How lenders in India are getting fooled by documents that look completely real

We build financial document analysis software for Indian lenders. Over the past two years, the fraud patterns we see in bank statements submitted for loan applications have changed significantly.

The old version of document fraud was easy to catch. A scanned PDF with the wrong font. A balance column that didn't add up. A statement with inconsistent date formatting. A trained analyst would spot it in 15 minutes.

The new version is harder. Generative AI tools can now produce bank statements with correct running balances, plausible transaction histories, consistent formatting, and clean PDF metadata. The document passes every visual check. There is nothing obviously wrong with it.

The detection has to shift from "does this look right" to "does this behave right."

What does that mean in practice? You look at transaction sequencing. Does money move through this account the way it would for someone with this income profile, at this bank, over this time window? You look at counterparty patterns. Are the UPI inflows consistent with a salaried employee or do they look like layered deposits from multiple sources? You look at circular flows. Do funds leave and return within a few days in a pattern that inflates apparent turnover?

The same shift is now happening with GST returns and ITR documents submitted alongside loan applications. A fabricated GSTR-3B can show Rs.80 lakh monthly turnover when the bank statement shows Rs.12 lakh in credits. An ITR can declare income that bears no relationship to what actually moved through the account.

The fix is cross-document verification - checking each document not just for internal consistency but against every other document in the application file.

This is the problem Precisa is built for. Bank statements, GSTR, ITR — analysed together, not in isolation.