How AI and machine learning is changing the way Insurers process claims

machine learning

In Insurance, everything comes down to claims. An insurer's ability to handle claims efficiently and accurately drives its profitability, customer experience, and long-term financial health.

However, insurers across the globe are facing unprecedented challenges that make it difficult to support the high standards of customers’ expectations and maintain a healthy bottom line. These challenges arise from the gathering of vast amounts of internal and external claims data. 

In this recent webinar hosted by Insurance Post in association with Datarobot an expert panel explored how claims could benefit from the digital transformation which is being seen elsewhere within the sector. 

Among the questions discussed are:

  • What are the biggest challenges insurers are facing when it comes to claims management?
  • How can technology be used to improve the efficiency and accuracy of the claims handling process?
  • How can technology be used to quickly analyse and gain insights from data to drive better business decisions?
  • How can machine learning models help fight insurance claims fraud and optimize recoveries?
  • When it comes to more complex claims, what advantages can machine learning bring?
  • How can machine learning models help improve customer experience?

Joining us for the discussion are: 

Neil Ashley, Head of Digital Claims, Aviva  

Robin Challand, claims director, Ageas

John Pyall, senior product and wordings manager, Great Lakes Insurance UK Branch – Munich Re

Alastair Robertson, UK head of continuous improvement & automation, Zurich

Quncai Zou, actuarial data scientist, Datarobot

To watch the webinar click here

 

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