Tampered and Fraudulent Document Detection

• Head of Fraud Control Unit
• Claims Investigation Manager
• Head of Claims
• Chief Risk Officer

Reimbursement bills, motor repair invoices and death-claim papers are easy to alter with free editing tools. A changed amount on a pharmacy bill, a back-dated discharge summary or one hospital bill reused across several claims rarely stands out to an assessor working through a queue.

We build a document forensics layer that runs on every claim document as it is submitted. It examines the file, the image and the content: PDF structure and metadata, signs of local editing or pasted regions in images, arithmetic and date logic, and identifiers such as GSTIN or registration numbers against reference data you hold. It also searches your claim archive for near-duplicate pages. Each document gets a risk score with the specific signals that triggered it and highlighted regions on the page. High-risk files go to your fraud control unit as a case pack; everything else continues through normal processing, with a sample kept for quality review.

• Checks PDF structure and metadata for incremental edits, unusual producer software and font substitutions
• Detects pasted, cloned or locally altered regions in scanned and photographed images
• Recalculates bill totals, taxes and line items and checks date sequences across documents
• Validates GSTIN format and check digit, and hospital and doctor registration numbers against reference data
• Finds near-duplicate pages and photographs across your historical claim archive
• Produces an explained risk score with page overlays and a case pack for investigators

1. 01Collect original filesDocuments are taken as originally submitted, before any compression or re-scanning, together with claim metadata.
2. 02Run file and image forensicsPDF structure, metadata and image-level checks look for signs of editing, splicing or generation from templates.
3. 03Check content logicArithmetic, dates, identifiers and cross-document consistency are tested against rules and reference data.
4. 04Search for reusePerceptual hashes and text fingerprints are compared with the claim archive to find repeated pages or photos.
5. 05Score and routeSignals combine into an explained risk score; files above the threshold go to the fraud control unit as a case pack.
6. 06Investigate and feed backInvestigators record outcomes, which are used to tune thresholds and retire noisy signals.

1. Ingestion
   • Claim system document feed
   • Original-file preservation store
   • Claim metadata loader
2. Forensic analysis
   • PDF structure and metadata analyser
   • Image manipulation detector
   • Template and font consistency checks
3. Content and reference checks
   • Arithmetic and date logic rules
   • GSTIN and registration validators
   • Provider reference data
4. Similarity search
   • Perceptual image hashing
   • Text fingerprint index over the claim archive
5. Scoring and case management
   • Explained risk scoring
   • Investigator case pack with page overlays
   • Outcome feedback log

Investigators in your fraud control unit review every high-risk referral and decide whether to investigate, query or clear the claim. The system surfaces signals only; it never rejects a claim or labels a customer, hospital or garage as fraudulent.

• Core claims or TPA platform (via API or document export)
• Document management system or claim archive storage
• Fraud control unit case management tool
• Provider and garage master data
• Data warehouse for fraud MIS

• Signals explained in plain language; no unexplained scores reach investigators
• Thresholds set and reviewed with the fraud control unit, with periodic checks for skew against particular regions or provider types
• Re-photographed or heavily compressed documents marked as low forensic value rather than scored as suspicious
• No automatic claim rejection or customer communication
• Original files preserved unaltered for evidential use

• Supports the fraud monitoring framework and investigation function that IRDAI expects insurers to maintain, without replacing investigator judgement.
• Claim archives are searched only for fraud prevention and claim handling, consistent with purpose limitation under the DPDP Act 2023.

• Insurance

  Health Claim Document Extraction

  Turn hospital bills, discharge summaries and investigation reports into structured, checked claim data, with uncertain fields routed to an assessor instead of guessed.

• Insurance

  Motor Claim Damage Assessment from Photos

  Detect damaged panels and damage types from guided claim photos, check them against the workshop estimate and pre-inspection images, and give surveyors a structured evidence pack.

• Fintech & Payments

  Selfie-to-ID Face Match and Document Tamper Checks

  Compare a live selfie with the photo on an ID, check liveness and spot edited or replayed ID images, sending borderline cases to a reviewer with highlighted evidence.

• Accounting, Audit & Consulting

  Forensic Review of Expense Claims

  Review every expense claim, not a sample: read the receipts, check them against travel, leave and policy data, and rank suspicious patterns for forensic investigators.