While most startup founders would prefer not to pore over laws, regulations and interpretive materials to design a perfect product, it's an essential exercise for those developing financial services solutions. For fintechs and the other finserv-related startups (e.g., regtech, suptech, etc.) understanding the regulatory obligations of customers and prospects will be core to your mission. In some cases, the process of interpretation and analysis might be a heavy lift involving expert outside counsel, lobbying efforts, and specialized consulting services. A complicating factor for any fintech looking to solidify its understanding of regulatory paradigms is the gray area where regulators have issued cursory guidance, or no guidance at all. One gray-ish realm where financial services regulators have shown interest, but are largely treading lightly, has been offering guidance about the use of artificial intelligence ("AI").

The U.S. Securities and Exchange Commission (SEC) and the Financial Industry Regulatory Authority (FINRA) made several regulatory announcements this summer relating to cybersecurity, artificial intelligence (AI), and digital assets. These announcements are detailed below and include a FINRA summary report on the uses of AI in the securities industry, a FINRA regulatory notice regarding its members' activities relating to digital assets, and a risk alert from the SEC's Office of Compliance Inspections and Examinations (OCIE) on increased cybersecurity threats. On June 10, 2020, FINRA issued a summary report regarding existing and emerging uses of AI by securities industry participants. For a more detailed discussion of FINRA's summary report, please see our previous update. On July 9, 2020, FINRA reissued a request that member firms continue to proactively engage with their FINRA risk monitoring analyst regarding any type of digital asset activity, current or planned, similar to requests made in 2018 and again in 2019.

Dan McCaffrey has an ambitious goal: solving the world's looming food shortage. As vice president of data and analytics at The Climate Corporation (Climate), which is a subsidiary of Monsanto, McCaffrey leads a team of data scientists and engineers who are building an information platform that collects massive amounts of agricultural data and applies machine-learning techniques to discover new patterns. These analyses are then used to help farmers optimize their planting. "By 2050, the world is going to have too many people at the current rate of growth. And with shrinking amounts of farmland, we must find more efficient ways to feed them. So science is needed to help solve these things," McCaffrey explains. "The deeper we can go into providing recommendations on farming practices, the more value we can offer the farmer," McCaffrey adds.

In the Spring of 2008, Stephen Green, the then-Chairman of HSBC, penned his early reflections on the unfolding cataclysm later called the Financial Crisis. "There has been a massive breakdown of trust: trust in the financial system, trust in bankers, trust in business, trust in business leaders, trust in politicians, trust in the media, trust in the whole process of globalization – all have been severely damaged, in rich countries and in poor countries alike." Nearly a decade later, these words have a regrettable continued resonance. Indeed, such views featured prominently in Senate Banking Committee hearings late last year regarding the opening of false accounts at Wells Fargo. John Stumpf, the bank's then-CEO, argued that such behavior was an aberration: "That's not our culture," Stumpf said.

This past August, over 250 people at FINRA took two days to find data driven solutions for FINRA. With over 45 teams, there were some amazing ideas that came out of this hackathon. Below are 13 awesome ideas teams came up with. This team, NG Sonar, realized that our data models rely on manual processes for testing, implementing, and improving. Instead of a manual process, they showed how machine learning could be used to set up feedback loops to constantly evaluate a model's effectiveness.

The news was revealed by two exchange operators who are planning to apply artificial intelligence tools to perform market surveillance in the coming months, and according to a Wall Street regulator, they are not far behind, Reuters reports. The intentions of the use of the software is to for instance search through chat-room messages to detect any "bragging or back slapping" around the time of the launch of a big trade. It will also be able to unravel complex issues more efficiently, such as incidents called "layering" where orders are rapidly sent to exchanges to then get cancelled in order to artificially move a stock price. Tom Gira, executive vice president for market regulation at the Financial Industry Regulatory Authority (FINRA) believes that AI might even have the ability to detect new types of cicanery. "The biggest concern we have is that there is some manipulative scheme that we are not even aware of," he told Reuters.

Stock market cheats, A.I. will soon be looking for you. The sheer volume of transactions conducted in financial markets renders market surveillance by regulatory groups difficult, but machine learning and artificial intelligence tools will soon be employed to ferret out cheaters, according to Reuters. The Financial Industry Regulatory Authority (FINRA) is developing A.I. that it will start testing in 2017 along with its existing surveillance and detection mechanisms. NASDAQ and the London Stock Exchange Group intend to start using artificial intelligence to spot trade irregularities and violation patterns this year. Related: Future AI assistants like Siri could be trained by Joey from'Friends' Reuters reports that financial firms already use artificial intelligence for picking stocks and for monitoring their own firms' compliance.