Automated Fraud Detection System for Insurance Claims
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Solution Overview
Problem
Current methods for detecting fraud in industries such as insurance, banking, and healthcare are inefficient due to the limited number of investigators and the difficulty in identifying fraudulent requests, leading to high false-positive rates and increased costs.
Innovation Solution
A computer-based system that assesses the potential for fraud using multiple techniques, including identity searches, model comparisons, and business rule evaluations, to determine a fraud potential indicator, which can be used to prioritize investigations and reduce unnecessary reviews.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual investigation by adjustors and investigators is used to detect fraud, then detection accuracy may be improved, but resource limitations and high costs worsen
Solution Approach 1:
The patent introduces an automated fraud detection system that acts as an intermediary between fraud requests and human investigators. This system uses multiple fraud potential detection techniques including identity searches, model comparisons, and business rule evaluations to pre-screen requests, allowing limited human resources to focus only on high-risk cases while maintaining detection accuracy.
2Reliability
If manual investigation of every request is performed, then fraud detection completeness is improved, but time consumption and costs increase
Solution Approach 1:
The patent implements preliminary automated screening of fraud requests using multiple detection techniques before human investigation. The system evaluates fraud potential indicators, compares requests against fraud models, and performs identity searches in advance, so that only requests requiring human review are forwarded to investigators, significantly reducing overall processing time while maintaining completeness.
3Productivity
If automated fraud detection systems are used, then processing efficiency is improved, but false-positive rates worsen
Solution Approach 1:
The patent combines multiple fraud potential detection techniques including identity searches, model comparisons, and business rule evaluations into an integrated system. This multi-technique approach cross-validates findings and reduces false positives by requiring convergence of evidence from different detection methods before flagging a request as potentially fraudulent, while maintaining high processing efficiency.
Data Source
AI summary
Methods and systems are provided for assessing the potential for fraud of an insurance claim. In some embodiments, request data may be provided to a computer system. In some embodiments, at least one fraud potential indicator may be assessed to the request data from at least one comparison of at least one request data element to at least one fraud model. In some embodiments, a fraud potential indicator may be an estimate of the potential for fraud in an insurance claim. In some embodiments, at least one fraud potential indicator for request data may be assessed based on at least one comparison of at least one request data element to additional insurance data. Some embodiments may include assessing at least one fraud potential indicator for request data based on at least one fraud potential indicator.