Bibliography

The global landscape has seen the advent of new technology in offering innovative financial services and products and reshaping the financial sector, namely FinTech. In this review, we discuss the literature on recent FinTech development and its interaction with both banks and consumers. We synthesize the insights it provides into two domains: credit supply and payment and clearing services. The rise of FinTech has introduced digital transformation of the “bricks‐and‐mortar” banking model and dramatically changed the way financial services are delivered. We also present several future questions and directions that are worthy of investigation for researchers and policy‐makers.

“FinTech,” a contraction of ‘financial technology,” refers to technology enabled financial solutions. It is often seen today as the new marriage of financial services and information technology. However, the interlinkage of finance and technology has a long history and has evolved over three distinct eras, during which finance and technology have evolved together: first in the analogue context; then with a process of digitalization of finance from the late twentieth century onwards; and since 2008, a new era of FinTech emerging in both the developed and developing world. This new era is defined not by the financial products or services delivered, but by who delivers them and the application of rapidly developing technology at the retail and wholesale levels. This latest evolution of Fin Tech, led by start-ups, poses challenges for regulators and market participants alike, particularly in balancing the potential benefits of innovation with the possible risks of new approaches. We analyze the evolution of Fin Tech over the past 150 years, and on the basis of this analysis, argue against its too-early or rigid regulation at this juncture.

The regulatory changes and technological developments following the 2008 Global Financial Crisis are fundamentally changing the nature of financial markets, services and institutions. At the juncture of these two phenomena lies regulatory technology or ‘RegTech’ – the use of technology, particularly information technology, in the context of regulatory monitoring, reporting and compliance.

RegTech to date has focused on the digitization of manual reporting and compliance processes, for example in the context of know-your-customer requirements. This offers tremendous cost savings to the financial services industry and regulators. However, the potential of RegTech is far greater – it could enable a close to real-time and proportionate regulatory regime that identifies and addresses risk while also facilitating more efficient regulatory compliance.

We argue that the transformative nature of technology will only be captured by a new approach that sits at the nexus between data, digital identity and regulation. The development of financial technology (‘FinTech’), rapid developments in emerging markets, and recent pro-active stance of regulators in developing regulatory sandboxes, represent a unique combination of events, which could facilitate the transition from one regulatory model to another.

The exponential growth of FinTech is forcing financial regulators around the world to reconsider how best to balance the key regulatory objectives of innovation and financial stability. This paper considers the potential role of RegTech and smart regulation in facilitating this balancing act. Financial regulators have begun to use regulatory sandboxes in many parts of the world to achieve this end, however there is a clear opportunity for a further shift towards datafied and digitized regulation.

This chapter analyzes the impact of financial and regulatory technologies on systemic risk. Over the past decade a long-term process of digitization of finance has increasingly combined with datafication and new technologies including cloud computing, blockchain, big data and artificial intelligence in a new era of FinTech (“financial technology”). This process of digitization and datafication combined with new technologies can be seen across developed global markets and also in emerging and developing markets, where the process of digital financial transformation if anything is taking place even faster than in developed markets. The result: new forms of systemic risk, with cybersecurity and technological risks now major financial stability and national security threats. In addition, the entry of major technology firms into finance – TechFins – brings two new issues. The first arises in the context of new forms of potentially systemic infrastructure (such as data and cloud services providers). The second arises because data – like finance – benefits from economies of scope and scale and from network effects and – even more than finance – tends towards monopolistic or oligopolistic outcomes, resulting in the potential for systemic risk from new forms of “Too Big to Fail” and “Too Connected to Fail” phenomena. To conclude, we suggest some basic principles about how such risks can be monitored and addressed, focusing in particular on the role of regulatory technology (“RegTech”).

Money is, always and everywhere, a legal phenomenon. In the United States, the vast majority of the money supply consists of monetary liabilities — contractually enforceable promises — issued by commercial banks and money market funds. These private financial institutions are subject to highly sophisticated public regulatory frameworks designed, in part, to enhance the credibility of these promises. These regulatory frameworks thus give banks and money market funds an enormous comparative advantage in the issuance of monetary liabilities, transforming otherwise risky legal claims into so-called “safe assets” — good money. Despite this advantage, recent years have witnessed an explosion in the number and variety of financial institutions seeking to issue monetary liabilities. This new breed of monetary institutions includes peer-to-peer payment platforms such as PayPal and aspiring stablecoin issuers such as Facebook’s Libra Association. The defining feature of these new monetary institutions is that they seek to issue money outside the perimeter of conventional bank and money market fund regulation. This paper represents the first comprehensive examination of the antiquated patchwork of state regulatory frameworks that currently, or might soon, govern these new institutions. It finds that these frameworks are characterized by significant heterogeneity and often fail to meaningfully enhance the credibility of the promises that these institutions make to the holders of their monetary liabilities. Put bluntly: these institutions are issuing bad money. This paper therefore proposes a National Money Act designed to strengthen and harmonize the regulatory frameworks governing these new institutions and promote a more level competitive playing field.

Banking, derivatives, and structured finance may attract the lion’s share of accolades and approbation in global finance—but payment systems are where the money is. Historically, payment systems in most jurisdictions have been legally and operationally intertwined with the conventional banking system. The stability of these systems has thus benefited from the unique prudential regulatory regimes imposed on deposit-taking banks. These regimes include deposit guarantee schemes, emergence liquidity assistance or ‘lender of last resort’ facilities, and special bankruptcy or ‘resolution’ processes for failing banks. These regimes have the practical effect of relaxing the strict application of corporate bankruptcy law, thereby enabling banks—and the payment systems embedded within them—to continue to perform their core payment and other functions under conditions of severe institutional stress.

Recent years have witnessed the emergence of a vibrant, diverse, and rapidly growing shadow payment system. This system includes peer-to-peer payment systems such as PayPal, mobile money platforms such as M-Pesa, and crypto-currency exchanges such as Mt. Gox. The defining feature of this shadow payment system is that the financial institutions that populate it perform the same core payment functions as banks, but without benefiting from the prudential regulatory regimes that ensure bank-based payment systems can continue to function during periods of institutional stress free from the substantive and procedural constraints imposed by general corporate bankruptcy law. This paper examines the risks that the legal treatment of the shadow payment system poses to both customers and broader financial and economic stability, along with the likely effectiveness of various strategies that might be employed to address these risks.

Financial Technologies (FinTech) lie at the heart of disruptive innovation comprising critical infrastructure for much of modern business practice and national security. Modern FinTech sectors are data driven – startup finance, commodities and investment instrumentation, payment systems, trading platforms, exchange markets, market failure regulation, underwriting and syndication, risk assessment and management, advisory services, commercial banking, transaction settlement through financial intermediaries, corporate disclosure and governance, and currencies. This paper demonstrates that most FinTech innovations, scholarship and public policy development are significantly informed by big data analysis balancing: (1) FinTech innovation incentives, (2) market failure forensics, and (3) public policy development. FinTech almost always deserves a wary eye – experience reveals that many FinTech mechanisms externalize social costs of their design flaws, opacity/obscurity and malfunctioning. Some FinTechs appear intended to skirt regulation suffering regulatory lag, the delay following the first appearance of novel FinTechs and the later development, assessment, and deployment of reliable regulatory mechanisms. FinTech policy issues span from the traditional regulation of financial markets, through systemic costs of FinTech intellectual property (IP) concerns and ultimately to national security risks imposed by the financial system’s centrality among critical infrastructures.

Automated financial product advisors – “robo advisors” – are emerging across the financial services industry, helping consumers choose investments, banking products, and insurance policies. Robo advisors have the potential to lower the cost and increase the quality and transparency of financial advice for consumers. But they also pose significant new challenges for regulators who are accustomed to assessing human intermediaries. A well-designed robo advisor will be honest and competent, and it will recommend only suitable products. Because humans design and implement robo advisors, however, honesty, competence, and suitability cannot simply be assumed. Moreover, robo advisors pose new scale risks that are different in kind from that involved in assessing the conduct of thousands of individual actors. This essay identifies the core components of robo advisors, key questions that regulators need to be able to answer about them, and the capacities that regulators need to develop in order to answer those questions. The benefits to developing these capacities almost certainly exceed the costs, because the same returns to scale that make an automated advisor so cost-effective lead to similar returns to scale in assessing the quality of automated advisors.

Historically, financial institutions have relied on trade secrets and first-mover advantages, rather than patents, to protect their inventions. For the few financial patents that were issued, conventional wisdom was that they weren’t terribly interesting or important. In our 2014 study on financial patents, we showed that banks were breaking from past patterns and increasingly seeking patent protection. We explained that financial institutions were primarily building their patent portfolios as a defensive measure — i.e., to protect themselves from infringement suits. Indeed, the finance industry successfully lobbied Congress to include provisions in the America Invents Act of 2011 that made it easier to invalidate financial patents through administrative review. Yet, two significant developments call for a revisit of our 2014 study: first, the rise of fintech and, second, the recent $300 million verdict in the first bank-on-bank patent infringement suit — USAA v. Wells Fargo. This paper explores how the rise of fintech has changed the purpose of patenting among banks, and what a possible fintech patent war would mean for the future of both the financial and patent systems in this country.

For decades our common understanding of the organization of economic production has been that individuals order their productive activities in one of two ways: either as employees in firms, following the directions of managers, or as individuals in markets, following price signals. This dichotomy was first identified in the early work of Ronald Coase and was developed most explicitly in the work of institutional economist Oliver Williamson. Recently, public attention has focused on a fifteen-year-old phenomenon called free software or open source software. This phenomenon involves thousands, or even tens of thousands, of computer programmers who collaborate on large- and small-scale projects without traditional firm-based or market-based ownership of the resulting product. This Article explains why free software is only one example of a much broader social-economic phenomenon emerging in the digitally networked environment, a third mode of production that the author calls “commons-based peer production.” The Article begins by demonstrating the widespread use of commons-based peer production on the Internet through a number of detailed examples, such as Wikipedia, Slashdot, the Open Directory Project, and Google. The Article uses these examples to reveal fundamental characteristics of commons-based peer production that distinguish it from the property- and contract-based modes of firms and markets. The central distinguishing characteristic is that groups of individuals successfully collaborate on large-scale projects following a diverse cluster of motivational drives and social signals rather than market prices or managerial commands. The Article then explains why this mode has systematic advantages over markets and managerial hierarchies in the digitally networked environment when the object of production is information or culture. First, peer production has an advantage in what the author calls “information opportunity cost,” because it loses less information about who might be the best person for a given job. Second, there are substantial increasing allocation gains to be captured from allowing large clusters of potential contributors to interact with large clusters of information resources in search of new projects and opportunities for collaboration. The Article concludes with an overview of how these models use a variety of technological, social, and formal strategies to overcome the collective action problems usually solved in managerial and market-based systems by property, contract, and managerial commands. This Article contends that the common understanding of Miranda as a direct restraint on custodial interrogation by police is mistaken. Instead, Miranda, like the privilege against compulsory self-incrimination that serves as its constitutional foundation, is a rule of admissibility. As the text of the privilege, the Supreme Court’s Fifth Amendment jurisprudence, and the Miranda majority’s reasoning all demonstrate, neither the privilege nor Miranda can be violated without use of a compelled statement in a criminal case. Miranda controls police conduct only indirectly, by requiring suppression of statements taken in violation of the Miranda rules. At least two significant consequences flow from this understanding. First, police violations of the Miranda rules alone cannot support civil lawsuits under 42 U.S.C. § 1983. Second, and more importantly, police have no constitutional obligation to comply with the Miranda warnings and waiver regime. Rather, police are free to disregard Miranda if they deem it advantageous. If the Supreme Court had fashioned a stringent Miranda exclusionary doctrine-one similar to that which applies when prosecutors compel testimony by use of immunity grants-police would have good reason to comply with the Miranda rules even absent a constitutional duty. But, the Court has done the opposite, creating a host of evidentiary incentives for police to violate those rules. Thus, it is not surprising that some police officers and departments deliberately disregard Miranda in order to benefit from those incentives. Because many federal appellate courts already have interpreted Miranda as a rule that governs only admissibility, and there is a good chance that the Supreme Court will construe the privilege accordingly when it decides Chavez v. Martinez this Term, Miranda’s future appears bleak. It is likely that the Court will signal to police that they have no constitutional duty to follow Miranda rules and, at the same time, will leave intact its decisions tempting police to violate those rules. This Article offers an alternative approach, one by which the Court squares its Miranda doctrine with its treatment of the privilege in other contexts. This proposed approach would mandate that the Court treat Miranda as a rule of admissibility but also would require that it rethink many of the decisions that entice police to violate the Miranda rules.

