This paper explores the implications of a range of new financial technologies for financial inclusion. First, it tackles the basic question of how to define financial inclusion: What are the important aspects of financial inclusion? Presumably, an important element is the enablement of unbanked or underbanked consumers to access a wide range of financial services (such as payments, credit products, retirement planning, asset management, etc.) more easily and at lower, more affordable prices if they so choose. This paper also explores whether, or how, fintech companies are changing the characteristics of a range of services they already offer, such as person-to-person (P2P) payments; credit products including personal loans, student loans, mortgages, and advances of labor income; asset management and retirement planning (through so-called robo-advisors); and brokerage services. What are the risks associated with data security and privacy, suitability, fair lending practices, etc. that may arise or increase due to minimally regulated entities (generally nonbank financial intermediaries such as fintech mortgage originators) becoming important providers of financial services? In particular, does artificial intelligence/machine learning, along with social media content and other forms of alternative data, increase the risk of discrimination against protected consumer groups? Is the existing framework for consumer protection adequate? If not, how should it be enhanced?

Much of the policy interest in new technologies concerns the potential effects on the quantity, quality, and price of financial services for consumers and small businesses. This paper studies how lending to small businesses has evolved since just before the global financial crisis (GFC), with a special focus on the role of “new” lenders—those that rely on new or different lending technologies. These lenders’ technological advantage is further aided by the enhanced regulation of the largest banks enacted in the aftermath of the GFC. Using millions of manually classified Uniform Commercial Code loan records, this study documents that new lenders have gained substantial market share in small business lending since 2007 at the expense of banks, especially the largest banks. In terms of growth rate, fintech lenders have taken a commanding lead. This paper further examines whether banks have curtailed their credit provision particularly to small businesses in localities with a high share of low-income or minority households. Specifically, it seeks to understand how the regulatory capital constraints (such as through stress-testing) may interact with Community Reinvestment Act requirements. Finally, by linking records of Paycheck Protection Program loans and small business borrowers’ pre-pandemic loans, this study explores the implications of the changing landscape of small business lending for the design of public programs that would support small businesses.

The recently launched FedNow, the Federal Reserve’s instant payment service, could substantially expand the options for consumer payments. This paper will compare the new system with new public-sector real-time payment tools in other countries and explore possible interactions with existing domestic payment services, both traditional and new. It will also consider the implication of new technologies for Fed policy—particularly with regard to lender of last resort, financial stability, and fraud.

This panel, comprising industry practitioners and researchers, will speak to the promising aspects of distributed ledger technology (DLT) and smart contracts, including DLT's ability to streamline and automate a range of transactions, such as post-trade clearing and settlement, insurance-claim processing, and back-office support, and broadly speaking, its potential to transform how markets function. These experts will also discuss the limitations of DLT and smart contracts, some of which can be overcome with simple alterations to the DLT configuration or validation algorithm, such as the change from proof-of-work to proof-of-stake. Other limitations may be more fundamental, including the inherent trade-off between throughput and security that, for example, prevents double spending and smart contracts' reliance on oracles. Are there analogous aspects of older generations of technology from which we can draw useful lessons for the potential implications of DLT, such as the standardization of the to-be-announced (TBA) market? Are there technical advances that were inspired by DLT but are qualitatively different such that they can overcome the limitations of DLT?

This panel will focus on the promises of technology to enable smarter design and the implementation of more efficient and more effective regulation and supervision. How can technology make compliance faster and easier for the regulated and more readily verifiable for the regulators while reducing the costs for both? More specifically, how can technology improve the efficiency and efficacy of bank exams and stress tests? More generally, how can more data be shared without an imposition of additional burdens on regulated entities? Furthermore, how can technology provide the economical means to enhance the communication of policy (both monetary and regulatory) to the general public? How can new technology facilitate the regulation of central clearing platforms, real-time market monitoring, and other functions?

Technology is rapidly transforming the financial landscape. Since the Global Financial Crisis (GFC), changes in regulation and advances in artificial intelligence have led to a substantial increase in the market share of nonbanks, including Big Tech, the largest technology firms. Big Tech has ventured into the provision of payment services, asset management, and insurance, and these firms also have expanded into credit provision, mainly to vendors through their e-commerce platforms. Research shows that, unlike bank credit, Big Tech credit does not require physical assets as collateral and does not respond to fluctuations in property prices; instead, it reacts strongly to firms’ sales performance. This suggests important differences between Big Tech and traditional banks, with potential implications for the effectiveness of the credit channel. In light of this evidence, what is the impact of the expansion of Big Tech credit for the financial intermediation process and real economic activity? What are the implications for central banks and the transmission of monetary policy? Furthermore, the involvement of Big Tech in asset management and cloud computing services underscores these firms’ pivotal role in financial stability. How do Big Tech’s financial services influence the propagation of adverse supply or financial disturbances, such as those experienced in the aftermath of the GFC and the COVID-19 pandemic? What additional challenges do they pose to system-wide financial stability?