IntelliCredit — Multi-Agent Credit Appraisal
India-Stack-native credit intelligence. Seven autonomous AI agents ingest via the Account Aggregator network, reconcile GSTR-2A vs GSTR-3B for ITC fraud, and produce an explainable Credit Appraisal Memo — including counterfactual reasoning — in ~4 minutes.
// outcome
- 7
- 13 tbl
- ~4 min
- 3–6 wk
// problem
India's corporate loan appraisal takes 3–6 weeks and costs banks roughly ₹80,000 per file. Existing automation is shallow and unauditable.
// approach
Seven specialized LangGraph agents (ingestion, GSTR reconciliation, buyer-concentration risk, financial-trend analysis, fraud signal, counterfactual reasoning, memo writer) wired to a pgvector-backed retrieval layer for explainability. A 13-table PostgreSQL schema with provenance tracking and source attribution underwrites every credit decision; the memo writer enforces RBI compliance rules. Asynchronous orchestration on a real-time FastAPI / Redis pub-sub / WebSockets backend surfaces live workflow progress.
// results
- End-to-end appraisal in ~4 minutes (vs 3–6 weeks manual)
- Counterfactual reasoning: tells the borrower exactly what to change to get approved
- Audit-ready Credit Appraisal Memos with RBI compliance rules
- Account Aggregator + GSTN native integration
// screens
// in depth
Why counterfactual reasoning
A credit decision is only as useful as the path to overturn it. IntelliCredit’s counterfactual agent takes the appraisal output and the underlying GSTR/AA data, and produces the minimal set of changes — higher revenue disclosure, paid-down exposure, GST-filing cleanup — that would flip the outcome. The borrower gets a roadmap, not a verdict.