Data-driven, backend claim analysis, in real-time.
Bulk review claims using data-driven backend analysis via file transfer.
Aggregated results from a data-driven backend analysis to gain case insights
Aggregated results from a data-driven backend analysis to gain case insights
During claims processing, fraudulent and ineligible submissions dilute settlement funds and expose administrators to scrutiny. Our data intelligence platform evaluates every claim with multi-factor precision—so only legitimate class members get paid.
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Protect legitimate class members by eliminating fraud and ineligible submissions.
High-volume claims environments invite fraud rings, synthetic identities, and coordinated submission abuse. Traditional blocking methods reject valid claimants while letting sophisticated fraud through—diluting settlement funds, reducing class member payouts, and creating defensibility risk for counsel and administrators alike.
Our data intelligence platform applies multi-factor scoring using proprietary data to separate legitimate class members from fraudulent submissions with scientific precision—producing consistent, evidence-based eligibility decisions that withstand scrutiny from courts, administrators, and opposing experts.
Stop fraud at the source
The Anti-Fraud Triangle blocks fraud at the form, payment, and analysis stages—before it reaches the fund.
Bulk review claims after the claims period. Securely send claim files to ClaimScore and ClaimScore securely returns result files.
All
28
Matched
19
Unmatched
8
Errors
1
PassesCaseSpecificValidation
claimant-validation
TRUE
FALSE
FALSE
TRUE
TRUE
ClassMemberID
class-member_ID
SAC-0007681
SAC-0007682
SAC-0007683
SAC-0007684
SAC-0007685
Drag and drop your .csv file here, or Browse Files
You may adjust the import settings to match your files separator characters and other options.
ClaimScore connected directly to digital claim forms and results sent directly to claims or client management systems, in real time.
Documentation >Evaluate every submission through layered evidence signals to determine eligibility and identify fraudulent activity.
Scoring system >Identifies multi-entry fraud patterns, name variations, and shared contact attributes designed to bypass traditional checks.
Fraud breakdown >Incorporate our proprietary data to strengthen validation, confirm details and surface discrepancies.
Detect automation, anomalies, and suspicious behaviors using temporal and structural based signals.
Verify claimant identity and contact information to confirm legitimacy and ensure accurate attribution.
Provide clear, case-ready explanations that document every flag, scoring input, and eligibility decision.
Accuracy explained >
Discover how ClaimScore can safeguard your funds with a practical example, ensuring the class receives their rightful share.
Learn more >Trusted in the highest-profile matters.
Lopez v. Apple, Inc.
Hubbard, et al. v. Google LLC, et al.
Katz-Lacabe et al v. Oracle America, Inc.
Brooks v. Thomson Reuters Corp.
Mackmin et al. v. Visa Inc. et al.
In re Broiler Chicken Antitrust Litigation
Ruffin, et al. v. CVS Pharmacy, Inc.
Kessler, et al. v. The Quaker Oats Company
Hasemann, et al. v. Gerber Products Co., et al.
Bush v. Rust-Oleum Corporation, et al.
Jien et al v. Perdue Farms, Inc. et al
Pompilio, et al. v. Boar’s Head Provisions Co. Inc.
Nixon v. Grande Cosmetics, LLC
Brown et al v. JBS USA Food Company et al
Jimenez v. Artsana USA, Inc.
Perez v. Rash Curtis & Associates
Rosenfeld et al. v AC2T, Inc.
Landsheft v. Apple Inc.
Frasco v. Flo Health, Inc.
Bartone, et al v. Meta Platforms, Inc. et al
Bradley v. Brookhaven Borough
Zeichner v. Nord Security Inc. et al
Wyland v. Woopla, Inc.
Whiting v. Yellow Social Interactive Ltd.
Morris v. EVIG, LLC d/b/a Balance of Nature
In re: TelexFree Securities Litigation
