There are many different types and levels of insurance fraud. False claims, staged accidents, false applications are all well-understood and documented but fraud goes all the way down to an exaggerated claims for an extra few Euros in compensation. Most individuals wouldn’t bat an eyelid at an exaggerated insurance claim but this is fraud and it affects everybody. An increasingly large percentage of all the insurance premiums we pay (motor, household, health, travel, business etc.) are simply to cover the fraudulent losses suffered by the insurers. Everyone’s premiums would be considerably lower if it wasn’t for fraudulent insurance claim activities. Moreover, the nature of insurance fraud is becoming both increasingly complex and increasingly diverse (new types of coverage, cross-border frauds etc.).
Developing technologies – Robotics, Machine Learning and Artificial Intelligence are key technologies being developed in combating insurance fraud. Automation makes many rather basic / non-complex processes quicker, more effective, more cost-efficient and usually more precise. AI is particularly useful for spotting patterns. This, as a lot of insurance fraud mitigation and management is all about spotting patterns and connecting what are often seemingly unrelated events/circumstances/data. As all stakeholders engaged in combating insurance fraud begin to truly realize the potential of AI and intelligent automation, senior leaders must now consider the strategic requirements and commercial implications of artificial intelligence within their respective organizations.
It is these strategic discussions, use-cases, process improvements and commercial implications that will a key feature of discussions at our event in 2019.
Topics covered include:
Best practice in the use of Artificial Intelligence tools
Who are today’s fraudsters?
AI-enabled claims processing
Industry Data Sharing – The UK Approach
Accurate fact-checking procedures
Cross-company insurance fraud data-sharing
Navigating the post-GDPR world
Artificial Intelligence: pros and cons
Benefiting from accurate data analytics
Sharpen your investigative interviewing techniques
Smart investment in the fight against insurance fraud
Balancing diligent counter-fraud measures whilst providing a high quality service
Best-practice in insurance fraud investigation
Cross-border fraud data sharing and cooperation with law enforcement
Integrating artificial and human intelligence