🇺🇸United States

Missed Fraud in Claims Screening Leading to Revenue Leakage

3 verified sources

Definition

Fraudulent claims routinely pass through initial fraud detection and are paid as normal, creating direct, preventable claim overpayments. Traditional rules-based or low-coverage analytics only scan a small share of open claims, so a large fraction of fraud is never flagged for investigation and becomes pure leakage.

Key Findings

  • Financial Impact: Industry-wide: ~$300B per year in insurance claims fraud losses, with traditional methods reviewing only ~5% of open injury claims, implying the vast majority of this loss is unrecovered leakage attributable to ineffective detection and investigation workflows.
  • Frequency: Daily
  • Root Cause: Reliance on manual, rules-based, or partially automated fraud screening with limited data coverage and low sampling rates means only a small percentage of claims are analyzed in depth; investigative capacity is focused on the few flagged cases, allowing systemic under-detection of fraud across the remaining portfolio.

Why This Matters

This pain point represents a significant opportunity for B2B solutions targeting Claims Adjusting, Actuarial Services.

Affected Stakeholders

Claims adjusters, SIU (Special Investigations Unit) investigators, Actuaries and pricing teams, Claims operations managers, Fraud analytics leaders, Chief Claims Officer, Chief Actuary

Deep Analysis (Premium)

Financial Impact

$10M–$50M per year in preventable overpayments for a regional health plan, stemming from undetected claim fraud and abuse within the portion of claims never touched by current rules or audits, against a backdrop of hundreds of billions in industry fraud leakage. • $10M–$60M per year in unrealized savings for a large health plan because many fraud schemes are only detected after extensive payment or never surfaced at all. • $1M–$5M per year in unnecessary medical spend for a mid-sized self-insured employer due to undetected fraudulent or abusive claims buried in overall healthcare costs and high-cost claimants.

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Current Workarounds

Ad-hoc field checks tracked in Excel and WhatsApp coordination • Analysts export periodic claim runs from the TPA system to Excel, manually filter for outliers by provider, CPT codes, or member, and circulate one-off spreadsheets with suspicious items to benefits managers or external SIU partners. • Excel-based reserve adjustments from incomplete fraud data

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Methodology & Sources

Data collected via OSINT from regulatory filings, industry audits, and verified case studies.

Evidence Sources:

Related Business Risks

Excessive Investigation Cost and Overtime from High False-Positive Rates

$X per year (documented directionally: AI-driven systems can reduce false positives by up to 30%, implying current over-spend on investigation could be cut by nearly one-third where legacy methods are in place).

Cost of Poor Quality from Missed and Mishandled Fraud Cases

$X per year (qualitative evidence indicates that reducing false positives by ~30% and improving fraud detection accuracy by ~30% yields significant savings in avoided rework and overpayments).

Delayed Claim Resolution from Manual Fraud Checks Slowing Cash Flow

$X per year (directional: real-time AI and behavioral analytics can cut losses by up to 40% and speed processing by automating low-risk claims, indicating significant opportunity cost from current manual, slow verification).

Investigation Capacity Bottlenecks from Limited Automation

$X per year (industry evidence shows that traditional methods only analyze ~5% of open injury claims, indicating that investigator capacity is functionally capped and leading to substantial uncaught fraud and lost opportunity for recovery).

Regulatory and Legal Exposure from Deficient Fraud Investigation Practices

$X per year (varies by carrier; regulatory actions and litigation can range from hundreds of thousands to tens of millions per case, though specific dollar figures for systemic penalties tied solely to fraud investigation workflow are not aggregated in the identified sources).

Systemic Insurance Fraud and Abuse Evading Traditional Detection

Over $300B per year in insurance claims fraud losses across the industry, much of which represents systemic fraud and abuse that traditional detection methods fail to catch.

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