Nowhere has disruptive technology had a more profound impact than in financial services — and yet nowhere more do academics and policymakers lack a coherent theory of the phenomenon, much less a coherent set of regulatory prescriptions. Part of the challenge lies in the varied channels through which innovation upends market practices. Problems also lurk in the popular assumption that securities regulation operates against the backdrop of stable market gatekeepers like exchanges, broker-dealers and clearing systems — a fact scenario increasingly out of sync in 21st century capital markets. This Article explains how technological innovation not only “disrupts” capital markets — but also the exercise of regulatory supervision and oversight. It provides the first theoretical account tracking the migration of technology across multiple domains of today’s securities infrastructure and argues that an array of technological innovations are facilitating what can be understood as the disintermediation of the traditional gatekeepers that regulatory authorities have relied on (and regulated) since the 1930s for investor protection and market integrity. Effective securities regulation will thus have to be upgraded to account for a computerized (and often virtual) market microstructure that is subject to accelerating change. To provide context, the paper examines two key sources of disruptive innovation: 1) the automated financial services that are transforming the meaning and operation of market liquidity and 2) the private markets — specifically, the dark pools, ECNs, 144A trading platforms, and crowdfunding websites — that are creating an ever-expanding array of alternatives for both securities issuances and trading.

Whether in response to robo advising, artificial intelligence, or crypto-currencies such as Bitcoin, regulators around the world have made it a top policy priority to supervise the exponential growth of financial technology (or “fintech”) in the post-crisis era. However, applying traditional regulatory strategies to new technological ecosystems has proved conceptually difficult. Part of the challenge lies in managing the trade-offs that accompany the regulation of innovations that could, conceivably, both help and hurt consumers as well as market participants. Problems also arise from the common assumption that today’s fintech is a mere continuation of the story of innovation that has shaped finance for centuries.

This Article offers a new theoretical framework for understanding and regulating fintech by showing how the supervision of financial innovation is invariably bound by what can be described as a policy trilemma. Specifically, we argue that when seeking to provide clear rules, maintain market integrity, and encourage financial innovation, regulators have long been able to achieve, at best, only two out of these three goals. Moreover, today’s innovations exacerbate the trade-offs historically embodied in the trilemma by breaking down financial services supply chains into discrete parts and disintermediating traditional functions using cutting edge, but untested, technologies, thereby introducing unprecedented uncertainty as to their risks and benefits. This Article seeks to catalogue the strategies taken by regulatory authorities to navigate the trilemma and posits them as operating across a spectrum of interrelated responses. The Article then proposes supplemental administrative tools to support not only market, but also regulatory experimentation and innovation.

Europe’s road to RegTech has rested upon four apparently unrelated pillars: (1) extensive reporting requirements imposed after the Global Financial Crisis to control systemic risk and change in financial sector behaviour; (2) strict data protection rules reflecting European cultural concerns about data privacy and protection; (3) the facilitation of open banking to enhance competition in banking and particularly payments; and (4) a legislative framework for digital identification to further the European Single Market. The paper analyses these four pillars and suggests that together they are underpinning the development of a RegTech ecosystem in Europe and will continue to do so. We argue that the European Union’s financial services and data protection regulatory reforms have unintentionally driven the use of regulatory technologies (RegTech) by intermediaries, supervisors and regulators, and provided an environment within which RegTech can flourish. The experiences of Europe in this process will provide insights for other societies in developing their own RegTech ecosystems in order to support more efficient, stable, inclusive financial systems.

Around the world, regulators and policymakers are working to support the development of financial technology (FinTech) ecosystems. As one example, over 50 jurisdictions have now established or announced “financial regulatory sandboxes”. Others have announced or established “innovation hubs”, sometimes incorporating a regulatory sandbox as one element. This article argues that innovation hubs provide all the benefits that the policy discussion associates with regulatory sandboxes, while avoiding most downsides of regulatory sandboxes, and that many benefits typically attributed to sandboxes are the result of inconsistent terminology, and actually accrue from the work of innovation hubs. The paper presents, as the first contribution of its kind, data on regulatory sandboxes and innovation hubs and argues that the data so far available on sandboxes does not justify the statement that regulatory sandboxes are the most effective approach to building FinTech ecosystems. Given that regulatory sandboxes require significant financial contributions, sometimes new legislation, and intense regulatory risk management, and that sandboxes do not work as well on a stand-alone basis (i.e. without an innovation hub), while innovation hubs alone can provide more significant benefits in supporting the development of a FinTech ecosystem, regulators should focus their resources on developing effective innovation hubs, including in appropriate cases a sandbox as one possible element.

The authors examine the emergence and proliferation of stable cryptocurrencies and their uses. After evaluating the core shortcomings associated with fiat currencies, the authors highlight the benefits of stable cryptocurrencies for monetary policy making, overall market stability, and their bilateral impact on the emergence of decentralized commerce. The transition to digital currencies has already started. It is a matter of time until the use cases and applications of stable cryptocurrencies become more mainstream.

New market practices and business models are emerging around so-called stablecoins, a type of crypto asset with certain features that seek to stabilize the price of the coin. Stablecoins have the potential to offer a borderless and more accessible way to pay, addressing many shortcomings in existing payment systems around the world. Yet, these developments also raise fundamental legal issues. What questions should lawyers and financial advisors be asking to ensure risks are adequately addressed? What answers can stablecoin innovators give to financial authorities and industry stakeholders to provide comfort that there is a sound legal basis for the business models and market practices around their coin? U.S. commercial law, which is chiefly designed to support financial market activities, contains powerful principles that can usefully serve as building blocks for a foundational legal framework to uniquely advance a stablecoin’s economic purpose as a medium of exchange — allowing technologists to move fast, but safely. This Article spells out how to build such a legal basis by leveraging the core commercial law principles of (i) focusing on the principles of settlement finality, (ii) rules for adverse claims, (iii) discharge of the underlying obligation, and (iv) the concept of a security entitlement. It maps out how these principles are embodied under the U.S. commercial laws of investment securities (UCC Article 8) and of payments (UCC Articles 3, 4, and 4A). The goal in doing so is to show how innovators can incorporate novel, technology-driven market practices and business models into the existing financial law framework in a proven and effective way — how to leverage what is working today and does not need to be invented again. Awareness of the availability of these commercial law tools, and their limitations, can provide important help to stablecoin developers and market participants in managing their exposure, designing efficient financial innovations, and controlling the risk to the broader financial market.

Access to financial advice has been a matter of concern for financial regulators and policy-makers. In this age of financialisation, individuals have greater responsibility to seek private sector financial products and services in order to meet their financial needs in life. However, individuals’ needs for financial advice are often not met optimally. Advice that is compliant with regulatory requirements need not be tailor-made to individuals’ needs, and inhibiting factors such as inertia, distrust and cost all play a part in individuals’ disengagement from the financial advice industry. The article discusses a series of regulatory reforms in the UK to address issues such as distrust but such reforms entail trade-offs, such as increased cost in return for improved perceived credibility in the financial advice industry. The advent of robo-advice shows some promise in encouraging access to financial advice as it is often low-cost and easy to access at one’s convenience. However, robo-advice is at the moment a standardised and limited service that is yet far from meeting individual needs for personal financial planning. The article considers a futuristic vision of artificial intelligence that is enabled with both data and investment strategy know-how in order to deliver personalised financial advice to the mass market. The article argues that such a vision attracts changes in regulatory governance, and above all, governments should consider if personalised financial advice ought to be a public good. If so, a new scheme of public and private provision of financial advice could be fostered, with the help of technological transformations.

With the rise of cryptocurrency as a popular investment, cryptocurrency wallets and exchanges have proliferated, offering platforms that allow investors to hold and trade cryptocurrency. Because these platforms hold cryptocurrency on their customers’ behalf, they present problems associated with custody. Namely, how do investors ensure that these platforms do not misuse or mishandle their assets? And how will customer assets be treated if a platform enters bankruptcy? To answer these questions, this Note looks to the experience of broker-dealers, exploring the similarities between the problems confronting cryptocurrency platforms today and the problems that brokerdealers faced in the late 1960s. Widespread broker-dealer failures during the late 1960s revealed problems with mishandled client assets, insufficient capital, and inadequate protection of customer assets in bankruptcy. Similar problems plague cryptocurrency platforms today. This Note therefore points to the regulation of broker-dealers as a template for how to approach the regulation of cryptocurrency platforms. Looking to the regulatory responses to broker-dealer failures in the late 1960s—including the customer protection rule, net capital rule, and alternative bankruptcy regime created by the Securities Investor Protection Act—this Note proposes that a similar regulatory framework could be applied to cryptocurrency platforms.

