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AI agent for credit analysts

Concentration Limit Monitor Agent

Keep exposures within limits and catch breaches before approvals are signed

Risk managementMonitoringDecisionsFinance
See how it worksGet access
Concentration Limit Monitor Agent: what goes in, what the agent does and what you get

What it does

A bank can end up with 22 percent of its book in one industry because each loan looked fine alone. This agent aggregates exposures every day by borrower, industry and region and checks them against the limits. It models pending approvals to see what would breach if they close, and shows the headroom left. When something would breach, it proposes options such as selling a participation, reducing the commitment or waiting for a payoff, and recalculates the exposure with each option. It continues checking after each change. Credit officers approve any exception to the limits. Edge case: a borrower group with linked entities is aggregated as one, even when the entities have different names.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueYes, continueApprovedNoNo 1 STARTS WHEN Daily run or new approval proposed 2 USES A TOOL Aggregate exposure by borrower group, industry andregion 3 USES A TOOL Add pending approvals to the totals 4 CHECKS THE RESULT Is every exposure below its limit? If not: Identify the exposure and the loans that causeit. Back to step 2. 5 DOES Model options: participation, smaller commitment orwait 6 CHECKS THE RESULT Does at least one option bring exposure under thelimit? If not: Prepare an exception request with the numbers.Back to step 5. 7 DOES Draft the recommendation with headroom 8 YOU APPROVE Credit officers approve any exception 9 DOES Update the monitor and notify the lender through theofficers 10 RESULT Concentration report
Read the steps as a list
  1. Daily run or new approval proposed
  2. Aggregate exposure by borrower group, industry and region
  3. Add pending approvals to the totals
  4. Is every exposure below its limit?If not: Identify the exposure and the loans that cause it. Back to step 2.
  5. Model options: participation, smaller commitment or wait
  6. Does at least one option bring exposure under the limit?If not: Prepare an exception request with the numbers. Back to step 5.
  7. Draft the recommendation with headroom
  8. Credit officers approve any exceptionThe agent waits here for your OK.
  9. Update the monitor and notify the lender through the officers
  10. Concentration report

How it decides

It aggregates linked borrowers, compares with limits, and warns at 90 percent of a limit and flags a breach above 100 percent.

  • Warn at 90 percent of a limit
  • Flag a breach above 100 percent
  • Aggregate linked borrowers as one group
  • Include pending approvals in every test

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Warning level (default 90 percent)
  • Limits table (default the board-approved limits)
  • Dimensions monitored (default borrower, industry, region)
  • Run frequency (default daily)

What keeps you in control

It always asks you first

  • Credit officers approve any exception to a limit

Hard limits

  • Never approve or decline a loan
  • Never ignore pending approvals
  • Use the approved limit table

It stops when

  • Done: Exposure below limits or exception approved
  • Stop: Data source is incomplete, so hand to the analyst

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensDaily data shows the hospitality industry at 14.2 percent against a 15 percent limit. A pending $12 million loan would push it to 15.4. The agent models a $4 million participation, giving 14.9 percent, and rechecks the result. It drafts the recommendation. The officers approve the smaller commitment and no exception.

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