Samsung Life Uses Big Data for Underwriting... Will Enrollment Become Easier for Elderly and Patients?

Cooperation with French Reinsurer SCOR
Streamlined Procedures and Identification of Previously Unrecorded Diseases Possible

Samsung Life actively utilizes big data in the underwriting process to determine insurance application approvals. The previously complex procedures are expected to be simplified, allowing elderly and chronically ill individuals to subscribe more easily.

On the 10th, Samsung Life announced the introduction of 'virtual underwriting' using big data. This is a big data analysis program developed by the French reinsurance company SCOR, which predicts the acceptance of customers based on their medical history such as hypertension and thyroid disorders by utilizing Samsung Life's existing contract information. To this end, Samsung Life conducted a six-month joint project with SCOR and applied the results to simplified insurance screening.

Samsung Life's existing underwriting could only verify information about insured persons who had been accepted, making it difficult to relax screening criteria for diseases without prior acceptance history. However, with the introduction of virtual underwriting, it has become possible to make judgments on diseases that previously had no acceptance history.

Samsung Life built virtual scenarios based on 10 years of accumulated indemnity medical insurance contract data and derived expected issues for each disease. They also refined various prediction techniques to expand the range of insurable diseases while maintaining existing standards. In the future, the virtual underwriting system is planned to be expanded from simplified products to general products as well.

A Samsung Life official stated, "We have continuously pursued digital innovation to enhance customer subscription convenience and refine underwriting," adding, "With the introduction of virtual underwriting, we will be able to offer more subscription opportunities to chronically ill and elderly customers."

This content was produced with the assistance of AI translation services.