Banker Creates Credit Due Diligence Tool with 31 AI Prompts Using Only Claude
A domain expert with 17 years in MSME credit underwriting at Indian banks has developed and open-sourced a tool that uses AI prompts to accelerate credit due diligence. The creator has no coding background and built the entire system through conversation with Claude, Anthropic's AI.
The Problem and Solution
Traditional credit teams spend 3-4 weeks collecting 47 documents (balance sheets, stock statements, CMA data, CA certificates, ITRs, property papers) only to discover red flags like NCLT cases, cancelled GST registrations, or cheque bounce cases late in the process. The tool addresses this by extracting maximum intelligence from just 5 inputs: company name, city, GSTIN (India's tax ID), director name, and DIN (director identification number).
Technical Details
The system consists of 31 prompts across 10 categories:
- Entity verification
- Director/promoter background checks
- NCLT/insolvency search
- Market reputation
- GST turnover analysis
- Credit rating
- Group entity mapping
- Shell company detection
- Sector risk
- Final go/no-go memo
The prompts work across any LLM including ChatGPT, Claude, Gemini, Perplexity, and Copilot. No proprietary tools are needed - users simply copy, paste, and investigate.
How It Was Built
The creator, who describes themselves as "not a developer" and "can't write a single line of code from scratch," built the entire tool through conversation with Claude. This includes:
- The 31-prompt library
- A React app interface
- Constitution-based logic
- GitHub Pages deployment
The tool is a single HTML file with no backend, database, login requirements, or cost. The creator described the credit workflow, due diligence dimensions, and nuances of Indian banking regulations to Claude, which helped structure the prompts and build the web interface.
Context and Impact
MSME lending in India represents a $300B+ market serving 63 million MSMEs. The tool aims to compress the first stage of due diligence from 3 weeks to 30 minutes, potentially making credit more accessible to underserved businesses. The creator is not currently building a startup around this but is sharing it with the lending ecosystem.
The creator is seeking feedback on whether similar prompt-based pre-screening tools exist in other lending markets, if the concept would translate to SME lending in the US/UK/Southeast Asia, and experiences from other non-developers who have built domain tools using AI.
📖 Read the full source: r/ClaudeAI
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