By Dax Craig, CEO, ValenTechnologies

Agents and brokers represent high standards of professionalismand responsibility for their clients. Businesses and homeownersrely on your ability to secure the best insurance coverage at themost reasonable cost. That's particularly true during challengingtimes.

According to BusinessWeek, the number of natural disasterscosting $1 billion or more has doubled since 1996 when comparedwith the previous 15-year period. As the industry seeks to adapt,predictive analytics is one way insurers will protect their bottomline and make needed investments in technology and enhancedcustomer service capabilities.

Large carriers have been using predictive analytics for severalyears, and while some of the early iterations of predictiveanalytics were found to be lacking, significant advancements havemade the use of data and analytics stable and reliable in theinsurance industry. Now regional carriers are increasinglyincorporating predictive analytics to remain competitive.

Read related: “Telematics:Trouble or Tipping Point for Midsized Carriers?”

But what does this mean for independent insurance agents?

Predictive analytics uses statistical and analytical techniquesto develop predictive models that enable accurate predictions aboutfuture outcomes. Predictive models can take various forms, withmost models generating a score that indicates the likelihood agiven future scenario will occur. For instance, a predictive modelcan identify the probability that a policy will have a claim. Your customers demand a faster response time,which means underwriters need to return quotes to you more quickly.Consider the example of specialty insurer Markel and its acquisition of FirstComp (formerly Aspen), amove designed to grow its small market workers' comp business.Markel FirstComp created a straightforward online interface foragents to request workers' compensation quotes. What they found wasremarkable. When they provided a quote within one minute of theagent's request, they booked that policy 52 percent of the time.However, that percentage declined with each passing hour theywaited to respond with a quote. If Markel FirstComp waited a full24 hours to respond, their close rate plummeted to 30 percent.

Read related: “MarkelFirstComp Releases New Agency Portal.”

Both workers' comp and homeowners are highly unprofitable forcarriers. The average combined ratio for workers' comp is 115percent (100 percent is break-even; anything over 100 percentrepresents an underwriting loss for the carrier); for homeowners,the average combined ratio from 2008 to 2011 was 113 percentcompared to 102 percent across all property-casualty lines ofbusiness. To improve performance and better meet the needs ofagents, underwriters need advanced tools and methodologies thatprovide access to information in real-time.

Maintaining a viable, diverse insurance marketis valuable for the independent insurance agent market. Predictiveanalytics helps insurance carriers manage and spread risk much moreeffectively by segmenting higher risk policies from lower riskpolicies.

• Pricing advantages for better risks: Whenpolicyholders with favorable claims outcomes and risk profiles aremore easily and reliably identified, they will receive betterpricing.
• More relevant, individualized policy reviews:Instead of making wholesale judgments about certain types ofbusinesses or homes, underwriters using more relevantdata make better-informed decisions on individual policies.For instance, an underwriter can use predictive analytics todiscern that Roofing Company A is a better risk than RoofingCompany B.
• Greater efficiency: A big part of providinggood customer service today depends on the speed of your response.Customers expect information to be instantly available andinsurance carriers incorporating predictive analytics are able toquote business faster and more accurately.
• Maintain choice and market stability: Carrierssuffering from poor systemic performance negatively impact theirability to pay claims. You want to choose the best carrier for yourcustomer and have confidence that the carrier will be around forthe long term.

As with any new innovation, the way predictive analytics isimplemented will determine its success. Fortunately, insurers havelearned from early mistakes and made great strides in understandinghow to build valid predictive models and integrate these modelsinto their operations in a way that improves decision making andimproves agent response times.