Will AI Supercharge Regtech for Community Banks?

The ever-growing regulatory compliance burden often tops the list of headaches community bankers face, and most see no end in sight. According to the Conference of State Bank Supervisors (CSBS) Community Bank Sentiment Index, updated in July 2024, 80% of community bankers said they anticipate that their regulatory burden is only likely to get heavier in the future. 

The good news is that while the march toward greater regulation is unrelenting, community bankers have a growing array of regulatory technology tools—AI among them—to handle the workload. Even a brief look at some of the latest wrinkles in regtech suggests that AI is supercharging what can be accomplished in compliance, with new and improved solutions popping up every day.

A more equitable compliance playing field

For community banks, the new affordability of predictive analytics and other AI-driven regtech solutions is making a playing field that has never been described as level a little more equitable, according to Lakshmi Balasubramanyan, associate professor in banking and finance at Case Western Reserve University, a nonprofit research university in Cleveland.

“Even with limited resources, community banks are now able to access AI-driven advantages,” she says.

Charles Potts, executive vice president and chief innovation officer for ICBA, agrees. He also points out that while artificial intelligence may seem like just another hot topic of the moment, it’s not new for bankers. He notes that for the past 40 years, FICO scores have been based on predictive analytics and have been made possible by tools that “we are now calling ‘AI.’”

What is new, he says, is that while community banks have been awash in big data for decades, there are now a variety of AI tools within financial reach that let data be used in innovative ways. 

“AI tools have become more pervasive as the latest in computing power has made them more cost effective,” Potts says. “The brute force computing power that was historically needed now exists literally on our mobile devices.”

“To operationalize law, you have to turn it into data first. … Now, when laws change, we can identify the changes at the character level, which is much more precise.”

—Rohin Tagra, Azimuth

A range of use cases for AI in regtech

For community bankers seeking opportunities to jump on the AI-enabled regtech bandwagon, a great starting point is with a subset of artificial intelligence or robotic process automation, says Potts. 

Here, the objective is to identify repetitive processes and then use machine-learning tools and techniques to boost efficiencies. As additional “low-hanging fruit,” Potts points to back-office functions, many of which fall under the regulatory and compliance umbrella.   

Finosec, an Alpharetta, Ga.-based company that provides tools to help bankers meet their governance goals, has uploaded guidance from the Federal Financial Institutions Examination Council (FFIEC) and a variety of regulatory handbooks— as well as its own playbooks and processes—to create an AI-enabled assistant called “Regi Ranger.”  

“Bankers have a whole bunch of ‘thou shalts’ as guidance that they have to go out and do,” says Zach Duke, Finosec’s CEO and founder. Instead of depending solely on an information security or compliance officer, banks can now turn to Regi to both understand what changes need to take place to meet current regulations, as well as find ways to make these changes.

The true advantages of an AI solution like Regi are most apparent when new regulations are issued, says Duke. For instance, when interagency guidance on risk management for third-party relationships was issued in 2023 and updated earlier this year, the changes could be quickly summarized and even presented to a technology steering committee with the help of AI tools.

“The more we rely on AI, the more you’ll have to rely on your risk and compliance folks to provide the internal controls to make sure AI is performing properly.”

—Paul Viancourt, Ncontracts

Automated vs. manual compliance

Different vendors are offering their own twists on AI regtech solutions. Using AI, machine learning and proprietary algorithms, Azimuth in Jacksonville, Fla., took federal and state laws and turned them into structured database records. 

“To operationalize law, you have to turn it into data first,” says Rohin Tagra, founder and CEO of the regtech company. The data can then be used to create checklists of requirements for specific areas of banking, such as mortgages, credit cards and auto loans.  

“Now,” Tagra adds, “when laws change, we can identify the changes at the character level, which is much more precise.” 

By turning laws into testable algorithms, Azimuth helps financial institutions improve their compliance-testing processes, often quite dramatically. 

When a community bank manually tests its own compliance, it typically looks at two or three dozen examples to make sure that, for example, credit bureau reporting is being done in the right fashion or that the right disclosures have been distributed to customers. 

With Azimuth’s solution, says Tagra, it’s easy to test an entire customer portfolio for regulatory compliance rather than focusing on a small subset of customers. Here, he says, “you get much more [frequent and] accurate results and you’re sure that every customer is accounted for.”

Ironically, the explosion in the number of fintech vendors has created its own promising use case for AI. At Ncontracts, director of product marketing Paul Viancourt is convinced that his company’s contract management module, which leverages AI, is supercharging regtech. 

He notes that by running a contract through a large language model within set parameters, AI-fueled technology can analyze that contract and point to important details such as fee increases and other potential risks. When human beings set out to achieve the same ends, Viancourt explains, the process can be time consuming and expensive, especially when corporate or legal experts are conducting the review.

As an example of an area where AI can make an enormous difference, Viancourt cites core banking contracts, which often run several hundred pages in length. He believes AI can help bankers pull out key pieces of information, allowing them to negotiate more favorable deals.

Empower your employees

“There’s an alphabet soup of banking regulations from A to Z that have to be fulfilled,” says Case Western’s Balasubramanyan with regard to how AI is used for model development purposes. “A lot of community banks don’t have the manpower to stay up to date on regulatory compliance and go through all the regulatory submissions.”

Fortunately, AI and regtech are also supercharging the potential of a community bank’s existing compliance team.

When Finosec’s Duke imagines how AI will alter regtech in the future, many of the changes will stem from how regulatory staff operates. He notes that institutional knowledge will be codified within AI-driven systems, so “banks won’t have to be so reliant on one or two critical people.”

He also anticipates that as regtech becomes more widespread, the time needed for information security consultants and auditors will wane. 

“Looking at the future, the big advantage of AI and regtech is that these tools are going to make institutions and their teams more efficient, and that will let them reduce their employee costs,” Duke says. “Banks won’t have to hire as many people, and their existing employees can do more.”

If the compliance team of the future is leaner, will experts in this arena be obsolete? Not necessarily. Many experts instead maintain that compliance specialists will play an even more critical role. 

“From a risk management standpoint, humans are the ones who are going to act as internal controls to make sure that AI is doing what it’s supposed to do—and doing it the right way,” says Ncontracts’ Viancourt. 

“The more we rely on AI, the more you’ll have to rely on your risk and compliance folks to provide the internal controls to make sure AI is performing properly,” he explains. “In the end, we have to remember that the bank is on the hook for what AI does.”

An AI-heavy future

For Balasubramanyan, the truest sense in which AI could spur a revolution in bank compliance would be by making risk management less backward-looking and more dynamic.

She says that banks could use data and predictive analytics tools to determine when more deposits are needed or when risk in an auto-loan portfolio is ratcheting up too high, all in real time. “There’s going to be more proactive risk management, and we won’t be looking in the rearview mirror,” she says. 

Balasubramanyan also suggests that if bankers could dynamically navigate the economic landscape, they could hone their strategies and optimize their decision making.

While looking a few years down the road can powerfully illustrate how AI and regtech might alter compliance, it’s important to remember that this vision is not science fiction, says Potts. It is achievable today.

“AI’s promise is being delivered,” he says. “This is not only about the future. It’s about the here and now, too.”