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11

Claims: Getting it together

Open-access content 7th November 2017

Andrew Lowe explains why an industry-wide contributory claims database would be invaluable for commercial property insurance

2

In the past year, the UK commercial property market reached its highest value. Yet, it is a sector of the insurance industry that could be exposing itself to increased losses owing to its limited ability to gain a complete picture of risk, both at an accumulated level - to determine risk exposures across a book of business - and at point of quote. A study by LexisNexis Risk Solutions found only a third of insurers have a complete understanding of the location and associated risks of their commercial property portfolios. 

To gain both an accumulated and granular view of risk, key risk data needs to be aggregated across five data sources: property, place, people, policy history and past claims. 

Actuaries are already able to aggregate property, place and people-risk data from multiple sources and intelligently map this data to support risk selection and pricing of exposures. However, the risk profile assessment should be supplemented with past claims data as well as past policy information, such as whether there have been any mid-term cancellations, policy adjustments or gaps in cover. These data attributes have a direct correlation with loss costs based on analysis of our policy history motor database. This found, for example, that people with a gap in cover in the past year had up to a 50% higher loss cost than those that didn't, and people with a policy cancelled prematurely had up to a 33% increase to loss cost.

In contrast with the private motor insurance market, which uses CUE - a centralised contributory database of motor insurance claims data - access to commercial property claims data is limited to the experience of the insurer. While claims information is valuable for actuarial risk analysis, it will not be a true picture of all the claims associated with that policyholder or property.  An industry-wide view of all commercial property claims related to single properties or a whole property portfolio would bring a new dimension to the understanding of risk exposure. We're pushing against an open door - 83% of the commercial property insurers we surveyed would support the development of an industry-wide contributory claims database, believing it would be extremely valuable, and 85% would be willing to share their own claims data. Furthermore, 62% would be willing to contribute to an industry-wide property database. 

A centralised claims database is just one example of the explosion in captured data in the insurance sector that will allow new analytics approaches and new ways of understanding risk. Although the commercial property insurance market has been slower to adapt to using data and analytics, owing to the complexity of the risks and manual nature of securing this business on a day-to-day basis, there is strong appetite for change. 86% of the UK commercial property insurers surveyed said they believe data and analytics will transform their business, and leveraging data is a top priority, followed very closely by managing profitability and better understanding the risk profile of their book. 

The actuarial profession already has the required skillsets to make a significant contribution, but key to this is gaining a wider appreciation of the datasets that exist or should exist in the future that will be of value for risk assessment. As well as searching for new data sources, actuaries may also choose to extend their expertise more fully into predictive analytics in the commercial property environment. 

The increasing sophistication of mapping tools overlaid with new datasets - from contributory claims records to data from smart building technology - will provide the insights the actuarial profession needs to fully understand its risk exposures.  


Andrew Lowe, business director, commercial insurance, at LexisNexis Risk Solutions 

This article appeared in our November 2017 issue of The Actuary.
Click here to view this issue
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11
Topics:
General Insurance
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