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Combat Insurance Claim Fraud: Reduce False Positives with GenAI & Graph

Combat Insurance Claim Fraud: Reduce False Positives with GenAI & Graph

April 25, 2024 11:00 AM
CT /
12:00 pm
ET
ON DEMAND WEBINAR
April 25, 2024
-
April 25, 2024
Combating Insurance Fraud with Cutting-Edge Technology

Insurance fraud costs businesses and consumers billions annually, impacting property & casualty, auto, and business insurance.  This complexity is furthered by varying regulations across all 50 U.S. states.

Join us for a fast-paced, informative webinar designed to equip you with the latest strategies to combat fraud.

Key Focus Areas:

  • Identifying Fraudulent Claims: Discover how Graph Databases (Graph DB), Graph Machine Learning (GML), and AI/ML/Large Language Models (LLMs) can boost claim fraud identification accuracy by over 45%.
  • Staying Ahead of Regulations: Learn how "Human-in-the-Loop" techniques ensure compliance with evolving state-level fraud prevention legislation.
  • Optimizing Investigations: Explore how Neo4J Graph technology, combined with visualization tools and machine learning from Expero, empowers investigators with faster, more efficient claim processing.

Key Learning Objectives:

  • Challenges in Claim Fraud Investigations: Delve into emerging threats, audit & compliance concerns, and investigate best practices for combating claim abuse.
  • Unlocking Technological Innovation: Understand why fraud investigators should leverage Neo4J with advanced AI, ML, graph algorithms, and LLM models to minimize false positives and enhance accuracy.
  • Empowering Investigators with Next-Gen Tools: Discover how visualization technologies and human-centric processes streamline workflows for fraud management, investigators, and data analysis teams.
  • Harnessing the Power of Explainable AI: Learn practical approaches to utilize AI, time-series data, spatial analytics, and ML/Graph algorithms (including LLMs) to empower non-technical investigators as "humans-in-the-loop" for improved accuracy and streamlined processes.

What You'll Learn

  • Master the Complexity of Insurance Fraud: Explore how government regulations and graph link analysis techniques are shaping the future of claim investigations.
  • Harness Neo4J Graph Analytics: Learn how to implement practical methods for claim fraud identification, complex dependency management, and "human-in-the-loop" collaboration.
  • The Art of the Possible: Witness live demonstrations showcasing Expero's Connected Platform, a powerful combination of visualization matching, graph analytics, and machine learning, designed to reduce false positives and enhance accuracy.

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April 25, 2024
11:00 am
CT /
12:00 pm
ET
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Combat Insurance Claim Fraud: Reduce False Positives with GenAI & Graph
America/Chicago
Apr 25, 2024 11:00 AM
CT /
Apr 25, 2024 12:00 PM
ET
https://experoinc.zoom.us/j/94523206777?pwd=anhkRXJjZkI2L2tLWGpkcVhoeU4wQT09
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Combating Insurance Fraud with Cutting-Edge Technology

Insurance fraud costs businesses and consumers billions annually, impacting property & casualty, auto, and business insurance.  This complexity is furthered by varying regulations across all 50 U.S. states.

Join us for a fast-paced, informative webinar designed to equip you with the latest strategies to combat fraud.

Key Focus Areas:

  • Identifying Fraudulent Claims: Discover how Graph Databases (Graph DB), Graph Machine Learning (GML), and AI/ML/Large Language Models (LLMs) can boost claim fraud identification accuracy by over 45%.
  • Staying Ahead of Regulations: Learn how "Human-in-the-Loop" techniques ensure compliance with evolving state-level fraud prevention legislation.
  • Optimizing Investigations: Explore how Neo4J Graph technology, combined with visualization tools and machine learning from Expero, empowers investigators with faster, more efficient claim processing.

Key Learning Objectives:

  • Challenges in Claim Fraud Investigations: Delve into emerging threats, audit & compliance concerns, and investigate best practices for combating claim abuse.
  • Unlocking Technological Innovation: Understand why fraud investigators should leverage Neo4J with advanced AI, ML, graph algorithms, and LLM models to minimize false positives and enhance accuracy.
  • Empowering Investigators with Next-Gen Tools: Discover how visualization technologies and human-centric processes streamline workflows for fraud management, investigators, and data analysis teams.
  • Harnessing the Power of Explainable AI: Learn practical approaches to utilize AI, time-series data, spatial analytics, and ML/Graph algorithms (including LLMs) to empower non-technical investigators as "humans-in-the-loop" for improved accuracy and streamlined processes.

What You'll Learn

  • Master the Complexity of Insurance Fraud: Explore how government regulations and graph link analysis techniques are shaping the future of claim investigations.
  • Harness Neo4J Graph Analytics: Learn how to implement practical methods for claim fraud identification, complex dependency management, and "human-in-the-loop" collaboration.
  • The Art of the Possible: Witness live demonstrations showcasing Expero's Connected Platform, a powerful combination of visualization matching, graph analytics, and machine learning, designed to reduce false positives and enhance accuracy.

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