Text Analytics Provides Insight into the Business
Insurance Networking News, December 2007
Analytics isn't a new concept, but considering the way insurers now use it, it may as well be. Where once fraud was the issue to enter insurers' minds when they heard the term analytics, they have now found more ways to use this technology. One approach is to employ text analytics, which often uses natural language processing (NLP), a subfield of artificial intelligence and computational linguistics, to convert unstructured data into valuable, structured data.
Frank Brooks, senior manager of data resource management at BlueCross BlueShield of Tennessee Inc. (BCBST), Chattanooga, defines text analytics as a technology that can transform unstructured text embedded in documents and databases into meaningful information in the form of new structured database fields.
Text analytics is vital to BCBST's enterprise content management strategy, which includes combing structured and unstructured data for analysis in order to provide valuable new insight into the business.
"Our initial challenge was our desire to know everything about a provider, which entails several things," Brooks says. "We started to see applications that need access not only to internal structured data, but access to external data and unstructured data, and we need to derive meaning or insight from the unstructured data."
BCBST evaluated two different text-analyzing tools during a proof-of-concept product evaluation earlier this year. Text Miner, a tool from Cary, N.C.-based SAS Institute Inc., is a complex solution that provides deep analysis of data and enables newly derived, structured data to be analyzed by existing BI tools. A second offering-IBM's OmniFind Analytics Edition-analyzes business language and is better suited for business-oriented people across the enterprise, Brooks says. "We've found if the user is in a specialized industry, two tools may be required-one for general business things such as customer service or contracts, and the other for specific knowledge based on the language used in that industry," he says.
The Hartford recognizes the technology's possibilities. "We use analytics for both structured data and recently, unstructured data," says Kaleb Adams, assistant VP, claims research, The Hartford Financial Services Group Inc., Hartford, Conn. "I've really tried to push text analytics out to the broader aspects of the organization."
Adams points out the fact that insurers are collecting more data every day and much of that data is not usable. "I read that 85% of data in claims was in unstructured text. We have claims that are still on the books from the 1950s. Insurers capture tons of data and text analytics mines that text and translates it into structured data."
Mary Crissey, analytics marketing manager at SAS agrees that insurers are collecting data they aren't using. "Insurers have been getting their data warehouses set up to keep and hold all those data sets and are collecting so much data they can't manually read it, so it's just sitting there." But this information can be helpful if it's turned into insight, she says. Text analytics will pull, clean, and analyze data. "It can conduct pattern detecting and cluster algorithms," Crissey says.
USE WITH BI
This new data can be used in many ways - including in conjunction with business intelligence. Text analytics tools can generate a structured data set that will interface with BI tools. "The BI field has been growing and continues to emerge and improve, and insurers have always been crunching numbers," Crissey says. "They're great with numbers, metrics, dollars and rates; that's their world, but they are still not taking full advantage of text."
Text analytics can turn the data and text that a computer can't structure into data with meaning, so it can be used in BI applications. "BI is based on having structured information," says Rita Knox analyst and research vice president at Stamford, Conn.-based Gartner Inc. "You have it in some sort of database where you know exactly what that piece of content is. It's in rows and columns, which you can view by drilling down to many levels. Text analytics identifies unstructured data in a way that enables BI applications to process the information."
Using text analytics can provide information and data that a user isn't even expecting, which is what The Hartford found when searching for a text analytics solution. "We brought in a series of vendors and crafted business cases for them. We gave them a series of note documents, sent them away and told them to come back with what they could find," Adams says. "We were able to give them a real business problem and evaluate each of the text mining solutions on the merits of their performance versus the merits of their Power Point presentation."
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