Month-end without the rebuild
Run the same analysis on this period's export and get a like-for-like read.
— Finance & Investment
Credit / Loan Underwriting
A deployable credit decision engine: application in, an Approve / Refer / Decline verdict out — scored against your own credit policy, with a credit officer sign-off before any letter is issued.
- Finance & Investment
- Traceable reasoning
- Runs anywhere
1–2 hours → ~5 minutes
For one document, brief or record at a time
No coding required
- Input
- Ledger, budget, forecast or model exports
- Output
- Computed figures with the workings retained per line item
- Runs in
- Skillsize · ChatGPT · Claude · Copilot
- Export
- SKILL.md · MCP
- Time saved
- ~1–2 hours per run
— USE CASES
What people use Credit / Loan Underwriting for
Variances explained, not just listed
Each material line item comes with a driver and a size, not only a number.
Cases reviewed on one standard
Hold every submission to the same test so approvals are consistent.
What it works from
- Ledger, budget, forecast or model exports
- Your thresholds, materiality rules and reporting structure
What you get back
- Computed figures with the workings retained per line item
- A commentary-ready pack aligned to how you report
Why this is expensive by hand
Finance work on the reporting period in scope is arithmetic plus interpretation, and it is the interpretation that drifts between analysts and months. Month-end without the rebuild is the typical trigger — run the same analysis on this period's export and get a like-for-like read. 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.
How this Skill produces it
Here the same job runs as a Skill. Your material goes in; computed figures with the workings retained per line item comes out, alongside a commentary-ready pack aligned to how you report. 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.
Who it's for
- Finance directors and FP&A teams
- Investment, deal and corporate development teams
- Controllers and reporting managers
- Consultants building or reviewing business cases
Run it in Skillsize — or export it anywhere
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.
ChatGPTClaudeCopilotAI Products (MCP)
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