Fraud detection
Synthetic identity, document manipulation, ring fraud, payout-stage scams. The four patterns that account for most small-lender losses, what AI catches, and what it still misses.
Bank statement tampering detection with LLMs: the forensic prompt chain that catches surgical edits
A four-check LLM forensic chain — arithmetic, cadence, vendor fingerprint, PDF metadata — that catches roughly four out of five surgical bank-statement edits before disbursal, with honest false-positive numbers.
10 red flags AI catches in loan applications (that humans miss under time pressure)
Ten specific red-flag patterns that LLMs reliably surface from pasted application text — with the signal, the prompt logic that catches it, and the false-positive rate you should expect.
AI fraud detection for lenders: patterns, prompts, and the playbook
The four fraud patterns every small lender eventually meets — synthetic identity, document manipulation, ring fraud, and payout-stage scams — and where AI actually catches them vs. where it still misses.