MITA: An Information-Extraction Approach to the Analysis of Free-Form Text in Life Insurance Applications
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TL;DR
MITA, MetLife's Intelligent Text Analyzer, uses the Infonnation Extraction technique of Natural Language Processing to structure the extensive text fields on a life insurance application to increase underwriting productivity by 20 to 30%.
Abstract
MetLife processes over 300,000 life insurance applications a year. Undernriting of these applications is labor intensive. Automation is difficult since they include many free-form text fields. MITA, MetLife's Intelligent Text Analyzer, uses the Infonnation Extraction --IE-- technique of Natural Language Processing to structure the extensive text fields on a life insurance application. Knowledge engineering, with the help of underwriters as domain experts, was performed to elicit significant concepts for both medical and occupational text fields. A corpus of 20,000 life insurance applications provided the syntactical and semantic patterns in which these underwriting concepts occur. The extracted information can then be analyzed by conventional knowledge based systems. We project that MITA and knowledge based analyzers will increase underwriting productivity by 20 to 30%.