Perfect Data, Wrong Risk

Perfect Data, Wrong Risk

When AI Turns the Internet Into an Underwriting File, Accurate Evidence Can Still Produce an Inaccurate Decision By James W. Moore Key Takeaways Underwriters have been checking websites and outside sources for decades. AI changes the economics by making that research...
Perfect Data, Wrong Risk

How Much of the Carrier Has to Be Left?

AI, Delegated Underwriting, and the Limits of Insurance Unbundling AnalysisThe Economics of AI in Insurance, Part 4By James W. Moore Key Takeaways Delegated underwriting and the separation of insurance functions long predate modern artificial intelligence. AI did not...
Perfect Data, Wrong Risk

The Carrier Owns the Decision Architecture

What Automated Underwriting Can Teach Us About AI Accountability Key Takeaways Insurance did not begin delegating decisions to machines with generative AI. Automated underwriting systems have been doing versions of it for decades, and they generally worked by making...
Perfect Data, Wrong Risk

Noise Diversifies. Bias Accumulates.

Judgment, Determinism, and the Shape of Error in Insurance Key Takeaways Large language models can produce different outputs from identical prompts even when configured to minimize randomness, but some of that variation comes from how the system processes requests...
The Coming AI Questions for Reinsurers

The Coming AI Questions for Reinsurers

The Economics of AI in Insurance, Part 3 By James W. Moore Key Takeaways Better underwriting does not create more risk-bearing capital. Carriers buy reinsurance for reasons that go well beyond confidence in their own risk selection, including capital, liquidity,...
What Happens When Underwriting Gets Cheap?

What Happens When Underwriting Gets Cheap?

Artificial Intelligence May Change Competition More Than Demand By James W. Moore   Key Takeaways AI’s most important effect on insurance may not be labor displacement but capacity displacement: the creation of underwriting capacity faster than insurable...