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1558 Enforcement Actions in the U.S. over past 30 days


FTC enforcements decreased 55% over the past 30 days


SEC issued enforcements: $37,812,859 over the past 30 days


50 Final Rules go into effect in the next 7 days


49 Mortgage Lending docs published in the last 7 days


1670 docs with extracted obligations from the last 7 days


new Proposed and Final Rules were published in the past 7 days


11906 new docs in within the last 7 days


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SF Business Times

The San Francisco Business Times recently met with our Co-Founder and CEO, Kayvan Alikhani, at our office in the Financial District, to discuss the issues that are plaguing compliance professionals in the financial services industry and how is applying machine learning and AI technology to alleviate their woes.

Below are some of the key takeaways from their discussion:

  • “On average, compliance professionals spend 25 to 30 percent of their time just chasing regulatory changes.”

    • is using machine learning to take what it calls an expensive, error-prone process and make it more efficient. Since the 2008 financial crisis, the number of regulatory changes in the United States has tripled. With, users can follow specific regulatory agencies and localities, and users receive customizable notifications when a regulation changes or new content surfaces: information they would otherwise find for themselves.
  • “When the status quo is a highly manual process and you want to replace it with automation, it’s difficult, you’re changing how people view things.”

    • Kelly Housh, a compliance professional with Bremer Bank, calls “handy.” Her favorite feature is the timeline filter tool, which allows her to look at the number of FDIC enforcement actions in a given quarter, for example. She estimates that alone saves her up to three hours of work.
  • “We need to show people that a company of 15 people using AI is as good as, if not more consistent, reliable and scalable than an organization that has three thousand lawyers.”

    • One way that has been able to increase the accuracy of its models over the past year and a half is through human validation. relies heavily on user feedback, its 15-member advisory board and even law students who check the accuracy of how content is categorized.

Check out the full post by reading the SFBT Article here!

Thank you San Francisco Business Times!

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