Routine business loan assessment
Produces a policy-based recommendation supported by debt service cover, leverage and the requested loan’s share of revenue. Makes the financial basis of each assessment explicit.
— Finance & Investment
Assesses a credit application against your own credit policy and returns a governed underwriting decision — approve, refer or decline — showing how affordability, risk and policy thresholds drove the outcome, and holding it for a credit officer sign-off before any letter is issued.
1–2 hours → ~5 minutes
For one document, brief or record at a time
No coding required
— USE CASES
Produces a policy-based recommendation supported by debt service cover, leverage and the requested loan’s share of revenue. Makes the financial basis of each assessment explicit.
Identifies sector restrictions and mandatory policy conditions that require referral or decline, regardless of the overall assessment. Cites the relevant clauses so exceptions remain visible.
Provides a structured decision record with a score breakdown, supporting calculations and policy references. Reserves decision-letter authorisation for a credit officer.
Uses comparable past decisions to inform the assessment while keeping current credit policy central. Creates a documented precedent for future case comparisons.
Business lending decisions require consistent treatment of financial evidence, sector appetite and policy exceptions. Routine business loan assessment is the typical trigger — produces a policy-based recommendation supported by debt service cover, leverage and the requested loan’s share of revenue. Makes the financial basis of each assessment explicit. Done properly it is defensible; done at pace it becomes a judgement call nobody can retrace. And "properly" usually means 1–2 hours of manual work.
Here the same job runs as a Skill. Your material goes in; approve, Refer or Decline recommendation comes out, alongside affordability and leverage calculations with supporting arithmetic. The judgement is built in — how items are broken up, what standard they are held to, and where the run stops for a human review. Net effect: 1–2 hours down to ~5 minutes, no drift between runs, and every conclusion traceable back to the evidence behind it.
Credit / Loan Underwriting exports as a structured SKILL.md file and is MCP-ready, so the same method runs in ChatGPT, Claude, Copilot or your own AI products. Adapt it to your methodology, and the intelligence stays yours — not locked to one vendor.
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