MSME Lending Intelligence (SwiftAudit)
How can autonomous multi-agent pipelines accelerate credit assessment for small and medium enterprises by triangulating unstructured banking PDFs with financial statements?
Engineered an agentic financial intelligence dashboard that ingests MSME bank statements and corporate filings, extracts structured transaction metrics, detects round-tripping and cash-flow irregularities, and synthesizes credit risk summaries for loan officers.
Problem Framing and Analytical Objective
Underwriting Micro, Small, and Medium Enterprises (MSMEs) is notoriously labor-intensive. Loan officers must manually parse disparate bank statements, tax returns (GST), and audit reports to detect circular transactions, debt-service capacity, and liquidity gaps.
SwiftAudit was built as a multi-modal agentic platform to automate cross-document triangulation and generate structured credit evaluation memos with full source citation.
Analytical Steps and Modeling Workflow
Document Parsing & Extraction
Extracted structured transaction tables and narrative disclosures from multi-page PDF bank statements and business financial reports.
Financial Triangulation Agents
Deployed specialized agents to reconcile reported revenues against bank credit deposits, identifying circular flow-of-funds or recurring bounce charges.
Credit Risk Scoring & Memo Generation
Generated automated Debt Service Coverage Ratios (DSCR), working capital health metrics, and executive summary memos highlighting identified risks.
Baseline Assumptions and Parameter Inputs
- Bank statement formats follow standard Indian scheduled commercial bank schemas.
- AI synthesis acts as an underwriter copilot; human-in-the-loop review is mandatory before credit sanction.
Analytical Judgement and Observed Insights
Automated extraction and reconciliation reduced preliminary document inspection time significantly, enabling rapid screening of credit applications.
Cross-referencing credit transactions against stated sales successfully flagged instances of high-frequency round-tripping between related-party entities.
Critical Limitations and Uncertainty Boundaries
- Poor-quality scanned or photocopied documents require specialized OCR preprocessing before reliable token extraction.
- Synthetic credit assessments do not replace on-site physical collateral verification or promoter character assessment.