You're losing 5-10% of claims payments to leakage: overpayments, duplicates, and undetected fraud

The Many Faces of Leakage

Claims leakage takes dozens of forms, most too subtle for manual detection:

• Duplicate payments: Same invoice submitted twice with slight variations in invoice number or amount. Both get paid because no one cross-checks.
• Inflated estimates: Body shop charges $850 for a bumper that costs $450 wholesale. Adjuster has no price benchmarking data and approves.
• Out-of-policy payments: Claim settled for $15K when policy limit is $10K. No one noticed because adjuster didn't validate coverage before approving.
• Unnecessary medical treatment: Claimant receives ongoing physical therapy long after recovery. No one questions why treatment continues indefinitely.
• Upcoding and unbundling: Medical providers bill separate codes for procedures that should be bundled. Increases payment by 30-40%.
• Phantom vendors: Payments to vendors who never performed work. Shell companies set up by organized fraud rings.
• Late reserves: Claims reserved too low initially, then increased multiple times. Each increase creates opportunity for leakage and poor loss forecasting.
• Fee padding: Legal fees, expert fees, investigator fees inflated with vague line items and no supporting documentation.

For a carrier paying $50M annually in claims, 5-10% leakage equals $2.5M-$5M in preventable losses per year.

Why Leakage Persists

Manual claims processes create systematic vulnerabilities:

• No cross-claim analysis: Adjusters review claims in isolation. Can't see that the same claimant filed 3 similar claims in 12 months (fraud pattern).
• Limited benchmarking: Adjusters lack data on typical repair costs, medical treatment durations, legal fee ranges. Rely on "gut feel" to judge reasonableness.
• Approval shortcuts: Under pressure to close claims quickly, adjusters rubber-stamp settlements without thorough validation. "Close enough" becomes the standard.
• Incomplete documentation: Missing invoices, estimates without itemization, medical records without diagnosis codes. Insufficient documentation enables overbilling.
• Vendor relationship bias: Adjusters work with same vendors repeatedly and stop questioning their pricing. "ABC Body Shop is always fair" — until they're not.
• Manual validation is impossible: An adjuster handling 50 claims can't manually check every line item on every invoice against policy limits, pricing benchmarks, fraud patterns, and historical data. Something always slips through.

1. Duplicate Payment Detection

Regure automatically detects duplicate invoices and payments before they're processed:

• Compares new invoices against all previous invoices for the same claim and vendor
• Fuzzy matching detects duplicates even when invoice numbers or amounts vary slightly
• Flags invoices with identical descriptions, dates, and amounts
• Cross-claim duplicate detection identifies same invoice submitted on multiple claims
• Payment history check prevents paying same vendor twice for same work
• Automatic alerts when duplicate is detected, blocking payment until reviewed

Industry data shows 2-4% of invoices are duplicate submissions. Regure catches them before payment.

2. Policy Limit Validation

Every settlement and payment is automatically validated against policy coverage:

• Integration with policy systems pulls coverage limits, deductibles, exclusions
• Automatic calculation of remaining coverage (limit minus prior payments)
• Real-time alerts when settlement would exceed policy limits
• Validation that claimed damage is covered under policy terms
• Deductible verification — ensures policyholder portion is collected
• Sub-limit tracking (e.g., $500 limit for jewelry, $2,000 for electronics)

Prevents out-of-policy payments that create E&O exposure and direct financial losses.

3. Pricing Benchmark Validation

Regure compares invoice amounts to industry pricing benchmarks and historical averages:

• Auto repairs: Integration with Mitchell, CCC, Audatex databases for parts and labor pricing by region
• Medical treatment: Comparison to Medicare fee schedules, usual and customary rates, and regional healthcare pricing
• Legal fees: Benchmarking against typical attorney rates by jurisdiction and case complexity
• Contractor services: Pricing validation for roofing, plumbing, electrical work based on regional market rates
• Historical pricing: Comparison to previous similar claims and vendor pricing history

Flags invoices 20%+ above benchmark for review. Adjusters can justify or negotiate based on data.

4. Fraud Pattern Recognition

AI analyzes claims for patterns associated with fraud and abuse:

• Repeat claimants: Flags individuals who file unusually frequent claims
• Staged accidents: Detects multiple claims with similar loss descriptions, locations, or parties involved
• Provider mills: Identifies medical or repair providers with suspiciously high claim volumes or costs
• Phantom vendors: Cross-references vendor addresses, phone numbers, and tax IDs to detect shell companies
• Treatment duration anomalies: Flags medical treatment extending far beyond typical recovery times
• Geographic clustering: Detects unusual concentration of claims from specific areas (fraud ring indicator)

ML models trained on confirmed fraud cases identify subtle patterns humans miss. Flag suspicious claims for SIU referral before payment.

5. Medical Bill Validation

Healthcare claims undergo specialized validation for medical coding and treatment appropriateness:

• CPT/ICD-10 validation: Ensures procedure codes and diagnosis codes are properly matched and medically necessary
• Upcoding detection: Flags billing codes that are more severe (and expensive) than diagnosis supports
• Unbundling detection: Identifies procedures billed separately that should be bundled under single code
• Treatment reasonableness: Compares treatment plans to evidence-based medical guidelines
• Prescription validation: Checks that prescribed medications match diagnosis and dosages are appropriate
• Provider credentialing: Validates that providers are licensed and in good standing

Medical billing contains 15-25% in improper charges (industry data). Automated validation catches overbilling before payment. See Document Processing for medical record extraction details.

6. Automated Audit Trail

Every validation check and override is logged for compliance and continuous improvement:

• Complete record of all automated checks performed on every claim
• Documentation when adjusters override system flags (with required justification)
• Trending reports show which adjusters approve flagged items most frequently (coaching opportunity)
• Leakage analytics quantify savings from caught duplicates, pricing negotiations, denied out-of-policy payments
• Continuous model improvement as fraud patterns evolve

Measure leakage reduction over time. Prove ROI. Identify which controls are most effective.