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πŸŽ₯ Webinar: Why Entity Resolution & Graph Based Analytics is Crucial for Modern Fraud Detection

Event Ended
Tuesday, Sep 23, 2025, 08:00 AM PDT
Online

Event details

4:00 PM BST | 5:00PM CEST | 11:00AM EDT 

Join Clark Frogley, Global Head of Fraud Solutions, and Shyam Bhatt, Head of Fraud Solutions at Quantexa for a webinar exploring why Entity Resolution and Graph-Based Analytics is crucial for modern fraud detection, and how to apply these tools. 

Insurance fraud doesn’t happen in isolation β€” and detecting it shouldn’t either. Modern insurance fraud demands modern detection.

Insurers now need to evolve their fraud strategies and move beyond claim-by-claim analysis to uncover wider schemes that span across claims, policies, and entities, through entity resolution and networks.

Join Quantexa's fraud experts for a live demo and in-depth conversation on how advanced entity resolution and network analytics are powering a new era of contextual decision intelligence.

During the session, you'll explore how cutting-edge software is enabling insurers to uncover hidden fraud rings, spot anomalies earlier, and scale their defences β€” all in real-time and without extensive manual investigation.

By attending this webinar, we will explore:

  • Learn how moving beyond traditional, siloed claim-by-claim analysis to entity-centric, graph-based approaches can uncover complex fraud schemes that span multiple claims, policies, and actors.
  • Experience a hands-on demonstration showing how cutting-edge software uses contextual decision intelligence to detect hidden fraud rings, spot anomalies earlier, and reduce reliance on manual investigation.
  • Gain insights into the advanced technology stack enabling scalable, real-time fraud detection β€” including practical applications for fraud analysts, data scientists, and technology leaders.β€―

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Community resources to explore

πŸ‘‹Join the Insurance Fraud User Group: 

πŸ“– From the Community Library: 

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Published 3 months ago
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Date and Time
Sep 23, 20258:00 AM - 9:00 AM PDT

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