Document fraud detection software that catches what reviewers miss

Document fraud detection software analyzes the files people submit to you, such as bank statements, payslips, tax returns and invoices, for signs of tampering, forgery or AI generation. Instead of judging how a document looks, it inspects the metadata, file structure, fonts and content consistency, then returns a trust score and a fraud-risk rating so your team knows which documents to trust and which to review.

Several layers of analysis run on every upload. Metadata forensics look for editing-software traces and timestamps that do not match the issuer. Content layer analysis finds direct text modifications, font inconsistencies and layered edits. Template matching compares the document against known issuer formats, and machine-learning models trained on millions of documents processed since 2019 flag unusual patterns across the page and the file structure. The result is a trust score, a fraud-risk rating and the warnings behind it, strongest first.

Financial and official PDFs: bank statements, bank letters, payslips, employment letters, tax returns including W-2s, 1099s and the 1040, invoices and utility bills, credit reports and benefit letters. Upload the original PDF from the bank, employer or issuer so the metadata and structure stay intact. VerifyPDF also checks identity documents such as passports, driver's licences, national IDs and residence permits from a clear photo or scan.

The forensic checks a trained reviewer needs about 10 minutes for run in under 5 seconds, and the software reads signals no reviewer can see: editing traces in the metadata, font substitutions in the text layer and structural anomalies in the file itself. Modern forgeries use the same fonts and layouts as the originals, so manual review catches the sloppy fakes and misses the good ones. The decision stays with your team: a flag is a signal to review, not a verdict.

Three ways. Use the dashboard and drag documents in, no integration required. Connect your own systems through the REST API: submit a document with one HTTP call, then poll for the result or receive it via webhook. Or give an AI agent the open-source VerifyPDF skill so automated workflows can verify documents through the same API. All three surfaces return the same trust score, fraud-risk rating and warnings.

Accuracy is around 99% on computer-generated financial documents such as bank statements, payslips and tax returns, provided the original PDF is submitted rather than a scan or screenshot. Every result includes the warnings behind the rating, so your team can weigh the evidence instead of trusting a black box.