Economics and laypeople use the term ‘firm’ differently. In explicitly defining both usages, Coase (1937) reconciles the gap between the idea that the price mechanism controls the allocation of resources within a market and the idea that conscious power, in the form of the entrepreneur, must do so. The entrepreneur embodies both initiative, or forecasting people’s desires, and management, or responding to market forces. The relationships that form when an entrepreneur directs resources define a firm. Firms may emerge when uncertainty allows buyers to dictate longer term contracts, when an entrepreneur can save marketing costs, and/or when government regulations like sales tax encourage it. Coase critiques a number of definitions of firms and explanations of their birth and growth. Usher and Dobb argue that the division of labor engenders the firm’s emergence, but the price mechanism is already an ‘integrating force in a differentiated economy.’ The real question is why the entrepreneur should replace the price mechanism as the integrating force. Knight argues that uncertainty breeds a group that guarantees wages. Coase objects for two reasons. Not only do knowledge and expertise become commodities, Knight also hypothesizes that it would be impractical for one to purchase goods or services without supervising the work. But contracts illustrate the flaw: first, expertise and knowledge can be purchased via a contract; second, purchasers don’t necessarily – and often don’t – supervise contracted labor. Thus Knight’s conceptualization cannot explain why the entrepreneur should supercede the price mechanism. Coase examines how firms grow: many assume that a firm’s size is limited if its cost curve slopes upward under perfect competition, because it will not pay for more output than can be produced when marginal cost equals marginal revenue. The proposition fails to explain not only why a market contains more than one variety of a good, but also that there may be a point at which producing a new product is less costly than an old one. Four factors determine firm growth: the cost of using the market, the cost of organizing different entrepreneurs, the number, and finally the quantity produced. These definitions approximate the firm’s organization. The question will always be whether it pays for the entrepreneur to take on additional costs and therefore grow. At the margin, the costs of organizing under the firm will equal the costs of organizing within the firm or of allowing the price mechanism to organize it. Businesses will continue to experiment, maintaining equilibrium. While equilibrium implies a static market, dynamic factors are also present; changing costs within both a firm and the larger market explain changes in firm size. This theory of moving equilibrium allows for a better understanding of the entrepreneur, who both innovates and manages. (RAS)

Through superior technology, financial technology (FinTech) firms may expand credit markets. Alternatively, consumers may substitute one credit provider for another, generating adverse selection problems for incumbent lenders. We analyze the unsecured consumer loan market and identify the influence of FinTech lending on commercial banks using a novel approach that takes advantage of regulatory restrictions for FinTech borrowers and investors. We show that high-risk FinTech loans substitute for bank loans while low-risk loans may be credit expansionary. However, the influence on banks is heterogeneous. Our results highlight the changing landscape of financial intermediation and the regulatory challenges faced by FinTech firms.

This Essay explores the barriers to deploying smart contracts in the consumer finance space: the humans themselves, existing consumer protection laws, and the other businesses which have financial contracts with consumers but that cannot deploy smart contracts. These three barriers render perfectly automated enforcement all but impossible. Nevertheless, there may be room for modifiable smart contracts in the consumer finance space – although these contracts may be only marginally more efficient than traditional contracts.

In the course of their growth and their more recent crisis, cryptocurrencies suffered from tremendous volatility. Volatility impaired cryptocurrencies’ ability to serve the needs generally associated with currencies, i.e. serve as a store of value as well as a medium of exchange and a unit of account. For this reason, developers and entrepreneurs have explored the opportunity to design “stablecoins”, stable cryptocurrencies, pegged to fiat currencies such as the US dollar and Euro. Stablecoins should in principle be stabilized recurring to collateral (in fiat currency, precious metal, or a basket of cryptocurrencies) or implementing algorithmic “seigniorage” mechanisms.

This Article analyzes stablecoins’ main characteristics, identifies their main categories, and also considers their role in cryptoeconomics and their infrastructural vocation for future developments of the distributed ledger technology. Furthermore, this Article builds on the problems affecting stablecoins, focusing in particular on: the apparent contradiction in implementing a fully decentralized system that is based on a central validator; the endemic opaqueness of auditing operations, in particular the collateral and the algorithmic stabilization mechanisms; conflict of interests emerging from stablecoins’ relationship with cryptoexchanges; and their role in the recent Bitcoin bubble. Finally, this Article highlights the regulatory uncertainty at the level of securities and commodities law that may characterize stablecoins in the same way as initial coin offerings (ICOs) and opens to the possibility that stablecoins may trigger a more active reaction from governments and central bankers in designing and effectively implementing central bank digital currencies (CBDCs). More broadly, this Article aims to highlight the factual interconnections linking ICOs, cryptocurrencies, stablecoins and CBDCs: although these entities belonging to different contexts (securities law and capital formation, payment systems, monetary policy), they are intertwined and are part of the same evolution.

We model how a cyber-attack may be amplified through the U.S. financial system, focusing on the wholesale payments network. We estimate that the impairment of any of the five most active U.S. banks will result in significant spillovers to other banks, with 38 percent of the network affected on average. The impact varies and can be larger on particular days and in geographies with concentrated banking markets. When banks respond to uncertainty by liquidity hoarding, the potential impact in forgone payment activity is dramatic, reaching more than 2.5 times daily GDP. In a reverse stress test, interruptions originating from banks with less than $10 billion in assets are sufficient to impair a significant amount of the system. Additional risk emerges from third-party providers, which connect otherwise unrelated banks.

This book covers the 6 elements of the financial system: lenders & borrowers; financial intermediaries, markets, and instruments; money creation; and price discovery.

High-frequency trading, dark pools, and the practices associated with them have come under tremendous scrutiny lately, giving rise to much hot rhetoric. Missing from the discussion, however, is a principled, comprehensive standard for evaluating such practices and the law that governs them. This Article fills that gap by providing a general framework for making serious normative judgments about stock-trading behavior and its regulation. In particular, we argue that such practices and laws should be evaluated with an eye to the secondary trading market’s impact on four main aspects of our economy: the use of existing productive capacity, the allocation of capital, the allocation of resources over time, and the allocation of risk. Three additional considerations should also be taken into account: the amount of resources consumed by the operation of the market, the market’s ability to innovate, and fairness.

More than eighty years after federal law first addressed stock market manipulation, federal courts remain fractured by disagreement and confusion about manipulation law’s most foundational questions. Only last year, plaintiffs petitioned the Supreme Court to resolve a sharp split among the federal circuits concerning manipulation law’s central question: whether trading activity alone can ever be considered illegal manipulation under federal law. Academics have been similarly confused economists and legal scholars cannot agree on whether manipulation is possible in principle; let alone on how, if it is, to address it properly in practice.

The ability to distinguish between people in setting the price of credit is often constrained by legal rules that aim to prevent discrimination. These legal requirements have developed focusing on human decision-making contexts, and so their effectiveness is challenged as pricing increasingly relies on intelligent algorithms that extract information from big data. In this Essay, we bring together existing legal requirements with the structure of machine-learning decision-making in order to identify tensions between old law and new methods and lay the ground for legal solutions. We argue that, while automated pricing rules provide increased transparency, their complexity also limits the application of existing law. Using a simulation exercise based on real-world mortgage data to illustrate our arguments, we note that restricting the characteristics that the algorithm is allowed to use can have a limited effect on disparity and can in fact increase pricing gaps. Furthermore, we argue that there are limits to interpreting the pricing rules set by machine learning that hinders the application of existing discrimination laws. We end by discussing a framework for testing discrimination that evaluates algorithmic pricing rules in a controlled environment. Unlike the human decision-making context, this framework allows for ex ante testing of price rules, facilitating comparisons between lenders.

Credit pricing is changing. Traditionally, lenders priced consumer credit by using a small set of borrower and loan characteristics, sometimes with the assistance of loan officers. Today, lenders increasingly use big data and advanced prediction technologies, such as machine-learning, to set the terms of credit. These modern underwriting practices could increase prices for protected groups, potentially giving rise to violations of anti-discrimination laws.

What is not new is the concern that personalized credit pricing relies on characteristics or inputs that reflect preexisting discrimination or disparities. Fair lending law has traditionally addressed this concern through input scrutiny, either by limiting the consideration of protected characteristics or by attempting to isolate inputs that cause disparities.

But input scrutiny is no longer effective. Using data on past mortgages, I simulate algorithmic credit pricing and demonstrate that input scrutiny fails to address discrimination concerns. The ubiquity of correlations in big data combined with the flexibility and complexity of machine-learning means that one cannot rule out the consideration of a protected characteristic even when formally excluded. Similarly, in the machine-learning context, it may be impossible to determine which inputs drive disparate outcomes.

Despite these fundamental changes, prominent approaches to applying discrimination law in the algorithmic age continue to embrace the input-centered approach of traditional law. These approaches suggest that we exclude protected characteristics and their proxies, limit algorithms to pre-approved inputs, and use statistical methods to neutralize the effect of protected characteristics. Using my simulation exercise, I demonstrate that these approaches fail on their own terms, are likely unfeasible, and overlook the benefits of accurate prediction.

I argue that the shortcomings of current approaches mean that fair lending law must make the necessary, though uncomfortable, shift to outcome-focused analysis. When it is no longer possible to scrutinize inputs, outcome analysis provides a way to evaluate whether a pricing method leads to impermissible disparities. This is true not only under the legal doctrine of disparate impact, which has always cared about outcomes, but also, under the doctrine of disparate treatment, which historically has avoided examining disparate outcomes. Now, disparate treatment too can no longer rely on input scrutiny and must be considered through the lens of outcomes. I propose a new framework that regulatory agencies, such as the Consumer Financial Protection Bureau, can adopt to measure the disparities created when moving to an algorithmic world, enabling an explicit analysis of the trade-off between prediction accuracy and other policy goals.

This article argues that when moving into fledgling credit markets – namely communities in which a significant portion of the population has never had access to formal consumer loans – fintech lending can cause significant adverse economic consequences to the public and create significant regulatory gaps that require addressing. These economic consequences include inaccurate risk-pricing as firms determine how to accurately process and use the range of information at their disposal, as well as, potential behavioral problems leading to widespread default as members of low-income communities, particularly those without a bank account (the so-called ‘unbanked’), access formal credit for the first time. Regulatory gaps emerge because intellectual silos continue to focus on consumer credit emerging from the banking sector, not fintech. This article focuses on the spread of fintech lending in Kenya since 2012 as a case study for its broader argument and examines potential starting points for developing regulatory frameworks for fintech lending.

This Article examines the applicability of the federal securities laws to digital currencies. Although some enforcement actions have been brought by the SEC, digital currency transactions remain largely unregulated. The securities laws contain a broad definition of what constitutes a security. Finding a security to exist triggers many regulatory provisions of the securities laws. There is considerable case law interpreting the now well-developed test for what constitutes an “investment contract” leading to the finding that a security exists. However, to date, there is sparse authority applying the securities laws to virtual, digital, or crypto currencies. This article examines the investment contract analysis and concludes that initial coin offerings and many, if not most digital currency transactions involve securities and therefore are subject to SEC jurisdiction and to the jurisdiction of state securities administrators. The article then outlines the regulatory consequences of applying the securities laws to digital currency transactions.

Digital assets are hot right now. Whether cryptocurrencies, like bitcoin, or initial coin offerings and tokens, this new asset class has captured the imagination of American investors. While it remains to be seen if this phenomenon has staying power, there is no doubt that these assets and their promoters have attracted the attention of the Securities and Exchange Commission. But neither Congress nor the SEC has formally elucidated which digital assets are securities and which are not.

This Article seeks to provide clarity in determining which digital assets are securities. It proposes two tests that operationalize the Supreme Court’s test in SEC v. W. J. Howey Co. The first test is the Bahamas Test, which asks whether a digital asset is sufficiently decentralized such that it is not a security. The second test is the Substantial Steps Test which is used to determine whether an investment is made with an expectation of profit. This Article takes a rules-based approach to provide clarity and begin a conversation about crafting more predictable jurisprudence and regulation in this area.

