 papers in-depth and present their main contributions, all of which we catalog in a DeFi research classification framework adapted from those developed by Aral et al. ( 2013 ) and Risius and Spohrer ( 2017 ). This framework differentiates between the level of analysis (e.g., users/society and DeFi platform) and the form of activities (e.g., design/features and management/value) in the context of DeFi. This allows us to synthesize current knowledge of DeFi from both academic and non-academic works in a structured manner. Then, the special distinction of this DeFi research classification framework enables us to systematically identify gaps in the literature and propose future research opportunities for all identified sub-areas of DeFi research.

The remainder of this article is structured as follows: the “ Conceptual background ” section elaborates on traditional financial systems, blockchain technology, and decentralized financial applications. The “ Research method ” section describes our methodological approach. In the “ Results ” section, we present the findings of our multivocal literature review. Finally, in the “ Discussion and future research opportunities ” section, we discuss the essential findings in greater detail and outline avenues for future research, after which we offer our conclusive observations in the “ Conclusion ” section.

Conceptual background

To gain a rigorous understanding of DeFi, one must first refine one’s understanding of various concepts in traditional finance, blockchain, and smart contract technology. The symbiosis of these traditional financial concepts and blockchain technology has led to DeFi and will also lead to a holistic view of its multi-disciplinary complexity, the topic of this study.

The traditional financial system

A financial system connects the supply and demand of capital (Barth & Brumbaugh, 1997 ; Thakor, 1996 ). At its core is the concept of money which fulfills three essential functions in that it serves as a means of exchange, a unit of account, and a store of value (Deutsche Bundesbank, 2019 ; Smith, 1910 ). Money can be transferred within the financial system as it consists of financial markets, intermediaries, and infrastructures (Boot & Thakor, 1997 ; Deutsche Bundesbank, 2019 ; Thakor, 1996 ).

Financial markets are an elusive term for subparts of the financial system that can be differentiated due to certain financial instruments (e.g., stock market, bond market) or the maturity of a claim (e.g., money market, capital market) (OECD, 2021 ). The particular value of financial markets to the economy is that they not only provide the price discovery of assets but also provide suppliers with investment opportunities and demanders of capital with options to source funds (Fabozzi 2008 ; Wurgler, 2000 ).

While suppliers and demanders come into financial markets at the start and the end of the flow of funds, the flow itself is controlled by intermediaries (Adambekova & Andekina, 2013 ). These intermediaries provide services to mitigate transaction costs, market risks, and asymmetric information in markets (Allen & Santomero, 1997 ; Tobin, 1989 ). The most important financial intermediaries include, among others, banks, brokers, investment funds, and insurance companies. All these intermediaries can create and trade different financial instruments to match the interests at play by facilitating the channeling of funds from the supply to the demand side (Allen & Santomero, 1997 ). In doing so, intermediaries can also act as counterparts in the trading process, ensuring sufficient market liquidity. For example, as banks take deposits and grant loans on money markets, they economize the formerly expensive search for a trade partner and make it possible to match lenders and borrowers with far greater efficiency (Deutsche Bundesbank, 2019 ; Gorton & Winton, 2003 ).

As the underlying infrastructure determines how financial instruments are transferred from providers to demanders, it concerns itself mainly with the technical aspects of the financial system (Deutsche Bundesbank, 2019 ). However, since the success and proliferation of financial technology companies (FinTech), innovative financial services and products have emerged, some of which have notably refined the existing infrastructures and financial services, such as settlement services like VISA or PayPal (Drasch et al., 2018 ; ECB, 1998 ; Puschmann, 2017 ; Schueffel, 2017 ).

Once globalization picked up pace, propelled by ever-greater technological advances, national financial systems became more interconnected and moved toward a global financial system (Cerny, 1994 ). In conjunction with the increasing popularity of securitization, this interconnectedness created a significant risk as the chain of intermediaries became too complex and obscure, ultimately contributing to the escalation of the subprime mortgage crisis, and thus a triggering event of the 2008 global financial crisis (Adrian & Shin, 2010 ; European Parliament et al., 2015 ). In the aftermath, several adjustments were made to financial safeguard laws to mitigate this systemic risk (Adrian & Shin, 2010 ; Minsky & Wray, 2008 ). For this reason, the financial infrastructure of centralized finance (CeFi) is predicated on a framework of technology, laws, and regulations within which participants of the financial system can act with unprecedented safety (Deutsche Bundesbank, 2019 ; Thakor, 1996 ).

Blockchain foundations

In response to the global financial crisis, Bitcoin has emerged as the first blockchain application to facilitate a peer-to-peer (P2P) and trustless electronic cash system (Nakamoto, 2008 ). Its origin dates back to a research stream in cryptography, started in the 1990s and focused on systems that replace trust-based models with cryptography to increase the sovereignty of individuals using it (Chaum, 1983 ; Dai, 1998 ; Szabo, 1994 ). Given this origin and decentralized structure, Bitcoin is strongly associated with distrust in central authorities, such as banks or governments.

This study is particularly relevant because the Bitcoin whitepaper provides the concept for creating a distributed ledger in a decentralized system using blockchain technology (Nakamoto, 2008 ). Blockchains store transaction data in blocks that are chronologically linked with cryptographic hash functions making past transactions theoretically immutable (Butijn et al., 2019 ; Nofer et al., 2017 ). All transactions are signed on public key infrastructure to authenticate and authorize them (Beck et al., 2017 ; Hari & Lakshman, 2016 ). They are distributed through a P2P network of participating nodes, storing a copy of the blockchain to prevent single failure points (Beck et al., 2017 ; Nakamoto, 2008 ). The recording of new transactions is governed by a consensus mechanism confirming incoming transactions’ validity(Beck et al., 2017 ; Nakamoto, 2008 ; Schlatt et al., 2023 ; Zheng et al., 2017 ). By taking into account the publicly accessible transaction history, the system can prevent the multiple spending of a single asset or currency, which solves the double-spending problem afflicting other decentralized systems (Dai, 1998 ; Nakamoto, 2008 ). Due to the formal rules of the system, enforced by the consensus mechanism, transactions on a blockchain are considered deterministic (Tai et al., 2017 ; Wood, 2014 ).

Because of this determinism, a blockchain cannot query data from outside but instead requires data feeds (oracles) that mediate by reporting (on-chaining) outside information to the blockchain. As it is impossible to ascertain the veracity of this information automatically, the blockchain relies on these agents to perform their tasks with integrity. This is commonly known as the “oracle problem” (Caldarelli, 2020 ).

Aside from recording and processing transactions, specific blockchains can store protocols and execute programming code. Ethereum is one such blockchain (Buterin, 2014 , 2016 ). It benefits of protocols often referred to as smart contracts as they extend the functionality and programmability of blockchains and enable more complex decentralized applications (dApps) on the blockchains (Grigo et al., 2020 ; Varma, 2019 ). Users can interact with dApps by invoking a transaction to the smart contract’s address (Buterin, 2014 ; Szabo, 1994 ).

Decentralized finance: A blockchain-based financial system

DeFi refers to an innovative banking and financial system replicating traditional financial services and instruments while eliminating trusted centralized institutions (Buterin, 2014 ; Schär, 2021 ; Schueffel, 2021 ; Zetzsche et al., 2020 ). DeFi has the potential not only to transport the merits of blockchain and smart contracts to traditional finance but also to improve existing infrastructures, markets, services, and instruments (Gramlich et al., 2022 ; Nadler & Schär, 2022 ; Schär, 2021 ). To date, the potential for greater efficiency has yet to be delivered, as is the transformation of payment and credit information systems (Cocco et al., 2017 ; Guo & Liang, 2016 ).

As illustrated in Fig.  1 , DeFi consists of multiple layers. Blockchains that store programming code form the foundation for further DeFi layers (Schär, 2021 ). While native assets originate from the blockchain, non-native assets are often referred to as tokens implemented with smart contracts. They are provided by standardized token formats covering many cases (Buterin, 2014 ; Schär, 2021 ). The protocol layer consists of such smart contracts. They define the fundamental building blocks of DeFi, such as exchanges, money markets, derivatives, or asset management (Schär, 2021 ). DeFi applications build on, modify, and combine these building blocks to financial services and instruments. In the top layer, aggregators further combine applications to build even more specific or complex instruments, or to provide users with single entry points for multiple services (Grigo et al., 2020 ; Schär, 2021 ). In addition to smart contracts, DeFi applications and aggregators frequently offer web-based front-ends to facilitate the use of their services (Jensen et al., 2021b ; Schär, 2021 ). Owing to the standardization and modularity properties, DeFi-based assets, protocols, and applications are highly interoperable and composable, earning them the moniker of “Money Lego” (Grigo et al., 2020 ).

DeFi stack (Schär, 2021 )

The two most established DeFi-based application types are decentralized exchanges (DEXes) and lending protocols (DefiLlama, 2022 ). While there are various types of DEXes, automated market makers (AMMs) are the most common. AMMs rely on liquidity pools where users can provide liquidity to trading pairs that other users can trade against (Xu et al., 2022 ). The ratio of assets in a liquidity pool, combined with the price curve of that pool, determines the current exchange rate (Bartoletti et al., 2021b ). Furthermore, the ratio of the liquidity pool’s size to the trade’s size determines the spread caused by that trade, making the size of liquidity a critical factor for AMMs. Meanwhile, lending protocols operate very similar to money markets in traditional finance, where lenders can provide funds to receive interest. A counterpart can borrow funds against some form of collateral that they must deposit, whereupon they pay interest on the borrowed funds. Interest curves determine the interest rates for lenders and borrowers based on the supply and demand ratio (Gudgeon et al., 2020b ). To specify the collateral ratio of borrowers and liquidate them in the event that they fall short of the specified minimum ratio, lending protocols draw on external data feeds (oracles) for asset prices. Aside from these two application types, DeFi offers many other vital financial services and instruments, such as stablecoins, derivatives, and insurance coverage.

Research method

Because the research published in DeFi has been sorely lacking in both comprehensibility and systematization, this paper’s twofold purpose is to structure the knowledge accumulated in this field and then identify future research avenues. Arguably, an exclusive focus on academic literature (AL) compromises the quality of a literature review in subject areas as applied as software engineering (Garousi et al., 2016 ; Kamei et al., 2021 ). With this risk in mind, we decided to conduct a systematic multivocal literature review (MLR), as proposed by Garousi et al., ( 2016 , 2019 ). This has allowed us to supplement the standard process of systematic literature reviews (SLR), as established by Kitchenham and Charters ( 2007 ), by also considering “grey literature” (GL). GL is defined as literature “[…] which is produced at all levels of government, academia, business, and industry in print and electronic form, but is not controlled by commercial publishers” (Farace & Schöpfel, 2010 , p. 71). A beneficial side effect of including GLs is that it prevents publication bias by pooling the knowledge of academics and practitioners (Buck et al., 2021 ; Garousi et al., 2019 ). In practical terms, we first used the SLR for AL, as modeled by Kitchenham and Charters ( 2007 ). Subsequently, we reviewed GL following the process developed by Garousi et al. ( 2019 ). As a result of these measures, we obtained a predefined method of identifying all AL and GL relevant to our research questions. Figure  2 illustrates our methodological approach.

MLR item sampling and refining process

Identifying relevant academic literature

By applying the method of Kitchenham and Charters ( 2007 ), we first developed an appropriate search string. We started with an initial search on Google Scholar, using the search strings “Decentralized Finance” and “DeFi” to gain a broad overview and determine any relevant terms related to our search string. Every newly obtained term was tested concerning its quality and inclusion rate, as indeed was a variation of each search string, which led to this final search string:

(“Decentralized Finance” OR “Decentralized Finance” OR “DeFi” OR “Open Finance”) AND (“Distributed Ledger” OR “DLT” OR “Blockchain”)

We applied this search string to nine reputable databases for AL: ACM Digital Library, AIS eLibrary, EBSCO Host, Emerald Insight, IEEE Xplore, Science Direct, Springer Link, Web of Science, and Wiley Online Library. Considering all of the literature published before March 1, 2022, we identified 595 AL items.

To further refine this sample, we set stricter inclusion and exclusion criteria (Garousi et al., 2019 ; Kitchenham & Charters, 2007 ). Included was any item that (1) was available in full text, (2) was published in peer-reviewed journals or conferences, and (3) explored the concept of DeFi. Excluded was every item that (1) only briefly mentioned the concept of DeFi without contributing to the state of knowledge and every item (2) that was not available in English. Having applied these criteria in the title, abstract, and full-text screening, we were left with 49 literature items. Finally, we performed a forward and backward search to include any other relevant literature (Webster & Watson, 2002 ). We again applied our inclusion and exclusion criteria to evaluate the newly obtained set of AL. In doing so, we identified one additional item, giving us a total of 50 relevant AL items. Finally, we provide an overview of all identified AL from the MLR process and their respective IDs in Appendix 1 .

Identifying relevant grey literature

Again, we started by defining an appropriate search string for the GL. Given the insights gained in the AL search process, we concluded that the same search string was suitable for GL databases. After carefully considering the three tiers of GL with varying outlet control and credibility (Garousi et al., 2019 ), we decided to include only GL that aligns with the first tier for quality reasons.

We ran our search through Google Scholar, RePEc, and arXiv, all three of which are databases commonly used for searches of first-tier GL (Garousi et al., 2019 ). The initial search on March 1, 2022, yielded 9527 GL items. In line with this method, we chose a rule that governs when to stop the GL search, this being the sophisticated stopping criteria proposed by Butijn et al. ( 2019 ). Accordingly, we included the first eight pages of each database and incrementally evaluated items on the following pages based on inclusion and exclusion criteria. We aborted the search if less than 50% of the page was deemed relevant. Only reviews of Google Scholar yielded more than eight pages of literature.

Another critical factor when conducting a rigorous MLR is the relevance of articles based on the inclusion and exclusion criteria for GL. With this in mind, we included only GL items that met the following three criteria: (1) they could be assigned to the first GL tier of whitepapers, magazines, and working papers (Garousi et al., 2019 ); (2) their text was available in full; and (3) they explored the concept of DeFi. Conversely, GL items were excluded if (1) they only mentioned the concept of DeFi without contributing to the state of knowledge and (2) the articles were not available in English.

Once again, we performed a forward and backward search to cast our net as wide as possible, allowing us to catch omissions. This time, we identified six further GL items. Since GL does not follow a peer-reviewed publishing process, the quality can vary, which is why the MLR method applies different criteria to assess the individual quality of each item (Garousi et al., 2019 ). Using this method, we were able to set strict exclusion parameters, meaning that we excluded any item that failed to satisfy at least 10 of our 17 criteria. Appendix 2 offers an overview of our GL quality criteria. Ultimately, we obtained 29 relevant GL items for our final set. Appendix 2 also provides an overview of all GL identified in the MLR process and their respective IDs.

After sampling and refining the AL and the GL sets, we obtained a final set of 79 (50AL + 29GL) relevant DeFi literature items for a multivocal analysis.

Descriptive overview of publications

As our results indicate, DeFi is an increasingly researched phenomenon (Grigo et al., 2020 ; Schär, 2021 ). In 2020, there was significant growth in AL (+ 17) and a smaller yet still notable increase in GL (+ 7). Annual GL contributions almost doubled from 2020 to 2021, while AL saw a growth of approximately one third. Figure  3 depicts the distribution of identified literature items per year.

Distribution of DeFi publications

As is apparent in Fig.  4 , these literature items’ sources vary. While most of the AL are conference papers ( n  = 33) and journal articles ( n  = 17), the GL is more or less equally distributed between e-prints, preprints, technical reports, whitepapers, and working papers.

Types of DeFi literature items

Defining decentralized finance

While the current body of knowledge exhibits certain commonalities in understanding DeFi, the specific aspects of DeFi form a vast and varied spectrum that has so far defied consensus. The purpose of this study is to facilitate such consensus by providing a definition of DeFi that is as concise and specific as possible without contradicting any of the literature items considered in our review.

To provide the above-mentioned consensus definition, we screened all identified literature items for their definition of DeFi. We noted that 37 of 79 articles contained such a definition. Having examined each one, we disassembled them into their components. An overview can be found in Table 1 . In addition, a more extensive overview can be found in Appendix 3 and Appendix 4 , which include all the remaining aspects mentioned in some but not all definitions. Also, to be found, there are all categorized synonyms and terms.

We ran multiple iterations to derive all relevant factors and discussed our results with the team of authors. We then consolidated and abstracted individual aspects used in similar contexts. For example, “on-chain” and “distributed ledger technology” were associated with the term “blockchain.” After performing a quantitative analysis, we decided to consider only those abstract aspects mentioned in at least 25% of all definitions. This required the exclusion of certain definitive criteria mentioned by only a few authors. However, we deemed this 25% threshold necessary to establish a broad enough consensus by providing a concise and comprehensive definition of DeFi without minor caveats caused by disagreements on too specific details. This thorough and iterative process of collecting, analyzing, and synthesizing all existing DeFi definitions in the literature resulted in the following consolidated definition:

DeFi is a decentralized financial system that enables financial services and instruments to be offered and used without the need for intermediaries as the system is based on public blockchains and smart contracts.

With this universally applicable definition of DeFi, we provide a foundation for the conceptualization of DeFi literature.

State of research in decentralized finance

Since DeFi is a complex system yet to be fully understood, we recognize the importance of examining it at its various levels, which involves looking at end-users, DeFi-based platforms, technological infrastructures, and the traditional financial sector. It is also crucial to perform this examination from multiple perspectives to account for technical, regulatory, and organizational criteria (Matsuo, 2020 ). The intention of analyzing, synthesizing, and presenting the most significant DeFi research in this structured and comprehensive manner is to offer practitioners and researchers alike an easily accessible opportunity to gain a better understanding of this increasingly relevant phenomenon.

It is our contention in this study that adopting a blockchain framework to the DeFi context is advisable because DeFi is based on blockchains and allows one to capitalize on inherent similarities and peculiarities in these two domains, be they in development, implementation, or topics of research. It also allows one to organize the current research body accordingly (see Buck et al., 2021 ; Schär, 2021 ).

Therefore, our resulting framework is based mainly on the work of Risius and Spohrer ( 2017 ) who adapted the research classification framework by Aral et al. ( 2013 ) to the context of blockchain. We are aware of other pioneering research classification frameworks used in the context of blockchain, such as those of Casino et al. ( 2019 ), Rossi et al. ( 2019 ), and Hughes et al. ( 2019 ). These other frameworks have merit in classifying blockchain for individual perspectives and use cases. However, they achieve this at the price of compromising the arguably more holistic approach that can capture multiple dimensions and interdisciplinary perspectives like the technological, regulatory, or managerial, the integrated appreciation of which allows for finer granularity when classifying literature items. As such, these frameworks would appear to be inappropriate for the requirements of this project and indeed for further adaptation to a DeFi framework. Meanwhile, the framework of Risius and Spohrer ( 2017 ) provides categories for detailed classification and analysis, so much so that it incorporates the most relevant elements of other frameworks, allows for greater adaptability to DeFi-specific requirements, and provides a structure that indicates future research opportunities.

It is worth noting, then, that our research classification framework addresses two distinct dimensions: (a) activities and (b) level of analysis. The “activities” dimension looks at all the actions performed in DeFi research and groups them into three sub-dimensions. Design & Features refers to the implementation and design of concepts and their features, while Measurement & Value addresses benefits, disadvantages, and value discussions. Finally, Management & Organization covers governance, usage, and overall organization. As for the dimension “level of analysis,” this is divided into four sub-dimensions as it refers to the levels on which respective activities are performed. First, Users & Society focuses on user groups and the public. Second, the level of analysis concerning DeFi Applications deals with the smart contracts, protocols, and apps built on the blockchain for DeFi to perform. Third, Blockchain Infrastructure targets the underlying blockchain. Finally, the fourth and final sub-dimension, Financial Industry , accounts for the traditional financial industry with established firms and institutions.

Please see Table 2 for a depiction of our DeFi research framework within which the IDs of our literature elements represent the identified articles. Black font refers to AL and blue font to GL. Notably, these categories are not exclusive, meaning that articles can be assigned to multiple categories. Table 3 provides a heat map of our DeFi research framework to make the relative number of classifications apparent by showing the concentration of DeFi areas that have been explored to date. Once we acknowledge such multiple classifications for specific items, we find 133 classifications (76 AL and 57 GL classifications).

We observed a high concentration of AL and GL literature at the intersection of Measurement & Value and DeFi Applications with the accumulation of 24% of all classifications in this category. A possible explanation could be that it is particularly important to explore the opportunities and disadvantages of DeFi applications for various stakeholders to highlight the added value, mitigate risks, or develop new use cases. We also noted that academic research appeared to have a strong focus on the Management & Organization/Users & Society category (16%), owing to extensive research on governance, regulatory analyses, and law proposals. Eventually, we identified “white spots” in the dimensions of Design & Features/Financial Industry and Management & Organization/Financial Industry that have so far received nearly no attention from scholars. Accordingly, we assume that these white spots are the novelty of DeFi.

In our subsequent analysis, we followed the methodological approach of Risius and Spohrer ( 2017 ). In particular, we analyzed the current knowledge and research trends in DeFi by studying the literature and embedding it in our DeFi framework. We also identified which major topics have been covered by the literature in each respective category (see Table 4 ). For an overview of paradigmatic research questions for each category, see Appendix 5 .

Design & Features/Users & Society

Articles in this category focused on how users perceive design choices and interact with specific features of DeFi. Since the willingness of users to adopt new concepts and technologies is crucial for their advancement (Venkatesh and Davis, 2003 ), our attention has to focus on understanding why users interact with the DeFi system and how certain aspects restrict its use. Articles in this category deal with how users perceive design choices and interact with specific features of DeFi.

The main factors governing user adoption include decentralization, innovation, interoperability, borderlessness, and transparency (Chen & Bellavitis, 2020 ). In this case, however, users have to perceive a notable added value when comparing DeFi to CeFi, which requires an evaluation of whether these features provide an added value sufficient for user adoption. Further worth noting is that users, by and large, do not care about resolving trust issues in CeFi due to regulatory security and convenience. Furthermore, since average users tend to find DeFi protocols challenging in their complexity, they often need support from CeFi (Bashir et al., 2016 ; Lockl & Stoetzer, 2021 ). If we consider the concept of group interests, as introduced by Aspris et al. ( 2021 ) and Irresberger et al. ( 2020 ), we can easily recognize the different groups participating in DeFi with different interests and needs. Irresberger et al. ( 2020 ) compare DeFi platforms in adoption, scale, or security and conclude that only a few might be optimal for certain users since their demands vary concerning these different features. Users can select two options for trading tokens: a (pseudo-) anonymous and trustless, decentralized exchange (DEX) or a frequently more liquid but centralized exchange (CEX). Such liquidity is essential for those who trade larger volumes (Aspris et al., 2021 ). When obtaining tokens, Chanson et al. ( 2020 ) suggest that user-generated content, such as discussion forums and blogs, may significantly impact on trading behavior.

So far, questions about the specific requirements of DeFi and its users are mainly unanswered. Particularly interesting among these questions is which features DeFi must provide to enhance user adoption and which knowledge users must have of DeFi, its concepts, and its features to ensure successful interaction.

