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AI can help the industry move from “RegTech” to “RiskTech”

In an article published in the Financial Brand, I made the argument that today’s generative and emerging agentic AI systems can help regulators and banks alike provide robust oversight by automating compliance tasks, monitoring transactions in real-time for suspicious activity, and continually analyzing large datasets to detect risks that may otherwise go unnoticed. They also create the opportunity for banks (and fintechs) to move beyond a “check-the-regulatory-box” approach to a model that enables a more proactive and continuous focus on identifying, managing, and mitigating the underlying risks to their organizations while simplifying regulatory reporting. 

In this post, I want to dig a bit deeper into use cases and vendors. Regulation and compliance have inspired dozens of startups and many millions in Silicon Valley VC investment, but figuring out who is doing what can be a challenge. The below is not meant as a comprehensive directory but rather an attempt to identify areas of focus and provide examples of which companies are focusing where. 


  1. Complaints Management and Oversight

    Sample Vendors: Narrative, Shiboleth, SpringLabs

    Use NLP and sentiment analysis to track customer grievances and identify systemic risk signals.

  2. Continuous Compliance Monitoring and Testing 

Sample Vendors: Themis, Cable

Implement AI solutions that monitor transaction flows and behaviors and document

updates in real-time to maintain constant compliance assurance. 

  1. Asset Tracking 

Sample Vendors: Narrative, Norm.ai, Kobalt 

Monitor assets across marketing, contracts, policies, and procedures for adherence to internal and external compliance requirements. 

  1. Call Analysis

    Sample Vendors: SpringLabs, Observe.ai 

    Transcribe and analyze call center interactions to detect potential mis-selling, fraud, or compliance issues.

  2. Transaction Screening 

Apply machine learning models to flag anomalous transactions and assist with anti-money laundering (AML) workflows. 

  1. Social Monitoring 

Sample Vendors: Narrative, MarketBeam

Use AI to track social media and forums for reputational risk signals and potential

market manipulation. It is important to note that while regulatory rollback may reduce

formal oversight, it doesn't eliminate public scrutiny, media attention, or litigation risk.

  1. Regulation Coverage Monitoring

    Sample Vendors: Panza.ai, Kobalt, Winnow

    Automate the scanning and analysis of new rules and regulations with AI-powered tools.


While banks and fintechs need to think about all the use cases listed above, it doesn’t necessarily make sense to try to add AI capabilities for all of them simultaneously. Given the likelihood and severity of risk in these areas, we believe the first three categories are the natural place to start.


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