Monitaur Blog

Original insights and perspectives about model governance and risk management

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Governing generative and agentic AI under SR 26-2: What financial institutions need to know

SR 26-2 excludes generative and agentic AI from model risk management scope, leaving banks exposed. Learn how Monitaur's Common Controls and FlightSim close the gap.

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AI Governance & Assurance

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The shift from “trust me” to “show me”: navigating high-risk AI and the imperative for objective assurance

Visionary. Customer Favorite. Leader.

We’re proud to share that Monitaur has been recognized as a Visionary in the inaugural Gartner® Magic Quadrant™ for AI Governance Platforms.

Colorado’s SB26-189: New requirements for automated decision-making technology and compliance strategies

SB26-189 replaces Colorado's AI Act with new documentation, disclosure, and human review requirements for automated decision-making. What risk and compliance teams need to know.

A delay in the EU AI Act is not a delay in AI risk

The EU AI Act delay isn't a reprieve. Here's how insurers should use the 16-month runway to build defensible AI governance before December 2027.

AI washing is the new greenwashing, and regulators are paying attention

SEC and NAIC are targeting AI washing. Learn what insurance carriers must document to substantiate AI claims before regulators come asking.

The governance gap in agentic AI: What happens when your AI agent makes a bad decision?

Nobody wants to answer the question until they have to. Then everyone asks it at once: "Who owns the decision when AI is wrong?”

The Autonomy Paradox: Why Agentic AI demands more governance, not less

The multi-step, autonomous nature of AI agents does not make existing risk frameworks obsolete. It makes them more essential than ever. A technical breakdown of what responsible deployment actually requires.

NAIC AI Systems Evaluation Tool Pilot: A Guide for Insurers

Monitaur CEO Anthony Habayeb breaks down the 2026 NAIC AI Pilot, its impact on insurance governance, and how carriers can prepare for upcoming exams.

Actuaries and data science: Bridging the gap

New methods from data science and AI present new opportunities for actuaries, but they haven't yet been absorbed into actuarial practices largely because of training and compliance barriers. We propose solutions for bridging this gap.