Insurers Are Striking Gold With Data Mining Technology
“There is no doubt in our minds that, if done right, data mining will become a standard part of the business for any company,” says Rama Prasad, vice president of solution design for Chicago-based CNA Insurance.
At the same time, he notes that if a companys business process is not sound and fails to address data-quality issues, no data mining product will help. “As they say, junk in, junk out,” he says.
Prasads remarks are in accord with the views of several other executives at large insurance companies that engage in data mining.
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Data mining involves sifting through a companys business and customer data to uncover patterns and relationships that could be useful to the business. Data mining can be done manually, or via computer programs that analyze the data automatically.
Vincent Armentano, president of workers compensation claims for Travelers Insurance, Hartford, Conn., calls data mining a “core strategy,” at least for his division. He says that data mining allows his division to go back into its data and to “use that hindsight to give us some foresight into what that next claims might look like.”
Armentano adds that data mining “brings you to the right event, but then what you do” with that event or how you handle it is up to you.
Prasad says that data mining “helps you get to the truth.” He explains that, while an insurance company may have based some decisions on “anecdotal evidence or hearsay,” data mining now can provide “data that you can trust.” As a result, a companys “decision-making becomes much more objective and very qualitative,” he says.
Richard L. Van Schoick, vice president of global marketing research for Prudential, based in Newark, N.J., says that data mining has been a “financially worthwhile pursuit” for the company.
He explains that Prudential can concentrate limited resources on maximizing its results. This means, for example, that Prudential “can spend less and offer more product to people more likely to buy.”
Gary Stromberger, director of decision support services for State Farm, Bloomington, Ill., says his company is “still in the learning stage” regarding the potential of data mining.
As a large company with large volumes of historical data, he says, State Farm is “very interested in the type of patterns, the types of observations that can appear to us by working and analyzing the data.”
Stromberger adds that the companys focus has actually been on data improvement initiatives to beef up its analytic capabilities.
Larry Koenen, a technical infrastructure specialist responsible for State Farms overall decision-support strategy, says the company has used data mining “as a tool within an overall information-understanding or analytic perspective.”
While not viewing it as “the end all,” State Farm considers data mining “a valuable way to sift through large amounts of information” that can then be validated through other means, Koenen says.
Bahman Dehkordi, also a State Farm technical infrastructure specialist, adds that the company does not rely on data mining alone for its decision support or decision-making. “Its generally a combination of tools and technology that we use,” he says.
Stromberger believes data mining “produces thought starters–something you never thought of before–and gives you the ability to investigate things further.” In short, “data mining gives you the capability of identifying questions you didnt know to ask,” he says.
Prasad says data mining has become “a standard part of[CNAs] architecture.” He reported that CNA uses data mining “broadly speaking torun our business.” More particularly, the company uses it for, among other things, “identifying all the key producers,” for marketing purposes and for customer service.
Data mining also helps CNA, which consists of multiple business units, to get “a very comprehensive and unified view” of its entire business, including its agents, according to Prasad.
One of the uses to which State Farm puts data mining is “market segmentation,” Stromberger says. “When weve introduced new programs, we can use that to look at their effectiveness.”
The global marketing department at Prudential primarily uses data mining “to identify key characteristics of products and customers, to indicate how they may react to things,” Stromberger states.