Parse any Indian bank statement in under 2 seconds. Get structured FOIR, salary credits, EMI obligations, fraud flags — ready for underwriting APIs. Not screen-scraped text. Decisions.
Most tools give you raw transaction data. We give you the underwriting signal: income, obligations, ratios, and fraud patterns — structured JSON your decision engine can consume directly.
07/08/2026 SALARY CREDIT EMPLOYER 87500.00 08/08/2026 UPI/123456/LOAN 12000.00 DR 09/08/2026 NEFT/HDFC BANK/EMI 8500.00 DR 12/08/2026 ATM WDL 5000.00 DR ... (2,400 more lines — figure it out yourself)
{
"avg_monthly_income": 87500,
"total_emi_obligations": 20500,
"foir": 23.4,
"salary_credits": [
{ "date": "2026-08-07", "amount": 87500,
"employer_pattern": "confirmed" }
],
"emi_lenders": [
{ "lender": "HDFC Bank", "amount": 8500 },
{ "lender": "UPI-Loan", "amount": 12000 }
],
"fraud_flags": [],
"avg_eom_balance": 34200,
"data_confidence": 0.97
}
From PDF upload to underwriting-ready JSON — five stages, one API call.
Template-free extraction — no manual mapping when a bank updates its PDF layout.
Also supports: Account Aggregator (AA) framework XML, PDF statements delivered via DigiLocker, image/photo statements (mobile captures).
Every lending workflow that touches a bank statement benefits.
Automate income verification and FOIR calculation for personal loans, consumer credit, and MSME working capital. Reduce manual underwriting from 4 hours to 4 minutes.
Standardise bank statement output across multiple origination partners. Each partner sends raw PDFs; your risk engine receives consistent structured data.
Extract current account cash flow metrics: average daily balance, seasonal patterns, GST credit turnover proxy, and top counterparty concentration risk.
Detect loan-washing (cash deposits inflating pre-loan balance), round-trip transfers, and salary patterns that don't match declared employer — before disbursal.
Consume AA framework XML feeds alongside traditional PDF statements. Single API, unified output regardless of data source format.
Embed bank statement analysis in field agent apps. Agent photographs statement; structured data appears in the CRM within 2 seconds. No manual data entry.
Built for RBI-regulated lenders. Every extraction is audit-logged.
| Regulation | Requirement | How Extract AI Handles It | Status |
|---|---|---|---|
| RBI Digital Lending Guidelines | Income verification must use verifiable data sources | Bank statements processed from borrower-authorised PDFs or AA feed. No screen-scraping. | Covered |
| NBFC-AA Framework | Data shared via AA must be used within consent scope | Consent scope metadata preserved in API call. No re-use beyond origination. | Covered |
| DPDP Act 2023 | Financial data must be processed with user consent | Processing only on explicit borrower consent. Data deleted post-analysis unless retained by lender. | Covered |
| RBI Fair Practices Code | Credit decisions must be explainable | Every flag and FOIR calculation includes a reasoning trace with transaction-level evidence. | Covered |
| ISO 27001 | Financial data handling security controls | Private deployment option; no data on shared SaaS infrastructure. | Covered |
API access for lean tech teams. Custom builds for lenders who need the full underwriting stack.
Minimum 500 pages/month
One-time. Source code yours.
Supports ADCB, Emirates NBD, FAB, Mashreq + others
Extract AI supports 40+ Indian banks including SBI, HDFC, ICICI, Axis, Kotak, PNB, Bank of Baroda, Canara Bank, Union Bank, Yes Bank, IndusInd, IDFC First, Federal Bank, South Indian Bank, and all major cooperative and regional rural banks. The system handles PDF, image-scanned, and password-protected statements, plus Account Aggregator (AA) XML feeds.
The system identifies salary credits (recurring inflows matching TDS patterns), maps outgoing EMI debits (fixed periodic obligations), and computes Fixed Obligations to Income Ratio as (total monthly obligations ÷ average monthly income) × 100. Output includes net monthly income, total obligations, FOIR percentage, and EMI breakdown by lender where identifiable from transaction narration.
Yes. Extract AI is designed for compliance with RBI Digital Lending Guidelines (Sept 2022 + May 2023 amendments), the Account Aggregator framework (NBFC-AA), and DPDP Act 2023. Data is processed on-premise or in a private cloud; bank statement data is never stored on shared infrastructure. Audit logs are maintained for every extraction call.
The system flags: cash deposit patterns that inflate average balance before loan application (loan-washing), round-trip transactions (self-transfers to sister accounts), salary credits that fall outside employer-typical ranges, sudden large inflows followed by immediate outflows, and mismatches between declared income and actual credit patterns. Each flag includes a confidence score and supporting transaction evidence.
Book a 30-minute call. We'll walk through your current underwriting flow and show exactly where Extract AI plugs in.