I propose both an interpretation of and an institutional optimization plan for the broad array of new Fed Liquidity Facilities announced in response to the Coronavirus Pandemic of 2020. These represent an attempt by our central bank to fund concerted state and municipal action as if it were federal action – a mode of action gone AWOL during the Trump occupation of the White House. In one sense this necessity is regrettable – tens of thousands are dying, while the need of vigorous federal governance is what prompted our Constitution in the first place. In another sense, however, the conundrum is simply the latest iteration of our republic’s perennial ambivalence over financial and political federalism alike, and accordingly yields an opportunity: That is to re-distribute our once-distributed Fed’s functionality across its more locally attentive subsidiaries, as envisaged in the Federal Reserve Act of 1913.

I propose means of immediately converting the Department of Treasury’s existing ‘TreasuryDirect’ system of freely available transaction accounts into a publicly administered digital savings and payments platform. A platform of this type is an essential public utility in any commercial society such as our own. It is additionally growth-promoting inasmuch as growth-tracking GDP is a measure of transaction volume, while transaction volume is a function of more efficient and inclusive transacting. As Congress seeks means of streamlining the payments infrastructure in a time of pandemic-induced crisis, the Treasury route recommends itself as the fastest way to digitize payments for 95% of our citizens and business enterprises. I also map means of migrating the Treasury architecture to the Fed over time once the crisis is past – as the ‘Greenback’ paper dollar itself did in the late 19th and early 20th centuries – and include my draft Treasury Dollar Act as an Appendix.

Decentralized cryptocurrencies are a new type of technology that can be used in several applications, such as transferring money, recording data, and investing. Unlike most businesses that can be invested in, decentralized cryptocurrencies do not have a specific legal entity that is responsible for consumer protection. The virtual and decentralized nature of this technology makes the application of traditional legal frameworks untenable. Furthermore, the absence of a specific legal entity makes enforcement of any new legal framework tenuous. For these two reasons, the current regulatory status of decentralized cryptocurrencies, or digital currencies, is enigmatic. This article contributes to the increasingly important discussion on the patchwork body of U.S. law pertaining to virtual currencies and blockchain technology. The main contribution of this article is to provide a systematic literature review of the governmental guidance releases, agencies, task forces, and proposed and approved bills pertaining to virtual currencies. This article explores the various definitions of virtual currencies provided by local, state, and federal governing bodies. Also, an indepth review of the enforcement actions taken is documented for the following agencies: the Commodity Futures Trading Commission, Financial Crimes Enforcement Network, Securities Exchange Commission, Department of Justice, Internal Revenue Service, and the Federal Trade Commission. The current legal status in five states that has pioneered the path to regulating Bitcoin and other virtual currencies is examined. These states include New York, California, Washington State, Florida, Hawaii, and Arizona. The difficult challenge for lawmakers is to design laws that stimulate innovation while protecting consumer welfare and satisfaction. This article hopes to help solve this challenge by synthesizing the large body of disparate literature on virtual currency regulation in the U.S.

The title of this essay is an homage to Ronald Coase’s classic work, The Nature of the Firm. For years, Professor Coase’s article has inspired corporate theorists and earned a place in the pantheon of corporate law scholarship. In this essay, I return to The Nature of the Firmto explore the fintech revolution and the supervisory challenges that aspects of this revolution have posed for regulatory authorities. Several of the examples I discuss concern the distinction between activities located within a firm and those arranged through market transactions often supplied through new and specialized fintech entities. Two others explore the changing nature of what it means to exercise managerial discretion in an era of machine learning and artificial intelligence.

Virtual Currency (VC) is an electronic currency that is neither government-funded nor backed by central bank. VC offers potential benefits over traditional currencies, including lower transaction fees and faster transfer of funds for services provided. In 2013, Financial Crimes Enforcement Network (FinCEN), defined virtual currency as “a medium of exchange that operates like a currency in some environments, but does not have all the attributes of real currency. In particular, virtual currency does not have legal tender status in any jurisdiction”. Some virtual currencies are used as a currency in online games or a digital world, however, there is no equivalent value in fiat currency for them, so named non-convertible. In the other side, a virtual currency that can be bought with and sold back for legal tender is called a convertible currency. One of the most popular type of convertible VCs is cryptocurrencies. They use security mechanisms such as cryptography for creating units of the currency and controlling the transactions. Cryptocurrency works based on Blockchain technology. Its main property is to provide anonymity for the transactions. Bitcoin, as an instance, is a cryptocurrency that has gained much attention in the market since 2009 when it was initially introduced. Since the focus of this paper is on cryptocurrency, which is a convertible virtual currency, we will use the term cryptocurrency and virtual currency or VC interchangeably with the cryptocurrency meaning.

Unlike earlier digital currencies, like e-gold, that had centralized architecture, the newer virtual currency networks are completely decentralized, with all parts of transactions performed by the users of the system. So usually cryptocurrencies use peer-to-peer technologies and no traditional financial institutions involved in transactions. This unique property provides different levels of anonymity for the users. The emergence of virtual currencies presents challenges to federal agencies responsible for financial regulation, law enforcement, consumer and investor protection. These challenges stem partly from certain characteristics of virtual currencies, such as the higher degree of anonymity they provide and the ease with which they can be sent across borders. VC also has raised concerns that they might be used to finance terrorism and to engage in other criminal activities such as money laundering and tax evasion. In this paper, we present our research on the legal issues of the cryptocurrency by analyzing the current regulations and discuss about possible solutions for the future of cryptocurrency.

As FinTech promises to increase competition for both banks and investment firms, we consider the market failures that emerge from its existence, particularly as they relate to issues of financial stability and investor protection. This chapter discusses the wave of technology-enabled disintermediation of financial services, asking how regulation should cope with the risks associated with disintermediating finance.

While regulation of financial intermediaries has been embraced because the industry is particularly prone to market failures, disintermediation has the potential to make current frameworks obsolete. The law & economics problem is twofold: 1) potential market failures, and 2) the issue of enforcement. This chapter discusses the foundations of financial intermediation and the traditional regulatory approaches to both banks and other providers of financial services. Our analysis establishes a distinction between FinTechs working outside and inside the blockchain. For the former, the crucial regulatory trade-off is between efficiency gains from innovation and regulatory arbitrage. For the latter, our analysis suggests that regulating the convertibility of cryptocurrencies into fiat money is a promising strategy not only to safeguard financial stability, but also to attract financial services to the regulatory perimeter, whenever it is efficient to do so.

The announcement by Facebook that Libra will “deliver on the promise of ‘the internet of money'” has drawn the attention of the financial world. Regulators, institutions, and users of financial products have all been prompted to react and, so far, no one managed to convince the association behind Libra to apply the brakes or to convince regulators to stop the project altogether. In this article, we propose that Libra might be best seen not as a financial newcomer, but as a critical enabler for Facebook to acquire a new source of personal data. By working with financial regulators seeking to address concerns with money laundering and terrorism, Facebook can position itself for privileged access to high-assurance digital identity information. For this reason, Libra merits the attention of not only financial regulators, but also the state actors that are concerned with reputational risks, the rule of law, public safety, and national defence.

Innovations in financial technology, or Fintech, has been ongoing for decades but has recently begun to accelerate. Soon, it will begin to outstrip the ability of regulators to keep pace. What will be the result if the financial sector becomes unregulated? One possibility — drawn from public choice economics — is that rent-seeking will be inhibited or eliminated. Rent-seeking is the distortion of law and regulation for the benefit of special interests, who expend resources to guarantee those distortions in their favor. Rent-seeking is inefficient and inhibits growth and innovation, yet it continues so long as the government has the power to intervene and play favorites in markets. As innovation accelerates, the power of regulators to effectively interfere will be significantly reduced, making rent-seeking an unprofitable venture and advancing the cause of markets and consumers.

The rise of financial technology (fintech) has the potential to provide better-quality financial services to more people. Although these enhanced financial services have arisen to meet consumer need, their regulatory status threatens that progress. Many fintech firms are regulated on a state-by-state basis even though their transactions are interstate, and they compete with firms that enjoy more consistent rules through federal preemption. This dynamic can harm efficiency, competitive equity, and political equity. This paper looks at developments in marketplace lending, money transmission, and online sales of securities in an attempt to identify situations in which greater federalization of the rules may be justified. It also considers a situation in which the federal government should abstain from intervening, even if it has the right to do so. Whether the states or federal government should take the lead in regulating fintech is an emerging and important question whose answer will affect the financial lives of consumers and investors. This paper seeks to begin a conversation about how we determine whether federalism or federalization is appropriate.

The financial regulatory system has been described as fragmented, with multiple overlapping regulators and a dual state-federal regulatory system. The system evolved piecemeal, punctuated by major changes in response to various historical financial crises. The most recent financial crisis also resulted in changes to the regulatory system through the Dodd-Frank Wall Street Reform and Consumer Protection Act in 2010 (Dodd-Frank Act; P.L. 111-203) and the Housing and Economic Recovery Act of 2008 (HERA; P.L. 110-289). To address the fragmented nature of the system, the Dodd-Frank Act created the Financial Stability Oversight Council (FSOC), a council of regulators and experts chaired by the Treasury Secretary.

At the federal level, regulators can be clustered in the following areas:

Depository regulators—Office of the Comptroller of the Currency (OCC), Federal Deposit Insurance Corporation (FDIC), and Federal Reserve for banks; and National Credit Union Administration (NCUA) for credit unions; Securities markets regulators—Securities and Exchange Commission (SEC) and Commodity Futures Trading Commission (CFTC); Government-sponsored enterprise (GSE) regulators—Federal Housing Finance Agency (FHFA), created by HERA, and Farm Credit Administration (FCA); and Consumer protection regulator—Consumer Financial Protection Bureau (CFPB), created by the Dodd-Frank Act.

These regulators regulate financial institutions, markets, and products using licensing, registration, rulemaking, supervisory, enforcement, and resolution powers. Other entities that play a role in financial regulation are interagency bodies, state regulators, and international regulatory fora. Notably, federal regulators generally play a secondary role in insurance markets.

Financial regulation aims to achieve diverse goals, which vary from regulator to regulator: market efficiency and integrity, consumer and investor protections, capital formation or access to credit, taxpayer protection, illicit activity prevention, and financial stability.

Policy debate revolves around the tradeoffs between these various goals. Different types of regulation—prudential (safety and soundness), disclosure, standard setting, competition, and price and rate regulations—are used to achieve these goals.

Many observers believe that the structure of the regulatory system influences regulatory outcomes. For that reason, there is ongoing congressional debate about the best way to structure the regulatory system. As background for that debate, this report provides an overview of the U.S. financial regulatory framework. It briefly describes each of the federal financial regulators and the types of institutions they supervise. It also discusses the other entities that play a role in financial regulation.

