Using analytics to drive claim outcomes
Insurers are leveraging analytics to help control leakage, resulting in more accurate claims results.
As we head toward the end of the baseball season, it’s hard not to think of the movie Moneyball, and how the sabermetrics take center stage in the real-life saga of Billy Beane and the Oakland Athletics (A’s). Sabermetrics is the analysis of baseball through objective, empirical evidence, especially baseball statistics that measure in-game activity rather than industry activity, such as attendance. By focusing on a player’s actual contribution to a team, this formula theoretically enables teams to hire undervalued players, in turn bringing salaries in line with affordability.
In insurance terms, think of it as leveraging analytics to control leakage. How can carriers leverage analytics to drive better outcomes? This could range from measuring internal metrics, such as disposition, to claim settlement metrics, such as average bodily injury (BI) paids. However, there are many other facets that are worth examining across the claims lifecycle.
In “Moneyball,” author Michael Lewis examines the disparities between big-market teams, such as the New York Yankees, who can fund a roster of big-name, high-paid free agents, and small market teams struggling to fill the stands. A prime example was the 2002 season, where the Yankees had a payroll of $126 million and the A’s had a payroll of about $40 million. Despite the disparity, the two teams tied for the best record in baseball, each winning 103 games (though both lost in the playoffs). The A’s, as it happened, lost to the small-market Twins, who paid their players just an iota more than Oakland.
Analytics opportunities
Now, let’s examine how analytics can drive results while decreasing costs. Three key areas rife with opportunities are bodily injury, auto physical damage and subrogation. Let’s first examine how carriers can utilize data to drive results when a person is injured.
Intuitively, we believe that certain venues are worth more than others. When looking at closed claim data and jury verdicts, this can be borne out statistically. You will pay more on a claim in Dade County, Florida, than you will in Baker County, Florida. Although, analytics can also debunk some myths, such as big cities having higher verdicts than small towns. An analysis of jury verdicts from places like Gadsden County, Florida, or Madison County, Illinois, would show that this simply isn’t the case.
What drives this? Attorney representation rates have a lot to do with this, which is why analytics around the early disposition of BIs is so important. Carriers who proactively seek to control the claim yield lower attorney representation rates, which translates into lower settlements, but it goes far beyond that.
The attorney alone doesn’t dictate what happens, which is why the attorney provider relationship is so important. If a claimant is referred to certain clinics, there may be significantly more medical build-up and diagnostic procedures. Understanding this third-party behavior allows carriers to fine-tune their investigations more effectively to focus on mitigating factors and utilization of fraud deterrents, such as surveillance.
Then there are the internal considerations. In a day and age when getting new employees is more challenging than ever, leveraging analytics to drive productivity is critical. Using tools for content extraction and summarization can give adjusters significantly more time to focus on the critical aspects of the claim, such as investigation, evaluation, negotiation and settlement.
In looking at auto physical damage, tremendous insights can be gained. Think back to the days when adjusting vehicles meant a clipboard, an estimatics form and a Polaroid camera. The key driver of injury probability was the crush to the vehicles and the clarity of the photographs. Over time, we have become much more advanced. There are applications to measure crush, examine metal striations and calculate g-forces that can refute a wide variety of injury claims. This is why a thorough investigation of all vehicles involved in an accident is so critical. The analysis of the data captured can provide keen insights that will drive the course of the claim investigation.
Moving to the world of subrogation, analytics are perhaps even more important, as they drive the recovery of money back to your organization. Understand, the characteristics of the most recoverable claims begin at first notice of loss (FNOL). By analyzing the facts of a case, carriers are better able to identify the most collectible, highest yield opportunities. By effectively triaging these claims with an analytics-driven approach, there is a reduction in staffing friction and an increase in productivity.
Success comes from moving away from people-driven processes, which were fine 30 years ago. Today, it takes a data-driven, digitized organization to find success. Data allows you to build models. Models are used to identify opportunities — real opportunities with high potential collectability.
These models also drive the lifecycle. What if a model shows you have a higher probability of collecting more in arbitration than in direct negotiation? Would you spend time on negotiation, or go straight to arbitration? What if your models can identify high-transaction, low-yield claims, such as uninsured motorist recoveries? Is it better to have your staff chasing those than high yield, high probability recoveries?
Throughout the life of a claim, analytics are critical to outcomes. This isn’t limited to the insurance industry. Think of the world beyond, where many advances have been made. Recall the last time you got a text from your credit card company asking if you made a charge. These are data-driven decisions by the company, often executed robotically.
From banking and telecom to the ads you see on Facebook or the shows that populate on your personalized Netflix queue, it is analytics being harnessed to make decisions, ask questions, predict outcomes or even generate entertainment content.
Billy Beane figured it out a number of years ago. Some industries have embraced analytics, others have been slow to adopt. However, those who have adopted a numbers-driven, digitized approach to solutions have rapidly gained a competitive advantage.
Chris Tidball (chris.tidball@exlservice.com) is vice president – sales and claims transformation strategy at EXL.
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