Risk factors for ill health insurance claims.

OBJECTIVES This study examined the information available at application for income protection insurance, to determine if any factors were predictive of a claim. The strength and significance of such factors were assessed and a predictive model was developed. BACKGROUND The factors underlying life assurance risks are well known, but this is not the case for income protection insurance. For accurate underwriting of income protection insurance, it is important to know what information available at application has power to predict a claim. Improving the scientific accuracy of underwriting is good business practice, as well as answering the demands of disability legislation. METHODS We studied all data available at application for 959 current claimants and 1417 non-claimants, using a case-control study design. Information included applicants' description of their occupation, marital status, build and habits, plus a questionnaire asking about their personal health. For some applicants medical reports were available as well. Information was transcribed onto a database, and univariate and multivariate analyses were performed. A predictive scoring system was established and its performance measured by receiver operating characteristic curves. RESULTS Significant associations with claiming were found for many variables, including age (odds-ratio 1.04, p < 0.001), height (0.11, p = 0.03), smoking (2.10, p < 0.001), abstinence from alcohol (1.56, p = 0.01), recent medical advice (1.34, p = 0.06), and having had a lower gastrointestinal disorder (1.51, p = 0.04). Using all the information from the application, a predictive model was constructed. This model had good predictive power with an area under the receiver operating characteristic curve of 72%. CONCLUSIONS Classical underwriting factors were generally shown to have predictive power for income protection insurance. The predictive scoring strengthens the scientific basis for underwriting and could be developed to simplify and expedite the underwriting process.