When policymakers summarize the challenges the European Union (EU) faces in developing a deep and liquid European capital market, a familiar pattern emerges: 1 “finance” in Europe translates as bank financing, but bank lending has remained at low levels after the financial crisis; investors suffer from home bias sticking with their member states rather than the EU; and financing conditions and many rules and market practices still remain different among the member states. The European Commission has developed a plethora of measures seeking to “strengthen the flow of private capital to growing businesses.” 2 Among these we find a modernization of the Prospectus Directive; proposals for simple, transparent, and standardized securitization; and a consumer financial services action plan. Rules on ownership of securities and on covered bonds are in the making, “fintech” has people hoping for better access to finance, and rules enabling “crowd funding” form part of the capital markets union’s (CMU) initiatives. From there, it seems a natural step to broaden plans of this genre to encompass funding via virtual currencies. A subcategory of these funding initiatives has become known as “initial coin offering (ICO),” even if the available options are not limited to the development of virtual currencies. How bright could we paint the future of virtual financing?

This paper suggests a first framework for what I will call “responsible” A.I.-based credit scoring, pulling together legal tools with a very different pedigree. The natural point of departure is to offer a definition.  Against the backdrop of the concerns outlined above, I use the term “responsible” as: achieving a good degree of data protection and preventing discrimination. The latter has been a long-standing requirement for information-processing in a credit context. The former responds to the radical change of “input” and methodology used for scoring decisions.

Digital wallets, such as ApplePay and Android Pay, are “smart” payment devices that can integrate payments with two-way, real-time communications of any type of data. Integration of payments with real-time communications holds out tremendous promise for consumers and merchants alike: the combination, in a single, convenient platform, of search functions, advertising, payment, shipping, customer service, and loyalty programs. Such an integrated retail platform offers consumers a faster and easier way to transact, and offers brick-and-mortar retailers an ecommerce-type ability to identify, attract, and retain customers. At the same time, however, digital wallets present materially different risks for both consumers and merchants than traditional plastic card payments precisely because of their “smart” nature.

For consumers, digital wallets can trigger an unfavorable shift in the applicable legal regime governing the transactions, increase fraud risk, create confusion regarding error resolution, expose consumers to non-FDIC-insured accounts, and substantially erode transactional privacy. These risks are often not salient to consumers, who cannot distinguish them by digital wallet. Consumers’ inability to protect against these risks points to a need for regulatory intervention by the Consumer Financial Protection Bureau to ensure minimum standards for digital wallets.

For merchants, digital wallets can deprive them of valuable customer information used for anti-fraud, advertising, loyalty, and customer service purposes. Digital wallets can also facilitate poaching of customers by competitors, impair merchants’ customer relationship management, deprive merchants of influence over consumers’ payment choice and routing, increase fraud risk, subject merchants to patent infringement liability, and ultimately increase the costs of accepting payments. Merchants are constrained in their ability to refuse or condition payments from digital wallets based on the risks presented because of merchant rules promulgated by credit card networks. These rules raise antitrust concerns because they foreclose entry to those digital wallets that offer merchants the most attractive valuation proposition, namely those wallets that do not use the credit card networks for payments.

Using a unique, order-level data set on artificial intelligence (AI) versus human bidding for a Chinese online market place lending platform, we uncover serious ethical challenges of the unregulated AI. We find AI “skims off the cream” through (1) strategic information provision, (2) fast trading, and (3) price manipulation. In a regression discontinuity design, we show individual investor returns decrease and borrowers pay more in financing costs due to AI cream-skimming. Further evidence reveals a misalignment of interest when a platform’s private interest in loan origination exceeds its expected loss in management fees. We also discuss the corresponding regulatory strategies.

Artificial intelligence is no longer solely in the realm of science fiction. Today, basic forms of machine learning algorithms are commonly used by a variety of companies. Also, advanced forms of machine learning are increasingly making their way into the consumer sphere and promise to optimize existing markets. For financial advising, machine learning algorithms promise to make advice available 24–7 and significantly reduce costs, thereby opening the market for financial advice to lower-income individuals. However, the use of machine learning algorithms also raises concerns. Among them, whether these machine learning algorithms can meet the existing fiduciary standard imposed on human financial advisers and how responsibility and liability should be partitioned when an autonomous algorithm falls short of the fiduciary standard and harms a client. After summarizing the applicable law regulating investment advisers and the current state of robo-advising, this Note evaluates whether robo-advisers can meet the fiduciary standard and proposes alternate liability schemes for dealing with increasingly sophisticated machine learning algorithms.

Artificial intelligence is an existential component of modern finance. The progress and promise realized and presented by artificial intelligence in finance has been thus far remarkable. It has made finance cheaper, faster, larger, more accessible, more profitable, and more efficient in many ways. Yet for all the significant progress and promise made possible by financial artificial intelligence, it also presents serious risks and limitations. This Article offers a study of those risks and limitations—the ways artificial intelligence and misunderstandings of it can harm and hinder law, finance, and society. It provides a broad examination of inherent and structural risks and limitations present in financial artificial intelligence, explains the implications posed by such dangers, and offers some recommendations for the road ahead. Specifically, it highlights the perils and pitfalls of artificial codes, data bias, virtual threats, and systemic risks relating to financial artificial intelligence. It also raises larger issues about the implications of financial artificial intelligence on financial cybersecurity, competition, and society in the near future. Ultimately, this Article aspires to share an insightful perspective for thinking anew about the wide-ranging effects at the intersection of artificial intelligence, finance, and the law with the hopes of creating better financial artificial intelligence—one that is less artificial, more intelligent, and ultimately more humane, and more human.

Markets face a new and daunting mode of manipulation. With this new mode of market manipulation, millions of dollars can vanish in seconds, rogue actors can halt the trading of billion-dollar companies, and trillion-dollar financial markets can be distorted with a simple click or a few lines of code. Every investor and institution is at risk. This is the new precarious reality of our financial markets.

This Article is about our ominous financial reality, this dangerous new mode of market manipulation, and the need for pragmatic policies to better address the rising threats to manipulate our financial markets. To start, the Article offers an overview about the recent rise and regulation of new financial technology. It begins with a close examination of The Flash Crash of 2010 and the publication of Flash Boys by Michael Lewis. Next, the Article surveys the changing landscape of market manipulation. It identifies traditional manipulation methods like cornering, front running, and pumping-and-dumping, as well as new manipulation methods like spoofing, pinging, and mass misinformation. It explains how new cybernetic market manipulation schemes that leverage modern technologies like electronic networks, social media, and artificial intelligence are more harmful than traditional schemes. The Article then grapples with why this new mode of market manipulation will present critical challenges for regulators. Finally, it recommends three pragmatic proposals for combating the new threats of cybernetic market manipulation by improving intermediary integrity, enhancing financial cybersecurity, and simplifying investment strategies. Ultimately, this Article provides an original and improved framework for thinking and acting anew about market regulation, market operations, and market manipulation.

Finance startups are offering automated advice, touchless payments, and other products that could bring great societal benefits, including lower prices and expanded access to credit. Yet unlike in other digital arenas in which American companies are global leaders, such as search engines and ride hailing, the United States lags in consumer financial technology. This Article posits that the current competition policy framework is holding back consumer financial innovation. It then identifies a contributor missing from the literature: the institutional design of federal regulators. Competition authority—including antitrust and the extension of business licenses—is spread across at least five agencies. Each is focused on other missions or industries. The Department of Justice (DOJ), hindered by statutes and knowledge gaps, devotes significantly fewer resources to banking than to other industries in merger review because it leans heavily on prudential regulators. The Federal Reserve and other prudential regulators prioritize financial stability, which conflicts with their competition mandate. No agency has the right authority, motivation, and expertise to promote consumer financial competition.

Innovation has raised the stakes for fixing this structural flaw in finance, and potentially in other heavily regulated industries. If allowed to compete fully, financial technology challengers (“fintechs”) could bring large consumer welfare advances and reduce the size of “Too Big to Fail” banks, thereby lessening the chances of a financial crisis. If allowed to grow unchecked, fintechs or the big banks acquiring them may reach the kind of digital market dominance seen in Google, Facebook, and Amazon, thereby increasing systemic risk. Whether the goal is to benefit consumers, strengthen markets, or prevent crises, a reallocation of competition authority would better position regulators to navigate the future of innovation.

The administrative state is leveraging algorithms to influence individuals’ private decisions. Agencies have begun to write rules to shape for-profit websites such as Expedia and have launched their own online tools such as the Consumer Financial Protection Bureau’s mortgage calculator. These digital intermediaries aim to guide people toward better schools, healthier food, and more savings. But enthusiasm for this regulatory paradigm rests on two questionable assumptions. First, digital intermediaries effectively police consumer markets. Second, they require minimal government involvement. Instead, some for-profit online advisers such as travel websites have become what many mortgage brokers were before the 2008 financial crisis. Although they make buying easier, they can also subtly advance their interests at the expense of those they serve. Publicly run alternatives lack accountability or—like the Affordable Care Act health-insurance exchanges—are massive undertakings. The unpleasant truth is that creating effective digital regulators would require investing heavily in a new oversight regime or sophisticated state machines. Either path would benefit from an interdisciplinary uniform process to modernize administrative, antitrust, commercial, and intellectual property laws. Ideally, a technology meta-agency would then help keep that legal framework updated.

Google’s, Apple’s, and other companies’ automated assistants are increasingly serving as personal shoppers. These digital intermediaries will save us time by purchasing grocery items, transferring bank accounts, and subscribing to cable. The literature has only begun to hint at the paradigm shift needed to navigate the legal risks and rewards of this coming era of automated commerce. This Article begins to fill that gap first by surveying legal battles related to contract exit, data access, and deception that will determine the extent to which automated assistants are able to help consumers to search and switch, potentially bringing tremendous societal benefits. Whereas observers have largely focused on protecting consumers and sellers from digital intermediaries’ market power, sellers like Amazon, Comcast, and Wells Fargo can also harm consumers by obstructing automated assistants. Advancing consumer welfare in the automated era requires not just consumer protection, but digital intermediary protection.

The Article also shows the unpredictable side of the end of switching costs. If digital assistants become pervasive, they could gain the ability to rapidly direct millions of consumers to new purchases whenever a lower price or new innovation becomes available. Significantly accelerated consumer switching — what I call hyperswitching — does not inevitably harm society. But in the extreme it could make some large markets more volatile, raising unemployment costs or financial stability concerns as more firms fail. This new kind of disruption could pose challenges for commercial and banking regulators akin to those familiar to securities regulators, who deploy idiosyncratic tools such as a pause button for the stock market. Even if sellers prevent extreme hyperswitching, managers may strategically prepare for hyperswitching with economically costly behavior such as hoarding liquid assets or forming conglomerates to provide insurance against a sudden exodus of customers. The transaction-cost focused literature has missed more macro-level drawbacks.

The regulatory architecture reflects these scholarly gaps. One set of agencies regulates automated assistants for consumer protection and antitrust violations, but does not go beyond those microeconomic inquiries. Nor do they prioritize strengthening digital intermediaries. Regulators with more macroeconomic missions lack jurisdiction over automated assistants. The intellectual framework and regulatory architecture should expand to encompass both the upsides and downsides of digital consumer sovereignty.

