Blog
AI, risk and operations, explained.
Practical guidance for lenders, banks, payments and commerce businesses. Each piece pairs how the work really runs with what the technology can safely do, at a pace your board and your examiner will support.
New here? Start with 01, 02 and 03.
01Be a careful fast follower: putting AI to work in lending
You do not have to be first. You have to be deliberate, documented and boring where it counts.Strategy · Technology · 3 min read →
02Fix the process before you add the AI
Automation amplifies whatever it touches. A messy process, automated, is just a faster mess.Operations · Strategy · 3 min read →
03Document intake: the safest first AI project in lending
High volume, repeatable, measurable, and a person stays in charge.Technology · Operations · 3 min read →
04Model risk management for AI, in proportion
SR 11-7 was not written for large language models, but its principles still apply.Governance · Technology · 3 min read →
05Buying AI from a vendor: due diligence that holds up in an exam
The 2023 interagency guidance on third-party risk is the frame examiners use.Governance · Technology · 3 min read →
06Explainable credit decisions: what applicants and examiners are owed
AI can help with lending without taking over the decision.Governance · Operations · 3 min read →
07Build, buy or integrate: a decision guide
Most institutions should buy and integrate. Build only where it is genuinely yours.Technology · Strategy · 3 min read →
08Your data is the real project
AI is only as good as the data it reads. Getting the data right pays off whether or not you ever buy AI.Technology · Operations · 3 min read →
09Servicing and collections: where operations and technology meet
Technology helps most when it supports a well-run operating model.Operations · Technology · 3 min read →
10How to know it worked: scorecards for pilots and what to tell your board
A pilot without a baseline and a stop rule is just an expense.Strategy · Operations · 3 min read →
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