Underwrite faster and safer by catching forged income docs before approval.
Detection layers are weighted for the document mix your industry actually reviews — IDs, statements, paystubs, invoices, leases, and policies.
Inspects EXIF, software signatures, edit history, and structural fingerprints.
Originals are processed in encrypted memory and removed after analysis. Reports stay redacted by default.
Lenders are the highest-value target for document fraud. A forged pay stub or edited bank statement can convert a decline into a default — and the loss lands months later, far from the original decision.
Manual document review is slow and inconsistent. Inline AI verification removes the bottleneck while making the underwriting trail audit-ready.
Inflated income on pay stubs
Edited balances and added deposits on statements
Stolen or recycled IDs across multiple loans
Synthetic identities engineered for bust-out
AI-generated supporting documents
Through your portal, broker network, or LOS integration.
Each doc returns a trust score, math check, and tamper flags.
Findings, evidence, and explainability surfaced in the application.
Immutable record stored for servicing, securitization, and disputes.
Personal and consumer lenders typically see the same three failure modes: submissions that look professional but were assembled from a template, real documents recycled from a prior application with edited fields, and fully AI-generated files that no longer trip rule-based checks.
The hardest of those is the second — recycled real documents — because the underlying file is genuine. TrueDoc looks at submission lineage and pixel-level evidence, not just whether the document "looks real."
TrueDoc is built to sit alongside your current process, not replace it. A typical rollout: documents land in your existing intake (CRM, LOS, ATS, or portal), TrueDoc returns a verdict and per-field evidence via API or dashboard, and your reviewers spend their time on the cases the model isn't confident on.
That keeps the personal and consumer lenders accountable for the final decision while removing the obvious-good and obvious-bad cases from the queue.
Two loss patterns dominate: inflated income on pay stubs, and edited balances and added deposits on statements. The first is loud — a single application that goes wrong. The second is quieter and more expensive: the same fabricated document type re-used across many submissions before anyone connects the cases.
Both show up in the per-finding evidence TrueDoc returns. Teams that review the recycled-document patterns weekly tend to catch organised submitters earlier in the lifecycle.
No credit card. Redacted report in under a minute.