Recent advances in the field of artificial intelligence have revived long-standing debates about what happens when robots become smarter than humans. Will they destroy us? Will they put us all out of work? Will they lead to a world of techno-savvy haves and techno-ignorant have-nots? These debates have found particular resonance in finance, where computers already play a dominant role. High-frequency traders, quant hedge funds, and robo-advisors all represent, to a greater or lesser degree, real-world instantiations of the impact that artificial intelligence is having on the field. This Article will argue that the primary danger of artificial intelligence in finance is not so much that it will surpass human intelligence, but rather that it will exacerbate human error. It will do so in three ways. First, because current artificial intelligence techniques rely heavily on identifying patterns in historical data, use of these techniques will lead to results that perpetuate the status quo (a status quo that exhibits all the features and failings of the data itself). Second, because some of the most “accurate” artificial intelligence strategies are the least transparent or explainable ones, decisionmakers may well give more weight to the results of these algorithms than they are due. Finally, because much of the financial industry depends not just on predicting what will happen in the world, but also on predicting what other people will predict will happen in the world, it is likely that small errors in applying artificial intelligence (either in data, programming, or execution) will have outsized effects on markets. This is not to say that artificial intelligence has no place in the financial industry, or even that it is bad for the industry. It clearly is here to stay, and, what is more, has much to offer in terms of efficiency, speed, and cost. But as governments and regulators begin to take stock of the technology, it is worthwhile considering artificial intelligence’s real-world limitations.

The financial crisis of 2008 has led to dramatic changes in the way that finance is regulated: the Dodd-Frank Act imposed broad and systemic regulation on the industry on a level not seen since the New Deal. But the financial regulatory reforms enacted since the crisis have been premised on an outdated idea of what financial services look like and how they are provided. Regulation has failed to take into account the rise of financial technology (or “fintech”) firms and the fundamental changes they have ushered in on a variety of fronts, from the way that banking works, to the way that capital is raised, even to the very form of money itself. These changes call for a wide-ranging reconceptualization of financial regulation in an era of technology-enabled finance. In particular, this Article argues that regulators’ focus on preventing the risks associated with “too big to fail” institutions overlooks the conceptually distinct risks associated with small, decentralized financial markets. In many ways, these risks can be greater than those presented by large institutions because decentralized fintech markets are more vulnerable to adverse economic shocks, are less transparent to regulators, and are more likely to encourage excessively risky behavior by market participants. The Article concludes by sketching out a variety of regulatory responses that better correspond to fintech’s particular risks and rewards.

There is a gap in the regulation of crypto-assets that Congress needs to fix. The gap is contributing to fraud and weak investor protection in the distribution and trading of crypto-assets. Better regulation will benefit crypto investors, further the development of new technologies, curtail the use of crypto-assets used for illicit payments, and reduce the risk of cyber-attacks, which can result in collateral damage elsewhere in our financial system. Crypto-assets cut across current jurisdictional boundaries and thus fall into gaps between regulatory authorities. While each of the Securities and Exchange Commission (SEC) and the Commodity Futures Trading Commission (CFTC) has some authority over crypto-assets, neither has sufficient jurisdiction, nor do they together.

New financial product designs, improved computer and telecommunications technology, and advances in the theory of finance have led to dramatic and rapid changes in the structure of global financial markets and institutions. This paper offers a functional perspective as the conceptual framework for analyzing the dynamics of institutional changes in financial intermediation and uses a series of examples to illustrate the range of institutional change that is likely to occur. These examples are used to frame the managerial issues surrounding the production process for intermediaries and to discuss the regulatory process for those intermediaries.

This chapter describes the legal history of objects that have been used as substitutes for legal tender in the United States and discusses the implications of that jurisprudence for modern virtual currencies. Beginning with wampum, which had a recognized exchange value as early as 1631, we examine Continental currency, fractional currency and shinplasters, Greenbacks and state bank notes and even “trading stamps” offered by S&H and other firms. We document that as these substitutes came into the market place, governments tended to view them with suspicion and often commenced criminal prosecutions to halt their issuance and use. Over time, however, certain substitutes for legal tender have gained acceptance from legal authorities, and in some cases, have even been adopted as forms of legal tender themselves.

With this historical framework in place, this article looks at the incipient regulation of virtual currencies in the United States, focusing on early digital currencies, e-gold and bitcoin. We note parallels between how substitutes for legal tender have been treated historically and how regulators and law enforcement have reacted to virtual currency products. In particular, we document the growing use of 18 U.S.C. § 1960 to criminally prosecute virtual currency participants for operating as unlicensed “money transmitters.”

The digital economy is changing everything, including how we borrow money. In the wake of the 2008 crisis, banks pulled back in their lending and, as a result, many consumers and small businesses found themselves unable to access credit. A wave of online firms called fintech lenders have filled the space left vacant by traditional financial institutions. These platforms are fast making antiques out of many mainstream lending practices, such as long paper applications and face-to-face meetings. Instead, through underwriting by automation—utilizing big data (including social media data) and machine learning—loan processing that once took days for mainstream lenders can now be done in minutes by fintech firms. The result of these fintech advances has been quicker access to capital, more economic efficiencies, and even greater prospects for access to credit for the unbanked and underbanked. “Click here” is the new “sign on the dotted line.”

But there is a lot still to learn about fintech lending. How do these firms work and what kinds of products do they offer? Moreover, what role will they play in the future of American debt markets, particularly when it comes to the role of machine learning in assessing a borrower’s creditworthiness? This Article explores these questions and assesses current government responses to the nascent industry. It also surveys the current consumer protection landscape for fintech lenders and analyzes a multi-year dataset of complaints submitted to the CFPB relative to products offered by these firms. The Article concludes by offering several policy recommendations for how to regulate this new world of bitcredit.

This article examines the emerging regulatory responses to an ongoing fintech disruption of traditional finance. Focusing primarily on the U.S. experience to date, it offers a three-part taxonomy of principal approaches to fintech taken by financial regulators: what I call the “experimentation” approach, the “incorporation” approach, and the “accommodation” approach. Within this framework, the article analyzes the pros and cons of establishing regulatory sandboxes and innovation hubs, issuing special fintech charters, and pursuing various regulatory-adjustment measures under a broad heading of RegTech.

The sudden rise of Initial Coin Offerings (ICOs) has created unprecedented challenges for the Securities & Exchange Commission (SEC). Rather than selling stock, ICOs typically raise funds by selling tokens (a type of cryptocurrency) to investors, many of whom hope to profit as the value of such tokens increases. Hundreds of companies developing projects relating to blockchain technology have sold tokens through ICOs directly to public investors without filing a registration statement with the SEC. Such sales are unlawful if such tokens fall within the ambiguous definition of a security.

This policy paper examines the SEC’s response to ICOs. It argues that selling tokens through an ICO without SEC registration requires escaping what we call the “Hinman paradox.” A token can only be widely distributed to the public if the project it is associated with is functional. But a blockchain project can only be functional if its tokens are widely distributed. Blockchain projects with simple, well-defined, and compelling objectives may be able to achieve the requisite degree of functionality and de-centralization so they can sell utility tokens without being subject to securities regulation. However, the SEC’s November 16, 2018 enforcement settlements send the message that non-functional token sales without a clear path to de-centralization will not be tolerated.

In addressing the problem of unregistered sales of digital tokens through initial coin offerings (ICOs), the SEC has proceeded through a strategy we call Regulation by Selective Enforcement. Rather than impose penalties on a significant number of violators, the SEC has brought a small number of significant cases. The SEC issued several extensive settlement releases that established without court intervention regulatory guidance about when ICO tokens are securities. The SEC has been able to pursue this strategy in part because there are multiple enforcers of the securities laws. State regulators and private plaintiffs have brought a significant number of cases against fraudulent ICOs, permitting the SEC to focus on developing issues of national importance. We conclude that while the SEC’s Regulation by Selective Enforcement strategy has been thoughtful and successful, some aspects of the agency’s approach are problematic.

Marketplace lending—also called peer-to-peer lending or online platform lending—is a nonbank lending industry that uses innovative financial technology (fintech) to make loans to consumers and small businesses. Although marketplace lending is small compared to traditional lending, it has grown quickly in recent years. In general, marketplace lenders accept applications for small, unsecured loans online and determine applicants’ creditworthiness using an automated algorithm. Often, the loans are then sold—individually or in pieces—directly to investors (although holding the loans on their own balance sheet is not uncommon). More traditional lenders are more apt to use employees to make credit assessments and to have a greater need for office and retail space. Traditional lenders also may hold loans themselves, but when they sell loans they are more apt to package many loans together into large securities rather than to sell a single loan or pieces of a single loan, like marketplace lenders. Due to these differences and to marketplace lending’s lack of industry track record, marketplace lending is facing uncertainty about its advantages, its risks, and how it should be treated by regulators.

Some observers assert that marketplace lending may pose an opportunity to expand the availability of credit to individuals and small businesses in a fair, safe, and efficient way. Marketplace lenders may have lower costs than traditional lenders, potentially allowing them to make more small loans than would be profitable for traditional lenders. In addition, some observers believe the accuracy of credit assessments will improve by using more data and advanced statistical modeling, as marketplace lenders do through their automated algorithms, leading to fewer delinquencies and write-offs. They argue that using more comprehensive data could also allow marketplace lenders to make credit assessments on potential borrowers with little or no traditional credit history.

Other observers warn about the uncertainty surrounding the industry and the potential risks marketplace lending poses to borrowers, loan investors, and the financial system. The industry only began to become prevalent during the current economic expansion and low-interest-rate environment, so little is known about how it will perform in other economic conditions. Many marketplace lenders do not hold the loans they make themselves and earn much of their revenue through origination and servicing fees, which potentially creates incentives for weak underwriting standards. Finally, some observers argue that lack of oversight may allow marketplace lenders to engage in unsafe or unfair lending practices.

Marketplace lenders are subject to existing federal and state regulations related to lending and security issuance, and some observers assert that the existing system is appropriate for regulating this lending. However, existing regulations were developed and implemented largely prior to the emergence of marketplace lending. Some observers argue that current regulation is unnecessarily burdensome or inefficient. By contrast, others argue that regulatory gaps and weaknesses exist and regulation should be strengthened. In addition, there is some uncertainty surrounding exactly how certain aspects of federal and state laws and regulations may be applied to marketplace lenders. Congress may consider policy issues related to these debates and uncertainties.

The evolution of the regulatory environment facing marketplace lenders is just one development that likely will occur in coming years. Traditional lenders that compete with marketplace lenders will adapt to the market entrants and market conditions, perhaps adopting certain marketplace lender technologies and practices. In addition, marketplace lending has not been through an entire economic cycle, and rising interest rates or the onset of a recession likely will reveal certain strengths and weaknesses of marketplace lending.

The banking sector is facing the formidable challenge of responding to COVID-related changes to customer behavior and the adverse impact of economic weakness. In parallel, there is the presence of a potential new class of competitors with powerful networks and deep investment pockets (the so-called big techs). This combination of factors will most likely drive significant discontinuity in the banking sector.