Design & Features/DeFi Applications

This category aims to highlight the design, features, and implementations of DeFi applications. A large share of the literature focused on the functionality and efficiency of automated market makers (AMMs). AMMs rely on arbitrageurs to balance prices with other markets, which causes suppliers certain losses in funds (Angeris & Chitra, 2020 ; Bartoletti et al., 2021b ; Pourpouneh et al., 2020 ; Xu et al., 2022 ). Liquidity providers must, therefore, be compensated. The literature is clear when it provides designs and implementations of economic mechanisms that incentivize liquidity and arbitrage (Bartoletti et al., 2021b ; Gawlikowicz et al., 2021 ).

Further research on market makers tends to focus on their interplay with price oracles, since they have to be correct for various DeFi services to perform to their full potential (Li, 2021 ). To increase the trustworthiness of on-chain data, oracles require specific features, including the correctness, availability, and accountability of data providers (Kumar et al., 2020 ). This is why Angeris and Chitra ( 2020 ) introduced the concept of constant function market makers (CFMM), their purpose being to overcome the oracle problem and synchronize on- and off-chain prices of assets. Meanwhile, Bahga and Madisetti ( 2020 ) introduced a value token transfer protocol (VTTP) to facilitate intra- and inter-chain transfers of crypto assets. Further advances were made when Lipton and Hardjono ( 2021 ) proposed AMMs for intra-chain transfers on the one hand and on the other hand gateways and atomic swaps for inter-chain transfers, which facilitates flexible transfers of crypto assets. However, this mechanism requires the atomicity of transactions, consistency of ledgers, isolation of the asset, and durability of commitment. Therefore, Rius and Gashier ( 2020 ) introduced a concept for on-chain forward contracts using smart contracts with full collateralization that relies on a price oracle, feeding a contract the final price on expiry.

Since those participating in DeFi are not clearly identified, they cannot acquire a good reputation, nor can loans be trust-based. Instead, they require over-collateralization (Bartoletti et al., 2021a ; Kroon et al., 2021 ), indicating capital inefficiency (Tien et al., 2020 ). Assets locked as collateral should be supplied to money markets to accrue interest and eliminate these opportunity costs and capital inefficiencies. Also feasible is a mechanism to provide locked collateral to money markets in case of an imminent liquidity crisis (Tien et al., 2020 ). Another potential approach includes using self-sovereign identity (SSI) to remove over-collateralization by assigning digital identities to the credit histories of users (Kroon et al., 2021 ).

To deal with smart contract flaws and programming errors, Perez and Gudgeon ( 2022 ) propose “dissimilar redundancy” as these could play a part in reverting transactions if bugs occur or attacks are made on programmatic flaws. This, however, incurs significantly higher developmental and operational costs (Perez & Gudgeon, 2022 ). An additional risk on the application layer, as identified by Jensen et al. ( 2021a ), is the re-centralization of application governance that results from a concentration in the distribution of governance tokens.

Further research is needed on whether these re-centralization risks can be mitigated using an adapted protocol design. Also in need of further research are the design and features of DeFi applications, as many of them remain afflicted by considerable problems. Two of the most frequently asked research questions are how DeFi applications can be protected against vulnerabilities and interdependencies with other protocols and how certain market inefficiencies can be mitigated, such as the need for over-collateralization.

Design & Features/Blockchain Infrastructure

In this category, the design and features of the blockchain are discussed in terms of the underlying infrastructure that enables DeFi applications. The literature elaborates on many features, including transparency (i.e., public verifiability of code and events), self-custody, pseudonymity, atomicity of transactions, transaction order malleability, transaction fees, availability of service, and anonymous development (Qin et al., 2021a ). Further features include decentralization, interoperability, borderlessness, and a deterministic consensus to prevent double-spending (Amler et al., 2021 ; Chen & Bellavitis, 2019 ).

While transparency is often perceived as a positive aspect, it facilitates attacks on transactions (Galal & Youssef, 2021 ; Zhou et al., 2022b ). Such attacks can take the shape of frontrunning, back running, sandwich attacks, replay attacks, and clogging, all of which rely on specific transaction orders that the block proposer in the network (e.g., miners or validators) can control (Qin et al., 2022 ; Zhou et al. 2022b ). According to Qin et al. ( 2022 ), there is early evidence of miners exploiting this power, denoted as maximum extractable value (MEV), either by themselves or by forming private agreements with others. The authors conclude that such agreements weaken blockchain consensus protocol security and that miners gain an unaccountable amount of influence through private agreement practices, which can lead to centralization. This assumption is reinforced by Aponte-Novoa et al. ( 2021 ) who found an increased concentration of hash rates in the hands of a few miners and called for a consideration of this discovery in all future designs of security protocols. These attack vectors are amplified due to the composability of DeFi applications because when protocols build on each, these weaknesses are inherited (Li et al., 2021 ).

To tackle the increasing challenge of interoperability between blockchains in the DeFi ecosystem, atomic swaps have been introduced. These are sequences of conditional transactions that transfer assets from one platform to another (interoperability) and can only fail or succeed as a whole (atomicity) (Han et al., 2019 ). In accordance with analyses in Measurement & Value/Blockchain Infrastructure , Han et al. ( 2019 ) pointed out that the atomic swap in its original form is less of a swap and more of a financial option, being unfair to one participant without an associated premium. Related concepts include “Atomic Bonded Cross-chain Debt” (ABCD), as proposed by Tefagh et al. ( 2020 ), that can be used for arbitrage transactions or that of Lipton and Hardjono ( 2021 ), who take advantage of gateway nodes for each blockchain and a gateway-to-gateway asset transfer. With this in mind, atomicity is often seen as a trait necessary to facilitate interoperability.

As our results indicate, scalability issues can compromise DeFi functionality (Amler et al., 2021 ; Brühl, 2020 ). One way of resolving this blockchain scalability issue, as Zhao et al. ( 2021 ) have shown, is to use a block synchronization protocol that only stores hashes, instead of the entire transaction data, resulting in higher transaction throughput. Indeed, in the case of Ethereum, it increased this throughput by an average of 83.55%.

To ensure that centralized entities engage in less malicious behavior concerning asset custody, Huili et al. ( 2021 ) designed a dynamic threshold elliptic curve digital signature algorithm (ECDSA) that requires the agreement of multiple custodians before assets can be transferred. Additionally, the proposed signature scheme supports adding and removing custodians from the custody procedure.

While the literature has highlighted the benefits and drawbacks of DeFi and blockchain being transparent, it remains unclear how much transparency is beneficial and on which layers this may be the case. This also raises the question of how much transparency is sustainable in DeFi if certain deficiencies are to be prevented, such as transaction order malleability. Furthermore, new technological paradigms like zero-knowledge proofs (ZKPs) require in-depth research to reconcile transparency and privacy trade-offs (Guggenberger et al., 2022 ). Aside from further research, there is also a clear need for technological advances in blockchain scalability. Our literature analysis identified scalability challenges among the key factors limiting DeFi functionality and adoption.

Design & Features/Financial Industry

DeFi offers financial services in a P2P network, which has implications for the financial industry. Work in this category covers concepts, designs, and features with the potential to make DeFi disruptive for traditional financial firms and institutions. The financial services that can be performed in DeFi comprise lending and borrowing, market-making, exchange of assets, payment services, contracting, portfolio management, insurance, and fundraising (Chen & Bellavitis, 2019 , 2020 ; Derviz et al., 2021 ; Katona, 2021 ; Qin et al. 2021a ). As Katona ( 2021 ) has found, however, DeFi does not yet offer the full range of CeFi services, while Qin et al. ( 2021a ) have noted specific services like flash loans only exist in DeFi. At this point, it is fair to say that DeFi is suited to certain financial services with rather promising features, including, for example, composability, decentralization, interoperability, transparency, automation, and transaction finality (Meegan & Koens, 2021 ); (Qin et al. 2021a ). It is also worth pointing out that frequently advertised features of DeFi include the provisioning of banking services for underbanked regions and the prevention of risks historically associated with centralized financial systems, the circumvention of regulatory bans, and more general benefits precipitated by financial innovation (Derviz et al., 2021 ).

Of further interest is that the identified financial features overlap with their technical counterparts Design & Features/Blockchain Infrastructure . Although DeFi promises improvements in the provision of financial services, various downsides have emerged (Meegan & Koens, 2021 ). The (pseudo-)anonymity and decentralization of wallet owners impede the enforcement of regulatory measures, chief among them the know-your-customer (KYC) checks and compliance with anti-money-laundering (AML) laws (Qin et al. 2021a ). It is apparent, then, that transparency is not only considered a trade-off regarding privacy rights (Meegan & Koens, 2021 ). In addition, it harms financial transactions, as discussed in Design & Features/Blockchain Infrastructure (Qin et al. 2021a ). However, transparency and regulatory uncertainty pose considerable challenges to adopting DeFi in the traditional financial service industry.

Although the literature has been clear on the point that DeFi has a problem with regulatory compliance, it has yet to answer the two urgent follow-up questions: how can this problem be resolved, and which role can transparency play in ensuring regulatory compliance? Unfortunately, further uncertainty surrounds DeFi and businesses’ requirements to support the creation of use cases and increase user adoption.

Measurement & Value/Users & Society

In this category, we cover the benefits and disadvantages of using DeFi, as experienced by individual users and broader society. We also provide an evaluation of these issues. As the literature has already broadly acknowledged, DeFi has the potential to create fundamental shifts in the economy, so much so that it could lead to a new financial paradigm (Bennett et al., 2020 ; Chen & Bellavitis, 2020 ; Katona, 2021 ; Schär, 2021 ; Schueffel, 2021 ). Then, DeFi is associated with many value propositions, including reducing transaction costs, financial inclusion and self-sovereignty of users, increased efficiency, and a high degree of innovation. However, it has also been noted that the value propositions of CeFi and DeFi can overlap. Where this is the case, DeFi has specific risks that exceed traditional financial risks, and these can impair DeFi’s value (Amler et al., 2021 ; Bennett et al., 2020 ; Carter & Jeng, 2021 ; Katona, 2021 ; Qin et al. 2021a ; Schär, 2021 ; Schueffel, 2021 ). These DeFi-specific risks can be classified as blockchain infrastructure, protocol, market, and other risks.

One substantial risk affecting blockchain infrastructure concerns its scalability. In other words, a blockchain network may suffer from limited throughput, which increases transaction costs and compromises accessibility (Amler et al., 2021 ; Carter & Jeng, 2021 ; Katona, 2021 ; Schär, 2021 ; Schueffel, 2021 ). In addition, there is the risk that transaction attacks increase price slippage and extract value, also known as MEV. To complicate matters further, consensus failures can occur, which can harm the security of the blockchain infrastructure and the integrity of the data (Carter & Jeng, 2021 ; Qin et al., 2022 ). Another risk affecting blockchain infrastructure is the violation of privacy rights, since transaction data is publicly available (Amler et al., 2021 ; Carter & Jeng, 2021 ; Qin et al. 2021a ; Schär, 2021 ). To showcase this risk, Hickey and Harrigan ( 2021 ) have demonstrated the feasibility of mapping real-world identities to blockchain addresses at a DEX through platform engagement. Meanwhile, Wang et al. assessed the anonymity of specialized privacy services like mixers. Based on their assessment, they concluded that specific user behavior could negatively affect privacy and possibly allow inferences to be made about personal information.

Moving on to protocol risks, it has to be noted that these include protocol dependencies, manipulations, and re-centralization, all of which can result in losses for users interacting with the protocol (Amler et al., 2021 ; Carter & Jeng, 2021 ; Katona, 2021 ; Qin et al. 2021a ; Schär, 2021 ). Since protocol dependencies result from composability, they refer to the risk of one protocol being influenced by another (e.g., oracles). On the other hand, protocol manipulations include technical and economical design errors that could be exploited. In contrast, re-centralization refers to admin keys of protocols that offer backdoors for emergency takeovers. The associated risk is that these could be used maliciously, whereupon decentralization would be jeopardized, so much so that it might lead to governance takeovers.

At the market level, there are risks of market manipulations, illiquidity, volatility of assets, and re-centralization (Amler et al., 2021 ; Carter & Jeng, 2021 ; Chen & Bellavitis, 2020 ; Katona, 2021 ; Qin et al. 2021a ). Market manipulations include price oracle attacks, pump and dump arbitrage, and other frauds where the profit of the tamper comes at the expense of the remaining users. Illiquidity refers to markets draining out and limiting access to financial markets and funds. The volatility of assets compromises individual financial transactions and wider adoption since they do not represent a store of value or stable means of exchange. Re-centralization on the market refers to entities obtaining central positions of critical importance, whereupon they can jeopardize decentralization as they represent single points of failure.

In addition, DeFi is beset by risks concerning limited adoption, usability, and dependency on CeF, and regulatory uncertainty, enabling illicit activities (Amler et al., 2021 ; Bennett et al., 2020 ; Carter & Jeng, 2021 ; Chen & Bellavitis, 2020 ; Katona, 2021 ; Qin et al. 2021a ; Schär, 2021 ; Schueffel, 2021 ). The first in that list of risks, regulatory uncertainty, is because there are no regulatory rules or guidelines on DeFi. This, along with the (pseudo-)anonymity and decentralization of DeFi, opens the door to illicit activities. The risks of limited adoption and usability are predicated on the currently rather limited network effects and user-friendliness of DeFi. As for the risk of dependency on CeFi, this is routed in the requirement for centralized financial intermediaries without whom there has been no prospect of real-world business applications of DeFi.

Since the literature to date has mainly focused on the risks associated with DeFi, further research is required to examine the extent to which users need DeFi and whether its value propositions will be born out in the long term. Another worthwhile research endeavor would appear to be a close analysis of the convergence of DeFi and CeFi.

Measurement & Value/DeFi Applications

When we consider the baseline requirements for DeFi to function, the critical question arises whether DeFi protocols, services, and markets are secure and efficient. To answer this question, the literature assigned to this category shares a common concern for the efficiency, manipulability, and vulnerabilities of DeFi applications.

As we have seen in Design & Features/DeFi Applications , certain types of DeFi applications are inefficient. For instance, AMMs are inefficient in that they rely on external arbitrageurs to synchronize asset prices with primary financial markets, which results in losses for liquidity providers that have to be compensated in the form of interest rates or service fees (Angeris & Chitra, 2020 ; Pourpouneh et al., 2020 ). As we have learned from the efficiency level analysis conducted by Pourpouneh et al. ( 2020 ), AMMs work exceptionally well for assets with high liquidity and low volatility. Indeed, they are essential in facilitating automatic market-making, fast trades, and forming a building block of DeFi applications. In times of high use, the interest models of lending protocols are the primary mechanism to incentivize liquidity. In contrast, in times of low use, they perform this function to incentivize borrowing (Qin et al., 2021b ), but in times of illiquidity, when suppliers are unable to withdraw funds, they fail to do so (Gudgeon et al., 2020a ; Gudgeon et al. 2020b ). This happens across different protocols with distinct interest rate curves. Furthermore, as Gudgeon et al. ( 2020b ) have found that borrowing rates of different lending protocols affect one another, which indicates that participants are incentivized to switch between low- and high-yield assets and platforms.

Overall, the market efficiency of various DeFi applications has increased, particularly since the introduction of governance tokens. For example, in lending protocols like compound finance, users enter increasingly lower collateralization ratios, increasing capital efficiency and the risk of liquidations (Gudgeon et al. 2020a ; Gudgeon et al. 2020b ; Perez et al., 2021 ). It is worth noting that this bears the risk of selling unnecessarily high amounts of borrowers’ collateral (Qin et al. 2021b ).

Regarding market manipulation, the literature highlighted wash trading, the technical term for the simultaneous buying and selling an asset to create artificial market activity. As Victor and Weintraud ( 2021 ) have found, wash trades have declined since the introduction of AMM-based DEXes, yet quite a strong incentive to continue the practice remains. For NFTs, however, wash trading may be less common than expected, which is thought to be due to high transaction fees (Wachter et al., 2022 ).

By examining various protocol risks, Carter and Jeng ( 2021 ) have identified interconnections with traditional financial systems as a further risk category. For instance, custodial stablecoins present a potential point of failure as centralized institutions hold reserves (Carter & Jeng, 2021 ). In contrast, non-custodial stablecoins are vulnerable to price oracle and MEV attacks, smart contract vulnerabilities, protocol dependencies, and hostile governance takeovers (Klages-Mundt et al., 2020 ). While algorithmic governance is highly susceptible to oracle attacks, agents’ governance re-introduces counterparty risk based on trust. Governance by decentralized voting focuses less on the system’s stability and more on maximizing profits (Brennecke et al. 2022a ). As a sub-group of non-custodial stablecoins, stablecoins pegged by on-chain collateralization are more resilient and secure when they use a native asset, such as Ether, and so long as the protocol manages the volatility (Carter & Jeng, 2021 ; Klages-Mundt et al., 2020 ; Schär, 2021 ). Having processed these findings, Brennecke et al. ( 2022a ) suggested that the research scope ought to be widened to “real-world” collaterals, e.g., the use of non-fungible tokens (NFTs) to tokenize real estate, which then could be used as collateral in cryptoasset-backed stablecoins for improved volatility reduction. In general, however, stablecoins are an essential and valuable component of the DeFi ecosystem, commonly used to create price stability for other crypto assets or fiat currencies (Schär, 2021 ; Schueffel, 2021 ).

DeFi relies on the integrity of internal and external data. Yet, since this is provided by platforms (oracles), there is a risk that it may be altered through manipulation or dysfunction (Xu et al., 2022 ). The alteration of provided results, also referred to as the oracle problem, is perhaps best dealt with in separate technical (e.g., code flaws) and social dimensions (e.g., misaligned incentives) (Caldarelli & Ellul, 2021 ). Centralized oracles are protocols for on-chain information controlled by a single agent. In contrast, consensus oracles present decentralized voting protocols in which a group of agents agrees on the state of the network. Oracles are essential intermediaries between blockchain systems and the real world (Bartoletti et al., 2021a ; Caldarelli & Ellul, 2021 ; Xu et al., 2022 ). For instance, oracles used in lending pools are key to feeding the prices of assets (e.g., collateral) into the protocols. Furthermore, AMMs can act as decentralized oracles but are vulnerable to flash loans and arbitrage attacks (Bartoletti et al., 2021a ; Xu et al., 2022 ). While custodial stablecoins do not require oracles, non-custodial stablecoins, like lending protocols, rely on price feeds of collaterals and the discovery of the collateralization ratios (Caldarelli & Ellul, 2021 ). With regard to financial derivatives, oracles are used for feeding data across DeFi platforms (Caldarelli & Ellul, 2021 ).

However, rather than merely skip past the afore-mentioned protocol risk in passing, let us take a brief moment to consider how flash loans jeopardize DeFi applications. Having analyzed profit-generating transactions across the intertwined protocols in DeFi, it has been shown by Zhou et al. ( 2022a ) and Qin et al. ( 2021c ) that most of these attacks are enabled by flash loans which reduce the required capital to conduct such attacks. Also worth noting is the fact that AMMs are often targeted because they act as decentralized price oracle for other protocols, making it possible to manipulate asset exchange. Furthermore, there is a trend of pump attacks focusing on low liquidity asset pairs. Thus, the size of the liquidity pool of AMMs determines the level of market security against such attack rates (Cao et al., 2021 ), and as extensive research has shown, the major contributing factors of these attacks are the composability and transparency of DeFi applications (Cao et al., 2021 ; Qin et al. 2021c ; Wang et al., 2021a ; Zhou et al. 2022a ).

As the complexity of DeFi has significantly increased, for instance, in the composability and wrapping process (i.e., supply of assets of one protocol to another), it opens up notable attack vectors on DeFi protocols (Caldarelli, 2022 ; Guggenberger et al., 2021a ; Tolmach et al., 2021 ). The complex wrapping process across different protocols could indicate deep DeFi integration of an asset, which incurs additional risk (Caldarelli, 2022 ; Wachter et al., 2021 ). Moreover, the ownership of governance tokens is largely concentrated, which poses a risk to the democracy of the DeFi ecosystem (Amler et al., 2021 ; Jensen et al., 2021a ; Wachter et al., 2021 ).

Whether DeFi growth is sustainable in the long run will be determined by the adoption and speculation of DeFi applications (Nadler & Schär, 2022 ; Silberholz et al., 2021 ). Since the DeFi boom, speculation on CEXes has declined and transferred to DeFi protocols, e.g., on-chain derivatives or DEXes. DeFi has a “crowding-out effect on both token utility and exchange-based speculation,” driven by the fact that both take up the infrastructure’s limited block space (Silberholz et al. 2021 ). Investors take more significant risks when the primary use of DeFi protocols is the speculation of tokens and their “yield farming” functionality, which is enabled by the high composability and wrapping of assets (Liu et al., 2020 ; Saengchote, 2021 ). However, the risk management of DeFi systems lacks scientific guidance and requires traditional financial risk assessment practices to increase their security and stability (Liu et al., 2020 ). In this context, DeFi bubbles originate mainly from DeFi protocol tokens, e.g., MKR (a governance token issued by the MakerDAO protocol) or LINK (a native token of the blockchain oracle project, Chainlink). To a lesser degree, however, they also originate from the underlying blockchain’s native assets, indicating that DeFi tokens are mainly separate assets with linkages to the native assets (Corbet et al., 2021 ).

To date, research in this field has generally focused on the risks and value propositions of different DeFi application areas that affect the ecosystem. What remains at large, however, are suggestions or solutions that maximize or maintain the value proposition of DeFi applications while minimizing their inherent risk. To remedy this, IS scholars could, for instance, design flash loans so that they pose no threat to DeFi, AMMs, or lending protocols. They would also do well to focus on making them resistant to flash loan attacks. Further research is necessary to improve the classification of DeFi wrapping processes. Indeed, a rigorous examination of the value propositions, importance, and drawbacks of wrapping processes regarding capital efficiency is essential if we are to reliably weigh the advantages of wrapping processes against the additional risks that arise from them.

Measurement & Value/Blockchain Infrastructure

At this level of analysis, we look at comparisons of various blockchain platforms for DeFi (Carter & Jeng, 2021 ; Irresberger et al., 2020 ). We also consider how the transfer of value between different blockchains has been covered (Bahga & Madisetti, 2020 ; Han et al., 2019 ; Lipton & Hardjono, 2021 ; Wang et al., 2021b ).

To date, no blockchain platform has demonstrated that it can achieve adoption, scalability, and security (Irresberger et al., 2020 ). The Ethereum blockchain, however, is the dominant platform for DeFi applications because it provides complex financial instruments. In contrast, the Bitcoin blockchain is of no value to most DeFi users due to its limited functionalities. With regard to performance, the transaction throughput of DeFi blockchains is lower than it is with traditional finance settlement methods, such as VISA. In addition, the underlying blockchain poses a systemic risk to DeFi due to MEV, consensus failures, miner centralization, and flaws in code, as discussed in Design & Features/Blockchain Infrastructure (Carter & Jeng, 2021 ; Irresberger et al., 2020 ).

As Bahga and Madisetti ( 2020 ) have found, existing blockchain platforms lack interoperability and ways of transferring value between one another. A potential solution has already been suggested in Design & Features/Blockchain Infrastructure : atomic swaps. From an economic perspective, however, atomic swaps have been deemed unfair (Han et al., 2019 ; Wang et al. 2021b ) due to their optionality (see Design & Features/Blockchain Infrastructure ). Besides, as Lipton and Hardjono ( 2021 ) have pointed out, other technical problems mean that atomic swaps are only feasible between similar blockchains, e.g., public-only or permissioned-only. It is fair to conclude that considerable hurdles are yet to be overcome on the way to blockchain interoperability. It is certainly encouraging that Lipton and Hardjono ( 2021 ) have taken a brief first look at private and permissioned blockchains, yet, to date, these blockchains and their usage for DeFi remain largely unexplored.

