By Dax Craig, CEO, Valen Technologies

Agents and brokers represent high standards of professionalism and responsibility for their clients. Businesses and homeowners rely on your ability to secure the best insurance coverage at the most reasonable cost. That's particularly true during challenging times.

According to BusinessWeek, the number of natural disasters costing $1 billion or more has doubled since 1996 when compared with the previous 15-year period. As the industry seeks to adapt, predictive analytics is one way insurers will protect their bottom line and make needed investments in technology and enhanced customer service capabilities.

Large carriers have been using predictive analytics for several years, and while some of the early iterations of predictive analytics were found to be lacking, significant advancements have made the use of data and analytics stable and reliable in the insurance industry. Now regional carriers are increasingly incorporating predictive analytics to remain competitive.

But what does this mean for independent insurance agents?

Predictive analytics uses statistical and analytical techniques to develop predictive models that enable accurate predictions about future outcomes. Predictive models can take various forms, with most models generating a score that indicates the likelihood a given future scenario will occur. For instance, a predictive model can 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), a move designed to grow its small market workers' comp business. Markel FirstComp created a straightforward online interface for agents to request workers' compensation quotes. What they found was remarkable. When they provided a quote within one minute of the agent's request, they booked that policy 52 percent of the time. However, that percentage declined with each passing hour they waited to respond with a quote. If Markel FirstComp waited a full 24 hours to respond, their close rate plummeted to 30 percent.

Read related: “Markel FirstComp Releases New Agency Portal.”

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

Maintaining a viable, diverse insurance market is valuable for the independent insurance agent market. Predictive analytics helps insurance carriers manage and spread risk much more effectively by segmenting higher risk policies from lower risk policies.

Pricing advantages for better risks: When policyholders with favorable claims outcomes and risk profiles are more easily and reliably identified, they will receive better pricing.
More relevant, individualized policy reviews: Instead of making wholesale judgments about certain types of businesses or homes, underwriters using more relevant data make better-informed decisions on individual policies. For instance, an underwriter can use predictive analytics to discern that Roofing Company A is a better risk than Roofing Company B.
Greater efficiency: A big part of providing good customer service today depends on the speed of your response. Customers expect information to be instantly available and insurance carriers incorporating predictive analytics are able to quote business faster and more accurately.
Maintain choice and market stability: Carriers suffering from poor systemic performance negatively impact their ability to pay claims. You want to choose the best carrier for your customer and have confidence that the carrier will be around for the long term.

As with any new innovation, the way predictive analytics is implemented will determine its success. Fortunately, insurers have learned from early mistakes and made great strides in understanding how to build valid predictive models and integrate these models into their operations in a way that improves decision making and improves agent response times.

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