LexisNexis Risk Solutions

August 11, 2017

With 35% of U.S. households shopping for insurance at least once during the last year,* today’s personal lines environment is fiercely competitive and carriers are under increasing pressure to price with precision.  Luckily, there are three emerging trends that can help you achieve more accurate pricing.

Trend 1―Creating next generation credit-based insurance scores from new data sources

Using credit report data to help predict insurance loss is not new. However, there is a new type of credit data now available that can help insurers glean additional insights that lead to more accurate and refined credit-based insurance scores―and hence, more accurate pricing. Trended credit data offers up to a 24-month historical view of a customer’s robust raw credit data (such as detailed payment practices), thereby revealing a much more comprehensive and behaviorally-based picture of an insured, rather than simply a snapshot of a moment in time.

The financial industry is now using public records data (such as criminal convictions, liens, judgments and utility bills) to gain insightful information about policy behavior that is not available through credit-based data alone. Forward-thinking carriers in the commercial and life lines are starting to combine this type of information with credit-based data when rating insureds.

The expectation is that over time, carriers will be able to use these new data sources to create next generation insurance scores that will be even more useful for predicting risk and setting accurate rates.

Trend 2―Applying auto data to homeowners pricing

Savvy carriers are recognizing that ratings variables used in auto insurance pricing have relevance to homeowners pricing as well. Attributes like policy tenure, lapses in coverage, and driver and vehicle information are proving to be predictable, explainable and intuitive in terms of filling in what could be missing pieces of the puzzle of an insured’s profile―for example, when a first-time homeowner applies for homeowners insurance. Leveraging insights across lines of business makes great sense, both financially and in terms of risk mitigation.

Trend 3―Implementing new by-peril rating categories

More and more carriers are breaking out and rating on individual perils like theft, fire, wind, hail, water among others in their rating models. The most progressive carriers are looking at additional variables in their by-peril models to create even more separation between themselves and the rest of the pack. For example, carriers who are seeking to differentiate themselves in the market are also looking at first responder-based community services along with demographically-based social dynamics to understand their impact on loss. Local loss history adds an additional level of insight to risks within a specific rating territory. Topography is another local feature that plays a role in loss and is finding its way into some carriers’ ratings models. Historical weather patterns are proving to provide insight within the more advanced by-peril rating models.

Lastly, as digital services become pervasive, the Internet of Things (IoT) is being looked at as the industry explores devices that can bring deeper understanding to risks from fire, water, and weather events―since they make up such a huge proportion of loss costs. Though in its infancy, the expectation is that IoT will eventually become an integrated component in sophisticated carriers’ by-peril rating plans.

Putting it all together

New data sources, cross-lines leverage, and more sophisticated and robust by-peril rating categories and practices are emerging trends all carriers can apply to their pricing process in the manner that works best for their book of business. Taking advantage of these trends can help any carrier price policies more precisely.

*Source: LexisNexis Analytics Shopping Study, 2016