Measurement & Value/Financial Industry

Here, the analysis of DeFi focuses on its value to institutions and businesses in the traditional financial ecosystem. Considering the ambitions and background of DeFi, an important question that the literature in this category should answer is whether DeFi will replace the traditional financial system or how these two systems will affect one another.

Every study included in this category connects DeFi to Bitcoin. This is due to perceived commonalities regarding their raison d’être, the fading trust in banks, and their shared goal to decentralize financial services and intermediation (Chen & Bellavitis, 2020 ; Derviz et al., 2021 ; Grassi et al., 2022 ; Katona, 2021 ). In this context, distrust in banks is coupled with the suspicion that intermediaries do not act in the user’s best interest. This is known as the principal-agent problem. As mentioned in Design & Features/Users & Society , there is a risk that users do not trust DeFi. This can get in the way of adoption. Furthermore, the convenience of using CeFi services will prevent major shifts from centralized to decentralized systems, as evidenced by the fact that DEXes are mainly on-ramps for smaller projects to regulated CEXes with higher trade volumes. In contrast, CEXes play a gatekeeper role by certifying the quality and credibility of different projects, indicating user segmentation between these two types of exchanges (Aspris et al., 2021 ). However, transferring assets to a CEX means relinquishing control and raising security issues (Aspris et al., 2021 ; Huili et al., 2021 ). A potential solution might be integrating DeFi into an institutionalized setting, as this might foster trust while keeping control of assets. DeFi applications would focus its value proposition more on interoperability and high convenience for customers than disintermediation (Lockl & Stoetzer, 2021 ).

It is worth remembering that it is a core purpose of DeFi to replicate all traditional financial instruments and services in a decentralized and digitalized manner (Grassi et al., 2022 ; Kumar et al., 2020 ). In assessing this purpose, the literature has formulated four major business models of DeFi: decentralized currencies, payment services, fundraising, and contracting. All four are intended to fix the afore-mentioned issues of CeFi services (Chen & Bellavitis, 2020 ; Schueffel, 2021 ).

Decentralized currencies are conceived to control the devaluation and inflation issues of fiat currencies (Chen & Bellavitis, 2020 ; Derviz et al., 2021 ; Kumar et al., 2020 ; Qin et al. 2021a ). However, as Qin et al. ( 2021a ) have argued, well-managed inflation is required to keep a financial system scalable to growing demands and future economic activities. Meanwhile, the decentralized payment service constitutes cost-reducing and borderless P2P payments between parties, which could enable new business models based on micropayment (Chen & Bellavitis, 2019 ; Schueffel, 2021 ). However, it remains to be seen whether the transaction costs of DeFi applications can be reduced substantially, as they are subject to blockchain scalability (Katona, 2021 ; Meegan & Koens, 2021 ). The other DeFi business model, decentralized fundraising, is based on the potential to raise funds for a project via DeFi applications. Fundraising through ICOs and Initial Exchange Offerings (IEOs) is particularly valuable if a token represents an inherent utility for a DeFi project (Arnold et al., 2019 ; Chen & Bellavitis, 2019 ). As for decentralized contracting, this business model is also known as decentralized autonomous financial intermediation, for instance, in the form of lending or borrowing. On a cautionary note, however, it is worth pointing out that while this is believed to have the potential to keep costs in check and turbocharge innovations, the deposited assets are not protected by traditional financial laws, such as the deposit guarantee act (Derviz et al., 2021 ; Meegan & Koens, 2021 ; Qin et al. 2021a ; Xu & Vadgama, 2021 ). With this significant risk in mind, Meegan and Koens ( 2021 ) and Xu and Vadgama ( 2021 ) have cast doubt on whether DeFi protocols fulfill the role of banks. Derviz et al. ( 2021 ) proposed using central bank digital currencies (CBDCs) as reserve-backed stablecoins to bridge traditional finance with fiat currencies and DeFi with cryptocurrencies. This proposal to bridge DeFi and CeFi on re-centralized points in DeFi to tackle its issues with trusted traditional financial institutions is supported by multiple other scholars (Meegan & Koens, 2021 ; Qin et al. 2021a ; Schueffel, 2021 ; Zetzsche et al., 2020 ).

Indeed, we have found a general consensus in the literature amassed in this category that DeFi is unlikely to replace traditional finance. There is also, however, a multi-faceted appreciation of DeFi as a system, many features of which hold significant promise for the financial industry, which is why many scholars expect that both systems will most likely coexist and learn from each other (Chen & Bellavitis, 2020 ; Derviz et al., 2021 ; Grassi et al., 2022 ; Meegan & Koens, 2021 ; Qin et al. 2021a ; Schueffel, 2021 ). While research in this area has highlighted differences in the value propositions of CeFi and DeFi, no specific guidance has been forthcoming on when it may be sensible to use either DeFi or CeFi services. A similar lack of clarity can be found in the as yet hardly conducted analysis of how both systems’ development may follow similar trajectories and how particular learnings from the traditional financial system may apply to DeFi. Furthermore, although scholars agree that distrust in the traditional financial system is a driving force behind the development and adoption of DeFi, rather like in the case of Bitcoin, the pressing question is whether DeFi applications and their assets can act as a hedge against the traditional financial system remains unanswered.

Management & Organization/Users & Society

In this category, we looked at the literature through the lens of managerial and organizational aspects of DeFi concerning users and society. This explains the focus on work done by regulators and lawmakers. Considering the previous findings in Measurement & Value/Financial Industry , we argue that the three most pressing questions to be answered are how regulators address the afore-mentioned risks of DeFi, why there is regulatory uncertainty, and how it can be resolved. It would appear to be a matter of some urgency, then, that researchers, policymakers, and practitioners develop policies for integrating DeFi into current and future economic and societal settings.

To use a DeFi application typically requires a centralized intermediary who facilitates on-ramping to the crypto ecosystem in the first step, e.g., CEXes. These centralized points are mainly used to enforce laws (Zetzsche et al., 2020 ). For counter-financing terrorism (CFT) and anti-money laundering (AML) verification, regulators require financial services firms to conduct thorough KYC procedures for their customers. They have generally been deemed very helpful in combating illicit activities. However, they increase service provision costs and link the pseudonymous address to the “real world” identity, making tracing transactions much easier (Qin et al. 2021a ). Nevertheless, Qin et al. ( 2021a ) have pointed out that it is possible to bypass regulations by inherently operating in DeFi or using Mixers. In contrast, the off-ramping of assets still appears to be a challenging task. A further matter of concern is that anonymity-enhanced cryptocurrencies like Dash can facilitate illicit activities and harm KYC, CFT, and AML regulations (Taylor, 2021 ).

It is not enough, however, to address centralized points. Thorough audits and sophisticated laws for the entire DeFi ecosystem are required (Suga et al., 2020 ), yet to date, there is no evidence of the necessary expertise in this area (Bennett et al., 2020 ; Suga et al., 2020 ). Furthermore, due to DeFi’s borderlessness and decentralization, DeFi applications fall within the remit of multiple jurisdictions. It stands to reason, then, that the application of integrative regulations and safety guarantees like emergency support is difficult. It is also worth remembering that blockchain-based transaction data from DeFi applications are publicly accessible and subject to general data protection laws, such as the EU’s GDPR (Qin et al. 2021a ; Zetzsche et al., 2020 ). Moreover, the classification of crypto assets, such as governance tokens or NFTs, is anything but a trivial task, especially in the current absence of sophisticated regulatory guidance (Bennett et al., 2020 ; Doan et al., 2021 ; Ushida & Angel, 2021 ). Depending on the classification of assets in DeFi, regulation is overseen by regulatory authorities like the American Securities and Exchange Commission (SEC). However, the SEC requires the agents in DeFi to cooperate and not lag on DeFi innovations (Guseva, 2021 ).

The literature also covers potential alternatives in the regulation of DeFi and cryptocurrencies. As Wright and Meier ( 2021 ) have discussed, the regulation proposed by the US American financial crimes enforcement network (FinCEN) targets banks and money service businesses (MSBs), so it requires a complete recording and reporting of customer transactions (FinCEN, 2020 ). However, the proposal may lead to an increased service cost and a decrease in user experience, which would arguably result in users switching to decentralized platforms once and for all, as these are harder to regulate (Wright & Meier, 2021 ). Similar to the FinCEN, European authorities have introduced a licensing regime that targets the regulation of “Markets in Crypto Assets” (MiCA) (European Commission, 2022 ). In order to provide legal certainty and investor protection, MiCa regulation categorizes crypto assets by mapping them to existing types of financial instruments (Maia & Vieira dos Santos, 2021 ). However, decentralized projects such as DeFi protocols are not within the scope of this proposal because they are not yet accountable to a legal entity. It is, therefore, a matter of some urgency that further regulations are put in place in conjunction with which the as yet to be provided regulatory guidance can mitigate DeFi risks such as cyber-attacks, fraud, manipulation, and liquidity risk (Maia & Vieira dos Santos, 2021 ).

Effective regulation in a DeFi context means “(i) compliance with requirements such as registration of securities offerings, know-your-customer (KYC) rules, and the like, and (ii) attention to the contract and property rules integral to the enforceability of claims on assets” (Hughes, 2021 ). A promising solution might be automating compliance by integrating laws into code. After all, effective laws can only be drafted to the satisfaction of the majority of shareholders if this is done with a multi-stakeholder approach (Hughes, 2021 ; Matsuo, 2020 ; Takanashi, 2020 ). To engender a healthy DeFi ecosystem, one such multi-stakeholder approach might consider permissionless innovation, global space, and pursuing goals on both sides, that of regulators and DeFi stakeholders (Matsuo, 2020 ). This cooperative approach could benefit both sides as regulators could use new technology to enforce laws, while DeFi could benefit from various legal protection laws (Schrepel & Buterin, 2020 ). However, making such a multi-stakeholder approach work in the real world might prove difficult since developers would appear reluctant to cooperate with regulators (Takanashi, 2020 ). To complicate matters further, effective regulation of DeFi demands standardization and distribution of knowledge among stakeholders (Matsuo, 2020 ).

In accordance with the results in Measurement & Value/Users & Society , regulatory uncertainty posed an intriguing challenge to widespread user adoption of DeFi-based services and instruments. Against this background, future research should focus on how regulatory authorities can be integrated in order for them to play a central role in the development process of DeFi applications. Establishing consensus in this area will require interdisciplinary research efforts, especially regarding legal and regulatory perspectives. A prime example is a need to draw on various areas of expertise when examining the degree to which protocol code can be adopted as a form of “automated law.” As our literature review has indicated, several suggestions exist to establish a multilateral and multi-stakeholder approach to DeFi regulation. Since this is also consistent with findings in Measurement & Value/Financial Industry , there would seem to be broad agreement on the need for future research into the feasibility of such an approach. It is certainly fair to say that, from an end-user perspective, the current trade-offs between privacy and transparency in DeFi applications are a critical issue that ought to be addressed with appropriate regulatory measures.

Management & Organization/DeFi Applications

This category concerns itself with the governance of DeFi applications. Considering the results of Management & Organization/Users & Society , we argue that the question of how regulatory compliance can be implemented on a protocol level should be discussed with notable urgency. However, we found that the literature side-stepped this question to consider instead the mechanics of governing and organizing DeFi protocols with a particular focus on token economics, such as DAOs, stablecoins, and exchanges.

While governing DAOs using tokens has its merits, it also raises several concerns. On the other hand, token holders of DAOs without ownership have limited influence, prime examples being operative and external actors. This does not incentivize security governance (Brennecke et al. 2022a ). A further matter of concern is that developers of specific protocols hold admin keys to that protocol, which concentrates power (Ushida & Angel, 2021 ). Therefore, governance must be disincentivized from mismanagement and protected from attack vectors, for instance, by slashing governance token value (Klages-Mundt et al., 2020 ). Also worth considering in this context, simple on-chain voting processes do not capture the complexity of protocol interplay, whereas off-chain governance systems seem obscure. Generally speaking, the successful design of governance mechanisms requires a careful balancing act between transparency on the one hand and security on the other (Ushida & Angel, 2021 ). This involves a keen appreciation of the fact that the security of a protocol can impair the governance of connected protocols (e.g., by oracles) and the underlying blockchain governance (e.g., by MEV) (Gudgeon et al., 2020a , b ; Klages-Mundt et al., 2020 ; Ushida & Angel, 2021 ).

More frequent use of governance tokens incentivizes economic activity, e.g., lending and borrowing in lending protocols (Perez et al., 2021 ). However, this is only sustainable if the price of the governance token is sufficiently high (Klages-Mundt et al., 2020 ; Perez et al., 2021 ). Even when it is sustainable, users accept more risk, increasing the likelihood of liquidations in collateralized lending protocols.

Also somewhat problematic is the degree of decentralization of protocols in which governance tokens are concentrated among a small subset of addresses. Empirical studies have shown that a high concentration of governance tokens is associated with a small number of wallet addresses (Jensen et al., 2021a ; Nadler & Schär, 2022 ). However, this does not necessarily mean DeFi applications are vulnerable to governance attacks. Moreover, security mechanisms like time locking vary from protocol to protocol. Nevertheless, they still have implications for the governance design of DeFi protocols (Jensen et al., 2021a ; Nadler & Schär, 2022 ).

As the results of our review indicate, research on DeFi applications at an organizational level is expanding. The following question concerns the extent to which the governance of DeFi applications needs to be decentralized to ensure the integrity of dApps and the ecosystem at large. Subsequently, the question arises regarding how dApps should be regulated in this context. For example, organizational theories established in management research might be a good starting point to further develop and adapt them to DeFi application governance mechanisms.

Management & Organization/Blockchain Infrastructure

Much like the preceding one, this section deals with the blockchain infrastructure’s governance. After considering the previous findings in Measurement & Value/DeFi Applications and Managements & Organization/DeFi Applications , we here conclude that further research is required to address the transparency, security trade-off, and re-centralization issues of miners.

If a blockchain is public and free to use, it facilitates decentralization by distributing control. As shown in Management & Organization/DeFi Applications , this theoretically enables the blockchain to complement antitrust laws by facilitating a competitive market, although protocols may still be somewhat centralized (Schrepel & Buterin, 2020 ). However, open blockchains face a high degree of centralization of hashing power, which poses a significant security risk to the network. Nevertheless, 51% of attacks are neither profitable nor sensible since the credibility of the network and the value of its assets will decline after an attack (Aponte-Novoa et al., 2021 ). On the other hand, miners can extract value by ordering transactions arbitrarily to their needs due to the transparency of transactions, thereby benefiting them economically. As a result, the blockchain consensus can be compromised because miners may try to fork the blockchain to extract MEV (Qin et al., 2022 ).

A further problem of the blockchain infrastructure is scalability (Zhao et al., 2021 ). Block generation time must be consistently higher than block propagation delay. If this is not the case and blocks are created faster than nodes can receive them, it can lead to consensus security issues, e.g., forks (Zhao et al., 2021 ). A propagation delay can decrease block generation time and facilitate a “LightBlock” protocol (see Design & Features/Blockchain Infrastructure ).

As for DeFi’s application level, the question arises of how the infrastructural level should be governed. Blockchains are decentralized by nature, and yet validators can still accumulate power. For example, validators can allocate a very high amount of capital in PoS-based blockchains, allowing them to overtake the block production and potentially manipulate DeFi applications. Further research is required to examine, design, and implement countermeasures to mitigate the risk of high accumulation of validator power in blockchains. The need for further research in this context is particularly apparent given the small number of studies at the intersection of the Management & Organization/Blockchain Infrastructure category (see Table 3 ).

Management & Organization/Financial Industry

In this category, our focus shifted to the managerial decisions of incumbents in the traditional financial system. The literature in this section dealt with strategies the financial industry employs concerning DeFi.

As shown in Measurement & Value/Financial Industry , promoting DeFi has so far relied on highlighting the shortcomings of traditional finance and distrust in banks. Our results indicate that this may not be the optimal way to approach DeFi adoption in the financial sector (Lockl & Stoetzer, 2021 ). According to Lockl and Stoetzer ( 2021 ), DeFi should instead be promoted by highlighting its advantages over traditional services. There is complete consensus among the articles in this category that traditional financial institutions do not feel threatened by the emergence of DeFi but rather see it as a welcome opportunity to use new technology (Derviz et al., 2021 ; Lockl & Stoetzer, 2021 ; Meegan & Koens, 2021 ). Indeed, they even concur with a convergence of both financial systems. This convergence is expected to increase users’ benefits in the financial sector, for example, by integrating DeFi into existing product portfolios and legacy features (Derviz et al., 2021 ; Lockl & Stoetzer, 2021 ; Meegan & Koens, 2021 ). As discussed above, a promising point to initiate such a convergence is the introduction of stablecoins using CBDCs (Derviz et al., 2021 ). As Meegan and Koens ( 2021 ) have pointed out, traditional financial businesses and institutions tend to be risk-averse, which is why further research on DeFi will have to focus on reducing uncertainties and helping the traditional financial sector understand and engage with DeFi.

As Suga et al. ( 2020 ) have highlighted, centralized institutions linked to DeFi, especially CEXes, have their security issues due to the lack of skilled system architects, engineers, and operators. The scholarly view is that audits, multi-signature key schemes, and standardization of security management will bolster governance. Much like Klages-Mundt et al. ( 2020 ), Suga et al. ( 2020 ) have advised caution because CEXes operating on a segregated blockchain without further security measures could harbor notable disadvantages.

To recap, DeFi presents an opportunity to improve prevailing infrastructures, processes, and services in CeFi. With this opportunity in mind, IS scholars are encouraged to examine how the convergence of both DeFi and CeFi can be expedited. As we advance, researchers would do well to study the role of central bank digital currencies (CBDCs). Furthermore, they would be well advised to focus on the regulation of DeFi services when CeFi institutions decide to integrate these services into their infrastructure and product portfolio. Therefore, research in this area should explore the potential of regulating, first and foremost pivotal points (e.g., crypto exchanges), to inform policymakers on how DeFi should be approached from a regulatory perspective.

Discussion and future research opportunities

Our analysis in the previous pages has stressed the need for a common understanding, as the literature published to date was sorely lacking consensus on a definition of DeFi (Katona, 2021 ). Indeed, scholars seemed to have a vastly different understanding when defining DeFi concerning particular aspects of DeFi. For instance, Kumar et al., ( 2020 , p. 1) defined DeFi as an “ecosystem of financial applications built on top of some public blockchain,” yet this definition fails to account for the automation benefits of smart contract protocols. These protocols, however, are among the essential building blocks that enable the deterministic execution of programming code in DeFi-based services and instruments (Chen & Bellavitis, 2020 ; Schär, 2021 ; Zetzsche et al., 2020 ). Another definition proposed by Gudgeon et al. 2020b , p. 92) contends that DeFi “is the emergence of protocols which facilitate programmatic borrowing and saving.” However, this definition is only true of two specific DeFi-based services, even though DeFi encompasses several applications beyond borrowing and saving services, such as stablecoins, insurances, and asset management (Brennecke et al., 2022b ; Gramlich et al., 2022 ; Guggenberger et al. 2021a ). We also noted that the level of abstraction in the proposed definitions of DeFi varied significantly. For example, Zhou et al. 2022a , p. 919) stated simply that “blockchain-based decentralized finance protocols [are] commonly referred to as DeFi.” In contrast, Grassi et al., ( 2022 , p. 327) defined DeFi very precisely as “the creation of an alternative financial system, where anyone, anywhere, can access financial services (e.g., lending, insurance, investment) based on digital assets. This ecosystem of financial applications relies and is built on top of a given public blockchain, often Ethereum, as smart contracts are the fundamental building blocks of DeFi.” While both of these definitions are accurate, the gap between them needs to be bridged or closed if there is to be a common ground for understanding DeFi.

Based on our literature analysis, we provide a definition that is as concise and comprehensive as it is universally applicable (see the “ Results ” section). Our proposed definition is abstracted from and generally applicable to other definitions of DeFi (e.g., Schär, 2021 ; Zetzsche et al., 2020 ). These concerns were at the center of our research process, not least because only a widely applicable definition could serve as a basis for developing our DeFi research classification framework. This framework then allowed us to systemize the relevant research sub-areas of DeFi. While the identified activities correspond to those described by Risius and Spohrer ( 2017 ), the level of our analysis was specifically adapted to the DeFi phenomenon.

In addition to providing structure to the existing literature, this research framework also allowed us to gain deeper insights into DeFi. The DeFi stack presented by Schär ( 2021 ) offers a firm understanding of the technologies behind DeFi by presenting its main components. Our research framework, in contrast, presents an abstract overview of the DeFi phenomenon. Doing so allowed us to understand not only the technical elements ( Design & Features ) but also the entire business ecosystem that is part of DeFi ( Financial Industry and Management & Organization ). In our view, this socio-technical conceptualization of DeFi ( Users & Society ) plays a key part in reflecting the entire spectrum of DeFi and the current state of research.

Similarly, Meyer et al. ( 2022 ) have presented a rigorous socio-technical conceptualization. They have done so by sub-dividing DeFi into the three levels of “micro,” “meso,” and “macro,” all of which in turn have varying sub-categories. With all due modesty, however, the framework presented in these pages has specific unmatched merits in systematizing the literature. For instance, we distinguish between an overall analysis of users and society (societal needs, i.e., usefulness) and an overall analysis of companies and firms (business needs, i.e., profit generation). Moreover, the systematization we developed assumes distinct boundaries between the different levels, which allows for a more precise classification of the phenomenon within the framework. For example, in the systematization of Meyer et al. ( 2022 ), it remains unclear whether the analysis of illegal behavior on Ethereum DEXes is part of the micro-level because it concerns a specific type of dApp, or whether it is part of the meso-level because it concerns insights about the ecosystem. Looking, instead, at the activity level, with particular regard to the Design & Features dimension, such as the one we propose, solves this issue of unclear categorization.

We summarize our results and thus the state-of-the-art research in DeFi on a category-overarching level and draw prominent meta-findings. In general, we find that DeFi comprises various properties, for example, transparency, composability, decentralization, interoperability, borderlessness, and transaction atomicity. These properties are the basis for a decentralized financial system (see Design & Features/Financial Industry ). However, they also contribute to an unstable, less secure, inefficient, and manipulable ecosystem (see, Measurement & Value ). DeFi currently fulfills these functions to varying degrees, which partially leads to trade-offs (e.g., privacy and transparency). The question of to which degree what DeFi feature should be satisfied remains unanswered. In addition, the dichotomy of DeFi in the context of regulation and legislation leads to uncertainty. Existing regulatory approaches only focus on specific elements of DeFi without recognizing decentralized aspects. There are challenges in applying these rules, mainly due to the decentralization and borderless nature of DeFi. Thus, the literature urges sophisticated laws to consider the very nature of DeFi based on a multi-stakeholder approach (see Management & Organization/Users & Society ).

