Linking AI Initiatives to Real-World Outcomes
FRAUD DETECTION: MITIGATE RISK & BOOST CONVERSION
A major payer.
The client was in need of identifying claims fraud using a systematic approach. They wanted to manage fraud and boost conversion with the accuracy of machine learning.
- Combination of Deep Learning based professional service and modularized AI components used according to organization’s cognitive maturity
- Business transformation with smarter cognitive outcomes
- Adding industry, business and customer insights to the value chain
- Seamlessly integrate data across functions
- Developed a fraud detection tool that:
- Uses state-of-the-art machine learning techniques such as Bayesian Networks and Link Analysis
- Uses Storm and Spark to run models on large data volumes
- Predicts the likelihood of fraud for a claim
- Deployment of real-time information sharing across physicians, clinics, members, and payer organizations, pattern identification to detect potential frauds towards claims.
- Payer analytics used interoperability data analysis to track and mitigate potential frauds before realization
- The payer increased fraud recoveries by over 30%
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