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Using AI and Advanced Analytics to Prevent Insurance Fraud: From Red Flags to Real Action

How can insurers use artificial intelligence, advanced analytics, and forensic approaches to connect prevention, detection, and investigation into a comprehensive and effective anti‑fraud system?

Insurance fraud is becoming increasingly complex and often involves third parties such as suppliers, agents, brokers, and other business partners. While preventive controls remain essential, insurers are increasingly faced with the question of how to act effectively once red flags have already been detected — how to conduct an investigation, gather evidence, and make well‑grounded decisions.

In this webinar, you will learn how forward-looking insurers leverage AI‑powered analytical solutions, structured third‑party reviews, and forensic tools to effectively address complex claims that may also involve suspected abuses.

The webinar is intended for professionals working in fraud prevention, compliance, internal audit, risk management, management, IT, and data analytics within the insurance industry.

The webinar is free of charge and will be held in English.

Key benefits for participants:

In this webinar, we will highlight processes that lead to benefits such as:

  • reduced financial losses due to early detection and effective response to fraud,
  • improved transparency in third‑party management and better handling of conflicts of interest,
  • faster and better‑substantiated investigations supported by data and analytics,
  • an integrated fraud‑management system connecting prevention and remediation,
  • stronger regulatory compliance and defensive positioning during audits and disputes,
  • practical insights from real insurance cases, not just theoretical models.

Speakers:

  • Janja Skamlič, CFE, Partner, Forensic and Integrity services, EY Slovenia
  • Gaja Novković, CFE, CIA, Assistant Manager, Forensic and Integrity services, EY Slovenia
  • Klemen Radetič, CFE, Head of Fraud Management, Triglav Insurance Group 

Webcast

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