This is a good take, but

> A machine learning organization thinks of risk entirely differently than an automated risk underwriting organization.

It's possible and maybe even advisable to use machine learning in the automated risk underwriting business, but it is a different setup / set of objectives.

As the author notes, IMO the adversarial and antifraud aspect of risk underwriting turns it less into a straight-up estimation problem and much more into a game theory type of problem. ML models can assist in evaluating risk, but you do indeed have to be preocuppied by your risk as a party to the transaction in the first place, and not just trying to predict prices as a third party observer (which by itself is pretty riskless).