Claims Fraud Detection and Subrogation Prioritization

AI-assisted claims workflow for insurers that detects potentially fraudulent or high-risk claims, supports end-to-end claims handling and triage, and prioritizes subrogation and forensic review to improve recovery, speed, and accuracy.

The Problem

Claims fraud detection and subrogation prioritization for insurance claims operations

Organizations face these key challenges:

1

High volume of claims with limited adjuster and SIU capacity

2

Fraud indicators spread across notes, documents, images, and historical claims

3

Legacy claims systems create fragmented workflows and duplicate data entry

4

Static rules generate too many false positives or miss novel fraud patterns

Impact When Solved

Reduce manual claim review workload by auto-prioritizing low-risk vs high-risk claimsIncrease fraud referral precision with anomaly and network-based risk scoringImprove subrogation recovery by identifying third-party liability earlierShorten FNOL-to-triage and investigation cycle times

The Shift

Before AI~85% Manual

Human Does

  • Review FNOL details, reports, bills, photos, and adjuster notes manually
  • Apply static fraud, severity, and subrogation rules to triage claims
  • Escalate suspicious, complex, or recoverable claims to SIU or recovery specialists
  • Investigate liability, request missing evidence, and decide claim handling next steps

Automation

    With AI~75% Automated

    Human Does

    • Approve SIU referral, forensic review, subrogation pursuit, and other material claim decisions
    • Review AI-ranked high-risk or high-recovery claims and validate recommended actions
    • Handle exceptions, novel scenarios, and disputed claims requiring judgment

    AI Handles

    • Continuously score claims for fraud risk, severity, and subrogation potential as new evidence arrives
    • Extract facts, entities, timelines, and liability signals from claim documents, notes, and images
    • Detect anomalies, contradictions, and related-claim patterns to prioritize investigation
    • Generate case summaries, missing-evidence prompts, and next-best-action routing recommendations

    Operating Intelligence

    How Claims Fraud Detection and Subrogation Prioritization runs once it is live

    AI runs the first three steps autonomously.

    Humans own every decision.

    The system gets smarter each cycle.

    Confidence89%
    ArchetypeRecommend & Decide
    Shape6-step converge
    Human gates1
    Autonomy
    67%AI controls 4 of 6 steps

    Who is in control at each step

    Each column marks the operating owner for that step. AI-led actions sit above the divider, human decisions and feedback loops sit below it.

    Loop shapeconverge

    Step 1

    Assemble Context

    Step 2

    Analyze

    Step 3

    Recommend

    Step 4

    Human Decision

    Step 5

    Execute

    Step 6

    Feedback

    AI lead

    Autonomous execution

    1AI
    2AI
    3AI
    5AI
    gate

    Human lead

    Approval, override, feedback

    4Human
    6 Loop
    AI-led step
    Human-controlled step
    Feedback loop
    TL;DR

    AI handles assembly, analysis, and execution. The human gate sits at the decision point. Every cycle refines future recommendations.

    The Loop

    6 steps

    1 operating angles mapped

    Operational Depth

    Technologies

    Technologies commonly used in Claims Fraud Detection and Subrogation Prioritization implementations:

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    Key Players

    Companies actively working on Claims Fraud Detection and Subrogation Prioritization solutions:

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    Real-World Use Cases

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