Our joint report with the International Banking Federation (IBFed) analizes the competitive dynamics in major markets. The status quo is defined by continued dominance of traditional banking players, and a niche penetration by big techs and specialist fintech in most major markets. However, in a few major markets, the analysis highlights how the unique scale and “ecosystem” model of big techs has the potential to fundamentally change competitive dynamics in banking. We have spoken with a broad range of industry participants and policymakers across most major markets to gauge current views and challenges for the future.

In our report, we raise important questions for policy-makers, banks and society in general. Big tech technology capabilities can bring benefits in customer outcomes and efficiency that can be put to good use for society — to serve inclusion, to fight financial crime, to improve the cyber and operational resilience of our financial system, to name a few. But they also raise new types of risks and challenge the traditional “vertical” (sector-oriented) model of regulation and supervision, which may no longer serve society’s best interest today.

The main question for banks is how to prepare for the possibility of a major incursion of the big techs into their core markets, where this has not happened already. It is possible that big techs choose not to engage in core banking markets, but the general sense from our interviews it is not a question of if but when. Banks may therefore need to rewrite their past formula of success, and transform the way they serve customers, interact with third-parties and make the very fundamental strategic choices of whether they wish to compete as a “network” business model or compete in specific businesses serving others’ network.

Financial services policy-makers — quite rightly — have prioritized COVID response and forebearance in the banking sector. However, there is a clear need to get on the front foot to support and shape an orderly modernization of the financial sector that will be required in the post-COVID economic and financial regeneration. The two extremes of policymaker response are unattractive: 1. unfettered, open competition with a blanket relaxation of participation rules will pole-axe weak banking business models and create financial stability risks and probably consumer protection issues; 2. high barriers to entry for non-banking players will slow down innovation and protract the existence of non-viable banking models. There is an optimal policy response somewhere in between the two extremes: this will require policy-makers to think differently with respect to competitive boundaries, accept higher uncertainty and faster responses and possibly re-think the institutional architecture that governs the intersection of financial services and technology sectors.

In a world that is understandably concerned with COVID response, we hope these insights highlight the risks of a disruptive change that could result from banking sector weakness and restructuring and encourage policy-makers and the banking sector to invest time in shaping successful future business models and the orderly transition required.

Securities law traditionally only permits corporations that have registered with the Securities and Exchange Commission (SEC)and completed an initial public offering (IPO) to sell equity to the general public—often a long, expensive process. The initial coin offering (ICO) emerged in 2013 as a fundraising tool private blockchain-based companies have used over the past several years to raise billions of dollars, seeking to circumvent registration with the SEC and the public offering process altogether. But their early success brought the attention of the SEC, and in 2017 the SEC clearly asserted the right to regulate ICOs. Since then U.S. ICO promoters have struggled to avoid the SEC’s assertion of jurisdiction, contorting their offerings in an effort to avoid regulation. They have largely failed. This piece argues that government regulation is a feature, not a bug for ICOs. If ICO entrepreneurs acknowledge SEC jurisdiction—and if the SEC, for its part, implements creative mechanisms to protect investors – blockchain businesses can raise capital from the general public while continuing to serve the underlying goals of U.S. securities law.

In the history of the Chinese communist movement, the re-emergence of the term “permanent” or “uninterrupted” revolution is clearly associated with the Great Leap Forward of 1958. It is then that the concept was first put forward once more after an eclipse of 30 years, and though it has since been employed from time to time, the most important articles on the subject were published in 1958 and 1959. The Cultural Revolution, has, however, altered our perception of this as of so many other important matters, both by making available new information and by placing the events of the previous decade in a new perspective.

Equity crowdfunding allows startup companies to sell shares of stock, bonds or other securities to the public using online capital markets. This allows entrepreneurs to avoid the costly process of a traditional IPO. Equity crowdfunding started in America in May 2016. This article explores the types of companies that utilize equity crowdfunding, and finds that most issuers are early-stage companies; most are corporations; there is significant geographic diversity amongst the issuers, and twenty-eight percent of issuers are female-founded or female led, which is much higher than in venture capital or angel investing.

This article explores the importance of an efficient retail payment system and develops an integrated framework for evaluation of the retail payment system by policy makers. It examines the costs and benefits of the various types of retail payment system, focusing on the seven desirable benefits of the retail payment system: (1) finality and reversibility; (2) universality (ability to use at point of sale and remotely); (3) recordkeeping; (4) liquidity (maximizing interest earning assets); (5) security and safety; (6) financial inclusion and access; and (7) fungibility and ease of use (seven benefits).

The article discusses the Coase Theorem, a proposition from transaction cost economics that provides a useful tool for analyzing transaction efficiency. Increased costs are not bad per se since parties are often willing to incur higher costs to achieve their desired results, e.g. higher costs for a more secure form of payment. Indeed, higher costs may often generate higher value to both parties to a transaction. What one wants to reduce are “friction” costs, costs that neither party wants to pay to achieve a desired result, e.g. higher costs produced by lack of information.

While each retail payment system provides certain advantages, e.g. cash for small transactions, overall the analysis suggests that debit and credit cards represent the most desirable payment system for achieving the seven benefits set forth above. This is supported by statistics that indicate that retail payments have increasingly moved toward card payments.

Negligence law is often asked to adapt to new technologies. So it is with artificial intelligence (AI). But AI is different. Drawing on examples in medicine, financial advice, data security, and driving in semi-autonomous vehicles, this Article argues that AI poses serious challenges for negligence law. By inserting a layer of inscrutable, unintuitive, and statistically-derived code in between a human decisionmaker and the consequences of that decision, AI disrupts our typical understanding of responsibility for choices gone wrong. The Article argues that AI’s unique nature introduces four complications into negligence: 1) unforeseeability of specific errors that AI will make; 2) capacity limitations when humans interact with AI; 3) introducing AI-specific software vulnerabilities into decisions not previously mediated by software; and 4) distributional concerns based on AI’s statistical nature and potential for bias.

Tort scholars have mostly overlooked these challenges. This is understandable because they have been focused on autonomous robots, especially autonomous vehicles, which can easily kill, maim, or injure people. But this focus has neglected to consider the full range of what AI is. Outside of robots, AI technologies are not autonomous. Rather, they are primarily decision-assistance tools that aim to improve on the inefficiency, arbitrariness, and bias of human decisions. By focusing on a technology that eliminates users, tort scholars have concerned themselves with product liability and innovation, and as a result, have missed the implications for negligence law, the governing regime when harm comes from users of AI.

The Article also situates these observations in broader themes of negligence law: the relationship between bounded rationality and foreseeability, the need to update reasonableness conceptions based on new technology, and the difficulties of merging statistical facts with individual determinations, such as fault. This analysis suggests that though there might be a way to create systems of regulatory support to allow negligence law to operate as intended, an approach to oversight that it not based in individual fault is likely to be a more fruitful approach.

Securities traders are currently competing to use Artificial Intelligence (A.I.) in order to make more profitable decisions in the marketplace. While A.I. provides superior abilities in recognizing market patterns, its complexity can obscure its decision-making process beyond human comprehension. Problematically, the current securities laws prohibiting manipulation of securities prices rest liability for violations on a trader’s intent. In order to prepare for A.I. market participants, both courts and regulators need to accept that human concepts of decision-making will be inadequate in regulating A.I. behavior. However, the wealth of case law in the market manipulation doctrine need not be cast aside. Industry regulators should instead require A.I. users to harness the power of their machines to provide meaningful feedback in order to both detect potential manipulations and create evidentiary records in the event that allegations of A.I. manipulation arise.

Between 2010 and 2014, the regional price of aluminum in the United States (Midwest premium) increased threefold. We argue that the Midwest premium was likely manipulated during this period through the exercise of market power in the aluminum storage market. We first use a difference-in-differences model to show that there was a statistically significant increase of $0.07 per pound in the regional price of aluminum relative to the regional price of a production complement, copper. We then use several instrumental variables to show that this increase was driven by a single financial company’s accumulation of an unprecedented level of aluminum inventories in Detroit. Since this scheme targeted the regional price of aluminum, regulators who monitored only spot and futures prices would not have noticed anything peculiar. We therefore present an algorithm for real-time detection of similar manipulation schemes in regional commodity markets. The algorithm confirms the existence of a structural break in the U.S. aluminum market in late 2011. Using the algorithm, regulators could have detected the scheme as early as December 2012, more than six months before it was publicized by an article in The New York Times. We also apply the algorithm to another suspected case of regional price manipulation in the European aluminum market and find a similar break in 2011, suggesting the scheme may have been implemented beyond the United States.

In a short period of time virtual currencies have gained significant traction and become an economic reality, with Bitcoin being the most dominant among over 500 virtual currencies. Bitcoin and other virtual currencies present a particularly difficult and unique jurisdictional challenge to existing regulatory enforcement because of their: ability to transcend national borders in the fraction of a second; and anonymity due to encryption.

In January 2014 the Uniform Law Commission (ULC) created a Study Committee on Alternative and Mobile Payments (Study Committee). The focus of the Study Committee (now designated a Drafting Committee) is to devise an optimal licensing system for intermediaries that perform financial services for third parties relating to digital or virtual currencies. The Study Committee/Drafting Committee concluded that the New York regulatory framework for virtual currencies (New York “Bitlicense” Regulation) is “well drafted” and (with some changes) could serve as a beginning template for a uniform law. At this writing, a remaining significant issue is the extent to which the proposed uniform law should go beyond the licensing, compliance and enforcement issues common to the CSBS regulatory framework and the New York “BitLicense” Regulations, to cover substantive commercial transaction issues as in the UCC. Advances such as the blockchain technology underlying Bitcoin and many other virtual currencies may hold great promise for efficiencies in the transfer cost of money and data.

This article addresses the legal and financial implications of virtual currencies, and is organized as follows. Part II. presents a brief history describing the evolution and function of money and currencies. Part III. describes the development of virtual currencies and Bitcoin in particular. Part IV. discusses traditional payment and regulatory systems. Part V. looks at criminal law issues relating to currencies. Part VI. considers the history of modern payment systems and regulation, currency stability issues, and the possible threat to financial order posed by virtual currencies. Part VII. Explores the future of regulation in this area of law. Implications for further research are then presented. The focus is the impact on payment systems of the rapidly developing use of virtual and cybercurrencies, especially bitcoins.

This volume of the Washington University Journal of Law and Policy examines fintech, focusing on the regulatory and other challenges it poses. The symposium benefits from contributions by prominent scholars of financial and securities regulation. These contributions examine the structure of firms and markets, considering fintech activities occurring within existing firms and regulatory perimeters and activities that spill over the boundaries we currently take for granted. The contributors examine the emerging regulatory responses to fintech, taxonomizing them. They consider which regulatory approaches, or ecosystems, will best help fintech to develop. They examine how fintech applies to fundraising, examining initial coin offerings (ICOs) and equity crowdfunding, techniques that attract attention for different reasons—ICOs because they occur so frequently beyond existing regulatory perimeters when they should not and equity crowdfunding because it occurs so infrequently despite enjoying regulatory accommodations. Our authors also examine the promise and limits of “smart” contracts in consumer finance. They explore “stable cryptocurrencies.” They look to Kenya for a case study of fintech lending in fledgling credit markets.

