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Competition, customer analytics and under-insurance

Competition, customer analytics and under-insurance

July 17, 2014 12:54 PM | Posted by Paul Schoff | Print this page

One interesting observation to come out of the Interim Report is about technological change and the role of 'big data' customer analytics in the general insurance context. The Interim Report says that:

The trend towards individualised risk-based pricing is growing, as firms access larger data sets, including data from outside their own businesses, and develop more sophisticated analytical techniques.

It is competition among general insurers which has been a driver of the quest to gather and use customer data to more accurately price of risk. Competition drives an insurer to remove more uncertainty than its rivals, for example by using data to better price risk. That is because the more accurately an insurer can price risk, then the more accurately it can forecast insurance margin and the more confidently it can compete using that margin.

The Interim Report highlights that competition using data to more accurately price risk may in fact create issues of underinsurance.

…the better understanding of risk can cause problems for people who are found to be a higher risk. They may face higher premiums or a loss of access. This is a particular problem where consumers are not able to change their risk profile or find it difficult to do so.

Indeed, big data and customer analytics may even pose existential threats to some products. Taken to its logical extreme, customer analytics can undermine the very foundation of insurance, namely uncertainty. This means risk can't be pooled. If it isn't uncertain, it isn't insurable.

The question posed by the Interim Report is therefore very important:

What evidence and data are available to assess whether more granular risk-based pricing will lead to exclusion or further underinsurance?

Only with evidence based analysis can a sensible appraisal be made of the need for reform or intervention, for example, by limiting the information which insurers can use in assessing risk or stepping in with statutory / government schemes where customer analytics lead to 'market failure' in the sense that under insurance or non-insurance reaches socially and economically undesirable levels.

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