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Business Intelligence Makes Insurers More-Competitive Risk Managers

For most insurers, business intelligence means point solutions at best. But those carriers that weave analytics into the fabric of their organizations are equipped to drive more precision in pricing and greater profitability to the bottom line.

In Depth: Business Intelligence and Risk. Overcoming Barriers to Integrated Risk Management. Insurers Challenged to Adopt Business Intelligence. Case Study: Great American Unifies Business Intelligence on IBM Cognos Platform.
For businesses that run on the analysis of information, insurers have proven notably reluctant to apply business intelligence (BI) and analytic technologies to risk management at both the corporate strategic level and in the front lines of underwriting. For a variety of reasons, enterprise risk management (ERM) solutions have been talked about far more than implemented, and BI and predictive analytics generally have been applied haphazardly or piecemeal, if at all.

The financial crisis, however, has heightened interest in risk management technologies, owing to senior executives' fears of disastrous overexposure to risk. Their concerns are legitimate, but for insurance more than any other financial services sector, risk also is opportunity, and BI should be utilized more as a competitive weapon than a defensive shield. As insurance has become commoditized and investment returns have become less reliable, carriers' ability to more precisely analyze and underwrite risks can be a key source of competitive differentiation.

Analytic capabilities are central to the tactics and strategy of San Diego-based ICW Group Insurance Companies, whose lines of business include personal and commercial auto, commercial property, surety, and workers' compensation. ICW Group ($389 million in 2007 gross written premium) applies predictive analytics to underwriting, catastrophe modeling, and claims and service functions, according to Mary Boyd, SVP and managing director of Explorer Insurance Co., a member company of ICW Group.

Boyd says the company's first objective in building analytic capabilities was to achieve profitable growth through precise pricing. "We want to minimize profitability-eroding risks and have the ability to better price risks. We can then address a broader spectrum of the market than we otherwise could," she explains.

More-precise pricing also confers greater year-over-year stability in financial results, explains Richard Manship, VP and chief actuary, ICW Group. "Many companies that write workers' compensation have found themselves in the position of explaining their results 18 months after they've written a policy," he says. "With predictive assessment tools, companies can predict loss ratio and the corresponding combined ratio on the front end as they're writing policies, instead of on the back end."

Adds Boyd, "Predictive analytics help us understand the quality of the business we wrote as of yesterday. You don't have to rely upon the lagging indicators of prior years' results to have a reasonably accurate understanding of your book profile and projected profitability. Further, we can use those leading indicators to project our pricing need."

In the short term that future will become more challenging, as the insurance market softens and becomes more price-sensitive, believes Scott Schenker, senior managing director, SMART Business Consulting (Devon, Pa.). But, "Ultimately analytics help you understand how to maximize the return on your capital against risk," he says. "It's interesting just how much capital availability drives the pricing of reinsurance, and understanding that ... can be extremely powerful."

Unfortunately few carriers now exploit that power, Schenker laments. A lack of transparency and consistency at the tactical underwriting level constitutes one major obstacle, he says, explaining that carriers often lack the ability to recognize a single risk coming through different channels, resulting in different offices competing for the same business.

4 keys to Intelligent Risk Management.Many insurers are also vulnerable to a combination of fuzzy underwriting guidelines and an inability to ensure compliance to them, Schenker adds. Insurers are especially exposed when they make unscientific assumptions about roughly analogous business segments and fail to adequately appreciate the underlying risks. "I've seen a number of companies go into run-off after entering a new line of business," Schenker recalls. "An example would be a carrier moving from standard workers' comp to a specialty line workers' comp — they might think it's basically the same when in fact the loss profile can be significantly different."

Even when underwriting operations are tight and consistent, Schenker emphasizes, carriers are still likely to lack a centralized view of information that enables accurate and timely understanding of risk at the portfolio level, which in turn is essential for tactical underwriting and pricing concerns. "I still see quite a number of organizations that don't even have a basic data warehouse in place for reporting," he says. "Without some very detailed information, your analytics aren't going to be very good."

Carriers have invested a great deal in BI and analytics, as well as the data stores that feed them, but rarely is that investment for anything beyond highly specific uses, notes Srini Venkatasanthanam, VP of product strategy, Oracle (Redwood Shores, Calif.). Adding to the typical problems associated with business silos, insurers' data follies include building multiple smaller data marts to serve disparate BI tools for different departments, he says. "Successful enterprise BI requires a successful enterprise data warehousing strategy," Venkatasanthanam counsels.

Insurers with an enterprise strategy for BI and risk management will have the right information and the right tools for strategic planning, he stresses. "They are able to underwrite better — they are able to go back and look at their underwriting decisions to see what worked and didn't, and to be able to rapidly adjust," Venkatasanthanam says. "From a profitability perspective, this BI/analytics is a key capability, and companies that have already enabled it are in a much better position to ride out the soft market."

Anthony O'Donnell has covered technology in the insurance industry since 2000, when he joined the editorial staff of Insurance & Technology. As an editor and reporter for I&T and the InformationWeek Financial Services of TechWeb he has written on all areas of information ... View Full Bio

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