We also observe that DeFi faces several risks of re-centralization, for example, in oracles, reserve-backed stablecoins, hashing power, and CEXes (see Design & Features, Measurement & Value, Management & Organization ). They all fulfill a critical role in DeFi but bear counterparty risks and single points of failure. The literature suggests a common approach for regulatory actions and encourages the convergence between CeFi and DeFi, for example, by introducing CBDCs (see Management & Organization ). Moreover, the literature points out that DeFi bears systemic risk (e.g., wrapped assets), increasing the complexity of the entire system (see DeFi Applications, Blockchain Infrastructure ). Specifically, if an asset or protocol fails to fulfill its task, it could affect other parts of the system and lead to a chain reaction (see Measurement & Value ). Consequently, these effects could spill over to other protocols involved in the “wrap chain,” similar to the systematic risk in the securitization process and was a major cause of the 2008 global financial crisis.

Although the literature proposes concepts, designs, and implementations to address some issues of DeFi, they focus mainly on the design of smart contracts. The effectiveness of these design proposals remains unsolved due to the lack of thorough testing (see Design & Features, Measurement & Value ). In this context, DeFi security is a matter of securing the respective protocols and their underlying blockchain (see DeFi Applications, Blockchain Infrastructure ). If the blockchain is not secure, the protocols are at risk, and vice versa, e.g., in MEV attacks (see Design & Features, Measurement & Value ). In addition, research on blockchain features for DeFi does not require smart contracts for its functionality, for example, in Bitcoin (see Design & Features/Blockchain Infrastructure ). In contrast, DeFi’s core financial services and instruments seem to be developed mainly on the Ethereum platform, allowing more sophisticated functionality than Bitcoin. Furthermore, the literature does not specify whether private or consortium blockchains play an important role in DeFi.

DeFi has not yet reached mainstream adoption because of its large risks, inefficient markets, and complex wrapping operations (see Measurement & Value, Management & Organization ). With matured markets, increased security, and greater user adoption, the currently high return on investments will converge with those of traditional financial markets, indicating that the basis of sustainable DeFi growth likely resides on other value propositions. In that sense, DeFi and CeFi share similar objectives in providing financial services to customers (see Financial Industry ). However, the literature emphasizes that both ecosystems should learn from each other. For example, DeFi can adopt established risk models used in CeFi (see Financial Industry, Users & Society ). We believe that neither DeFi nor CeFi will be replaced, but expect both to coexist, adopt methods of the other, and converge in the long term. Lastly, the literature points out philosophical elements in DeFi (e.g., cypherpunk philosophy or crypto-anarchism). Among some crypto supporters, decentralized financial applications like cryptocurrencies count as an alternative to the traditional financial system because they distrust government authority and traditional financial institutions (see Measurement & Value, Management & Organization ). However, adhering to this philosophy hinders progress in DeFi adoption, particularly regarding regulatory uncertainty and integration into an institutionalized environment in traditional finance (see Management & Organization/Users & Society, Financial Industry ).

Overall, the meta-results based on our analysis of the current DeFi literature using the classification framework helped us identify gaps in the literature. Against this background, we propose promising future research opportunities, which we present in Table 5 .

The proposed research agenda demonstrates the complexity of DeFi and the research needed to achieve further improvement and unleash DeFi’s full potential. Future research in DeFi, therefore, requires both qualitative and quantitative approaches and can be approached through interdisciplinary research from computer science, economics, and social sciences, but also management and law perspectives. Although there are several opportunities for researchers, we encourage them to specifically focus on conducting research in the following two areas: (1) Many research questions can be attributed to the differences between a decentralized (primarily blockchain-based) financial system and the traditional financial system. Designing blockchain protocols and user interfaces that account for the fundamental differences between DeFi and traditional finance can help mitigate risk and unlock DeFi’s potential—a critical step toward improving its use and adoption. (2) We also want to highlight the connection of the emerging DeFi ecosystem to the current financial landscape and socioeconomic aspects. Finally, a strong need exists to explore where DeFi can be linked to or integrated with existing institutions and structures to promote DeFi adoption. Furthermore, future research should address what DeFi applications are necessary to facilitate this connection and what specific knowledge is required among all stakeholders to lever DeFi.

This study provides a systematic summary of the literature published on DeFi at the time of writing. Our methodology allowed us to propose a consolidating definition of DeFi based on a broad and varied spectrum of prior definitions. In addition, we used our conceptual framework to present and structure the research conducted to date and shed light on future research opportunities by establishing a DeFi research agenda. We hope these insights will prove valuable in exploring ways to foster the healthy development of DeFi.

Despite our best efforts, however, this study has certain inevitable limitations. While our methodology ensured that we excluded irrelevant literature, it is conceivable that our search string did not capture some relevant articles (e.g., literature that only covers blockchain topics with implications for DeFi without further elaborating on these implications). However, this limitation had no impact on the completeness of our literature review because these articles, if known to exist, are likely to have been considered in works directly related to DeFi. In this case, they have been captured in our selection process. As for our review of the grey literature, we had to select a stopping criterion that may have excluded relevant papers. However, since we chose an exhaustive stopping criterion, this limitation may be considered less consequential than if a strict stopping criterion like a flat page range had been chosen. Overall, we are confident that, although we may not have directly covered every relevant article with implications for DeFi, we captured most of the literature, knowledge, and insights on DeFi.

Having analyzed the literature on DeFi from different disciplines (law, IT, and finance), we have looked at DeFi through a wide-angle lens to recognize an emerging financial ecosystem based on blockchain, and we have seen that this system has, at its core, a fascinating dichotomy. In the best case, it enables financial services in a truly decentralized financial system with unique and democratizing concepts and features. In the worst case, it undermines the rule of law, enables illicit financial activity, and endangers everyone that puts funds in it. These theoretical cases notwithstanding, at this point, it would appear to perform neither of these roles nor is it likely ever to do so in the real world.

In the final analysis, we frame the current implementation of DeFi as an emerging financial system that suffers from the very features from which it draws its value propositions. It would appear that DeFi will only overcome its issues by giving up on its initial philosophy of true decentralization and independence, instead working together with regulators, lawmakers, and traditional financial institutions. It does not look like DeFi will fully replace traditional finance and its institutions. Instead, it is expected that both financial systems will have to converge to serve the greatest common good for users.

We wish to end on a positive note, a call for a multi-faceted mindset. Stakeholders of DeFi ought to detach themselves from the isolated view based solely on personal needs and expectations of DeFi. Instead, they would do well to consider the big picture painted on these pages. Given that DeFi is still in its infancy, we suggest that, as with any child, those engaging with it keep an open mind regarding further advancements, research, and value propositions. However, as we hope to have shown, this mature view of DeFi requires one to see it in differentiated, multi-faceted terms, and thus neither as a silver bullet that can sort out all issues of the traditional financial system nor as a new-age and inherently malicious financial system.

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Emerging Institutional Logics in Decentralized Finance: A Multi-stakeholder Analysis

Student thesis : Master thesis

The financial sector is faced with a paradigm shift in the form of Decentralized Finance (DeFi), offering enhanced accessibility, autonomy, and efficiency. This thesis analyses the emerging institutional logics within the DeFi ecosystem, to understand the dynamics that underpin it. The thesis utilizes a grounded theory approach in combination with the Gioia methodology to analyse data sources from various stakeholder groups involved in the DeFi ecosystem. This results in a robust analytical framework that identifies five key dimensions: Technical Foundations and Innovations, Challenges and Risks, Evolving Regulatory Dynamics, Transformative Impact on Traditional Finance, and Socioeconomic Impact and Market Dynamics. In addition, this thesis theorizes the “DeFi Dynamics Model” based on the identified dimensions, and highlights two logics within the DeFi space, competing for dominance. Finally, the theoretical and practical implications of these findings are discussed, which provide valuable insights for academics, policymakers, and industry stakeholders. As DeFi continues to evolve, this thesis provides a fundamental exploration of its institutional underpinnings and thus a roadmap for future research and practical engagement.

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Visit our blog for frequent posts about our association., call for students - master thesis on decentralized finance: analyzing digital financial instruments on ethereum.

ITSA offers support for a master thesis together with the Johannes Gutenberg University of Mainz. The emergence of cryptographic tokens created a new academic field. ITSA developed a token classification framework to clearly capture the differences between tokens. Based on these classifications, distinct and specific research of token economies, the use and acceptance of tokens, and others are exciting opportunities. This thesis is dedicated to DeFi and analyzing digital financial instruments on Ethereum.

Authors: Maximilian Bruckner, Constantin Ketz, Christian Viehof, Philipp Sandner

Project description

Cryptog r aphic tokens running on DLT systems will soon form an integral part of various major economic sectors (e.g. financial markets, information and media, manufacturing and trade). As such they are going to provide utility and value in many different forms to business and society as a whole. Moreover, cryptographic tokens are also on the verge of representing a recognized institutional asset class. Yet, the current token markets still lack a tangible and holistic framework for the identification, classification, and analysis of different token types, which leads to economic, technological as well as regulatory uncertainty and a lack of transparency for all players involved. With the objective of addressing these shortcomings, the International Token Standardization Association (ITSA) e.V. aims at implementing comprehensive market standards for the global token economy.

The ITSA offers this cooperation together with the Johannes Gutenberg University of Mainz.

Goal of the thesis

The aim of this thesis is to examine decentralized finance (DeFi) in the use case Ethereum. It has to be shown where the advantages and disadvantages are in a decentralized financial system and what relevance DeFi has accordning to the current state of affairs. Finally, a profound discussion of current use cases and the analysis of these will be the basic building block of this thesis.

Requirements

For this thesis we are looking for:

• A highly motivated student with strong analytical skills and advanced skills in working with databases (e.g. SQL, VBA Excel).
• The student should also be interested in working in a team within a dynamic international environment.
• Knowledge of German is welcome, but not a must.

Support will be provided by:

• Prof. Dr. Andranik Tumasjan
• Prof. Dr. Philipp Sandner

If you are interested in the topic and think you are the right person to get involved, contact Christian Viehof, Executive Director at ITSA ([email protected]).

Collaborate with ITSA!

As we are well aware of the subjectivity of each framework and its existing biases, we would also like to invite all readers to provide their feedback on our approach and/or to join the ITC Working Group to develop the next ITC update together with us. Just like all other standardization projects of the International Token Standardization Association (ITSA) e.V., the International Token Classification (ITC) framework will be updated and developed further regularly. Therefore, we would highly appreciate external feedback or suggestions on new Dimensions to be added or new ecosystem trends to be incorporated. Finally, we are always looking for partners that are interested to classify new sets of tokens together with us, either as part of a research project, an academic thesis, or any other viable cooperative setting. You can find contact details in the remarks section of this article.

If you like this article, we would be happy if you forward it to your colleagues or share it on social networks. More information about the International Token Standardization Association can be found on the Internet , on Twitter , or LinkedIn .

Prof. Dr. Philipp Sandner is head of the Frankfurt School Blockchain Center (FSBC) at the Frankfurt School of Finance & Management. In 2018, he was ranked as one of the “Top 30” economists by the Frankfurter Allgemeine Zeitung (FAZ), a major newspaper in Germany. Further, he belongs to the “Top 40 under 40” — a ranking by the German business magazine Capital. The expertise of Prof. Sandner in particular includes blockchain technology, crypto assets, distributed ledger technology (DLT), Euro-on-Ledger, initial coin offerings (ICOs), security tokens (STOs), digital transformation, and entrepreneurship. You can contact him via mail , via LinkedIn , or follow him on Twitter

Maximilian Bruckner is Executive Director at the International Token Standardization Association (ITSA) e.V., working to create the world’s largest token database including a classification framework and unique token identifiers and locators. He has a strong international background with significant time spent in Spain, South Africa, and Canada. Currently pursuing studies at the Frankfurt School of Finance and Management, you can contact him via [email protected] and connect on LinkedIn if you would like to further discuss ITSA or have any other open questions.

Christian Viehof is an Executive Director at the International Token Standardization Association (ITSA) e.V., working to create the world’s largest token database including a classification framework and unique token identifiers and locators. He completed his Bachelor in Economics at the University of Bonn, the Hong Kong University, and the London School of Economics and Political Science with a focus on Behavioral Economics and Finance. Currently pursuing his Master of Finance at the Frankfurt School of Finance and Management, you can contact him via [email protected] and connect with him on Linkedin , if you would like to further discuss ITSA e.V. or have any open questions.

ITSA e.V. aims at promoting the development and implementation of comprehensive market standards for blockchain- and DLT-based cryptographic tokens. To increase transparency and safety on global token markets, ITSA e.V. assigns a unique and fork-resilient identifier (the ITIN) to each token and classifies the token according to our International Token Classification Framework (ITC). This data is then entered into the TOKENBASE. It is our vision to create the world’s largest DLT token database and see our market standards be implemented across the world. Our working groups are actively driving the development and progress of both the ITIN and the ITC.

• The International Token Identification Number (ITIN) is a 9-digit alphanumeric technical identifier for both fungible and non-fungible DLT-based tokens. Thanks to its underlying Uniform Token Locator (UTL), ITIN presents a unique and fork-resilient identification of tokens. The ITIN also allows for the connecting and matching of other media and data to the token, such as legal contracts or price data, and increases safety and operational transparency when handling these tokens.
• The International Token Classification (ITC) is a multi-dimensional, expandable framework for the classification of tokens. Current dimensions include technological, economic, legal, and regulatory dimensions with multiple sub-dimensions. By mid-2021, there will be at least two new dimensions added, including a tax dimension. So far, our classification framework has been applied to 99% of the token market according to the market capitalization of classified tokens.
• ITSA’s Tokenbase currently holds data on over 4000 tokens. Tokenbase is a holistic database for the analysis of tokens and combines our identification and classification data with market and blockchain data from external providers.

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On the Sustainability of Decentralized Finance

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Article Contents

I. introduction, ii. defi vs traditional finance, iii. defi and its technological foundations, iv. defi vs the state, v. assimilating defi: the empire strikes back, vi. decentralization and concentration: the centrality of the state, vii. looking forward.

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Decentralized Finance

Dirk A Zetzsche is Professor of Law, ADA Chair in Financial Law (Inclusive Finance), Faculty of Law, Economics and Finance, University of Luxembourg; Director, Center for Business and Corporate Law, Heinrich-Heine-University. Dirk can be contacted at [email protected]

Douglas W Arner is Kerry Holdings Professor in Law and Director, Asian Institute of International Financial Law, University of Hong Kong; Board Member, Centre for Finance, Technology & Entrepreneurship. Douglas can be contacted at [email protected]

Ross P Buckley is KPMG Law and King & Wood Mallesons Professor of Disruptive Innovation, Australian Research Council Laureate Fellow, and Scientia Professor, UNSW Sydney. This article benefited from presentation at the Georgetown University / Barbados Financial Services Commission Seminar on Sustainable De-Fi and Financial Inclusion and from the helpful discussions, comments, and questions from Chris Brummer and other event participants: Linn Anker-Sørensen, Raphael Auer, Luca Enriques, Jon Frost, and Dirk Schoenmaker. The authors thank the Georgetown University’s Institute of International Economic Law, the Hong Kong Research Grants Council Research Impact Fund, the Qatar National Research Fund National Priorities Programme, and the Australian Research Council Laureate Fellowship, for financial support, and Mia Trzecinski and Jessie Xiao for their expert research assistance. All responsibility is the authors’. Ross can be contacted at [email protected]

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Dirk A Zetzsche, Douglas W Arner, Ross P Buckley, Decentralized Finance, Journal of Financial Regulation , Volume 6, Issue 2, 20 September 2020, Pages 172–203, https://doi.org/10.1093/jfr/fjaa010

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DeFi (‘decentralized finance’) has joined FinTech (‘financial technology’), RegTech (‘regulatory technology’), cryptocurrencies, and digital assets as one of the most discussed emerging technological evolutions in global finance. Yet little is really understood about its meaning, legal implications, and policy consequences. In this article we introduce DeFi, put DeFi in the context of the traditional financial economy, connect DeFi to open banking, and end with some policy considerations. We suggest that decentralization has the potential to undermine traditional forms of accountability and erode the effectiveness of traditional financial regulation and enforcement. At the same time, we find that where parts of the financial services value chain are decentralized, there will be a reconcentration in a different (but possibly less regulated, less visible, and less transparent) part of the value chain. DeFi regulation could, and should, focus on this reconcentrated portion of the value chain to ensure effective oversight and risk control. Rather than eliminating the need for regulation, in fact DeFi requires regulation in order to achieve its core objective of decentralization. Furthermore, DeFi potentially offers an opportunity for the development of an entirely new way to design regulation: the idea of ‘embedded regulation’. Regulatory approaches could be built into the design of DeFi, thus potentially decentralizing both finance and its regulation, in the ultimate expression of RegTech.

‘Decentralized Finance’ (DeFi) is neither a legal nor a technical term. It is nonetheless increasingly used in the context of discussions about the future evolution of finance and its regulation. Common usage incorporates one or more elements of: (i) decentralization; (ii) distributed ledger technology and blockchain; (iii) smart contracts; (iv) disintermediation; and (v) open banking. 1 While decentralized systems such as Bitcoin rely on distributed ledger technology (DLT) and blockchain to underpin token-based ecosystems, the combination of DLT and blockchain is not the only way to achieve decentralization. Further, many distributed ledgers (and most distributed ledgers operated by large financial intermediaries) operate today with a hierarchical, centralized governance model, limiting access to permissioned participants only. In turn, decentralized does not necessarily mean distributed. 2 In a similar way, disintermediation is not a prerequisite for decentralization; rather, disintermediation may be one (side) effect of decentralization, given that the establishment costs of centralized infrastructure will be difficult to recoup in a world where services can be provided on a distributed or decentralized basis. Hence, in this article we understand DeFi to comprise, at its core, what its simple name suggests: the decentralized provision of financial services 3 through a mix of infrastructure, markets, technology, methods, and applications. Decentralized provision of financial services means, in turn, provision by multiple participants, intermediaries, and end-users spread over multiple jurisdictions, with interactions facilitated, and often in fact enabled in the first place, by technology.

We analyse the roots and tools of this decentralization of financial services and focus on how financial regulation will need to respond to it. In particular, we place DeFi in the context of the traditional financial economy, connect DeFi to open banking and RegTech (‘regulatory technology’), and end with some policy considerations.

Many find the promise of decentralization and its potential to displace the regulatory state with technology as a seductive ideal. We take a different approach here: rather than arguing the potential benefits of DeFi, we seek to identify what is actually taking place and the sorts of regulatory implications this may have. We analyse DeFi, not as a desired goal, but as a real-world phenomenon, and seek to understand the growing challenges this trend poses for financial regulation. Challenges to traditional modes of governance and regulation are one aspect.

We suggest that decentralization has the potential to undermine traditional forms of accountability and erode the effectiveness of traditional financial regulation and enforcement. We also predict some surprising effects: where parts of the financial services value chain are decentralized, we expect reconcentration in a different (but possibly less regulated, less visible, and less transparent) part of the value chain.

In short, DeFi requires careful regulatory attention. In situations where DeFi produces new forms of technological reliance, regulation needs to focus on the reconcentrated portion of the value chain to ensure effective oversight and risk control: in this framework, regulation is necessary in order to support decentralization, in much the same way that regulation is at the core of securities markets and other financial services. In other situations, regulation will be necessary to protect markets and participants from predation by non-decentralized system, for instance when a participant in one market seeks to take advantage of technology for regulatory arbitrage.

In more visionary ways of thinking, regulation may insist that compliance requirements and real-time supervisory access be embedded in the very technology that allows for decentralization, thereby potentially decentralizing both finance and its regulation in the ultimate expression of RegTech: not only ‘embedded supervision’ as suggested by Auer but in fact ‘embedded regulation’. 4

The article is structured as follows. Section II seeks to place DeFi in the context of traditional finance and its regulation. Section III (far from claiming completeness) seeks to highlight the central elements from a technical perspective of DeFi. Sections IV and V address financial regulation and supervision, analysing first the challenges for financial supervision and enforcement before turning to the options available to regulators and law makers across the globe. Section VI considers the connection between decentralization and open banking, arguing that decentralization requires sovereign intervention from several different standpoints: from the standpoint of mandating open and enforcing open access to data; from the standpoint of supervising or even operating the core underlying technological infrastructure; and from the standpoint of requiring the embedding of regulation directly into DeFi systems. Section VII concludes.

While most recent treatments approach DeFi from a technical perspective, 5 it is instructive to first highlight the structure of traditional finance before turning to discussion of how DeFi may contrast to this.

1. Traditional finance

At the heart of market-based finance is a series of intermediaries that bring together disparate participants. The paradigmatic intermediaries are financial institutions such as banks, and market providers such as securities exchanges. These intermediaries bring together a range of financial market participants, in particular those with finance resources (for example savers, lenders, and investors) and those seeking financial resources (for example borrowers, entrepreneurs etc). We often think of the intermediary as the central point when separating market-based financial systems into their traditional sectors of money, payments, banking, securities, and insurance.

Traditional finance is thus characterized by major intermediaries, which centralize functions and financial resources. This results in the hub-and-spoke conceptualization of finance and centres of finance. Technology and globalization together characterize traditional finance today.

2. Centralization for scale

When clients have local access to services such as payments, ATMs, savings, investments, and insurance, these services are not provided at the point of access. Rather, financial markets and activities traditionally cluster in local, regional, and super-regional/global access points (‘hubs’). 6 These services are in substance provided from a financial centre where sufficient concentration of transaction volumes and numbers in a given sector(s) or service(s) allow the development of expertise and resources. 7 Depending on the sector(s) / service(s), the required volume and numbers may be developed locally, regionally, or globally.

Take the example of a rarely traded currency issued by a developing country’s central bank. The currency tends to be illiquid as there is limited demand, often aggravated by underdeveloped market infrastructure and barriers to access. In order to bring together sufficient supply and demand, and for transactions to take place at all, it may be necessary to look beyond the domestic market to regional or global markets. Similarly, certain investment and insurance services require global diversification to function well. In contrast, the domestic or regional level typically provides sufficient scale for the efficient provision of basic financial services such as cash business (ATMs), savings, and loans.

Following this economic logic, financial centres have evolved, with local, regional, and global roles and significance. For instance, New York, London, and Hong Kong provide investment banking services around the globe—or at least throughout their region/timezone. London (at least prior to Brexit) served as a centre of the global derivatives and foreign exchange markets; Luxembourg served as the global investment fund hub; Switzerland and Singapore served as global private banking centres; and the Bahamas served as a global insurance hub. Centres are constantly evolving and competing, with competition in FinTech (‘financial technology’) in particular now focusing on Singapore and London. 8 As a competitive factor, these hubs usually provide tailormade sets of financial regulation and enforcement of these rules, in an effort to protect the parties transacting through the hub.

3. Regulation and traditional finance

These financial centres fundamentally depend on trust and confidence in order to function. 9 Trust and confidence, along with the basic functioning of financial systems, is underpinned by law: rules, institutions, regulation, and courts. 10 While many of these systems originally evolved as forms of private ordering or self-regulatory frameworks, over time the state has taken an increasing role as a result of failures of private ordering and self-regulation that have come to the surface periodically, often in the context of financial crises. This can be seen in the context of money as a sovereign function, as well as the role of government regulation in almost all aspects of finance, in particular in the aftermath of the 2008 financial crisis.