“Blockchain” is the word on the street these days, with every significant financial institution, from Goldman Sachs to Nasdaq, experimenting with this new technology. Many say that this remarkable innovation could radically transform our financial system, eliminating the costs and inefficiencies that plague our existing financial infrastructures, such as payment, settlement, and clearing systems. Venture capital investments are pouring into blockchain startups, which are scrambling to disrupt the “quadrillion” dollar markets represented by existing financial market infrastructures. A debate rages over whether public, “permissionless” blockchains (like Bitcoin’s) or private, “permissioned” blockchains (like those being designed at many large banks) are more desirable.

Amidst this flurry of innovation and investment, this paper enquires into the suitability of the Bitcoin blockchain to serve as the backbone of financial market infrastructure, and evaluates whether it is robust enough to serve as the foundation of major payment, settlement, clearing, or trading systems.

Positing a scenario in which the Bitcoin blockchain does serve as the technology enabling significant financial market infrastructures, this paper highlights the vital importance of functioning financial market infrastructure to global financial stability, and describes relevant principles that global financial regulators have adopted to help maintain this stability, focusing particularly on governance, risk management, and operational risk.

The paper then moves to explicate the operational risks generated by the most fundamental features of Bitcoin: its status as decentralized, open-source software. Illuminating the inevitable operational risks of software, such as its vulnerability to bugs and hacking (as well as Bitcoin’s unique 51% Attack vulnerability), uneven adoption of new releases, and its opaque nature to all except coders, the paper argues that these technology risks are exacerbated by the governance risks generated by Bitcoin’s ambiguous governance structure. The paper then teases out the operational risks spawned by decentralized, open-source governance, including that no one is responsible for resolving a crisis with the software; no one can legitimately serve as “the voice” of the software; code maintenance and repair may be delayed or imperfect because not enough time is devoted to the code by volunteer software developers (or, if the coders are paid by private companies, the code development may be influenced by conflicts of interest); consensus on important changes to the code may be difficult or impossible to achieve, leading to splits in the blockchain; and the software developers who “run” the Bitcoin blockchain seem to have backgrounds in software coding rather than in policy-making or risk-management for financial market infrastructure.

The paper concludes that these operational risks, generated by Bitcoin’s most fundamental, presumably inalterable, structures, significantly undermine the Bitcoin blockchain’s suitability to serve as financial market infrastructure.

The digital marketplace is wide-reaching, complicated and self-reinforcing. The systems developed to oversee an earlier time are burdened by industrial era statutes and decades of precedent that render them insufficient for the digital present.

• In the absence of federal oversight, the dominant digital companies have made their own rules and imposed them on consumers and the market. Just as industrial capitalism operated—and thrived—under public interest obligations, so should internet capitalism be grounded in public interest expectations.
• Those expectations—and the new rules to implement them—should be the reinstatement of responsibilities long established in common law: the duty of care and the duty to deal.
• To accomplish this a new Digital Platform Agency should be created with a new, agile approach to oversight built on risk management rather than micromanagement. This would include a cooperatively developed and enforceable code of conduct for specific digital activities. As both a failsafe and an incentive, the agency would also retain its own independent right of action.

This Article shows that fintech exacerbates the difficulties of standard setting in international financial regulation. Earlier work introduced the “Innovation Trilemma” (the Trilemma). When seeking to balance the goals of achieving market integrity and innovation through clear and simple rulemaking, regulators can—at best—achieve only two out of these three objectives. Fintech’s unique characteristics—a reliance on automation and artificial intelligence, novel types of big data, as well as the use of disintermediating financial supply chains comprising a mix of traditional firms as well as technology specialists and newcomers—complicates the application of the Trilemma. Rulemaking struggles to achieve needed clarity where innovative algorithms introduce informational uncertainties and complex risks for market integrity. Further, regulation’s ability to impose compliance costs on firms in response to these risks is limited when a preference for innovation favors smaller upstarts and nontraditional players.

International financial regulation presents even steeper challenges when viewed through the lens of the Trilemma. First, rules clarity is harder to achieve owing to divergences in national legal systems, administrative processes, and market structures. Secondly, fintech increases negotiation costs in international standard setting owing to the emergence of a much more expansive cast of economies—like China and India—that dominate as fintech hubs alongside the traditional power players such as the United States or European Union (EU). With distinctive policy preferences, emerging economies constitute powerful voices that mean that negotiation must account for a wider range of distributive preferences. Finally, standard setting must bridge the particularities of domestic market structures that are experiencing varying degrees of disintermediation and transformations in financial supply chains. Rules that impose high compliance costs may be acceptable to economies dominated by traditional intermediaries but may lack buy-in from those where nonbank firms hold sway. In concluding, this Article briefly surveys strategies for fostering greater global cooperation in standard setting for fintech.

The rise of FinTech has not only advanced operational efficiency of the financial industry but also posed challenges to regulatory efficiency. There is a growing consensus on the importance and urgency for financial regulators to enhance their capacity through the use of RegTech. RegTech is widely considered as holding a great potential to facilitate the supervisory process and enhance the regulatory compliance. The current studies of RegTech, however, remains in its infancy. Most of the literature identifies and stock-takes different technologies and discusses how to apply them to facilitate financial regulation and supervision. These studies, in our view, mainly focus on the conduct aspect of RegTech. Of equal importance, yet largely overlooked, is the organizational aspect of RegTech, that is, how the organizational design and culture of a financial regulator affects its capability and suitability for applying RegTech to facilitate financial regulation and supervision.

This paper attempts to fill this gap by offering more insights on how to organize a financial regulator to ensure its accountability, flexibility, and adaptiveness in the era of RegTech. We argue that such a regulator requires the character of a public-private partnership, which should contain some public elements to ensure the unbiasedness of financial supervision and some private elements to adapt to rapid technological changes. This paper firstly conducts a comparative analysis of the worldwide organizational models of financial regulators, by which we identify four major types and compare the different public-private relationship between them. The paper then applies the analytical framework of the Transaction Cost Economics, particularly the Theory of Firm and the Comparative Institutional Approach, to theorize a spectrum of public-private-partnership for different organizational models of financial regulators, ranging from a firm-type of partnership to a contract type of partnership. Based on this theorized spectrum, together with the comparative institutional approach, this paper identifies four more possible models of public-private-partnership that may help financial regulators streamline their organizational structure to promote the adoption of RegTech. These models include a mixed ownership RegTech corporation, a contracted RegTech supporter, a quasi-public financial regulator, and directly delegated gatekeepers. Policymakers and financial regulators across the globe can consider and choose a model that better suits its own regulatory and supervisory needs.

This paper documents implications of Germany’s draft regulation on electronic securities for RegTech and SupTech. Regulation of electronic securities or a dematerialized system should not only serve the development of the private sector, FinTech and RegTech for regulatory compliance but also serve the public sector, namely support RegTech for regulators and SupTech for financial supervisors. Electronic securities have the potential to increase operational efficiency and accuracy both in compliance and supervision, namely, corporate governance, audit, and surveillance by deploying RegTech and SupTech systems. Digital transformation in the financial sector should include considerations in line with the digital finance requirements, such as closing the technology gap between the private and public sectors and managing asymmetric technology risks. Germany’s draft regulation is a strong signal for digital transformation in Germany; however, it does not foresee a fully dematerialized system, a prerequisite for well-designed RegTech and SupTech systems.

In this article, we discuss and analyse the main components of a digital financial supervisory system with supervisory technology (SupTech). This work offers a new SupTech definition and configures the digital pillars of a financial supervisory system. We contribute to the TECHs in Finance (FinTech, RegTech, SupTech) literature with two new concepts: “prudential supervisory disclosure” and “sustainable finance technology”, or SuFTech.

This work also touches on real TECHs in Finance cases from several countries. We find that the May 6, 2010 market crash at the U.S. financial markets, one of the biggest FinTech crises, addresses the importance of having a well-functioning SupTech system. The case also points out that even a leading technology-producing country or a developed country faces unprecedented FinTech crashes or crises unless the country’s financial supervisors keep pace with technology and develop a well-functioning SupTech system.

The transformative potential of distributed ledger technology (“DLT”), especially in the financial sector, is attracting enormous interest. Many financial institutions are investing heavily in proof-of-concept demonstrations and the rollout of pilot applications of DLT technology. Part of the attraction of distributed ledger systems such as Blockchain lies in transcending law and regulation. From a technological perspective, DLT is generally seen as offering unbreakable security, immutability, and unparalleled transparency, making law and regulation unnecessary. Yet while the law may be dull and the technology exciting, the impact of the law cannot be simply wished away. With data distributed among many ledgers, legal risk remains. DLT projects may well be found by courts to constitute joint ventures, with liability spread across all owners and operators of systems serving as distributed ledgers. Instead of being subject to law nowhere, organizers may instead be subject to the law wherever there are system users. Regulators seeking to support appropriate approaches to twenty-first century financial infrastructure must focus on these legal consequences.

Prior to the Global Financial Crisis, financial innovation was viewed very positively, resulting in a laissez-faire, deregulatory approach to financial regulation. Since the Crisis the regulatory pendulum has swung to the other extreme. Post-Crisis regulation, plus rapid technological change, have spurred the development of financial technology companies (FinTechs). FinTechs and data-driven financial services providers profoundly challenge the current regulatory paradigm. Financial regulators are increasingly seeking to balance the traditional regulatory objectives of financial stability and consumer protection with promoting growth and innovation. The resulting regulatory innovations include technology (RegTech), regulatory sandboxes and special charters. This paper analyses possible new regulatory approaches, ranging from doing nothing (which spans being permissive to highly restrictive, depending on context), cautious permissiveness (on a case-by-case basis, or through special charters), structured experimentalism (such as sandboxes or piloting), and development of specific new regulatory frameworks. Building on this framework, we argue for a new regulatory approach, which incorporates these rebalanced objectives, and which we term ‘smart regulation.’ Our new automated and proportionate regime builds on shared principles from a range of jurisdictions and supports innovation in financial markets. The fragmentation of market participants and the increased use of technology requires regulators to adopt a sequential reform process, starting with digitization, before building digitally-smart regulation. Our paper provides a roadmap for this process.

The rise of financial technology (FinTech) and its potential impact on legal regimes have received close academic attention in recent years, but much of that scholarship has focused on the attributes of individual applications and technologies. By contrast, we focus on the less obvious – but far more significant – development of operating systems for finance, particularly those that govern the global economy for investment. As with software generally, these operating systems are relatively inconspicuous, but extremely powerful, particularly given their role in controlling the world’s $50 trillion investment fund industry, where they already play a significant role in asset management for pension funds and other major institutional investors. We identify the scope of these systems, the economic reasons for their dramatic ascendency, and the legal implications that arise from their possible failures and successes, highlighting the potential for such systems to escape regulation while simultaneously stifling innovation and competition.