The U.S. National Association of Insurance Commissioners (NAIC) is piloting its AI Systems Evaluatio...
The U.S. National Association of Insurance Commissioners (NAIC) is piloting its AI Systems Evaluatio...
Whether it’s for reassurance, a gut feeling that something’s off, or to manage an unknown, this is a...
TL;DR • Central governance isn’t always enough for algorithmic systems delivered with/by vendors. • ...
TL;DR • The FS AI RMF has useful but scattered expectations on fairness, buried in more than 500 pag...
TL;DR • The final article in a 5-part series. • Part 1 explained triggers for testing and deep dives...
TL;DR • Part 4 of a 5-part series. • Part 1 explained triggers for testing and deep dives: new produ...
TL;DR • Part 3 of a 5-part series. • Part 1 explained triggers for testing and deep dives: new produ...
TL;DR • Part 2 of a 5-part series. • Part 1 outlined how some events clearly trigger deeper dives an...
TL;DR • Part 1 of a 5-part series. • Some events clearly trigger deeper dives and retesting: new pro...
TL;DR • Algorithm/AI definitions are messy, and reference glossaries don’t always agree. • Different...
We already know that ineffective algorithms have a direct monetary impact. But the deeper, longer-la...
“Best practice” gets thrown around a lot in AI and algorithm governance discussions. I hear it often...
This article is a bit long-winded, but there is a point. Bear with me. This week marks 25 years of w...
TL;DR • This featured resource is from the U.S. Treasury. • A new AI Lexicon for financial services....
TL;DR • Evaluate models on performance: Apply the same decision quality standards to your models tha...
TL;DR • UAT often tests for staff workflows, not the actual customer outcome or experience. • BVT ve...
TL;DR • Many significant system errors aren't technical failures; they're business rules that were i...
TL;DR • It’s not a trade-off: We don't have to choose between being ethical and being effective. • A...
TL;DR • Modern tech can help with speed and scale, but doesn’t automatically solve decision quality....
TL;DR • We sometimes confuse algorithmic "bias" with bad intent, but it’s usually just efficiency go...