Life insurance is not immune to the transformative impact of artificial intelligence (AI). AI offers unprecedented levels of precision, speed, and customization in a field historically reliant on laborious manual procedures and statistical assumptions. This paper investigates how AI-driven underwriting can be incorporated into life insurers’ digital business strategy, using Momentum’s in-app screening tool as a primary case study. The study proposes a theoretical AI underwriting architecture that maximizes risk assessment and policy issuance by leveraging machine learning algorithms, biometric information, and behavioral insights. The advantages, disadvantages, opportunities, and threats of adopting AI underwriting are analyzed through a SWOT analysis, highlighting ethical and legal considerations around algorithmic bias, regulatory compliance, and explainability. The findings suggest that while AI underwriting can provide insurers a competitive edge in a crowded market, its implementation requires robust frameworks, ethical design, and regulatory alignment.

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AI-Driven Underwriting in Life Insurance: Transforming Risk Assessment in e-Business

  • Sonaly Maharaj,
  • Rhulani Maluleka,
  • Abelwe Maluleka

摘要

Life insurance is not immune to the transformative impact of artificial intelligence (AI). AI offers unprecedented levels of precision, speed, and customization in a field historically reliant on laborious manual procedures and statistical assumptions. This paper investigates how AI-driven underwriting can be incorporated into life insurers’ digital business strategy, using Momentum’s in-app screening tool as a primary case study. The study proposes a theoretical AI underwriting architecture that maximizes risk assessment and policy issuance by leveraging machine learning algorithms, biometric information, and behavioral insights. The advantages, disadvantages, opportunities, and threats of adopting AI underwriting are analyzed through a SWOT analysis, highlighting ethical and legal considerations around algorithmic bias, regulatory compliance, and explainability. The findings suggest that while AI underwriting can provide insurers a competitive edge in a crowded market, its implementation requires robust frameworks, ethical design, and regulatory alignment.