Market-based financial systems thus are often seen as fundamentally unstable, with instability and other forms of market failures being addressed by regulation, albeit never entirely successfully. 11

It is this weakness that underlies the ideal of DeFi and its techno-utopian vision of finance without the dominance of concentrated intermediaries—and the too-big-to-fail risks that they embody—and without reliance on the weaknesses of states, governments, and regulators. DeFi presents a vision of a world in which technology replaces frail humans and their institutions. It is at its heart a utopian vision but one with attractions for many. However, over time, it has moved from a utopian vision to a simpler idea in which technology can potentially eliminate the risks inherent in the concentrated systems central to traditional finance.

4. DeFi: a response and challenge for traditional modes and conceptions of finance?

In the past, hubs were necessary since services were provided locally and booked on a single balance sheet, with the provider of that balance sheet usually headquartered in a hub. This hub would usually be protected by high regulatory and supervisory standards, reflecting the large quantity of risks from pooling and balance sheet concentration at the hub.

DeFi challenges this hub logic. Where scale can be created by technology rather than by bundling business in a hub, hubs make little sense, because a hub comes with downsides for clients: they need to adjust in terms of language and law, subscribe to the high compliance standards reflecting the concentration of risks, accept information costs (for instance, for legal counsel), and may be subject to penalties for non-compliance with laws implemented at the hub level, but not (yet) at the local level. As many developing countries lack equivalent regulation and supervision, hub access becomes problematic. Clients from countries with weaker institutional environments need to rely on costly workarounds, sometimes through several jurisdictions functioning as regional hubs (in particular as often seen in the Gulf). This means that firms from developing countries can often only access services provided in global financial centres indirectly (albeit at cheaper costs than by accessing them directly). In the example used for emerging market currencies, for instance, services could be tokenized and provided to the token holder regardless of places of origin of provider and recipient, with Bitcoin a prominent example: Bitcoin holders are linked through common technology rather than a massive balance sheet in a highly regulated payment hub.

Finally, hub structures create dependencies which may be unattractive from the political standpoint—for instance, if RMB or EUR are settled in London or New York, the English and US regulators acquire influence over the currency, which may be used in the political context.

As a result of technological evolution, the future of finance may look different. This justifies a closer look at the underlying technologies, systems and infrastructure that underpin decentralization and decentralized finance—the focus of section III . However, as we argue in the remainder of this article, we suspect that the future may not look so different after all—we consider it more likely that traditional finance will assimilate DeFi and in particular its core technologies rather than vice versa.

Underlying the utopian ideal of DeFi—an ideal in which technology allows the elimination of the traditional centralized governance structures seen with traditional finance and financial centres—as well as its more pragmatic practical evolution, is a series of technologies. As a result of long-term technological evolutionary processes, the technological potential to underpin entire systems without any one necessarily being in charge exists, as demonstrated—if nothing else—by Bitcoin.

1. DeFi and the patterns of technological evolution

DeFi emerges from three important patterns in technological evolution: Moore’s law, Kryder’s law, and another pattern for which there is, to our knowledge, no term yet established. Moore’s law refers to the assumption that the amount of data processing power grows exponentially. 12 Kryder’s law posits the same for data storage capacity. 13 The combination of ever-increasing processing power and ever-increasing data storage capacity leads to ever-lower costs for both. The third factor making DeFi possible is the tremendous growth we have seen in communications bandwidth combined with decreasing costs—a phenomenon which has been discussed since the late 1990s, 14 if not earlier. The underlying assumption of bandwidth growth at decreasing costs is supported by increasing network efficiencies, which lead to more bandwidth per dollar invested. This may arise, inter alia, from lower production costs of network components, denser and faster ports, higher utilization, and integrated photonics, 15 or the use of higher frequency microwaves requiring smaller cells using multiple frequency bands (with 5G as an example).

These three evolutionary patterns enable hardware virtualization: software is hosted, updated, and run at decentralized servers rather than on each workstation. Only data that needs to be processed locally (under conditions of instant online connection and abundant bandwidth) tends to remain processed locally. Hardware virtualization allows for the creation and set-up of service-oriented architecture (‘software as a service’) which is at the heart of DeFi. Interestingly, at the same time Moore’s law, Kryder’s law, and bandwidth growth at decreasing costs all continue to apply, providing the potential for ever greater development of machine learning and other forms of artificial intelligence (AI) 16 as well as ‘edge’ based systems, where significant amounts of independent processing takes place in the context of individual devices (for instance in the context of the Internet of Things (IoT) accessing virtual as well as local data and processing power). These trends in technology and in the intellectual processes which allow their combination and use in ever more ways are transforming finance and most everything else as well.

2. ABCD: the roots of DeFi

At the core of DeFi stand a number of new technologies best summarized with the acronym ‘ABCD’, representing the four technologies at the heart of FinTech and RegTech: A I, B lockchain (including distributed ledgers and smart contracts), C loud, and D ata (big and small); or, in another iteration, A I, B ig Data, C loud, and D LT (including blockchain and smart contracts).

Although many will be familiar with these concepts, we will give a brief account of the underlying technologies to underpin our analysis of DeFi’s policy implications.

a. Artificial intelligence

The idea underlying AI is to develop software that mimics human cognitive functions, such as ‘learning’ and ‘problem solving’. 17 AI puts data to use by drawing conclusions as to the probability of an event from prior knowledge of conditions related to the event; the greater the volume of data, the more insightful and accurate the inferences drawn from the data. 18 Machine learning is a subset of AI that uses statistical, data-based methods to progressively improve the performance of computers on a given task, without humans reprogramming the computer system to achieve enhanced performance. 19 In practice, the learning is achieved through extensive ‘practice’ with multiple feedback rounds through which the machine is told whether it has passed or failed a task.

b. Blockchain, distributed ledger technology, and smart contracts

A distributed ledger is ‘a database that is consensually shared and synchronized across networks spread across multiple sites, institutions or geographies, allowing a transaction to have [multiple private or] public “witnesses”’. 20 The sharing of data results in a database distributed across a network of servers, all of which together function as a ledger. 21 Distributed ledgers are characterized by an absence of, or minimal, central administration and no centralized data storage. They are, hence, ‘distributed’, in the sense that the authorization for the recording of a given piece of information results from the software-driven interaction of multiple participants. Coupled with cryptographic solutions, such features (decentralization and distribution across a network of computers) curtail the risk of data manipulation, 22 thereby solving the problem of having to trust third parties, specifically data storage service providers, as this is the point where the data is stored and can most easily be manipulated. 23

The modus operandi of distributed ledgers is best understood by looking at their counterpart, the concentrated ledger. Let us assume that a centralized register administered by a single entity contains all relevant data, and let us further assume that, contrary to present practice, the centralized register is not secured and thus ‘semi-distributed’ through a myriad of back-ups stored on multiple servers. That arrangement entails a number of risks. First, if the hardware where the register is ‘located’ is destroyed, the information content, as well as the authority to ascertain that it is correct, is lost. Second, disloyal employees of the database administrator or an unfaithful administrator may manipulate the information content of the register. Third, a cyber-attack may result in manipulations and data losses. 24

Distributed ledgers address these problems by raising the barrier for manipulation. The underlying technology requires consensus of many data storage points (‘nodes’). If there are n nodes (instead of one concentrated ledger) and e describes the effort necessary to break into any single server, all other conditions being equal (safety per server etc), the effort necessary to manipulate all the linked servers will be n × e rather than 1 × e .

Distributed ledgers are usually paired with a blockchain protocol. Blockchain refers to the storage of data in data bundles (the ‘blocks’) in a strict time-related series with each block linked to the previous and subsequent blocks through a time stamp as well as a number of protocols providing evidence of a user’s authority to amend the data stored. 25 The blockchain renders data corruption even harder, because a successful cyberattack would have to simultaneously corrupt not just one set of data but all subsequent data sets (ie the whole blockchain) as well as the time stamps simultaneously.

Distributed ledgers have provided fertile ground for the application of another innovation that seeks to address the problem of trust in human interactions (in particular relating to compliance with and enforcement of contracts) while at the same enhancing efficiency: smart contracts. 26 While neither smart, nor contracts in a legal sense, they are self-executing software protocols that reflect some of the terms of an agreement between two parties. 27 The conditions of the agreement are directly written into lines of code. Smart contracts permit the execution of transactions between disparate, anonymous parties without the need for an external enforcement mechanism (such as a court, an arbitrator, or a central clearing facility). They render transactions traceable, transparent, and irreversible. Processes driven by smart contracts may take place via and be recorded on distributed ledgers secured via blockchain. This particular combination is at the core of most discussions relating to DeFi. 28

c. Cloud services

DeFi, with regard to cloud computing, 29 refers to the decentralization of server capacity. Rather than using one server at one server centre, datasets can be distributed over many server centres accessible through the internet by many users located around the globe, more or less simultaneously.

Cloud computing refers to on-demand availability of data storage and processing power without the users owning or controlling the servers providing these services. Cloud computing relies on data centres operated by commercial providers; these providers rent capacity to customers, who access the capacity over the internet.

In order to provide for cloud stability in light of volatile demand and energy supply, to diversify against demand peaks, and ensure economic operations where energy costs fluctuate through the day, cloud service providers typically link server centres across different time zones, countries, and economic regions, and channel excess demand to servers where data processing capacity is cheaper, due to lower demand and energy costs.

Data are at the core of all of these innovations, resulting from the digitization of an ever-increasing range of processes: the idea of the ‘digitization of everything’ that underlies theories of the Fourth Industrial Revolution. 30 The ever-greater volume of data supports both traditional data analytics and ‘Big Data’ approaches. Big Data analytics refers to the collection and processing of data sets that are too large or too complex for traditional data processing applications. 31 Big Data applications look at massive numbers of data points and apply advanced data analytics methods to detect unexpected correlations, test expected correlations for causation, or determine the probability of a predefined pattern. 32

3. The interrelations between DeFi and ABCD

These four rapidly evolving technologies are each typically central to, because they are applied in the pursuit of, the decentralization of finance. Many decentralized financial functions utilize (i) the powerful efficiencies and cost-savings offered by AI; (ii) the superior record-keeping and efficiencies of smart contracts embedded on distributed ledgers secured via blockchain; (iii) the potentially decisive power of the algorithmic analysis of data; and (iv) cloud systems to host virtually all decentralized financial functions. 33 Each of these four technologies benefit from the ‘laws’ of technology discussed earlier, since each of these technologies individually becomes less expensive and more convenient and efficient to use—thus enabling cooperation among the multiple participants that together provide the financial services in a decentralized manner.

4. Libra as DeFi?

An example of how DeFi might manifest may prove helpful. Probably the most successful example so far is Bitcoin—in terms of its decentralization if not its financial utility. Perhaps the most significant proposal so far is the first generation of Facebook’s Libra proposal, Libra 1.0. 34 While Libra 1.0 was to start as a centralized permissioned system, it intended eventually to become a decentralized permissionless system. 35 In the Libra 1.0 structure, the consortium participants (a number of multinational firms and organizations) would function as nodes linking a myriad of Libra exchanges and wallet providers (attached to the Libra distributed ledger) to Libra holders. Libra 1.0 has been replaced by Libra 2.0, which has a similar structure, albeit in the context of a permanently permissioned network; hence it will not form an example of DeFi in its purest form but instead risks resulting in exactly the sort of centralization of power and control against which DeFi rebels.

Libra 1.0 demonstrated how in some cases it would be possible for DeFi not necessarily to mean all parts of the system must be decentralized. The structure of Libra 1.0’s node function was to be, at least initially, only partially distributed, with the blockchain operating as a private, rather than public, system. The potential liability of the large players that would function as nodes of the Libra blockchain provides an important incentive for this approach: their large balance sheets and clear localization mean they would be held liable in case of default, malfunction, and misconduct, while the many individuals relying on Libra would probably not face these risks. 36 At the same time of course, this structure would allow the early consortia members to benefit directly from their investment. For these and other reasons, by far the largest number of DLT applications in finance are structured as permissioned as opposed to permissionless systems. This, of course, now includes Libra 2.0 as well.

While the transformative potential of permissionless systems excites, the economic and legal realities in most cases—with the conspicuous exception of Bitcoin—have prevented full decentralization to date. However, efforts in this respect are at the heart of the DeFi ideal, if not its actual evolution.

Despite technological limitations of the Bitcoin design, particularly in terms of speed and scalability, DeFi enthusiasts argue that the cryptoanarchist vision which was part of the motivation for Bitcoin is now attainable: the democratization of finance.

5. ‘Democratization’ of finance

DeFi enthusiasts go beyond technical decentralization. For them, DeFi offers governance structures they perceive as the ‘democratization’ of finance, while incumbents might well view such structures as ‘anarchy’.

At the core of this claim lies a positive connotation of disintermediation (understood as disrupting incumbent financial institutions, particularly those that are very large: the ‘too-big-to-fail’ problem at the heart of the 2008 financial crisis) and of decreasing state influence and control of the financial system. Tech proponents frame the vision as follows:

Imagine a global, open alternative to every financial service you use today—savings, loans, trading, insurance and more—accessible to anyone in the world with a smartphone and internet connection. 37

At a first look, such an idea seems to be very attractive, not least from the standpoint of financial inclusion, an area where we likewise argue that digital finance has transformative potential 38 which comes from the decentralization of finance enabling the embedding of local compliance standards and customs which tend to reduce costs of access to financial services. The DeFi vision however is more than this: the objective is to develop systems which use technology to eliminate borders, jurisdiction, and the necessity of centralized control including governments. However, further analysis reveals that much larger challenges are likely to arise (discussed in sections IV and V ), which leads us to challenge whether DeFi, certainly in its purest form, is in fact desirable, without even addressing the limited likelihood of it coming to pass.

These ideas also relate to one of the other major themes emerging in finance: the idea of ‘open banking’ or ‘open finance’, to which we return in section VI .

Despite the excitement over its potential, DeFi comes with many challenges. From a legal perspective, DeFi may arguably undermine the rule of law, at least as we normally think about this from the standpoint of the Westphalian nation-state, and may also bring tech risks previously unknown and on a scale never before seen.

1. Undermining the rule of law?

In terms of the rule of law, DeFi poses a direct challenge to state-based systems, in that in its strong form (as fully decentralized finance) it seeks to eliminate the role of the state as rule-maker and enforcer. In its purest expression, DeFi thus serves as the ultimate form of ‘code is law’, with technology replacing state-based legal systems. 39 But beyond the obvious challenge of the strong form of DeFi, weaker forms of DeFi (in which some control remains with system operators) nonetheless pose major challenges for traditional geographically based, nation-state legal systems.

2. The challenges of jurisdiction, enforcement, and data protection and privacy

Three examples highlight how DeFi may be seen to undermine the rule of law: legal jurisdiction and applicable law, enforcement, and data protection and privacy.

a. Jurisdiction and applicable law

In a DeFi world of whatever form—anywhere along the spectrum from fully centralized to fully decentralized—determining the jurisdiction of courts and applicable law becomes increasingly difficult. Take, for instance, an unincorporated distributed ledger system, such as those used for Bitcoin or Ether. Private international law and civil procedural law look at the substantive claim to determine a court’s jurisdiction and the applicable law. The substantive claim regarding distributed ledgers may be based on entirely different legal concepts in different jurisdictions, including but not limited to contracts, torts, joint venture and partnership law, antitrust law, and in some jurisdictions blockchain-specific legislation. 40 Decentralization results in uncertainty as to which courts and laws apply—if any. 41

The same concern—determining jurisdiction—also extends to matters of financial regulation. While we think of finance as global, as is logical given the hub structure outlined at section II.1 , the reality is a world of individual legal jurisdictions and regulators, coordinated through a range of soft-law systems. Established approaches tend to look at the entity that provides the service, the client to whom the product is sold or services provided, or the market in which it is traded. Each of these is problematic in the age of DeFi: in a network economy multiple entities provide parts of a service and clients are similarly spread around the globe, and markets and individual providers lose importance as supervisory access and control points.

Further, technology allowing decentralization may render entity-based approaches generally less effective. 42 The often-discussed alternative—a focus on functions—may be less than convincing where the services are performed by a set of algorithms in a permissionless system, for two reasons: first, where decentralization is advanced it would require the supervision of a myriad of small contributors to the services, many of which lack the size and financial resources to pay supervision fees and many of which contribute only gradually and partially to the overall service; and, second, machine learning technologies may permanently change the nature of these functions. 43 DeFi may force us to look beyond the entities involved and concentrate supervisory efforts on the underlying technological infrastructure that ties all contributors together. In fact, more and more of the risks in DeFi projects will come from the technology connecting all relevant entities rather than simply the entities formally connected to the project.

Take the example of BlackRock’s risk management platform, Aladdin. 44 Beyond BlackRock’s own US$6 trillion in assets under management, Aladdin provides risk data, and measures and controls risk for more than US$20 trillion in assets, which is around 10 per cent of the world’s financial assets—a figure equal to four times the value of all cash in the world, 45 the annual GDP of the United States, or total US stock market capitalization. 46 About 25,000 investment professionals globally—13,000 from BlackRock and 12,000 from BlackRock’s clients—rely on Aladdin. More than 1,000 internal and external developers work continuously on the ongoing development of the platform. 47 Overall, Aladdin hosts the portfolios of 210 institutions worldwide, including some of the largest asset owners (for example, California State Teachers’ Retirement System (CalSTRS)) and competitors including Schroders and Vanguard. 48 Yet, Aladdin as such has neither entity status, nor licence nor headquarters, and thus is not directly subject to financial regulation and supervision. Aladdin is a mere set of algorithms with a server and lots of data available to be processed. 49 Aladdin is connected globally, yet owned by the asset management giant BlackRock. Technically decentralized by connecting hundreds of entities, Aladdin is economically and technologically centralized. This ensures Blackrock’s control over the strategic development of, and accountability for all of, Aladdin’s functions. 50

Imagine now a DeFi Aladdin not controlled by BlackRock: an independent data framework on which market participants could operate—developing their own applications and frameworks without any dominance of a single firm in investment and maintenance. For instance, we can envisage an open risk management platform whose code and functions are written by multiple individual programmers (instructed by multiple risk managers) developing multiple new platform functions and efficiencies. 51 This would have the advantage of generating a variety of niche risk management models for the risk managers’ choice—in addition to the standard ones Aladdin will, in any event, offer—thereby potentially reducing the systemic dimensions of model risk. 52

In case of need, regulators currently have jurisdiction over Aladdin indirectly, through the regulated entity BlackRock, as well through as the asset managers employing Aladdin. A fully decentralized, self-directing Aladdin, however, would have serious legal consequences when it came to determining which regulator and supervisory authority would be in charge. A fully DeFi Aladdin would, most likely, be located everywhere and nowhere—which would make it very difficult to ascertain jurisdiction, assign responsibility and liability rules, and penalize misconduct. Even if we rely on indirect regulation and supervision, the regulated entities will have little means to comply with the regulators’ demands: if it is a truly independent system, they might not be able to influence its operation. Supervisory requirements in relation to, for example, organization, governance, legal structure, and management are impossible if there are no staff. Where, for instance, are the headquarters of the BTC blockchain? Does BTC mining take place where the nodes are, even though each block of BTC will probably be mined in a different location? And where are the BTC wallets or the BTC beneficial owners located? Each of these criteria result potentially in different supervisory jurisdictions. The important point is there is no ‘traditional’ firm, entity, or headquarters to which financial regulation will apply; without this our regulatory agencies are likely to struggle to exert control and the salient, risk-reducing effect of law and regulation will thus be much diminished.

It has frequently been argued that DLT is not subject to law anywhere; we have made the counterargument that the likely result is that it is subject to law everywhere , with every major participant and developer potentially at risk of liability. 53 It is this dichotomy between liability and economic benefit which makes it so difficult to develop true DeFi frameworks.

b. Enforcement

Enforcement becomes problematic in the context of DeFi. For instance, financial regulation on outsourcing and delegation, as a general principle, seeks to ensure that one entity is in charge and liable for compliance with all laws and regulations applicable to that entity even where that entity relies on external service providers, and regulation generally requires entities to manage legal, concentration, and reputation risks relating to outsourcing. 54 In short, these rules create a hierarchy of liability and accountability, based on contractual rather than technical or financial relationships, where the supervised entity needs to ensure compliance from all service providers connected to it. How, in the world of DeFi, could a supervised entity enforce its oversight requirements vis-a-vis multiple, dispersed network participants that are spread around the world and subject to entirely different rules, ethics, and reputational concerns?

The core concern is not that the network participants reside in different countries, but that they are dispersed and decentralized. Non-compliance with rules in a network setting is best understood if considered as a risk of defection. The service-integrating entity internalizes all risks from services further down in the financial services value chain. As the entity most likely to be sanctioned and held liable, and in the absence of under-capitalization, it has a general interest in compliance to avoid sanctions and liability. The interests of the providers of the services that are integrated are not necessarily the same: to the extent that the provider is too financially insignificant to be sanctioned and be held liable, they fear neither sanctions nor liability. In a DeFi setting, many different providers contribute to the end product, and in the absence of collusion among the network participants, issues of causation may well erect insurmountable hurdles to liability and sanctions since the burden is on the claimant or sanctioning entity to show that the specific non-compliance of a minor contributor caused the problems at issue. For this reason, where compliance is costly the many small contributors each have a strong incentive to defect—that is, to deviate from the integrator’s general interest in complying with law, regulations, and contractual provisions. The risk of defection increases with the number of parties involved and decreases with the benefits generated by compliance for each party.

In the cross-border world of DeFi, this incentive structure creates additional difficulties. The costs of complying only with one’s own rules are lower than complying with those rules plus the rules of one or more foreign jurisdictions, due to information costs and the necessity of duplicative processes internally and externally. Regardless of how expensive or inexpensive one’s own rules and regulation, where the delegate complies with both its own and the outsourcing entity’s rules, the compliance costs of the outsourcing entity are always lower than the compliance costs of the delegate. 55

Assume two parties, X and Y, located in two different countries, with X, from a legal perspective, being the integrator and Y the contributor. While X has only its home jurisdiction costs, Y has at least the costs of X’s jurisdiction, plus its own, since compliance costs are never zero. 56 Whether Y complies then depends on Y’s benefits from Y’s function as a delegate. In a world of centralized finance, the benefits would be concentrated in X as the entity that has client access, and these benefits would be shared with Y, thus Y is compensated for compliance with X’s laws, reducing X’s benefit. 57

The problem of DeFi is that we are not talking about two entities (X;Y), but potentially dozens if not hundreds (with N referring to these multiple entities). 58 In turn, X must compensate the many entities (N) for compliance with foreign laws in order to make their compliance profitable, while we see no reason why X’s benefits would increase from doing so. In turn, either X stops cooperating with others (in which case there is no decentralized finance) or X’s profitability decreases (rendering X more likely to defect to save costs) or the many entities (N) receive less for their compliance with foreign laws, so their likelihood of defection increases. 59 In both DeFi scenarios we will see less compliance by either X or the many entities (N), that is, existing rules will be enforced less stringently than in a world of a centralized financial services value chain.

