All Use-Cases
MSME Credit Use-Case

NBFC Underwriting for Traders

Automated underwriting for trader-led MSME files with volatile bank statement patterns and thin formal documentation.

Who It's For

Target Audience

NBFC credit teams financing kirana distributors, wholesalers, and trading businesses.

The Challenge

What Makes This Hard

Trader accounts often show mixed personal and business cash flows, seasonal spikes, and fragmented counterparties. Manual review increases turnaround time and inconsistency.

How Santulan Solves It

Santulan combines bank statement intelligence, GST trails, and policy-aligned risk flags to generate structured underwriting packs for trader segments.

Lower decision TAT for trader files

Consistent cash-flow quality scoring

Early fraud and circular-flow signal detection

Policy-aligned approvals with explainable factors

How It Works

01

Ingest borrower data

Collect bank statement, GST, and borrower profile data for the requested credit line.

02

Policy-aligned analysis

Score cashflow quality, detect anomalies, and apply lender-specific underwriting policy checks.

03

Credit decision pack

Review explainable risk factors and produce a structured recommendation for sanction or decline.

Frequently Asked Questions

How does Santulan improve underwriting for trader businesses?

Santulan reconstructs transaction behavior, normalizes supplier and buyer patterns, and highlights repayment capacity markers so analysts can review trader files faster and with better consistency.

Can this workflow be integrated with existing LOS systems?

Yes. Output can be consumed through APIs and embedded into LOS workflows with configurable scorecards and policy rules.

Does it work for seasonal or cyclic businesses?

Yes. The model tracks seasonal volatility and compares it against peer behavior to avoid penalizing expected business cycles.

Ready to implement this workflow?

Book a demo and see a live underwriting workflow built around your borrower segment.