Auto Fraud Case Analyzer
Detect fraud patterns, organize evidence, and build investigation narratives for claims
What You Can Do
Analyze insurance claims against 50+ documented fraud indicators, automatically organize evidence into searchable timelines, and generate comprehensive investigation narratives that connect claim details to suspicious patterns. You'll identify red flags faster, structure case evidence systematically, and produce investigation narratives that SIU teams can immediately act on—cutting analysis time from hours to minutes while maintaining rigorous documentation standards.
Features
Evaluates claims against 50+ known fraud patterns including staged accidents, soft tissue inflation, timeline inconsistencies, and claimant background red flags. Scores confidence level for each indicator found.
Extracts dates, events, and communications from claim narratives and automatically structures them into searchable, chronological timelines. Flags gaps and suspicious timing patterns automatically.
Synthesizes claim data, fraud indicators, and evidence timelines into structured investigation narratives that clearly connect dots for investigators and compliance teams.
Identifies relationships, co-claimants, and repeated parties (repair shops, medical providers, attorneys) across case details to surface organized fraud rings or serial filers.
Flags contradictions within claim narratives, between medical records and incident descriptions, and across statements from multiple parties with specific quotes and timestamps.
Automatically creates targeted interview questions designed to expose inconsistencies and probe suspicious areas based on detected fraud indicators.
Calculates an overall fraud risk score (1-100) based on weighted fraud indicators, consistency checks, and pattern matching to prioritize investigations.
Formats findings into structured investigation reports with evidence summaries, findings, conclusions, and recommended next steps ready for management review.
Example Output
Input: Claim narrative from 3-vehicle accident with soft tissue injuries and medical treatment from related provider.
Output:
FRAUD RISK SCORE: 72/100 (High)
DETECTED INDICATORS (6):
- Soft tissue injuries only (95% confidence)
- Same medical provider as prior claims (88% confidence)
- Repair estimate exceeds typical for damage photos (81% confidence)
- Treatment began within 24 hours (minor correlation)
TIMELINE:
06/15/2024 14:22 - Accident reported (email timestamp)
06/15/2024 16:45 - Claimant calls clinic (phone records)
06/16/2024 09:00 - Initial medical exam (medical records)
06/16/2024 11:30 - Repair estimate submitted (gap: 21 hours)
CO-PARTY CONNECTIONS:
- Dr. Ahmed Khan, PhysioHealth clinic: appears in 4 prior claims (2023-2024)
- Mike's Auto Repair: appears in 2 prior claims from same claimant
RECOMMENDED ACTIONS:
1. Request complete medical records from prior 3 years
2. Interview claimant regarding relationship to medical provider
3. Compare repair estimate against damage photos (request supplemental)
What's Included
- Fraud Indicator Library: 50+ documented fraud patterns organized by type (claim-level, claimant-level, provider-level) with research citations and typical confidence levels.
- Evidence Extraction Templates: Pre-built templates for extracting dates, parties, amounts, and key phrases from unstructured claim narratives, medical records, and correspondence.
- Investigation Workflow: Step-by-step process for uploading claim data, running analysis, reviewing findings, and exporting investigation reports in compliance-ready formats.
- SIU Best Practices Guide: Reference material on fraud investigation methodology, documentation standards, and interview techniques that align with industry compliance requirements.
- Customization Framework: Guidance for tailoring fraud indicators to your line of business (auto, workers' comp, etc.) and regional patterns.
Who It's For
- Special Investigation Unit (SIU) Investigators
- Insurance Claims Adjusters
- Fraud Analysts & Compliance Officers
- Claims Management Supervisors
- Risk Managers & Loss Prevention Teams
Best For
- High-value claim triage and prioritization
- Structured evidence organization for investigations
- Fraud indicator screening at claim intake
- Investigation narrative writing for case files
- Pattern detection across claim populations
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