One may wonder whether scale effects in compliance offset the non-compliance effect of decentralization. If a service provider serves clients primarily from one jurisdiction with one set of financial regulation applicable, we would expect that provider to adjust its own organization to that regulatory environment of its clients. Yet, this is not the DeFi world: DeFi means cooperation on a cross-border basis ; for small firms cross-border regulatory harmonization is even less likely than for large financial institutions, further reducing scale effects in compliance. 60

On top of this comes a problem incurred by the different valuation models of the old and new economy: 61 existing financial institutions have few ways to ensure compliance and honest conduct from very large technology firms. This is due to the size, scope, scale, power, different culture, and current valuation of BigTech firms when compared to BigFinance institutions. Customers cannot credibly put a firm under pressure if that firm’s market value is many times larger than their own 62 and if they depend on the firm’s services, given very high switching costs, strong information asymmetries as to the underlying technology and service quality, and few alternatives due to high market concentration. 63 In such a dynamic, the outsourcing relationship is inverted and the tail wags the dog.

This becomes obviously even more problematic if there is no tech firm in charge of the DeFi infrastructure at all, in those— so far very rare—instances in which technological systems become self-operating, whether intelligently (in the context of AI and its ultimate expression, the singularity) or through complete automation (arguably at the heart of the DeFi ideal).

c. Data protection and privacy

Decentralization in the datafied world means that data are accessible at many points rather than one. 64 Given the cloud and DLT operate on arrays of servers rather than individual single servers, saving data in the cloud or on a DLT means spreading data over multiple servers. Data protection and privacy violations are potentially very costly to institutions relying on DeFi. 65 The argument that arises is that regardless of what data protection principles apply, any data generated will be ‘decentralized’ this way, rendering concepts of ‘data ownership’ or, more precisely, ‘effective data control’, merely theoretical. Even if there was legal standing to sue for data protection or privacy violations and data deletion, some data particles would remain—in this sense, the internet does not forget.

At the same time, in reality today, as a result of jurisdictional data requirements and data localization rules such as the EU’s General Data Protection Regulation (GDPR), we observe jurisdictional (re-)concentration of data. 66 The major cloud service providers (Amazon, Microsoft, IBM, Alibaba, Google, Apple) increasingly locate data in data centres located in an ever-increasing range of individual jurisdictions. 67 Any of these data centres ‘contains’ the data of a given client, such as a large financial institution or tech company. The end result of this interaction of technology, law, and economic incentives is not as envisaged by DeFi proponents: centralization is often at the heart of decentralization as a result of this interaction.

DeFi in both the ideal and also the reality is thus a challenge to the traditional legal role of the state, either from the standpoint of intention in the DeFi ideal or the reality of technological evolution.

3. Increasing tech risk

In addition, the very centrality of technology as the foundation of DeFi brings entirely new risks: DeFi in whatever form increases technological security risks due to tech dependency and connectivity. 68 This is the case regardless of whether one considers ‘strong form’ DeFi or ‘weak’ DeFi, or even DeFi built on centralization (eg cloud).

a. Tech dependency

The risks from the rapid growth of financial technology continue to rise while international FinTech governance lags behind. Another risk stems from the increasing mix of national security and financial stability factors in financial regulation, leading to potentially sub-optimal regulation. Finally, the ongoing concentration in crucial financial market infrastructure and the underlying tech industry furthers a tech-monoculture which facilitates cyberattacks: a weakness detected and used for a cyberattack on one network may be used to force entry into another network. 69 If one adds the interdependence due to decentralization of finance, the outcome becomes potentially very dangerous. 70

b. Connectivity

DeFi connects many servers around the globe, and these servers are owned, operated, updated and otherwise influenced by many different entities. While the network structure can reduce the risk of manipulation, as with distributed ledgers, it also enhances two other types of cyber risks. First, the number of access points to the network have multiplied. Each access point provides a cyber risk that needs to be managed. Second, many servers are connected, and new risks may come from this connectivity.

At the end of the day, any extensive DeFi system provides a huge potential vulnerability: imagine a world in which a highly successful, fully decentralized Libra provides the monetary instrument and payment system for a very large portion of the world. What if it is hacked? Or should we ask ‘when’ rather than ‘if’ it is hacked?

c. Lack of support points

If a tech operation providing material financial infrastructure experiences difficulties, it is much more difficult to organize meaningful support for a decentralized network than for a concentrated system, where technical or financial support 71 for one entity will mean that the entity providing the infrastructure has the technical or financial means to address the operational difficulties until a long-term solution can be worked out. Such technical or financial support can be through, for instance, emergency liquidity assistance, ‘lender of last resort’ facilities, deposit guarantee schemes, or, indirectly, bankruptcy protection by way of a special resolution schemes. 72

This is particularly important in crises where systems and rescue schemes are stressed. Imagine that a network function depends on a myriad of small entities cooperating across the globe and all relying on crucial spare parts—in times where travel is severely impaired it is easier to channel spare parts to a handful of firms than to dispersed network partners.

These issues suggest that the state will not be yielding to the challenge of the DeFi ideal any time soon.

As we have laid out, DeFi in its ideal form clearly brings with it a range of challenges, particularly from the standpoint of state sovereignty but also from its technological dependence. While these are likely to mean that the ideal does not become the reality, the foundational technologies are nonetheless transforming finance. At the same time, certain aspects of the ideal have real value from the standpoint of improving traditional finance. The result is that the DeFi is increasingly being assimilated into traditional finance rather than disrupting it.

The question is how to balance the challenges with the opportunities in the context of policy and regulation.

1. Balancing investor protection and technological development

The greatest amount of regulatory attention to DeFi so far has focused on the traditional concerns of money laundering, financial crime, market integrity, and investor and customer protection, particularly in the context of crowdfunding, cryptocurrencies, and Initial Coin Offerings (ICOs). We have previously argued for a functional approach in the context of addressing regulatory concerns around digital assets. 73 Facebook’s Libra proposal has also dramatically increased the relevance of considerations of systemic risk as well as of challenges to state sovereignty in monetary affairs. In each case, traditional regulatory approaches are being extended as necessary in order to address new innovations.

There are a number of aspects of DeFi regulation, however, that are proving challenging.

From a conceptual framework, one problem is developing appropriate approaches to regulation for a truly decentralized system that is, at least in the beginning, centralized in the hands of its developers. In the US, a proposal from Hester Pierce of the US Securities and Exchange Commission (SEC) highlights the challenges in this respect:

Many crypto entrepreneurs are seeking to build decentralized networks in which a token serves as a means of exchange on, or provides access to a function of the network. In the course of building out the network, they need to get the tokens into the hands of other people. But these efforts can be stymied by concerns that such efforts may fall within the ambit of federal securities laws. The fear of running afoul of the securities laws is real. Given the SEC’s enforcement activity in this area, these fears are not unfounded. 74

Commissioner Pierce suggests a viable potential approach, built on a ‘safe harbour’ for centralized, yet DeFi-to-be platforms which can be secured through a series of steps designed to balance investor protection with the needs of innovation in seeking to build decentralized systems, including for finance. While Commissioner Pierce’s proposals are seemingly yet to attract majority support within the SEC, they highlight the difficulties in striking a balance between innovation and protecting passive, potentially vulnerable constituencies.

2. Enhancing regulatory cooperation

The challenges are even greater in the cross-border context. Since determining jurisdiction is far from easy, DeFi projects tend to fall under many different state, federal/national, and regional licensing and supervision regimes. Each potentially involved regulator will impose additional conditions reflecting its own perspective, mandate, and powers. 75 This will result in a mixed and potentially fragmented regulatory framework which will both limit some of DeFi’s advantages and at the same time make it difficult to address its risks. A highly fragmented regulatory landscape is also likely to lead to inefficient regulation that is in some respects very strict and in others too lax, increasing risks of regulatory arbitrage and gaps.

The better alternative is substituted compliance, 76 or in European law terms, equivalence. 77 Once a DeFi project is licensed in one jurisdiction, other jurisdictions could recognize its supervision in the home jurisdiction and reduce their own requirements, for instance on capital reserves, risk management, and IT infrastructure (this is on the basis that the financial legislation and supervision in the home country has substantially the same effects as the legislation and supervision in the host country). While simple in theory, substituted compliance/equivalence has proven difficult to achieve in practice, outside the specific context of the EU’s passporting regime. The most significant developments have occurred in the context of over-the-counter (OTC) derivatives (in response to problems observed in conflicts resulting from differential implementation of internationally agreed approaches to issues which arose in the 2008 financial crisis). Conflicts between OTC derivatives regulations are a major concern of discussions at the G20 and FSB level about fragmentation. 78 At the same time, the EU’s move towards rule-based access for financial institutions from third countries has been stalled by Brexit.

In the context of banks and financial market infrastructure, however, regulators since the 2008 global financial crisis and the 2010 Eurozone debt crisis have largely abandoned the home regulator approach; even the EU has moved in the form of the European Supervisory Authorities (ESAs) European Securities and Markets Authority (ESMA), European Banking Authority (EBA), and European Insurance and Occupational Pensions Authority (EIOPA), and in the Eurozone with the European Central Bank, towards a regional supervisor as opposed to the pre-crisis structures of lead home regulators. This is another of the fundamental issues that arises in international discussions of fragmentation.

Given that substituted compliance comes with a loss of sovereignty of the respective regulator and supervisory authority, in the current crisis of multilateralism it would be overly optimistic to expect any sudden change to the unilateral approach. It is increasingly difficult to compromise on basic questions relating to substituted compliance, for instance which supervisory authority is in charge and the scope of the substitution: while the EU has expanded the equivalence principle into the field of data protection, with GDPR allowing data transfer into countries that have equivalent data protection regulations and enforcement as the EU, 79 strong data protection regulations are largely absent in the US and China, 80 to name but two important jurisdictions. Even jurisdictions friendly to substituted compliance hesitate to rely on this concept for providers that service retail clients.

At the same time, cooperation based on Memoranda of Understanding (such as those brokered by IOSCO 81 ) does not result in the same level of cost reductions for the supervised entities and come with high costs for smaller authorities needing to maintain multiple memoranda with multiple authorities over multiple sectors and activities worldwide.

Notwithstanding the former, regulators are encouraged to intensify cooperation on DeFi matters. This should include working groups or supervisory colleges on global DeFi projects, to counter the collective intelligence of DeFi users with the authorities’ collective insights. In fact, global DeFi systems could warrant the adoption of a specific global cooperation framework among regulators, as is under discussion for global stablecoins 82 and for global payment systems. 83

A specific global approach for addressing global DeFi systems may be appropriate and in fact necessary from both the DeFi and regulatory standpoint. Such an approach could be based on IOSCO’s Multilateral Memorandum of Understanding, laying out common minimum approaches as a precondition for joining, perhaps combined with supervisory college structures for systems involving multiple operators across multiple jurisdictions, of which Libra is probably the most significant potential example so far. For instance, the Libra 2.0 white paper offers explicitly such a ‘supervisory college’: a committee of regulators from the jurisdictions across which it will operate, chaired by its home regulator (in this case proposed to be the Swiss Financial Market Supervisory Authority (FINMA)).

3. Tech risk management

In addressing tech risks it will be crucial to expand the breadth of cyber incident scenarios internationally that are likely to arise from decentralization. This will ask a variety of financial and tech firms not only to assess system weaknesses and costs by way of stress tests, but also to clarify liability assignment, which may be instrumental to reducing uncertainty in cases of cyber-caused crises. In a geographically decentralized context, such stress tests have to be designed and conducted as collaborative efforts among a number of regulators.

Cooperation among mature tech and financial institutions and regulators may further the understanding of the nature and scale of risks, given that the most effective way to advance effective cyber risk and data assessments is through networks of cyber risk and data specialists exchanging best practices. 84 Regulators in this setting can be instrumental by (i) demanding cooperation, and (ii) creating the atmosphere for cooperation and exchanges of lessons learned by potentially granting leniency to institutions in case of failure if institutions have seriously and constantly contributed to cyber and data working groups prior to the failure.

4. Data, reserve, and tech localization

Regulators may respond to the new dimension of enforcement difficulties by requiring data and reserve localization.

Data localization requirements were originally developed in data protection laws to ensure a national regulator’s sovereignty over its citizens. 85 In recent years, however, financial supervisory authorities have increasingly imposed similar requirements: when a group of companies is in trouble, the data necessary to maintain crucial services in the respective country must be stored, and remain accessible, even in times of crisis and if the financial services conglomerate become insolvent. The challenge of data localization requests is to determine which data are crucial to perform the service, and where such data should be localized if many countries are involved? Take the example of Big Data applications—localization will help little if it means hiving off a small section of a big data pool that can cover only a minor part of real-world correlations. 86 These issues have been pushed forward dramatically in the context of the COVID-19 pandemic, where data collection by governments and BigTech firms is increasingly central to management of the crisis.

Banking regulators practice reserve localization in order to ensure sufficient funds for an institution’s risk coverage relating to its exposure in the regulator’s jurisdiction: this is the core of requirements for separately capitalized subsidiaries combined with TLAC (Total Loss Absorbency Capital 87 ). The additional stability generated by reserve localization, however, comes with the downside of potential under-diversification of global exposures. This can render impossible certain DeFi business models.

Take the example of the Libra Reserve. Under the Libra 1.0 white paper the Libra Reserve would hold A+-rated assets from a multitude of jurisdictions. This requires rebalancing of exposures over time, resulting in an incredibly challenging risk management process if billions of Libra holders use Libra as their main means of payment. If this risk management fails, US Libra holders may find themselves exposed to currency risks—the very risk the Libra project promised to curtail. This may explain why in the Libra 2.0 white paper, the proposed structure is individual stablecoins tied to the major currencies—USD Libra, EU Libra, Yen Libra—with a synthetic combination available. This is a much different—and economically less decentralized—proposition than Libra 1.0. 88 Libra 1.0 showed what is technically possible , but the changes reflected in Libra 2.0 were required by the attitudes of powerful regulators. The potential size of Libra/Facebook forced regulators to take action. However, many other examples of DeFi, most notably Bitcoin and, for a time, ICOs, could operate and grow without an immediate regulatory response. This is unsurprising given that regulation is costly, both in terms of money and reputation, and these costs are often only worth incurring, especially on a large scale, if the case in favour of regulation is clear. Thus some successful DeFi applications have slipped through the regulatory net and gained significant size unimpeded by financial regulation—and this likely to happen again in the future.

In addition to the incumbent methods of data and reserve localization, we propose adding a third measure: tech localization. For crisis continuity management, as for sustainability reasons, regulators could require infrastructure providers to keep crucial spare parts and tech support for the network available within the territory to secure network operations within their territory. If all regulators apply similar requirements, the network will be based on more localized tech supply and be more stable in crises which interfere with global supply chains.

Each of these examples highlights that although there are indeed challenges in addressing DeFi, there are viable regulatory approaches available, which would allow the state to assimilate DeFi, rather than face disruption.

At the same time, we suggest that exercise of centralized sovereign authority may in fact be necessary to achieving DeFi’s central objective of decentralization.

Central to DeFi is a reaction to risks of concentration and dominance. Can DeFi render regulators superfluous? This is part of the DeFi vision but is not easy to attain. While DeFi proponents hope it can be done, we doubt this will happen in the foreseeable future. 89 While the Pierce proposal highlighted in section V can be seen as a step in that direction, a second look reveals that the Pierce proposal follows traditional patterns of risk-based supervision: under that proposal, regulators define the minimum decentralization parameters that developers of decentralized systems must address as part of the evolution from initial creation to full decentralization. Only rules addressing risks associated with the centralized function of an ‘issuer’ cease to apply with sufficient decentralization achieved. Other rules such as those on Anti-Money Laundering and Counter-Terrorism Financing (AML/CTF) and minimum disclosure continue to apply and remain to be supervised. The application of the Pierce proposal does not render regulators superfluous.

While evolving from different sources, the objectives of DeFi and ‘open banking’/‘open finance’ overlap. Could this be a way to address concentration and dominance in finance?

1. Open finance as antitrust

Essentially, ‘open finance’ is based on decentralized rather than centralized control of data, in particular the data relating to individuals and its potential for use in finance.

Open finance, as a policy goal, is justified on pro-competition and other regulatory grounds, as it addresses market efficiency and antitrust concerns stemming from economies of scale and networks effects in the data economy, where the size of the data pool determines competitive strength 90 and where technology firms like Amazon, Google, Alibaba, and others have foregone profits for years to build platforms with overwhelmingly dominant market share. At the core of all this are network effects plus economies of scope and scale, which combine to give rise to the potential for industry concentration and dominance. Data-driven industries often naturally gravitate towards ‘winner takes all outcomes’, with the potential for significant benefits followed by significant negative externalities. American tech and data markets have tended towards oligopoly or monopoly over time, 91 a process which seems to have occurred in China as well. Both jurisdictions have allowed commercial enterprises to acquire control of large consumer and other data pools. The core assets of those platforms are the pools of data relating to shoppers and merchants. Once these data pools are assembled they can be used for targeting advertising, undercutting prices, offering new tailored services more quickly to more clients, or data analysis in all markets where superior information benefits profits.

Legal competition and antitrust scholars argue that where investors reward growth over profit, predatory pricing becomes highly rational and, even when costly, is a worthwhile strategy since it ensures monopoly rents due to control over the essential infrastructure on which their rivals depend: ‘This dual role also enables a platform to exploit information collected on companies using its services to undermine them as competitors.’ 92 This has prompted the policy demand to treat data as a product, since information and data, although different from traditional goods and services, pose problems familiar to antitrust law, such as monopolistic behaviour and collusion. 93 Treating data as a product becomes a particular consideration in avoiding potential reductions in innovation and therefore in long-term growth and development.

These debates are increasingly strong in the EU, the US, and across the world, even in China. 94 To our knowledge, only the EU, the UK, and Australia have so far adopted open banking (with the EU’s revised Payment Services Directive (PSD2) for payment services the first closely related initiative) but many countries around the world are working towards implementing such strategies or at least analysing them closely. 95

What role does open banking/open finance play in DeFi—and the converse—what role will DeFi play in open banking/open finance? In essence, open banking facilitates greatly increased levels of democratization of finance by enabling participants to simply, swiftly, and safely provide their raw financial data to competitors of their current financial services provider. 96 This should support the growth of many new competitors in financial services. Most financial ecosystems are dominated by a relatively small number of very large banks or, in the case of China, very large tech companies providing financial services. Open banking should result in a far greater range of product offerings and ecosystem participants. These new participants will not be burdened with legacy systems and many will utilize more cost-efficient decentralized systems. As part of DeFi, DLT in particular could be used to decentralize and democratize access to data, thereby reducing concentration and control of the data both by the state and by BigTech / BigFinance. Open data and DLT aim for much the same things and DLT-based open data infrastructure will form the tech core of DeFi.

2. Countering pro-concentration effects

DeFi relies, to a large extent, on data, processing, and storage power distributed across the globe over many servers and re-concentrated for purposes such as bundling liquidity and Big Data applications. Promoting DeFi as such may thus be too simple an approach—rather we need to ask which parts of the financial services chain should be decentralized and which parts (re)concentrated.

Three data-related factors together may lead to friction in the market for financial services, preventing private ordering from leading to socially optimal outcomes in the sense that market forces ensure competition among services providers. These factors are traditional economies of scale, data-driven economics of scale, and network effects. 97 The argument is that DeFi is different because it is decentralized, with core infrastructure neither owned nor controlled by any participant.

In this regard, open data (or open finance) is a two-edged sword. While the EU (with GDPR and PSD2) has required the financial industry to develop appropriate systems for data management and limited the use the industry can make of pooled data (thereby reducing the advantages of traditional financial institutions through their data pools), it has also driven the standardization of data processes outside of finance—potentially making for a larger data pool and enabling new entrants to potentially access more data of their individual customers. In other words, data are now more freely accessible and transferable than ever before. Large technology companies know well how to make use of the new rights to data transfer—much more so than do new entrants, with access to customers limited by budgets and resources. This could prompt utterly unexpected results. While PSD2 and GDPR were originally designed to curtail the power of data behemoths, the eventual outcome of these two groundbreaking initiatives may well be less competition due to the greater concentration of data in the hands of the few. 98 As a result, it may be necessary for regulators to impose open data requirements only on firms with a potentially dominant position, regardless of whether they are financial institutions or tech firms.

Nonetheless, requirements for open data/open finance fit well with the DeFi objectives of democratization and decentralization, albeit on the basis of state regulation. At the opposite extreme, DeFi infrastructure could be provided directly as a sovereign function—an idea that is being increasingly advanced in discussions of central bank digital currencies. 99

3. Nationalization of core infrastructure

Government development, provision, control, or even nationalization of core DeFi infrastructure may be necessary, as radical a step as the latter may initially sound. If this happens, the claims of decentralization will be utterly upended as DeFi will have had the opposite effect of its professed mission to reduce government control.

First, nationalization leads to informational advantages as to what data and financial streams are processed via the network. Second, the public stakeholder can force upon the network the cybersecurity measures that it deems necessary. Third, setting and enforcing data and reserve localization by legal means and supervisory tools become less important—the public stakeholder could simply (re-)arrange the systems architecture to meet its localization requirements. Finally, the public stakeholder could apply all tools available to address pro-concentration effects, given that public stakeholders are less driven by the need to make profits.

Naturally, nationalization can take various forms, ranging from taking a stake, co-management, and public coordination by a regulator or central bank to full ownership of a decentralized system or network. The range of potential structures ranges from something like SWIFT to domestic real-time gross settlement (RTGS) systems, faster payment systems, property registries, and central bank digital currencies. For DeFi the first variant—a public-private partnership where a public authority assumes a node function 100 —is probably most advisable in many cases, given that full ownership would require reconcentration and create a new single point of failure, thereby removing key benefits of decentralization.

While national operation or control of crucial financial market infrastructure sounds radical, it is, in fact, far from it. For example, the US Federal Reserve currently functions as operator of the National Settlement Service (NSS), the Fedwire® Funds Service, and—together with the Electronic Payments Network (EPN)—the Automated Clearing House (ACH) system, through which depository institutions send each other batches of electronic credit and debit transfers. 101 Further, the US Federal Reserve has committed to develop and operate the FedNow Service, a real-time payment and settlement service expected to start operations in 2023. 102 Other examples include the European Central Bank’s payment-vs-delivery system Target-2-Securities, which ensures that the transfer of securities and derivatives can occur among local and global custodians and central securities depositaries, 103 as well as the Bank of England’s CHAPS system. 104

In the DeFi space, a number of initiatives that are nationalizations in function, if not in name, can be found. For example, the Unified Payments Interface (UPI) that introduced real-time settlement in inter-bank payments in India was developed by the National Payments Corporation of India and regulated by the Reserve Bank of India. Designed to support direct payments on a mobile platform, it has reached more than 800 million transactions per month and is now developing cross-border linkages. 105 India’s UPI has become the role model for networked mobile finance, 106 leading to similar initiatives around the world. With the UPI, the Indian central bank has acquired control over the technological link between all payment providers and its clients; any new institution can link itself to the network by using the UPI, thereby breaking the control of incumbent financial institutions and enabling innovation.

Another example is provided by the People Bank of China’s plan to introduce a new ‘Digital Yuan’—the Digital Currency/Electronic Payment (DCEP) project at least partially in response to initiatives such as Facebook’s Libra. 107 Finally, we are seeing an increasing range of DLT-based corporate, securities, secured transactions, and other forms of property registries, providing the decentralized infrastructure for a wide range of financial and economic activity but under the overall supervision of governments, public actors, or public-private partnerships.

Thus, despite the anti-government ideal, it may well be that the government is in fact necessary to achieve democratization and decentralization.

