Skip to main content
Solution · MSME Lending

Bank Statement Analysis for MSME Lenders: Synthetic Financials for the Unbanked

The Indian MSME credit-demand gap is roughly ₹65 trillion. The reason it persists is that the segment is too large to walk away from and too thin-file to underwrite with conventional financial-statement evidence. TransactIQ's four-layer synthetic financial construction — personal/business separation, synthetic P&L, balance sheet, and cash flow — is the working credit-decision substrate built for that segment.

What TransactIQ does for an MSME lending pipeline

The four synthetic-financial layers plus the surrounding capabilities an MSME lender credit policy actually depends on.

Layer 1 — Personal vs business separation

MSME proprietors and many small private-limited promoters route personal and business activity through overlapping accounts. Layer 1 separates the two streams using counterparty, narration pattern, frequency, and round-number cues — without which any further synthetic financial view is contaminated.

Layer 2 — Synthetic P&L

From the business-stream cash flows, construct a working synthetic profit-and-loss view: channel-level revenue (GST counterparty inflows, gateway settlements, marketplace payouts) against vendor outflows, salary outflows, GST-payment outflows, rent, utilities, and interest. The shape an MSME credit decision actually needs.

Layer 3 — Synthetic balance sheet

A working-capital view inferred from bank activity — receivables proxy (gateway/marketplace receivables in flight), payables proxy (vendor outflow lag), cash position, and outstanding debt obligations. Not an audited balance sheet, but an evidence-backed approximation for the unbanked or thin-file applicant.

Layer 4 — Synthetic cash flow

Operating, investing, and financing cash-flow inference. Operating from business-stream net flow. Investing from capex-shaped outflows (large infrequent outflows to capital-goods counterparties). Financing from EMI outflows, loan disbursal inflows, and promoter contribution patterns.

PSL-MSME classification signals

Udyam-linkage signals where available, micro/small/medium classification cues from turnover and counterparty mix, manufacturing-vs-services split — feeds the lender Priority Sector Lending classification and target-segment reporting.

CGTMSE eligibility signals

Surfacing the activity patterns relevant to Credit Guarantee Fund Trust for Micro and Small Enterprises eligibility — collateral-free term, working-capital posture, and the segment cues a CGTMSE-routed underwriter actually checks.

GST input-vs-bank-credit cross-validation

Where the MSME files GST and shares portal access, TransactIQ cross-validates GSTR-1 outward turnover against bank inflows from GST counterparties, and GSTR-2B inward credit against vendor outflows — a powerful sanity check on declared revenue and a meaningful evasion signal.

Bounce predictor and round-tripping

Round-tripping detection across inter-account circular flows is critical for MSME underwriting — synthetic turnover inflation is the single most common revenue-overstatement pattern. Bounce predictor for the unsecured-MSME-loan and working-capital book.

Coverage on the long tail

MSME applicants bank with private, PSU, co-operative, and small-finance banks — often more than one. TransactIQ covers 200+ banks including PSU dot-matrix and district central co-operatives, the categories where most incumbent BSA vendors degrade.

Why TransactIQ for MSME lending

Four dimensions where an MSME-lending credit head typically compares vendors.

Dimension Typical incumbent posture TransactIQ
Unbanked / thin-file MSME applicants Standard BSA produces transaction-level signals (bounce, salary, EMI). Limited synthesis up to financial-statement shape. Four-layer synthetic financials (P&L, balance sheet, cash flow) inferred from bank activity — the working view an MSME credit decision needs when audited financials are absent.
Personal-vs-business contamination Most BSA outputs treat the statement as a single stream; personal and business activity are aggregated. Layer 1 separates the two streams before any aggregate signal is computed — without which a synthetic financial view is unreliable.
GST cross-validation GST cross-validation is typically a separate vendor or in-house build. Where GST portal access is available, bank-credit-vs-GSTR-1 turnover and vendor-outflow-vs-GSTR-2B credit are cross-validated as a single signal — a sanity check on declared revenue.
Coverage on co-operative and PSU banks Coverage varies on PSU dot-matrix and district central co-operative banks — the categories where many MSME applicants actually transact. Benchmarked specifically on the degraded tail. Customer outcome: match-rate progression from 51% to 88% on a comparable adjacent-domain workload.
Compliance and security posture
ISO 27001:2022 RBI IT Governance aligned PSL-MSME classification posture DPDP Act 2023 aligned AWS Mumbai (ap-south-1) India data residency by architecture Tamper-evident per-statement audit record

See the synthetic financial view on your MSME pipeline

Send a representative sample of MSME-applicant statements. Receive the four-layer synthetic financial output alongside a coverage and accuracy benchmark.

Request MSME benchmark