Explainable Risk Factor Decomposition and Automated Underwriting Intelligence: AI-Based Decision Support Architectures for Insurance Underwriting

Authors

  • Theophilus Akinbami Professor of Electrical Engineering, Federal University of Technology Akure (FUTA)

Keywords:

explainable risk factor decomposition, automated underwriting intelligence, decision support architectures, insurance underwriting, machine learning

Abstract

Traditionally, the maintained and evaluated records of Quiet often today, underwriters are having to develop stricter guidelines with regard to class evaluation, therefore putting more pressure on the increasingly data-driven decisions made by the underwriting teams. This trend is significantly impacted by the exponentially evolving technology, which is transforming processes previously governed by conventions and talent in taste.

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Published

31-12-2024

How to Cite

[1]
“Explainable Risk Factor Decomposition and Automated Underwriting Intelligence: AI-Based Decision Support Architectures for Insurance Underwriting”, J. Computational Intel. & Robotics, vol. 4, no. 2, pp. 13–21, Dec. 2024, Accessed: Jun. 04, 2026. [Online]. Available: https://thesciencebrigade.com/jcir/article/view/717