Kayvan Alikhani.

When Kayvan Alikhani, co-founder and CEO of San Francisco-based Compliance.ai, surveyed general counsel at U.S. companies, they told him they were overwhelmed by the sheer volume of regulatory changes by state and federal agencies.

So his company came up with a way to use lawyers, law professors and law students to collaborate on a workflow automation tool for U.S.-based financial services companies, exchanging their work for experience with, and free use of, the company's AI.

The tool's concept involves taking “a general counsel in one bank from a siloed approach to compliance, based on one set of decisions, to an expert, crowdsourced approach,” Alikhani said in a recent interview with Corporate Counsel.

This approach can help the GC or a compliance officer spot patterns, predict regulatory trends and allocate resources accordingly, he added. Alikhani said the company began by using interviews, surveys, analyses and research to look at a day in the life of a regulatory compliance officer and how one manages the volume and content of changes. He said the review found “a huge amount of manual work going into just collecting all the information—rules, regulations, agency guidances, executive orders, notices, work enforcement actions.”

It didn't take much study to realize most companies were under-resourced for the task. Alikhani said, “A midsized organization in the U.S. receives on average one such document every 10 to 15 minutes, from several different jurisdictions—local, state and federal. Hundreds of documents a day.”

Every document has to be studied and analyzed for how it affects each business. The workload was out of control, Alikhani said.

“Now imagine you have thousands of banks in the same markets, selling some of the same products, dealing with the same jurisdictions and the same regulatory agencies. They share a huge amount of commonality, yet each one is doing the same research and analysis independently.”

Compliance.ai joins groups of organizations on the internet using artificial intelligence to classify, rate and rank the changes on a common platform.

The company uses experts—the lawyers, law profs and law students—to extract and prioritize key attributes of regulatory changes and to tell a GC or compliance officer when any change is relevant to her company and why. It's a personalized risk assessment.

Through supervised learning, the human teachers—called contributors—raise the confidence level of the computers.

He said he first recruited law students from the nearby University of San Francisco Law School, then expanded to include law schools at Michigan State University in East Lansing; Washington and Lee University in Lexington, Virginia; Widener University in Wilmington, Delaware; and University of Nevada, Las Vegas.

The business now has 60 to 65 trained student contributors, he said, with some 50 other universities interested in participating. Many of the students hope to boost future careers in fintech, blockchain or cryptocurrency areas by gaining experience with machine learning in the finance industry.

Do they work for free? Well, yes at first, he said, but they work from afar, at their own workstations and computers, and at their own pace.

There are some rewards. The contributors receive free use of the research tool to do their own research or analyses on projects or cases. Those who do good work for the company are recognized with prizes, gift certificates, bonuses or even scholarships, he said.

Those who do outstanding work are hired as paid consultants.

Although focused on U.S. organizations now, Alikhani expects to grow the business into Canada, Europe and the U.K. next. He said he also hopes to recruit students internationally, starting in India.