Intelligent Insurance Fraud Detection with Speech and Image DNA for a Leading US-Based Company
Overview
The client, an insurance provider, faced challenges in detecting nuanced fraud signals across claims, including limitations in voice forensics that impacted early and accurate identification. They aimed to strengthen fraud detection capabilities and improve how suspicious claims are identified and assessed. ACL Digital enhanced their system using integrated data and advanced analytics, enabling more effective fraud detection and decision-making.
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Challenges
Limited detection of nuanced fraud signals
Inefficient early claim risk assessment
Data silos restricted cross-claim fraud visibility
Solution
- Implemented Digital Speech DNA to detect suspicious speech patterns and identify links to known fraudsters using voice forensics
- Deployed Digital Image DNA to flag misuse and duplication of images across claims
- Introduced a claim scoring mechanism with Initial Claim Credibility Score and Claimant Reputational Score to prioritize reviews
- Enabled secure data sharing through a private, permissioned blockchain for anonymized intelligence exchange and compliance
Outcomes
- Achieved 96% accuracy in insurance fraud detection using machine learning models
- Enabled detection of suspicious speech patterns and image misuse within claims
- Facilitated anonymized intelligence sharing through a private, permissioned blockchain
