BANKING
AI decisions that hold up .
From credit and fraud ML models to LLM assistants for bankers, with the evidence model risk and compliance teams need.
What we hear
“Our model inventory doesn’t include the LLM tools people are actually using.”
“Validation takes months, so the business works around it.”
“We can’t show an examiner which data fed a decision six months ago.”
“Vendors embed AI in software we already bought, and nobody reviewed it.”
"Where did this answer come from?"
Relationship managers use an LLM assistant to answer questions about a client’s credit agreement. One answer misstates a covenant, and the client relationship is at risk. A3R sets up the assistant so that can’t pass unnoticed:
- Approved sources only: the assistant answers only from approved documents for that client, and every answer cites the clause it used.
- Clear limits: questions outside its approved scope get “I can’t answer that,” not a guess.
- Numbers are checked: covenants, rates, and limits in an answer are compared with the source values before the banker sees them.
- A complete record: every question, answer, and source is logged for the model risk team, and testing reruns when the vendor updates the LLM model.
What you get
Complete AI inventory
ML models, LLM tools, and AI inside vendor software, each with an owner.
Risk-based tiering
Aligned to the 2026 interagency model risk management guidance (SR 26-2).
A proportionate validation playbook
Fast lanes for low-risk use, deeper review where the risk is real.
Decision lineage
From source data to output, retrievable months later.
Exam evidence pack
Produced as AI runs, not reconstructed for the exam.
Vendor AI review
For AI features added to software you already license.
Start with the assessment.
In about four weeks, you’ll know what AI you’re running, where you stand on the maturity curve, and what to fix first.