Verify suspicious payment, transfer, and messaging screenshots before you trust them.
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Estimated savings based on replacing a 10–15 minute manual document review with automated TrueDoc analysis.
Proprietary detection scans template variance, metadata drift, pixel-level retouching, and structural anomalies the human eye misses.
Inspects EXIF, software signatures, edit history, and structural fingerprints.
Originals are processed in encrypted memory and removed after analysis. Reports stay redacted by default.
Screenshots are the most trusted — and easiest to fake — proof in digital commerce. Free tools can edit a payment screenshot in under a minute.
TrueDoc looks beyond what the eye sees: pixel-level forensics, font and spacing consistency, metadata, and AI-generation signatures.
Edited 'proof of payment' screenshots (bank, PayPal, Venmo, Revolut, Wise)
Faked crypto transfer confirmations and wallet balances
Doctored chat and DM screenshots used in disputes
Composite screenshots stitched from multiple sources
Fully AI-generated screenshots of UIs that never existed
PNG, JPG, or PDF.
ELA, pixel splicing, font consistency, metadata, and AI-generation signals.
Suspicious areas are marked with confidence scores.
Trust, request alternative proof, or escalate.
Edited screenshots are the single most common 'proof of payment' fraud in P2P trades, marketplace deals, and crypto OTC.
TrueDoc inspects font rendering, character spacing, anti-aliasing, and pixel-level splicing patterns that human eyes rarely catch. Where metadata is present, creator-tool and edit-trace inconsistencies feed the verdict.
Limitation: re-screenshotting and heavy compression strip many forensic signals. When confidence is low, always request an alternative proof (transaction ID, on-chain hash, bank export).
Most "AI detector" tools look at one signal — usually a perplexity score on extracted text. The screenshot fraud checker runs that as one layer of many. It also evaluates metadata lineage (software, edit history, geo), pixel-level forensics (ELA, font kerning, retouching regions), and structural anomalies in the underlying PDF or image container.
The reason: edited 'proof of payment' screenshots (bank, paypal, venmo, revolut, wise) rarely leaves only one fingerprint. A convincing forgery usually fails on two or three of those layers, even when one of them looks clean.
A high-risk verdict on Bank and wallet transfer screenshots, P2P payment app screenshots, Crypto exchange confirmations returns per-field evidence — not just a score. You see the suspicious regions highlighted on the page, the specific metadata fields that triggered the flag (for example, "Faked crypto transfer confirmations and wallet balances"), and the layer each finding came from.
That structure is what makes the verdict actionable: marketplace sellers and p2p traders can read why a document was flagged before deciding to reject, request a reupload, or escalate.
Scanned originals, mobile-camera shots, and re-exported PDFs are the three most common sources of benign anomalies. The screenshot fraud checker scores those differently from the patterns associated with deliberate forgery — for example, a recompressed JPEG from a phone is not treated the same as a recompressed JPEG with a font substitution.
When a document is flagged, the report tells you which signal triggered it. If the only signal is a low-confidence compression artifact, the verdict is downgraded rather than counted as fraud.
No credit card. Redacted report in under a minute.