Fake payslip detection that stops income fraud before approval.
Fake payslip detection for loans is the forensic verification of payslip documents submitted with credit applications - personal loans, mortgages, auto loans, BNPL. TamperCheck catches edited, fabricated, and AI-generated payslips before they reach underwriting, protecting lenders from income fraud that traditional verification misses.
The problem
Why payslip fraud is the #1 loan-application document fraud
Payslips are the most-edited document in loan applications. Income is the primary underwriting variable, and a payslip is easy to fake: most look similar, the structure is well known, and the figures are small enough to feel low-stakes to fraudsters. The result is that payslip fraud accounts for the largest share of document fraud across personal lending, mortgages, and auto finance.
Three patterns dominate: net pay inflation (changing a single number), fabricated payslips (generated entirely from a template), and AI-generated payslips (created by a generative model from a text prompt). All three pass visual review. Even bank-statement cross-checks are unreliable - fraudsters know to inflate both documents consistently.
Fake payslip detection has to be forensic, not arithmetic. The signals are in the PDF structure, the font metrics, the producer metadata, and the spectral properties of any embedded images. TamperCheck inspects all of them automatically.
What we detect
Forensic signals that expose fraud
Net-pay arithmetic verification
Gross pay, deductions, tax, super/401k, and net pay must all reconcile. A single edited figure breaks the chain; TamperCheck catches it.
Font metric consistency
Edited fields often use slightly different font weights or spacing. Cross-field font metric comparison reveals these edits.
Producer metadata audit
Real payroll systems (ADP, Xero, Gusto, MYOB, BambooHR) produce PDFs with consistent producer signatures. Edits introduce new tool fingerprints.
AI-generated payslip detection
Fully synthetic payslips from generative AI tools have spectral signatures that real payroll-system PDFs don't. The CV layer is trained on these.
Year-to-date plausibility
YTD figures, pay period sequencing, and date consistency are cross-checked against the claimed pay frequency.
Bank statement cross-validation (optional)
When the borrower submits a bank statement, TamperCheck cross-validates that the net pay actually credits the account on the claimed date.
The solution
How lenders use TamperCheck for payslip fraud detection
Most lenders integrate TamperCheck into the document collection step of the loan origination workflow. Every payslip uploaded by an applicant is sent to the TamperCheck API, and the verdict gates the application's progress to underwriting.
How it works
- Integrates with any LOS - Encompass, Calyx, nCino, MeridianLink, or custom
- Runs on every payslip - not just flagged applications
- $0.50 per document - a fraction of any approved fraudulent loan
- Verdict in ~1 minute - keeps origination workflows moving
- Risk score for auto-routing - clean payslips skip manual review
- Works with multiple payslips per applicant - cross-validates them
- Zero storage - critical for borrower data compliance
FAQ
Common questions
See it working on your documents
Start with $5 in free credits - no contract, no card required. Upload your first document and get a verdict in about a minute.