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Insurers must deploy predictive analytics to navigate future challenges, says Ovum

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The insurance industry must be prepared for future market challenges, the quickening pace of customer-driven commerce and the continuing spread of the digital economy, says Ovum.

 
According to the independent analyst, insurers can improve their competitive position by implementing predictive analytics and using the wealth of rich data available from social media channels and conceptual sources such as the “Internet of Things”.
 
A new report from Ovum suggests that in order to be better prepared, insurers should focus on creative initiatives that analyse data from a number of sources, including social media, third parties and machine-to-machine communications. By concentrating predictive analytics on key areas of the business – namely business operations, marketing and customer relations – insurers will be able to determine which markets to enter or leave, shape target market initiatives and estimate potential losses for the book of business as each customer is added.
 
“Insurers are already well aware of the impending threats/challenges including tightening regulation, demanding customers, an ageing population and weakened economies,” says Barry Rabkin, principal analyst at Ovum. “The critical differentiator for insurers will be minimising future risk thorough predictive analytics by tapping into the vast amounts of rich data.”
 
Rabkin says a new role is emerging – the data scientist role – and this will be as important as the well-known data miner role in the insurance industry. Ovum is already seeing a growing number of insurance companies creating new departments of these types of quantitatively skilled professionals. This role will take a deeper approach to research (i.e. collect more data and explore more hypotheses) and generate recommendations that are scalable down to individual lines of insurance business. Ovum believes that data scientists and data miners will work closely together to discuss "what if" questions regarding their predictive analytics initiatives.

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