Combating Claim Fraud: Reduce False Positives with AI, LLM & Graph Database

Insurance Fraud costs businesses and consumers $308.6 billion a year. Learn how Expero and Neo4J can combat claim fraud and reduce false positives in claims.

The National Association of Insurance Commissioners (NAIC) cites that The Coalition Against Insurance Fraud costs businesses and consumers $308.6 billion a year.* Many of those claims are in property & casualty, automotive and also business insurance. Further complicating the process, is all 50 states in the US have different regulatory bodies, each with different rules and regulations. Some states have enacted legislation to combat the different types of insurance fraud schemes such as agent and broker schemes, underwriting irregularities, vehicle insurance schemes, property schemes, doctor and personal injury schemes, up-charging damages, inflating damage values, salvage fraud, and many others. Special Investigations teams are looking at deeply linked patterns with Neo4J Graph algorithms to define other emerging new technology to reduce settlement times, optimize detection of fraud, while enhancing the claims adjustment efficiency.

Join Michael Moore, Senior Director, Strategy & Innovation at Neo4J and Scott Heath, VP Fraud & Analytics at Expero in a hands-on session that demonstrates how to employ ML with Neo4J Graph technology, Human-in-the-loop, and visualization techniques to ensure your organization complies with Special Investigations units.

The focus of this webinar is to identify areas in which Graph DB and Graph Machine Learning, Geospatial, TimeSeries, AI/ML/LLM, Visualization, and Graph technology can increase the accuracy of claim fraud identification by over 45%, and to show how including the ‘Human in the Loop’ can get you ahead of your state’s fraud prevention legislation.

Key Learning Topics:

Key Challenges In Insurance Claim Fraud

Discuss issues in the investigation and claim fraud, loss and abuse processes, emerging threat vectors, impact areas of audit & compliance and what is to be expected in 2023/24.

Technology Innovations

Understand why fraud, waste and abuse investigators need to care about new technologies like Neo4J with next-generation AI combined with ML/Neo4J graph algorithms, master data matching logic, graph analytics and LLM Models. These technologies assist in reducing false positives and increasing accuracy.

Empower Investigator Teams

Explore new capabilities in visualization technology and human processes that increase throughput and provide valuable human intelligence, creating quicker and more efficient outcomes for different roles like fraud management, investigators and data and analytics teams by using AI/Graph analytics.

Rise Of ML & AI With ‘Explainability’

Learn practical methods of harnessing the ensemble of AI, time-series, IoT data, spatial analytics, and ML/Graph algorithms, including LLM Models, that involve non-technical investigators as ‘humans-in-the-loop’ for higher accuracy and streamlined processes.

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