ABL Life Develops AI-Based 'Underwriting Criteria Differentiation Model'

Campaign for Health Checkup and Premium Waiver for Low-Risk Whole Life Insurance Customers
진행

[Asia Economy Reporter Ki Ha-young] ABL Life announced on the 14th that it has independently developed an AI-based 'Personalized Underwriting Criteria Differentiation Model' and will apply it to its underwriting system. Customers classified as low-risk by this model who additionally subscribe to whole life insurance will be exempted from health examinations and contract validity checks in a campaign running until the end of next month.

The Personalized Underwriting Criteria Differentiation Model is a system that applies differentiated underwriting criteria according to the customer's risk level. It was developed to provide customers with more accurate and reasonable insurance coverage benefits.

This model applied machine learning techniques based on big data from over 90,000 customer experiences. Approximately 300 variables were applied, including customer age, total accident insurance claim amount, smoking amount, smoking duration, body mass index, premium payment level, and premium delinquency rate. By autonomously identifying patterns and learning within the customer experience big data, it can predict the likelihood of future accidents.

Choi Hyun-sook, Head of Customer Support, said, "With the introduction of the AI-integrated Personalized Underwriting Criteria Differentiation Model, it is now possible to classify individual risks differently, allowing customers with relatively low risk to receive more reasonable underwriting criteria. We will strive to provide customers with reasonable, customized insurance coverage services based on our leading digital capabilities."

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