4. RegTech and embedded regulation

Finally, in looking at regulation and DeFi, a real opportunity may come in the form of RegTech—the use of technology for regulatory compliance, monitoring, and supervision (sometimes called ‘supervisory technology’ 108 ), and infrastructure and system design. 109

In order to strengthen supervision and enforcement in the context of decentralization, competent authorities should design technology-based regulatory systems and systems of supervision. Regulatory requirements could be embedded technically into DeFi systems in order to use the same framework to embed systems to achieve regulatory objectives as part of the authorization requirements inherent in DeFi development.

This could take the form, for instance, of ‘ embedded supervision ’, that is, ‘a regulatory framework that provides for compliance in tokenized markets to be automatically monitored by reading the market’s ledger, thus reducing the need for firms to actively collect, verify and deliver data’. 110 Embedded supervision can thus be seen as an automated form of compliance, monitoring, and supervision, using the system itself to implement, monitor, and enforce compliance requirements.

For DeFi, we suggest an expansion of this idea: ‘embedded regulation’. 111 Under an ‘embedded regulation’ approach the key regulatory objectives of market integrity, market conduct, and financial stability are included as part of the design of any DeFi system; supervision is but one part of an effort to achieve the former. Beyond the service as such, any system’s architecture should include systems of transparency, disclosure, compliance, etc. In other words, a properly designed DeFi system should implement such features as part of its own automated structures, requiring input of certain data, assurances of quality, and other traditional forms of gatekeeping necessary for proper market functioning. This comes, naturally, with limited ability to override the systems’ limitation. For instance, we could envisage that certain types of conduct and certain combinations of conduct are not possible at all, while others are possible only with the supervisors’ consent, which in the DeFi world means the consent of many supervisors—a high barrier. At the same time, certain risk factors may be modified by supervisors while the system is running—basically a live systemic risk control.

Embedded regulation could also serve as the basis for addressing a range of cross-border collaboration issues: if data spread over many nodes of a given DLT are accumulated, sorted, and pooled by several supervisory authorities across several countries, re-concentration on the side of supervisors, collaborating in an embedded regulation platform, could offset some of the disadvantages with regard to determining jurisdiction and enforcing financial and data regulations.

The end result, however, may be that the objective of decentralization in fact requires an external guarantor—the platform where the regulation is embedded and that facilitates supervisory cooperation.

Looking forward, a number of initial conclusions are possible.

Increasing processing, storage and bandwidth capacity are enabling the potential for the decentralization of finance, while AI, blockchain, cloud and data provide the technological enabling environment for DeFi.

At the same time, by connecting multiple small actors decentralization may facilitate the creation of efficient scale with regard to data and liquidity pools that in the past has justified the regional or global clustering of services in financial centres and the pooling of both through large balance sheets. Decentralization may thus undermine some of the bundling activity performed by intermediaries. This trend is likely to be at most partial. In other words, decentralization will probably see more diverse and competitive financial services ecosystems, and reduce the centrality of the role of financial hubs, which will be to the good, but it will not remove the considerable data advantages enjoyed by the largest tech platforms such as Aladdin’s Blackrock in the US or Ant Financial in China.

Yet, DeFi, in its purest form, cannot meaningfully exist within a properly regulated setting, given that decentralization is no panacea—quite the opposite. The problem of pure DeFi is ‘the tragedy of the commons’. 112 As Aristotle said about children, and Milton Friedman adapted for the overall economy, ‘when everybody owns something, nobody owns it, and nobody has a direct interest in maintaining or improving its condition’. 113 Wherever technical and economic decentralization is taking place, incentives to invest in the sustainable development of a technology or business model potentially vanish: this is one of the core focuses of the economics discipline which is increasingly developing around theories of design of such systems.

DeFi also raises accountability and enforcement issues around issues of both public and private ordering. Most notably, difficulties of establishing standing to sue and of determining the applicable law and jurisdiction of regulators, supervisory authorities, and courts, and the difficulties of establishing how many clients or counterparties are located in a given jurisdiction, all undermine the rule of law in financial services. But then again, to some extent that is one of the major objectives of DeFi.

In reality, it is highly likely that both economic and legal factors explain why efficient DeFi can never be total, but at best partial: where parts of the financial services value chain are decentralized there will be a reconcentration of a different (but possibly less regulated, less visible and less transparent) part of the value chain, with cloud computing and BigData pools providing a vivid example. In this sense, real-world DeFi potentially increases concentration effects somewhere else in the financial system and introduces further dimensions of cyber risk from tech dependency and interconnectivity.

Law thus faces real challenges from DeFi. If DeFi is to work in its ultimate expression, the rules governing it will need to be embedded in the system. This is the ultimate opportunity for RegTech and possibly for building better markets through technology. Beyond this, law must adapt to the challenges of DeFi. Tools include those designed to enhance cooperation of competent authorities, enhance tech risk management, require data and reserve localization, require RegTech to strengthen financial supervision and enforcement, and mandate open data and open access to services where data economies lead naturally, as in other forms of core infrastructure, to reconcentration. These tools may well require a central role for government in monitoring and potentially controlling the central underlying systems: ironically, realization of the DeFi dream may well require government intervention. Given that DeFi will come with reconcentration somewhere in the value chain, this reconcentration enables, justifies, and requires control over the DeFi systems, with DeFi supervision to focus on these new point(s) of failure.

See Fabian Schär, ‘Decentralized Finance: On Blockchain- and Smart Contract-based Financial Markets’ (2020) < https://ssrn.com/abstract=3571335 > accessed 20 August 2020 (‘Decentralized Finance (DeFi)…generally refers to open financial infrastructures built upon public smart contract platforms, such as the Ethereum blockchain.…In contrast to the traditional financial sector, DeFi does not rely on intermediaries and centralized institutions. Instead, it is based on open protocols and decentralized applications (DApps)’); Yan Chen and Cristiano Bellavitis, ‘Decentralized Finance: Blockchain Technology and the Quest for an Open Financial System’ (2020) 13 Journal of Business Venturing Insights (forthcoming 2019) (‘Blockchain technology reduces transaction costs, creating a new paradigm for decentralized business models, which has led to the emergence of decentralized finance’); Robert Leonhard, ‘Decentralized Finance on the Ethereum Blockchain’ (2019) < https://ssrn.com/abstract=3359732 > accessed 20 August 2020 (‘This essay proposes an alternative form of financial planning that circumvents dysfunctional governments and insolvent banks. This alternative is referenced in online parlance as “decentralized finance.” The decentralized aspect derives from its use of the 6 blockchain protocol, which powers cryptocurrencies’).

This view is confirmed by technologically oriented websites, see BitKom, ‘Decentralized Finance (DeFi)—A new Fintech Revolution? The Blockchain Trend explained’ (2020) < https://www.bitkom.org/sites/default/files/2020-07/200729_whitepaper_decentralized-finance.pdf > accessed 20 August 2020 at 4 (‘DeFi refers to an ecosystem of financial applications that are built on top of a blockchain. Its common goal is to develop and operate in a decentralized way—without intermediaries such as banks, payment service providers or investment funds—all types of financial services on top of a transparent and trustless blockchain network’); EthHub, Decentralized Finance < https://docs.ethhub.io/built-on-ethereum/open-finance/what-is-open-finance > accessed 20 August 2020 (‘Decentralized Finance (a.k.a. “DeFi” or “Open Finance”) refers to a number of decentralized protocols building open financial infrastructure. These protocols are valuable because they’re creating the necessary plumbing to enable anyone in the world with an internet connection to access self-sovereign, censorship resistant financial services’).

See for cryptoassets, specifically, Angela Walch, ‘Deconstructing “Decentralization”: Exploring the Core Claim of Crypto Systems’ in Chris Brummer (ed), Crypto Assets: Legal and Monetary Perspectives (Oxford University Press 2019) 39, 49.

Decentralization with a focus on financial regulation has been, to our knowledge, not previously discussed from a legal perspective. Similar concerns were raised, however, in the context of blockchain-based cryto assets. See, for instance, Walch (n 2) 47–51 (starting with the statement that ‘no one knows what decentralization means’, describing a number of features of decentralization, and concluding (at 67) that the fuzziness of the term ‘decentralized’ has significant implications for law making as it furthers unsubstantiated conclusions.) We share Angela Walch’s concern, yet see merit in analysing decentralization as a real-world phenomenon in finance (as we do in this article), in contrast to using it as a descriptive term for a certain technology or application (as many do for cryptoassets). See also Wulf A Kaal, ‘Decentralization—Past, Present, and Future’ (2019) University of St Thomas (Minnesota) Legal Studies Research Paper No 19–23 < https://ssrn.com/abstract=3411897 > accessed 20 August 2020 (engaging in a general analysis of the impact of decentralization on commerce and society and arguing that ‘no two minds will agree on a common definition or scope and scale of decentralization’ before stating that ‘decentralization is not synonymous with partnership, delegation, de-concentration, disassortative, devolution, circulation’, and that ‘[d]ecentralization is not the addition of hierarchical levels in a centralized organization’ nor ‘just the redistribution of centrally organized authority or redistribution of centrally collected revenue’ nor ‘the delegation of centralized authority to managers on all levels of an organization’).

Raphael Auer, ‘Embedded supervision: how to build regulation into blockchain finance’ BIS Working Paper 811 (2019) < https://www.bis.org/publ/work811.htm > accessed 20 August 2020.

See for instance Schär (n 1) (detailing tokenized applications); Chen and Bellavitis (n 1) (relying on specific examples), Leonhard (n 1) (analysing opportunities to decentralize on the Ethereum blockchain).

Douglas W Arner, ‘The Competition of International Financial Centres and the Rule of Law’ in K Meesen (ed), Economic Law as an Economic Good (Sellier 2009) 203.

Arner (n 6).

See Deloitte, FSIReview: Driving FinTech Innovation in Financial Services Issue 13 (November 2016) 2 < www2.deloitte.com/content/dam/Deloitte/sg/Documents/financial-services/sg-fsi-fsireview-issue13-fintech.pdf > accessed 20 August 2020; ICAEW, ‘Fintech Innovation: Perspectives from Singapore and London’ (2018) 3 < https://charteredaccountantsworldwide.com/wp-content/uploads/2018/12/isca-icaew-fintech_innovation_perspectives_from_singapore_and_london-final.pdf > accessed 20 August 2020.

DW Arner, Financial Stability, Economic Growth and the Role of Law (Cambridge University Press 2007).

See K Pistor, The Code of Capital (Princeton University Press 2019).

RP Buckley and DW Arner, From Crisis to Crisis: The Global Financial System and Regulatory Failure (Kluwer Law International 2011).

According to the prediction by Intel’s founder, Gordon Moore, in 1965 (referred to as Moore’s law), the number of transistors that could be fixed per square inch on integrated circuits doubles every two years, while the costs are halved. Moore’s law predicted an enormous increase in data processing capacity. See Gordon E Moore, ‘Cramming More Components onto Integrated Circuits’ (1965) 38(8) Electronics 114.

Mark Kryder was Seagate Corp’s senior vice president of research and chief technology officer who focused on information storage throughout his life. Former CNN journalist Chip Walter honoured Mark Kryder’s lifetime achievement in an article highlighting the rising hard-disk capacity against the background of rising processor capacity (referred to as Moore’s law: see n 12). See Chip Walter, ‘Kryder’s Law’ (2005) 239(2) Scientific American 32.

See CA Eldering, ML Sylla and JA Eisenach, ‘Is there a Moore’s law for bandwidth?’ (1999) 37 IEEE Communications Magazine 117; KG Coffman and AM Odlyzko, ‘Internet growth: Is there a “Moore’s Law” for data traffic?’ in James Abello, Panos M Pardalos and Mauricio GC Resende (eds), Handbook of Massive Data Sets (Springer 2002).

See, for these technical preconditions, Scott Kipp, ‘Exponential Bandwidth Growth and Cost Declines’ Network World (10 April 2012) < www.networkworld.com/article/2187538/exponential-bandwidth-growth-and-cost-declines.html > accessed 20 August 2020.

See Dirk A Zetzsche and others, ‘Artificial Intelligence in Finance: Putting the Human in the Loop’ CFTE Academic Paper Series 1/2020 < https://ssrn.com/abstract=3531711 > accessed 20 August 2020.

See Stuart J Russel and Peter Norvig, Artificial Intelligence: A Modern Approach (3rd edn, Pearson 2016) (defining AI as devices that perceive their environment and take actions that maximize their chances of successfully achieving their task and describing the origin of the term AI in the Turing Test where ‘a computer passes the test if a human interrogator, after posing some written questions, cannot tell whether the written responses come from a person or from a computer’, and defining six core capabilities that together compose most of AI, including natural language processing, knowledge representation, automated reasoning, machine learning, computer vision, and robotics). The seminal work on AI is of course Alan M Turing, ‘Computer Machinery and Intelligence’ (1950) 49 Mind 433.

Russel and Norvig (n 17) 495–99.

Russel and Norvig (n 17) 693–859 (describing the training methods).

World Economic Forum, ‘Innovation-Driven Cyber-Risk to Customer Data in Financial Services’ White Paper 5 (2017) 6 (Figure 2) < www3.weforum.org/docs/WEF_Cyber_Risk_to_Customer_Data.pdf > accessed 20 August 2020.

See David Mills and others, ‘Distributed Ledger Technology in Payments, Clearing, and Settlement’ Washington: Board of Governors of the Federal Reserve System, Finance and Economics Discussion Series 2016-095 (2016) 10–11 < https://doi.org/10.17016/FEDS.2016.095 > accessed 20 August 2020.

We do not claim that distribution of ledgers is the sole instrument available to curtail data manipulation. For instance, lack of data manipulation can easily be proven in a centralized system using cryptographic techniques.

See Sinclair Davidson, Primavera De Filippi and Jason Potts, ‘Blockchains and the Economic Institutions of Capitalism’ (2018) 14 Journal of Institutional Economics 639 (arguing that blockchain technology is a new governance institution that competes with other economic institutions of capitalism, namely firms, markets, networks, and even governments); Primavera De Filippi and Aaron Wright, Blockchain and the Law: The Rule of Code (Harvard University Press 2018) 55, 136–40 (arguing that widespread deployment of blockchain will lead to tech-based business practices that could prompt a decline in importance of centralized authorities, such as governments, and urging a more active regulatory approach).

Any server can be manipulated with sufficient computing power and time (even if no other weakness in an encryption system is known to the attackers). See generally Jean-Philippe Aumasson , Serious Cryptography: A Practical Introduction to Modern Encryption (No Starch Press 2017) 10–18, 40–48.

These protocols seek to address the risk that the timestamp may be unreliable, or open to easy manipulation.

See Kevin Werbach and Nicolas Cornell, ‘Contracts Ex Machina’ (2017) 67 Duke Law Journal 313.

Smart contracts can implement and execute contractual conditions and, in this sense, certainly have legal effect, as identified by the UK LawTech Delivery Panel, Legal Statement on Cryptoassets and Smart Contracts (2019), at 8, but smart contracts cannot yet typically in practice embody all the terms of an enforceable legal contract purely in code.

See n 1 and accompanying text.

For an overview of cloud computing in the regulated financial sector see Hal S Scott, John Gulliver and Hillel Nadler, ‘Cloud Computing in the Financial Sector: A Global Perspective’ Program on International Financial Systems 2019 (July 2019).

See Klaus Schwab, Fourth Industrial Revolution (World Economic Forum 2016) 9–14 (predicting profound and systemic change due to physical, digital, and biological megatrends driving the renewal of industrial production).

See Viktor Mayer-Schönberger and Kenneth Cukier, Big Data: A Revolution That Will Transform How We Live, Work, and Think (John Murray 2013) 12–14 (predicting that big data will transform societies).

Mayer-Schönberger and Cukier (n 31) 6 (stating that the volume of information has outpaced IT engineers’ manual data handling capacity so that they need to reinvent data analysis tools; the latter will result in new forms of value creation that will affect markets, organizations, and other institutions).

Data stored ‘in the cloud’ are data stored on servers accessible from various points across the world that can be accessed and stored by many users distributed across the globe.

See Dirk Zetzsche, Ross Buckley and Douglas Arner, ‘Regulating Libra’ Oxford Journal of Legal Studies (forthcoming 2020); Libra Association, ‘White Paper v2.0’ (April 2020) < https://libra.org/en-US/white-paper/ > accessed 20 August 2020.

Libra 2.0 is no longer planning to move to a permissionless system. The Libra 2.0 white paper states:

In the first Libra white paper, we sought to achieve this goal by announcing our intention to eventually transition the network to a permissionless system. However, in the months since, a key concern expressed by regulators in a number of jurisdictions, including the Swiss Financial Market Supervisory Authority (FINMA), is that it would be challenging for the Association to guarantee that the compliance provisions of the network would be maintained if it were to transition to a permissionless network where, for example, no due diligence is performed on validators.

Rather, Libra’s intention now is to forego ‘the future transition to a permissionless system while maintaining its key economic properties’. See Libra Association (n 34).

On liability of nodes in DLTs, see Dirk Zetzsche, Ross Buckley and Douglas Arner, ‘The Distributed Liability of Distributed Ledgers’ [2018] University of Illinois Law Review 1361, 1383–86. See also Philipp Hacker, ‘Corporate Governance for Complex Cryptocurrencies? A Framework for Stability and Decision Making in Blockchain-Based Organizations’ in Phillipp Hacker and others (eds), Regulating Blockchain: Techno-Social and Legal Challenges (Oxford University Press 2019).

See Sid Coelho-Prabhu, ‘A Beginner’s Guide to Decentralized Finance (DeFi)’ CoinBase (6 January 2020) < https://blog.coinbase.com/a-beginners-guide-to-decentralized-finance-defi-574c68ff43c4 > accessed 20 August 2020.

See Douglas W Arner, Ross P Buckley and Dirk A Zetzsche, ‘Fintech for Financial Inclusion: A Framework for Digital Financial Transformation’ UNSW Law Research Paper No 18–87 (2018) 13, 18 < https://ssrn.com/abstract=3245287 > accessed 20 August 2020.

See John Flood and Lachlan Robb, ‘Trust, Anarcho-Capitalism, Blockchain and Initial Coin Offerings’ Griffith Law School Research Paper No 17–23 (2017), 19 < https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3074263 > accessed 20 August 2020; Lawrence Lessig, Code Version 2.0 (Basic Books 2006) ch 1 ‘Code is Law’ < http://codev2.cc/download+remix/Lessig-Codev2.pdf > accessed 20 August 2020.

See Zetzsche, Buckley and Arner (n 36) 1391–402.

See Matthias Lehmann, ‘Who Owns Bitcoin? Private Law Facing the Blockchain’ European Banking Institute Working Paper Series 2019/42 < https://ssrn.com/abstract=3402678 > accessed 20 August 2020.

Karen Yeung, ‘Regulation by Blockchain: The Emerging Battle for Supremacy Between the Code of Law and Code as Law’ (2019) 82 The Modern Law Review 207, where she writes: ‘The decentralized, distributed nature of public blockchains means that there is no single, centrally controlled and integrated entity which conventional legal systems can readily identify as potential bearers of legal rights and/or duties. This may generate difficulties for conventional law-makers’.

See Dirk A Zetzsche, Douglas W Arner, Ross P Buckley and Brian Tang, ‘Artificial Intelligence: Putting the Human in the Loop’ CFTE Working Paper (2020) < https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3531711 > accessed 28 September 2020.

See Dirk A Zetzsche and others, ‘Digital Finance Platforms: Towards a New Regulatory Paradigm’ University of Pennsylvania Journal of Business Law (forthcoming 2021) < www.ssrn.com/abstract=3532975 > accessed 21 August 2020.

See Will Dunn, ‘Meet Aladdin, The Computer “More Powerful Than Traditional Politics”’ The New Statesman (6 April 2018) < www.newstatesman.com/spotlight/2018/04/meet-aladdin-computer-more-powerful-traditional-politics > accessed 20 August 2020.

See Daniel Haberly and others, ‘Asset Management as a Digital Platform Industry: A Global Network Perspective’ (2019) 106 Geoforum 167, 168–170.

See Aladdin® platform overview, available on www. BlackRock.com (2020) < www.blackrock.com/aladdin/offerings/aladdin-overview > accessed 20 August 2020.

See Amy Whyte, ‘Can Anyone Bury BlackRock?’ Institutional Investor (1 October 2018) < www.institutionalinvestor.com/article/b1b672fxttfp1l/Can-Anyone-Bury-BlackRock > accessed 20 August 2020.

On Aladdin, see Zetzsche and others (n 42) 14–18.

We have outlined elsewhere that this control may itself pose problems, Zetzsche and others (n 42) 30–58.

Readers may doubt whether such a decentralized giant could develop scale and work and operate efficiently. Yet, the global applications of some open domain software challenge this doubt, with Linux’s usage in most web servers and supercomputers worldwide and LibreOffice, as two notable examples.

Model risk refers to the risk that a model does not reflect reality and potentially leads to misallocation of funds and losses if the parts of reality not reflected in the model become manifest. If all risk managers use the same model, model risk increases and can undermine financial stability. We do not claim that the open platform model erases model risk; the niche models may have their own problems, and BlackRock’s expertise and reputation may function as gatekeeper against poor modelling, but a diversity of models should at least work to reduce the systemic dimension of model risk.

Zetzsche, Buckley and Arner (n 36).

See Board of Governors of the Federal Reserve System, Division of Banking Supervision and Regulation Division of Consumer and Community Affairs, ‘Guidance on Managing Outsourcing Risk’ (2013) < www.federalreserve.gov/supervisionreg/srletters/sr1319a1.pdf > accessed 20 August 2020.

Note that the delegate’s other costs are most likely lower than the outsourcing entity’s costs otherwise outsourcing would not happen.

This holds true at least in the absence of substituted compliance—which we rarely see today.

Assume that B(X;Y) describes the shares of X and Y in the benefits, and C(X;Y) the costs of compliance of each party with the rules of their respective home jurisdiction . The fact that Y is compensated for compliance with X’s laws, reducing X’s benefit, could then be written as: B—B(Y) = B(X Y ).

Assume that N refers to the multiple entities: if B—B(N) = B(X N ) and B(Y) < B(N), then the result is B(X Y ) > B(X N ).

Note that this is independent of large penalties threatened by X’s regulator against either X or Y to N, since the threat of penalties will be factored in and make it more costly to comply, at least in theory—if X is hit by them, X will want to have a greater share leaving less for Y to N, while a threat being imposed on Y to N increases the benefits Y to N will want to have from X (and reduces X’s share).

Take the example of the US: small financial firms are often subject to state rather than federal regulation, resulting in 50 different legal environments. The same is true for other large markets, notably the EU, where due to proportionality as a regulatory maxim small financial firms are often exempted from the single European rulebook. For instance, small fund managers are exempted from European harmonized rules for alternative investment funds, pursuant to article 3 of the Directive 2011/61/EU of the European Parliament and of the Council of 8 June 2011 on Alternative Investment Fund Managers [2011] OJ L174/1 (AIFMD).

See Mark Fenwick, Joseph A McCahery and Erik PM Vermeulen, ‘The End of “Corporate” Governance: Hello “Platform” Governance’ (2019) 20(2) European Business Organization Law Review 171 (arguing that the most successful firms today operate as an intermediating platform, and that the platform model drives up valuations).

