Insurance Claims Auditor AI-Powered Fraud Detection & Risk Assessment System

Result

▫️$4.2M in fraudulent claims identified in first quarter
▫️Investigation time reduced by 68% for routine claims
▫️False positive rate decreased from 35% to 12%
▫️Previously undetected fraud rings identified through network analysis
▫️Legal defensibility of fraud determinations improved by 40%

Insurance Claims Auditor AI-Powered Fraud Detection & Risk Assessment System

Client Overview

▫️Confidential (national insurance provider)
▫️Industry: Insurance / Claims Processing Engagement
▫️Duration: 18 weeks Team
▫️Deployed: 2 AI engineers, 1 fraud specialist, 1 insurance domain expert from TechSteck Solutions

Objectives

▫️Identify potentially fraudulent claims with 90%+ accuracy
▫️Reduce manual claims investigation time by 50%
▫️Create natural language interface for claims history queries
▫️Connect related claims across family networks and providers
▫️Generate comprehensive claim risk assessments with evidence

Solution

- - TechSteck Solutions developed a comprehensive policy RAG system using:
  - ▫️OCR technology for document processing
  - ▫️LangChain for orchestration and reasoning
  - ▫️Neo4j for relationship mapping and graph search
  - ▫️Custom risk scoring engine with machine learning
  - ▫️RAG-enhanced fraud detection models

Workflow Architecture

1. 1. Claims Document Processing
  - - ▫️OCR digitization of claim forms, medical records, and police reports
    - ▫️Structured data extraction for policy details and coverage
    - ▫️Medical terminology recognition and standardization
    - ▫️Historical claim linkage across customers and providers
  1. Natural Language Claims Investigation
  - - ▫️Interactive query interface for adjusters and investigators
    - ▫️Real-time access to policy details and coverage limitations
    - ▫️Historical claim pattern analysis across customer history
    - ▫️Medical procedure and billing code verification
  1. Network Analysis
  - - ▫️Graph-based relationship mapping across claims
    - ▫️Detection of provider networks with unusual billing patterns
    - ▫️Family and household relationship mapping
    - ▫️Geographic clustering of similar claims
  1. Fraud Risk Scoring
  - - ▫️AI-generated risk scores based on multiple factors
    - ▫️Explanation of risk factors with supporting evidence
    - ▫️Inconsistency detection across claim documentation
    - ▫️Prioritized investigation queue based on risk levels

Conclusion

By integrating RAG capabilities with network analysis, TechSteck Solutions transformed the client’s claims processing workflow—identifying fraud more effectively, reducing investigation costs, and creating a system that continuously improves as it processes more claims data.

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