Are you deploying agentic AI in a regulated industry? Then you must implement model risk management (MRM).

Agentic AI is too powerful not to govern.

It can autonomously observe, decide, and take actions with very real effects on your business.

These effects can be both good and bad, depending on the stability and quality of your systems. MRM minimizes the risks by identifying and mitigating them early on.

Read this guide to learn how to implement it in this guide.

This Week: Modernizing Insurance Claims With AI ft. David Mocklow

Is the insurance industry overlooking its most critical opportunity for transformation?

Can claims handling become a strategic advantage rather than just a cost center?

David Mocklow, Office of the CUO at MSIG, shares why modernizing claims with AI is essential for customer trust, operational resilience, and long-term growth.

We covered:

• Why claims, not underwriting, will define tomorrow’s insurance leaders

• How AI can capture expert judgment before it walks out the door

• The staffing crisis in claims and what to do before it’s too late

• Why TPAs are outpacing carriers and what that means for competition

• What the capital markets can teach insurers about real-time claims signals

How Automated Insurance Claims Actually Work

What does it actually take to automate an insurance claims process end-to-end?

In this post, we walk through the real-world systems behind AI-powered claims handling, from document ingestion and classification to decision-making, quote generation, and human-in-the-loop review.

If you’re in insurance and serious about automation, this piece breaks down what that future looks like, clearly and concretely.