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AI in Financial Services:
Tools, Cases, and More

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What You'll Actually Get

Written for executives who need to make decisions about AI, not engineers who build it.

Implementation Case Studies

What's actually working at $500M–$5B institutions. Loan automation, fraud detection, deposit analytics, member-facing AI, with honest assessments of where rollouts stumbled and why.

Tools, Vendors, and Frameworks

We track 400+ AI vendors and the frameworks practitioners are actually using. When a new product category emerges or a major platform changes direction, you'll hear about it with context, not a press release.

Regulatory Context, Decoded

When regulators release new AI guidance, we cut through the legalese and explain what it actually means for your institution, and what questions to bring into your next leadership conversation.

Recent and Upcoming Topics

AI-assisted loan underwriting: tools, frameworks, and what's clearing fair lending review

BSA/AML automation at community scale: case studies from $1B–$3B institutions

Core vendor AI roadmaps: what Fiserv, Jack Henry, and FIS are shipping in 2026

How credit unions are deploying AI differently than banks: member service, collections, and more

Deposit growth and churn prediction: model approaches and the data pipelines that support them

Regulatory updates decoded: what new FDIC, OCC, and CFPB guidance means in practice