The Role of the US Government in Stimulating Technological Innovation in the Financial Services Industry
The pace of technological innovation within the financial services industry has left regulators and lawmakers scrambling to better understand the technology and implement laws to govern the usage of such technology in order to prevent its improper use. Traditional regulatory change in the United States tends be extremely slow and bogged down in a system of bureaucratic red tape. Thomas Kochan, a professor of work and employment relations at the Sloan School of Business at the Massachusetts Institute of Technology (MIT), notes, “Most of our laws and the regulations and procedures used to enforce them still reflect the earlier era [the New Deal Era of the 1930s]. The task of updating our policies, business strategies, and workplace practices to suit our knowledge-driven economy and diverse labor force is huge, essential and long overdue.” Professor Kochan is correct in his diagnosis of the woefully inadequate system of regulation in place now in the United States. Policies that may have seemed progressive in the 1930s are far too antiquated today and will need complete revamping in order to make sure such technological innovation is used for good.
A recent article in Forbes entitled, “A Regulation Revolution in Financial Services” notes if regulators hold still today, they’re actually “accelerating backward.” The Treasury Department, in an effort to not accelerate backwards, issued a fintech report in 2018 that calls on the federal financial agencies both to innovate and to coordinate. This has given rise to regulatory technology (“regtech,” for short). Regtech relies on interagency collaboration and private sector innovation to increase the speed at which federal and state laws can help detect and prevent abuses in the financial services industry. Regtech has also given rise to a slew of new jobs including those in the public (cyber public policy makers, for example) and private sectors (fintech jobs like engineers, programmers, and other private watchdog groups).
The United Nations reports that less than 1 percent of global financial crime is actually apprehended because of technology which is out of date and unscalable. Traditionally, financial crimes have “data typologies,” distinctive patterns that become easy to spot and can be consolidated and analyzed quickly. Today’s machine learning (ML) tools can find such patterns, while new encryption techniques can make it safe to share data much more widely while safeguarding privacy. Anti-money laundering, or AML, is one of the most advanced regulatory technology (“regtech”) use cases. Technology like regtech can also fix the AML “Know-Your-Customer” (KYC) rules, which currently block millions of innocent people from financial access because they lack traditional identity documents (government-issued identification, etc.). A crude example behind the idea of KYC is to prevent a terrorist from obtaining a credit card. New digital identity techniques can screen nearly everyone, cheaply and accurately and prevent those with malintent from obtaining precious financial resources. The same technology can be used to help with issues regarding “redlining” or the systemic discrimination of someone because they live in an area deemed to be poor financial risk. Banks can begin to extend credit to those underrepresented areas and take into account different considerations (like on-time utility payments, savings rates, etc.) when deciding on credit worthiness and develop new terms for financial inclusion. Clearly, there are huge societal benefits associated with the adoption of “regtech.”
Customer Lifecycle Management (CLM) is a critical component of the overall AML act; however, many organizations do not routinely conduct “check-ups” on their clients (i.e. making sure that the funds lent to a client are not being put to use for bad). Recently, many studies have indicated that before a mass shooting, a domestic terrorist is likely to open a new credit card or ask for a loan from a neighborhood bank before purchasing the guns and ammunition required to complete their evil acts. For example, Omar Mateen, who killed 49 people in 2016 at the Pulse nightclub in Orlando, opened six credit cards in the months leading up to the shooting, according to the New York Times. Three of those cards were from Visa. In the days before the massacre, he spent over $26,000 on guns, ammunition and a ring for his wife. His typical spending before: $1,500 a month on one card. Technology like KYC and CLM has the capability to bring major social benefit if it can be harnessed to alert proper authorities once it identifies suspicious purchases and can pick up on buying trends that lead to catastrophic events.
 Kochan, Thomas. Shaping the Future of Work: What Future Worker, Business, Government, and Education Leaders Need To Do For All To Prosper. 2015. MIT Sloan.