For instance, Amazon—the largest cloud provider in the world—has a market valuation of US$1 trillion while Goldman Sachs, the largest US financial institution, hardly reaches US$80 billion (as of August 2020). The former could easily purchase the latter, if their relations become an issue.

Of course, reputation may play a role, yet given that in addition to the BigTech’s reputation the reputation of the financial services firm is also at risk if issues materialize, both parties have an incentive to settle quietly, reducing the impact of reputation as a discipline-enhancing incentive.

See Financial Stability Board (FSB), ‘Decentralised Financial Technologies: Report on Financial Stability, Regulatory and Governance Implications’ (June 2019) 3–4 < www.fsb.org/wp-content/uploads/P060619.pdf > accessed 20 August 2020.

See Zetzsche, Buckley and Arner (n 36) 1375–79.

‘Regulation (EU) 2016/679 (General Data Protection Regulation)’ (2016) OJ L 119, 04.05.2016; cor. OJ L 127, 23.5.2018. For an overview of the GDPR’s approach and provisions, see Chris Jay Hoofnagle, Bart van der Sloot and Frederik Zuiderveen Borgesius, ‘The European Union General Data Protection Regulation: What It Is and What It Means’ (2019) 28 Information & Communications Technology Law 65. For an instructive overview of how to square blockchain-based decentralization with the GDPR’s requirements see Michelle Finck, Blockchain Regulation and Governance in Europe (Oxford University Press 2018) 88–116; M Finck, Blockchain and the General Data Protection Regulation , Study on behalf of the European Parliament, 24-07-2019, < https://www.europarl.europa.eu/thinktank/de/document.html?reference=EPRS_STU(2019)634445 > accessed 20 August 2020.

David Vaile and others, ‘Data Sovereignty and the Cloud: A Board and Executive Officer’s Guide’ Cyberspace Law and Policy Centre Version 1.0 (2013) 16 < www.bakercyberlawcentre.org/data_sovereignty/CLOUD_DataSovReport_Full.pdf > accessed 20 August 2020.

For a discussion of the risks of decentralized financial technologies for financial stability, see FSB (n 48) 6–7. See also Ross P Buckley and others, ‘TechRisk’ [2020] Singapore Journal of Legal Studies 35, defining ‘tech risk’ to include security, data protection and privacy, and concentration.

See Buckley and others (n 68).

Buckley and others (n 68) 16–19.

See for an overview of privileges granted to the ‘incumbent’ payment system, and the risks to clients and financial stability resulting from their lack with regard to new variants of payment systems, Dan Awrey and Kerstin van Zwieten, ‘The Shadow Payment System’ (2018) 43 Journal of Corporation Law 776, 794–95 and 796–808.

Awrey and Zwieten (n 71).

See Dirk A Zetzsche and others, ‘The ICO Gold Rush: It’s a Scam, It’s Bubble, It’s a Super Challenge for Regulators’ (2019) 60 Harvard International Law Journal 301; Douglas W Arner and others, ‘Cryptocurrencies, Blockchain and ICOs: Policy and Regulatory Challenges of Distributed Ledger Technology and Digital Assets in Asia’ in Christopher Brummer (ed), Cryptoassets: Legal and Economic Perspectives (Oxford University Press 2019).

Hester M Pierce, ‘Running on Empty: A Proposal to Fill the Gap between Regulation and Centralization’ (Chicago, 6 February 2020) < www.sec.gov/news/speech/peirce-remarks-blockress-2020-02-06 > accessed 20 August 2020.

Again, perhaps the best example of this in practice is occurring with Facebook’s Libra proposal.

See Howell E Jackson, ‘Substituted Compliance: The Emergence, Challenges, and Evolution of a New Regulatory Paradigm’ (2015) 1 Journal of Financial Regulation 169.

See on equivalence Dirk A Zetzsche, ‘Competitiveness of Financial Centres in Light of Financial and Tax Law Equivalence Requirements’ in Ross P Buckley, Emilios Avgouleas and Douglas W Arner (eds), Reconceptualizing Global Finance and Its Regulation (Cambridge University Press 2016) 393–406.

See FSB, ‘FSB Report on Market Fragmentation’ (4 June 2019) < https://www.fsb.org/2019/06/fsb-report-on-market-fragmentation-2/ > 21.

Pursuant to article 45 of the GDPR, a transfer of personal data to a third country outside the EU may take place if the European Commission has decided that the third country ensures an adequate level of protection.

See, for an overview of the approaches of China, the US, and the EU, Emmanuel Pernot-Leplay, ‘China’s Approach on Data Privacy Law: A Third Way Between the U.S. and the EU?’ (2020) 8(1) Penn State Journal of Law and International Affairs 1.

International Organization of Securities Commissions (IOSCO), ‘Multilateral Memorandum of Understanding Concerning Consultation and Cooperation and the Exchange of Information (MMoU)’ IOSCO (2020) < https://www.iosco.org/about/?subsection=mmou > accessed 20 August 2020.

FSB, ‘Addressing the regulatory, supervisory and oversight challenges raised by “global stablecoin” arrangements: Consultative document’ (14 April 2020) < https://www.fsb.org/2020/04/addressing-the-regulatory-supervisory-and-oversight-challenges-raised-by-global-stablecoin-arrangements-consultative-document > accessed 20 August 2020.

Bank for International Settlements, Committee on Payments and Market Infrastructures, Enhancing cross-border payments: building blocks of a global roadmap—Stage 2 report to the G20 (July 2020) < https://www.bis.org/cpmi/publ/d193.html > accessed 20 August 2020.

See Buckley and others (n 68) 15–16, 19.

Anupam Chander and Uyên P Lê, ‘Data Nationalism’ (2015) 64 Emory Law Journal 677.

See Nigel Cory, ‘Cross-Border Data Flows: Where Are the Barriers, and What Do They Cost?’ Information Technology and Innovation Foundation (May 2017) 7 < www2.itif.org/2017-cross-border-data-flows.pdf > accessed 20 August 2020. For a discussion of the costs of data localization, see Matthias Bauer and others, ‘The Costs of Data Localisation: Friendly Fire on Economic Recovery’ (2014) Ecipe Occasional Paper No 3/2014 < www.aicasia.org/wp-content/uploads/2017/06/OCC32014__1.pdf > accessed 20 August 2020.

TLAC refers to an international standard endorsed by the FSB, intended to ensure that global systemically important banks have enough capital and bail-in debt to minimize the risk of a government bailout.

Libra Association (n 34).

See, for the same argument in the context of Corporate Technologies, Luca Enriques and Dirk Zetzsche, ‘Corporate Technologies’ Hastings Law Journal (forthcoming 2020) < www.ssrn.com/abstract=3392321 > accessed 20 August 2020.

See European Parliament, Directorate General for Internal Policies, ‘Competition Issues in the Area of Financial Technology (Fintech)’ PE 631.061 (July 2018) 103–04 < www.europarl.europa.eu/RegData/etudes/IDAN/2019/631061/IPOL_IDA (2019)631061_EN.pdf> accessed 20 August 2020.

See Tim Wu, The Master Switch: The Rise and Fall of Information Empires (Vintage 2011) (arguing that American information industries tend to press towards monopolies). See also, on the promise and perils of technology-driven competition, Ariel Ezrachi and Maurice E Stucke, Virtual Competition: The Promise and Perils of the Algorithm-Driven Economy (Harvard University Press 2016).

See Lina M Khan, ‘Amazon’s Antitrust Paradox’ (2017) 126 Yale Law Journal 710, 803; K Sabeel Rahman and Lina Khan, ‘Restoring Competition in the U.S. Economy’ in Nell Abernathy, Mike Konczal and Kathy Milani (eds), Untamed: How to Check Corporate, Financial, and Monopoly Power (Roosevelt Institute 2016) (arguing that the harms from dominant platforms include lower income, rates of new business creation and local ownership, and outsized political and economic control in the hands of a few); see also ACCC, ‘Digital Platforms Inquiry: Preliminary Report’ (December 2018) < www.accc.gov.au/system/files/ACCC%20Digital%20Platforms%20Inquiry%20-%20Preliminary%20Report.pdf > accessed 20 August 2020.

See Mark R Patterson, Antitrust Law in the New Economy: Google, Yelp, LIBOR and the Control of Information (Harvard University Press 2017) (arguing in favour of conceptualizing information and user and use data as a product, since information and data although different from traditional goods and services, pose problems familiar to antitrust law, such as monopoly and collusion).

See Dirk A Zetzsche and others, ‘The Evolution and Future of Data-Driven Finance in the EU’ (2020) 57 Common Market Law Review 331.

A coalition of central banks have committed to work together to assess Central Bank Digital Currency (CBDC) use cases and design choices. These comprise the Bank of Canada, Bank of England, Bank of Japan, European Central Bank, Sveriges Riksbank, and Swiss National Bank. The People’s Bank of China is not a member, although its work is more progressed than that of any other central bank. Other central banks that have announced they are researching or testing use cases for CBDC include: Ukraine, France, Thailand, South Korea, Uruguay, Turkey, The Bahamas, South Africa, Eastern Caribbean Currency Union, Saudi Arabia, Marshall Islands, UAE, Brazil, Israel, Norway, Cambodia, Denmark, Ecuador, and Iceland. See Davis Polk, ‘The Federal Reserve and Central Bank Digital Currencies’ (20 August 2020) < https://alerts.davispolk.com/10/5131/uploads/the-federal-reserve-and-central-bank-digital-currencies.pdf?sid=281566df-9de6-477a-9d7e-834d74e82e20 > accessed 20 August 2020.

See Christopher C Nicholls, ‘Open Banking and the Rise of FinTech: Innovative Finance and Functional Regulation’ (2019) 35 Banking & Finance Law Review 121, 123.

See Zetzsche and others (n 34) 33–39.

See Zetzsche and others (n 42).

See on CBDCs, Bank for International Settlements, Committee on Payments and Market Infrastructures, Central Bank Digital Currencies (March 2018) < https://www.bis.org/cpmi/publ/d174.pdf > accessed 20 August 2020; Bank for International Settlements, Annual Economic Report 2020 , Ch III (‘Central banks and payments in the digital era’); Saule T Omarova, ‘Technology v Technocracy: Fintech as a Regulatory Challenge’ (2020) 6(1) Journal of Financial Regulation 75, 122–23; DW Arner and others, ‘After Libra, Digital Yuan and COVID-19: Central Bank Digital Currencies and the New World of Money and Payment Systems’ European Banking Institute Working Paper Series 65/2020 < https://ssrn.com/abstract=3622311 > last accessed 20 August 2020, all with further references.

See for a sample infrastructure Auer (n 4).

See Federal Reserve Board, ‘Automated Clearinghouse Services’ (6 January 2020) < www.federalreserve.gov/paymentsystems/fedach_about.htm > accessed 20 August 2020.

See Federal Reserve Board, ‘Press Release: Federal Reserve Announces Plan to Develop a New Round-the-Clock Real-Time Payment and Settlement Service to Support Faster Payments’ (5 August 2019) < www.federalreserve.gov/newsevents/pressreleases/other20190805a.htm > accessed 20 August 2020.

See Deloitte, ‘TARGET 2 Securities: Time to Settle’ Inside Magazine Issue 12 (June 2016) < www2.deloitte.com/content/dam/Deloitte/lu/Documents/financial-services/lu_target-2-securities.pdf > accessed 20 August 2020.

See, for an overview of CHAPS, Bank of England, ‘A Brief Introduction to RTGS and CHAPS’ (July 2019) < www.bankofengland.co.uk/-/media/boe/files/payments/rtgs-chaps-brief-intro.pdf > accessed 20 August 2020.

Andy Mukherjee, ‘India Going Cashless Could Be a Model for the World’ Washington Post (7 June 2019) < www.washingtonpost.com/business/india-going-cashless-could-be-a-model-for-the-world/2019/06/05/d8fec830-87ee-11e9-9d73-e2ba6bbf1b9b_story.html > accessed 20 August 2020.

See Advait Rao Palepu, ‘Can India’s UPI Become a Global Model? Google Thinks So’ Bloomberg Quint (14 December 2019) < www.bloombergquint.com/business/can-indias-upi-become-a-global-model-google-thinks-so > accessed 20 August 2020.

See Paul Vigna, ‘UBS-Led Group to Launch Blockchain-Based Trade-Settlement Platform’ Wall Street Journal (3 June 2019) < www.wsj.com/articles/ubs-led-group-to-launch-blockchain-based-trade-settlement-platform-11559554201 > accessed 20 August 2020.

See Luca Enriques, ‘Financial Supervisors and Regtech: Four Roles and Four Challenges’, Revue Trimestrielle de Droit Financier 53 (2017) < https://ssrn.com/abstract=3087292 > accessed 20 August 2020 (discussing this very role of technology for supervisors under the term ‘oversightTech’).

See Janos N Barberis, Douglas W Arner and Ross P Buckley (eds), The RegTech Book: The Financial Technology Handbook for Investors, Entrepreneurs and Visionaries in Regulation (Wiley 2019); Douglas W Arner, Janos N Barberis and Ross P Buckley, ‘FinTech, RegTech and the Reconceptualization of Financial Regulation’ (2017) 37 Northwestern Journal of International Law and Business 371.

See Auer (n 4) (arguing that embedded supervision would reduce compliance costs both on the side of supervisors and supervised entities).

This is an argument we have previously made in the context of ICOs, see Zetzsche and others (n 73).

See, on the original concept, William Forster Lloyd, Two Lectures on the Checks to Population (Oxford University 1833). The concept became widely known after it was used by Garrette Hardin (see Garrette Hardin, ‘ The Tragedy of the Commons’ (1968) 162 Science 1243).

See M Friedman and R Friedman, Free to Choose—A Personal Statement (Mariner Books 1990) 24.

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2024 Theses Doctoral

The Market Microstructure of Decentralized Exchanges

Jia, Ruizhe

Since Bitcoin’s inception in 2008, the spotlight has increasingly been towards its underlying blockchain technology (Campbell, 2016, Yermack, 2017, Cong and He, 2019, Chiu and Koeppl, 2019, Gan, Tsoukalas, and Netessine, 2021). The introduction of smart contracts in 2015 marked a pivotal shift, transforming blockchain from a mere payment infrastructure into a cornerstone for decentralized finance (DeFi) services, a domain where decentralized exchanges (DEXs) play a critical role. The book "DeFi and the Future of Finance" by Harvey, Ramachandran, and Santoro, 2021 presents a vision of a financial system dominated by DeFi, arguing that its decentralized nature could lead to more efficient, cost-effective financial systems than traditional centralized systems. However, transitioning from potential to reality necessitates a critical examination of the underlying market structures, particularly as they pertain to trading on DEXs. By focusing on the market microstructure of DEXs, the research presented in my thesis seeks to uncover existing inefficiencies, understand their origins, and propose solutions for more effective market designs. Chapter 1 sets the stage by exploring the background and foundational principles of blockchainand DEXs, preparing the reader for a deeper dive into their complexities. Chapter 2 highlights the challenges of the current DEX infrastructure, such as exposure to arbitrage losses for liquidity providers, and evaluates the effectiveness of design changes. Empirical evidence from the Silicon Valley Bank collapse illustrates the impact of arbitrageurs on liquidity provision. In Chapter 3, the focus shifts to the mechanics of price discovery in blockchain-based trading platforms. The study delves into how DEXs’ unique infrastructure, such as gas fee bidding and priority sequencing rules, impacts trading strategies and information dissemination. We delve into the trading strategies of informed traders within DEXs, revealing a preference for high-fee bids to signal information, employing a "jump bidding" strategy to limit competition. Finally, Chapter 4 challenges the current information settings of public blockchains, highlighting their inadequacies for trading due to issues like information leakage, frontrunning, and inefficient blockspace allocation. It evaluates the introduction of private transaction pools as a remedy to these challenges, examining their effects on allocative efficiency and overall welfare. It suggests that private transaction submission pools could enhance welfare and mitigate frontrunning risk, without eliminating it. In summary, this thesis aims to bridge the gap between the theoretical promise of DeFi and the practical challenges it faces. By investigating the market microstructure of DEXs, it provides insights into the design of more robust, efficient, and equitable financial systems operating over blockchain technologies.

• Operations research
• Blockchains (Databases)
• Exchange traded funds
• Stock exchanges

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• NCI Research Strategy

Public Perception of Decentralized Finance in Ireland: MSc in Fintech Research Project

Nalawade, Pancham Devidas (2023) Public Perception of Decentralized Finance in Ireland: MSc in Fintech Research Project. Masters thesis, Dublin, National College of Ireland.

This study explores the emerging field of Decentralized Finance (DeFi) in Ireland, with the objective of understanding public attitudes and factors influencing its adoption. Built upon the foundation of blockchain technology, Decentralized Finance (DeFi) presents a transformative shift in the realm of financial transactions by eliminating conventional intermediaries, consequently fostering a more inclusive and accessible landscape for financial services. This study aims to examine the perceived risks, benefits, and their impact on the adoption of decentralized finance (DeFi) by individuals. This study employs a combination of the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) to examine the patterns of acceptance towards technology within the realm of Decentralized Finance (DeFi). The data for this study were obtained through a survey conducted among 44 computing students from NCI. The collected data were then processed using the Python programming language and subsequently analysed using various statistical techniques, including Exploratory Data Analysis, Descriptive Statistics, and Factor Analysis. Initial results indicate a complex interaction between technological concerns and potential obstacles that shape the adoption pattern of decentralized finance (DeFi) in Ireland.

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• Department of Economics & Policy
• TUM School of Management
• Technical University of Munich

Impact of DeFi on Traditional Financial Markets

Project description.

Decentralized Financial (DeFi) services, build on public blockchain networks, are one of the most vibrant and fastest-growing technology innovations in the financial sector today. Implementing existing financial services in more efficiently as well as introducing entirely new financial possibilities, DeFi sets out to become the new global financial infrastructure.

Blockchain and Distributed Ledger Technology (DLT) allow these services to be decentralized, trustless, permissionless, transparent, and fully automated through programmable smart contracts executing transactions. This architecture makes traditional intermediary services obsolete, being a major threat to legacy players within the financial services market. The total value locked in smart contracts, taken as a key metric to measure the size in DeFi, rose from $600 million at the beginning of 2020 to $250 billion at the beginning of 2022. Compared to around $350 trillion of funds moved yearly within the traditional financial market, DeFi is still insignificant. In addition, DeFi currently faces several challenges, including regulatory issues, ease of use, as well as technical & market risks. Despite these obstacles, DeFi sets out to become a major new financial paradigm that may have a major impact on legacy players within the existing financial services market.

This project aims to obtain a better understanding of how DeFi may seed into the traditional financial service market in the (near) future. Within a broadly designed survey among (inter-)national DeFi market players as well as systematically analyzing interviews with experts in the field this research project will draw a clear picture of the current status as well as potential prospects of the DeFi ecosystem.   

Resarch Team

Christoph Gschnaidtner Christoph Gschnaidtner holds a Master of Science in Financial Mathematics and a Master of Science in the Bavarian elite graduate program Finance & Information Management, both from Technical University of Munich (TUM). He is currently a Research Fellow at the Department of Economics at the TUM School of Management, a member of the TUM Blockchain Research Cluster as well as a lecturer at the ADG Business school/Steinbeis-University. His research interests lie in the area of FX markets and the money of the future, Decentralized Finance, model calibration, and stochastic volatility models. Besides his academic career, he also has diverse working experience in the financial industry.

Dominik Haas Dominik Haas is in his final steps of the Master's program Management & Technology at TUM) His majors are Mechanical Engineering as well as Marketing, Strategy, and Leadership. During his studies, he gained professional experience in the manufacturing industry, at a Fortune 500 company, at an IT service provider, and at a fast scaling start-up. He has worked on topics including but not limited to data analysis, project management as well as corporate presentation. Currently, he is conducting research on the impact of Decentralized Finance on the financial sector as part of this research project.

Emanuel Renkl Emanuel Renkl studies behavioral and household finance with a particular focus on how fintech can increase the financial well-being of private consumers. His research is mostly based on industry collaborations in which he conducts large-scale field experiments. Before joining TUM School of Management in October 2020, Emanuel studied Quantitative Economics at Ludwigs-Maximilians-Universität München. In his Master's thesis, he applied behavioral nudges in a field experiment to nudge users of a fintech app to use a budgeting and savings tool. Prior to his Ph.D. studies, Emanuel gained practical experience in banking, consulting, and fintech.

Daniel Schlager Daniel Schlager is a Master's student at the Technical University of Munich in the Management & Technology program with a focus on Finance & Accounting. During his studies, he gained various experiences in the areas of corporate strategy, digital transformation, and banking services. Among other things, he worked for strategy departments of large corporations, in the digital product development of a start-up, and currently for a leading IT consultancy. At the latter, he focuses on technology-related innovations with a special focus on blockchain technology. In this context, he develops topics in the area of digital assets, tokenization, DeFi, and metaverse in cooperation with clients.

Contact Information

Department of Economics & Policy TUM School of Management Technical University of Munich Arcisstraße 21 80333 Munich

Contact Person: Christoph Gschnaidtner Email: [email protected] Room: 2531

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Decentralized Finance (Theses and IDPs)

💡 background, 🦾who we are, 🧠 topics of interest, 📄 requirements to any work, 📬 how to apply.

Your thesis will be part of a research project analyzing opportunities in the fast developing blockchain and decentralized finance space. Blockchain use cases are rapidly evolving in a varity of different industries, backed by increasing interest and respective investments from venture capital funds, hedge funds and tech companies.

The Chair for Strategy and Organization is focused on research with impact. This means we do not want to repeat old ideas and base our research solely on the research people did 10 years ago. Instead, we currently research topics that will shape the future. Topics such as Agile Organizations and Digital Disruption, Blockchain Technology , Creativity and Innovation , Digital Transformation and Business Model Innovation , Diversity , Education: Education Technology and Performance Management , HRTech, Leadership, and Teams . We are always early in noticing trends, technologies, strategies, and organizations that shape the future, which has its ups and downs.

There are a couple of topics available regarding DeFi - they require DeFi pre-knowledge, interest in technical analyses and willingness to conduct empirical research. Please reach out in case of interest. This thesis offer also provides you with flexibility to come up with your own research question in the DeFi-related field of your passion and interest.

The scope of the thesis will be determined based on your background (Business vs. IT) and type of thesis / project study.

• Decentralized Finance
• Business Models and Industries of the Future
• Reliable and self-driven
• Enthusiasm for Blockchain
• Strong analytical skills
• Ability to do internet and desk research, connect with practitioners, conduct expirmental studies
• Passion to learn more about the future and do research with impact

We do not want your research to gather dust in some corner of bookshelf but make it accessible to the world. Thus, we warmly encourage you to create some or all of the following:

• Infograph - visually represent some of your work (find examples here )
• Slide Deck - summarize your research and possibly present it
• Extract most important sequences from podcasts, videos, and other media
• 3-4 Tweets about the most important findings and summarizing the topic
• optional: Medium Article - let people outside the university know about your research and start your personal brand

If you are interested, please contact Eva Meyer (e-mail below) by submitting your CV and grade report. Please also briefly outline your experience/knowledge regarding DeFi and - if applicable - your tentative research idea (research question, data and methods, possible outcomes with a tentative outline all in word as *.docx)

We're greatly looking forward to hearing more about you!

👉 [email protected]