This paper explores the implications of a range of new financial technologies for financial inclusion. First, it will tackle 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. The net effects likely depend to a large extent on the trade-off between efficiency gains through better technologies and potential increases in market power. Existing research shows that advances in information technology have conferred a greater advantage to large banking organizations and thus have propelled more consolidation. Bank consolidation, in turn, has tended to reduce lending to small businesses. Will a similar outcome ensue if new technologies result in further concentration in the banking sector? Will tech-based lenders enhance competition in small-business lending? How will the new technologies interact with the reformed Community Reinvestment Act (CRA)? If that interaction leads to greater and/or less expensive credit availability for small businesses, will it foster entrepreneurship? A bank's access to large volumes of data enables it to more easily tailor services to individual consumers or small businesses. Smaller banks, which tend to lend to small businesses based on relationships rather than data, will likely be at a disadvantage to larger lenders with such access. Could public policy measures help level the playing field and preserve relationship-based services for small businesses? In particular, how can the CRA and Consumer Financial Protection Bureau (CFPB) rulemaking be adapted to achieve these goals?

The recently launched FedNow, the Federal Reserve's instant payment service, could substantially expand the options for consumer payments. This paper explores the interactions between new payment services, such as FedNow, and the existing array of payment services, both traditional (including automated clearing house [ACH]) and new, digital options (for example, mobile person-to-person [P2P] payments). It also considers the implications of new payment technologies for the conduct of monetary policy, as well as how the Fed fulfills its role as the liquidity provider of last resort. In addition, the paper explores how new, faster payment technologies may affect financial stability, for example, by enabling faster bank runs and easier opportunities for fraudulent transactions. How may these new technologies enable more efficient delivery of government transfer payments, and how may they impact the liquidity of the Treasury securities market? What will it mean for the dollar's role in the international financial system? Can we learn any lessons from precursors and current experiments in foreign countries following the introduction of public-sector real-time payment tools?

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?

The Federal Reserve will have to adapt as new technologies transform the financial landscape. Existing research shows that regulatory arbitrage and nonbank lenders' superior technology have led to their substantial market-share gain since the Global Financial Crisis. Evidence also suggests that nonbank lenders increase their market share at the expense of banks during periods of monetary tightening. In light of these findings, what are the implications, if any, for the execution and transmission of monetary policy if banks lose more ground to fintech and Big Tech firms? At the same time, the growing importance of nonbank financial institutions (NBFIs) means that they are more likely to cause system-wide financial instability. How can systemically important NBFIs be identified? Should the Federal Reserve's liquidity facilities be extended to these nonbank systemically important financial institutions (SIFIs)? If so, under what circumstances and with what attendant regulations? Moreover, given the importance of technology for the operation of NBFIs, how can the Fed continue to be a reliable liquidity backstop when the cause of a market disruption is not a lack of liquidity, but rather the integrity of the underlying technology? Are there rules and regulations, stress tests, or other measures the Fed should be empowered to implement to minimize the likelihood of such failures of technology? And what emergency procedures can be put in place should such an event occur?