Commercial Insurance Breakthrough: Discovering Profits Through Losses

Exploring the benefits of participating in an industry-wide loss history database.

Ernie Feirer is vice president and general manager, Commercial Insurance, LexisNexis Risk Solutions.

Technology has intensified the service expectations in nearly all industries.  What was introduced in insurance 25 years ago, now you can’t do business without.  Today, we’re in the age of comparison, using social media and mobile for many transactions. The time has come for business customers, who continue to increase their own automation to improve customer service, but don’t always receive reciprocity from the commercial property-casualty insurance industry.

Commercial underwriting and pricing have in some ways lagged behind the broader business marketplace.  The industry has relied largely on manual loss-history data collection that places carriers in a lose-lose situation: find thorough information, which prolongs the quoting process by weeks or quote without complete information at the risk of mispricing due to a limited or inaccurate profile of the applicant.

Think about brokers trying to quote risks in their pipelines.  They are charged with collecting information in a timely manner, but have limited means of verifying that the applicant’s loss history is accurate or complete.  Brokers juggle requests for various types of information across carriers, but must also juggle the risks and costs associated with being inaccurate or taking too long to service their customers.

At the point of renewal, is there new information that may impact the quote, such as changes in reserves?  During the policy term, reserves on pre-existing claims with prior carriers may have gone up.  With manual loss history collection, adjusted reserve levels over the current policy term may be overlooked due to the challenges of retrieving data from previous carriers. 

Underwriters often miss pre-existing claims from prior carriers where reserves have changed during the existing policy term, and even in-house reserve data may be difficult to uncover during the renewal quoting process.  As a result, the risk may be underpriced.

Today, however, change is under way.  While the benefits of technological advancement have long been apparent in certain areas of the insurance industry—in particular the heavy automation within personal lines over the past couple of decades—some of the most exciting developments are those that bring more complete data to the forefront on complex commercial policy decisions.

By participating in a contributory loss history database, a concept that is an engrained, integral part of the personal lines workflow, commercial insurers can meet the more sophisticated requirements of their brokers and business insureds while discovering premium growth opportunities at the same time.

What is a contributory loss-history database?

A contributory loss-history database is a centralized repository of data where every contributor receives real-time access to the industry-wide dataset.  For commercial insurance, this means the availability of data across all standard commercial lines of business, including commercial package, commercial auto, business owner policy (BOP), workers’ compensation, and umbrella insurance.

A database of this nature needs to accommodate diverse searches to meet varied needs, with three types of searches predominating.  First, users can query by business and/or the business owner’s name, typically the first line of attack to access the full file.  Second, searches by location identify site-specific losses.  And third, searches by policy number isolate loss data for a specific policy.

Finding Profitable Opportunities

A contributory loss-history database for commercial P&C insurance helps assure adequate pricing by resolving problems intrinsic to manual collection.  Consider the manual verses automated loss history collection processes:

  • Manual process—possible missing information at new business and renewal: Traditional collection procedures jeopardize informed underwriting decisions as brokers work through the laborious and time-consuming process to compile comprehensive loss history data from the applicant’s prior carriers.  Information is often missing or overlooked as a result.  Additionally, when preparing a renewal quote, underwriters often forego checking for changes in reserves from prior carrier claims due to the cumbersome nature of the manual collection process.  Changes to reserves on these claims are then not reflected in the renewal quote.  In both new business and renewal cases, the risk is potentially underpriced.

 

  • Automated process—full documentation for intelligent decisions:  With access to an industry-wide loss history database, applications are submitted with fully documented loss histories, all in a standardized, consistent format.  The underwriter uses this information to provide an accurate and fair quote based on a complete view of the applicant’s prior claims.  

At point of renewal, carriers use the database to revisit pre-existing claims with open reserves and adjust renewal quotes accordingly.  This can uncover changes to reserves that present an opportunity to charge more premium. 

Looking ahead

The complexity of commercial p&c insurance presents challenges, but also great opportunities.  With substantial disparities among insurance companies in terms of systems and processes, an industry-wide loss history database enables improved claim coding and other standardization to simplify loss data analysis and interpretation.

This sets the stage for further automation and business intelligence to be used in commercial insurance to bring underwriting, rating and even claims adjudication to a new level of sophistication.  In the meantime, immediate access to accurate and complete loss history data streamlines business processes and helps ensure prompt and accurate pricing.

 

About the Author
Ernie Feirer

Ernie Feirer

Ernie Feirer, CPCU, is Vice President and General Manager, Commercial Insurance, LexisNexis Risk Solutions. His experience spans 30+ years specializing in data, analytics ,and claims, within data and analytics providers and insurers.

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