Smarter Insurance

What Makes it Smarter...
Automated data analysis and workflow identifies claims most likely to be fraudulent and expedites the settlement of legitimate claims, improving customer
satisfaction and loyalty while reducing third-party collection fees.

Smarter Insurance: Data analysis identifies potential frauds faster and more accurately
Instrumented: Data from the claimant’s first notice of loss is analyzed immediately after the claim is submitted.

Interconnected: Each claim is scored with the likelihood of it being fraudulent, sending questionable claims to the Special Investigative Unit (SIU).

Intelligent: Initial scoring of all claims identifies potential fraud faster, prioritizes the SIU’s work more efficiently, and improves customer satisfaction through faster settlement of legitimate claims.

Infinity Property & Casualty Corporation, a provider of nonstandard personal automobile insurance with an emphasis on higher-risk drivers, depends on its ability to identify fraudulent claims for sustained profitability. As a result of implementing IBM® SPSS® Modeler, Collaboration & Deployment Services, and Decision Management, Infinity P&C has doubled the accuracy of its fraud identification, contributing to a return on investment of 403% per a Nucleus Research study. And the benefits don’t stop there: According to Bill Dibble, senior vice president in Claims Operations at Infinity P&C, the use of predictive analytics in serving the company’s legitimate claimants is of equal or even greater importance.

Dibble evaluated multiple solutions before settling on SPSS. “When we were looking for a way to automate workflows and data collection, I didn’t just want fraud-predictive modeling software,” he says. “I was looking for a product for the enterprise, one that we could use for a variety of predictive analytics. Primarily, I was interested in speeding the settlement of claims that did not contain elements of fraud. SPSS was the clear winner in meeting all of our requirements.”

Low-hanging fruit
Initially, Dibble focused the power of predictive analytics to assist the company’s Special Investigative Unit (SIU). “In the early days of SIU, adjusters would use laminated cards with ‘red flags’ to indicate potential fraud. Taking those ‘red flags’ and developing rules seemed like an area of low-hanging fruit where we could quickly demonstrate the benefit of our investment in predictive analytics.”

Dibble then leveraged a successful approach from another part of the business. “We recognized how important credit was in the underwriting arena, and I thought, ‘Let’s score our claims in the same way, to give us an indicator of potential fraud.’ The larger the number we attach to a case, the more apt we are to have a fraud situation. Lower number, get the claim paid.” Dibble notes that fraud represents a $20 billion exposure to the insurance industry and in certain venues could be an element in around 40 percent of claims. “A key benefit of the IBM SPSS system is its ability to continually analyze and score these claims, which helps ensure that we get the claim to the right adjuster at the right time,” he says.

Adds Tony Smarrelli, vice president of National Operations: “Industry reports estimate one out of five claims is pure fraud – either opportunity fraud, where someone exaggerates an injury or vehicle damage, or the hard-core criminal rings that work with unethical clinics and attorneys. Rather than putting all five customers through an investigatory process, SPSS helps us ‘fast-track’ four of them and close their cases within a matter of days. This results in much happier customers, contributes to a more efficient workflow with improved cycle times and improves retention due to an overall better claims experience.”

An unexpected benefit
Dibble saw subrogation, the process of collecting damages from the at-fault driver’s insurance company, as another piece of low-hanging fruit – and he was right. In the first month of using SPSS, Infinity P&C saw record recovery on paid collision claims, adding about $1 million directly to the company’s bottom line and virtually eliminating the third-party collection fees of more than $70,000 per month that the company was used to paying. What’s more, each of the following four or five months was even better than the previous one. “I never thought we would recover the money that we’ve recovered with SPSS in the subrogation area,” he says. “That was a real surprise to us. It brought a lot of attention to SPSS within the company, and to the value of predictive analytics in general.”

The rules-based IBM SPSS solution is well suited to Infinity P&C’s business. For example, in states that have no-fault benefits, an insurance company can recover commercial vehicles or vehicles over a certain gross vehicle weight. “We can put a rule in IBM SPSS that if medical expenses are paid on a claim involving this type of vehicle, it is immediately referred to the subrogation department,” explains Dibble. “This is a real-time ability that keeps us from missing potentially valuable subrogation opportunities, which used to happen a lot when we relied solely on adjuster intuition.”

The rules are just as important on the fraud investigation side. Continues Dibble: “If we see an accident that happened around 1:00 a.m. and involved a gas-guzzling GMC Suburban, we need to start looking for fraud. So we dig a little deeper: Is this guy upside-down on his loan, such that he owes more money than the car is worth? Did the accident happen in a remote spot, suggesting that it may have been staged? Does the individual move frequently or list multiple addresses? As these elements are added to the equation, the score keeps building, and the case is more and more likely to be referred to one of our SIU investigators.”

With SPSS, Infinity P&C has reduced SIU referral time from an average of 45–60 days to approximately 1–3 days, which means that investigators can get to work on the case before memories and stories start to change, rental and storage charges mount, and the likelihood of getting an attorney involved increases. The company is also creating a better claim for the SIU to investigate; a higher score correlates to a higher probability of fraud.

Making us smarter
SPSS rules start to score the claim immediately on first notice of loss (FNOL) when the claimant reports the accident. “We have completely revised our FNOL screens to collect more data points,” says Dibble. “SPSS has made us much smarter in asking questions.” Currently SPSS collects data mainly from the company’s claims and policy systems; a future initiative to leverage the product’s text mining capabilities will make the information in claims notes available as well.

Having proven its value in subrogation and SIU, the SPSS solution is poised for expansion within Infinity P&C. “One of our key objectives moving forward will be what we call ‘right scripting,’ where we can script the appropriate questions for call center agents based on the answers they get from the claimant,” says Dibble. “We’ll also be instituting a process to flag claims with high litigation potential. By reviewing past litigation claims, we can identify predictive traits and handle those cases on a priority basis.” Decision management, customer retention, pricing analysis, and dashboards are also potential future applications of SPSS technology.

But at the end of the day, excellent customer service remains the driving force behind Infinity P&C’s use of predictive analytics. Concludes Dibble: “My goal is to pay the legitimate customer very quickly and get him on his way. People who are more economically challenged need their car; they typically don’t have a spare vehicle. This is the car they use to go back and forth to work, so I want to get them out and on the road without delay. IBM SPSS makes this possible.”

Solution Components
Software

• IBM SPSS Modeler
• IBM® SPSS® Collaboration and

Deployment Services

• IBM® SPSS® Decision Management 6 and its predecessor, IBM SPSS Risk Control Builder

About IBM Business Analytics
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