How predictive analytics is transforming risk management | News

Predictive analytics and big data analysis are not new concepts. The insurance industry has been looking at how to leverage data for better insights into customers and more accurate risk assessment for a while. Now technological advances allied with more cost-efficient computer processing power is creating unprecedented opportunities. But how can corporates and risk managers make better use of data in risk management?

Huge volumes of data make it challenging for companies to extrapolate value and use predictive analytics to their advantage.

According to Airmic, many risk managers are not making the most of the information surge. Many have been using the same information sources and statistical techniques for several years.

“Risk managers are being told by senior executives and the board that the company requires better data on their risks. The company requires better insurance data for that,” says Georgina Wainwright, Research and Development Manager at Airmic.

“It is a huge challenge for risk managers. They are conscious of the prolific nature of technology and the excessive volume of data being pooled together, which is not being collected effectively.” 

The data journey

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