Document fraud software analyzes the documents your customers send — ID, bank details, payslips, tax notices, company registration extracts — and flags those that have been fabricated or altered. On paper, every solution promises to "detect fakes in seconds". In practice, they do not detect the same things. Here is how to evaluate an anti-fraud document solution and test it before choosing.

What to expect from a document fraud solution

Three objectives, which must be met together:

• stop forgeries before they cause harm — a loan granted, an account opened, a payment diverted, a claim paid;
• not block genuine customers: an overly strict tool drives away clean files and overloads your teams with unnecessary checks;
• justify every decision: know why a document was rejected, to answer both the customer and the supervisor.

To understand fraud techniques and the signals a tool must catch, start with our guide on document fraud detection.

8 criteria for choosing document fraud software

1. Document coverage

List the documents you actually receive and check that each one is covered. Many tools excel at ID documents but are weak on proof of income or company documents — which are nevertheless the most frequently forged. Also check geographic coverage if you have foreign customers.

2. Number of analysis layers

A good solution does not settle for an image score. It combines:

• visual analysis: local edits, fonts, alignment, inconsistent areas;
• file analysis: metadata, modification history, PDF structure;
• internal consistency: calculations, check digits (MRZ, IBAN), formats;
• cross-consistency between documents in the same file;
• source verification: 2D-Doc codes, official registers.

The more independent layers there are, the harder it is for a fraudster to get around all of them.

3. Handling photos and scans

Your customers will not always send the original PDF. Ask how the tool behaves with a phone photo, a poor-quality scan or a screenshot — and whether it can recognize a photo of a screen.

4. Explainable alerts

"Fraud score: 0.82" helps no one. The analyst must see what triggered the alert and where: the edited area, the inconsistent field, the file's modification date. That is what makes it possible to decide quickly and document the decision.

5. False positive rate

Ask for figures on your own documents, not on a demo set. A high false positive rate has a hidden cost: every unjustified alert means a manual check and sometimes a lost customer.

6. Integration into the journey

Detection must happen at upload, so you can immediately ask the customer for another document rather than three days later. Check for an API, a hosted journey and connectors to your tools.

7. Link with identity and KYC

A genuine document can be used by an impostor. Document fraud detection works best when combined with identity verification with liveness detection and KYC, in the same file.

8. Security and compliance

Supporting documents contain personal and sometimes sensitive data. Require hosting in the European Union, a configurable retention period, access logging and a GDPR-compliant contractual framework.

How to test a solution before choosing

1. Build a test set from your own files: clean documents and forgeries already identified by your teams.
2. Include the hard cases: a single falsified field, a poor-quality photo, a foreign document.
3. Measure two things: forgeries detected, and clean documents wrongly flagged.
4. Have an analyst review the alerts: are they understandable and actionable?
5. Time the processing of a complete file, alerts included.

Which sectors need document fraud detection?

• Banking, lending and leasing: proof of income and identity at approval.
• Insurance: underwriting and claims handling.
• Fintechs and payment institutions: remote account opening.
• Real estate and rentals: tenant files.
• Automotive and dealerships: financing and long-term leasing.
• B2B platforms: vetting sellers, partners and suppliers, with a KYB check.

Dataleon's document fraud solution

Dataleon's document fraud software analyzes every document in the file — IDs, company registration extracts, bank details, payslips, supporting documents — combining image analysis, metadata, consistency checks and cross-document matching. Every alert is explained and located on the document. Detection is built into the client portal, the risk engine and AML screening: a detected forgery directly affects the file's score.

FAQ

What is the difference between document fraud detection and identity verification?

Identity verification checks that a person is the holder of the document presented. Document fraud detection checks that the documents themselves have not been fabricated or altered. The two are complementary.

Does document fraud software replace analysts?

No: it focuses them on the cases that require judgment. Clean files pass automatically; suspicious ones arrive with the detected signals.

How much does a document fraud solution cost?

Most offers combine a subscription with per-document or per-file pricing. Compare the total cost, including manual review time. See our pricing.

Request a demo and test the solution on your own documents.