Question 1

How do you address SR-11-7 for AI/ML models?

Accepted Answer

Model risk management documentation, validation framework, monitoring posture, and the data-lineage chain that ties model inputs to source systems. We build the data and governance foundation; your model risk team owns the formal validation.

Question 2

What about the EU AI Act high-risk classification?

Accepted Answer

The high-risk classification under the EU AI Act applies to credit scoring, insurance underwriting, and similar uses. We help structure the data inventory, lineage, and governance that the conformity assessment requires.

Question 3

Can you help with CFPB-supervised AI deployments?

Accepted Answer

Yes. CFPB has been clear that ECOA and fair lending laws apply to AI underwriting decisions. The data layer that supports model explainability and adverse-action notice generation is part of our practice.

Question 4

What does AI readiness actually mean?

Accepted Answer

AI readiness means the data foundation is clean enough, the governance is defensible enough, and the metric layer is consistent enough that AI deployment lands without producing the kind of hallucinations or compliance issues that block production use. The work is mostly at the data layer.

Question 5

Do you build AI models or just the data layer?

Accepted Answer

We focus on the data foundation that supports AI deployment. Model selection, training, and tuning we coordinate with the client's AI team or specialist partners. The data layer is where most AI pilots stall.