Artificial Intelligence Applications in Predictive Underwriting for Commercial Lines Insurance

Authors

  • Pankaj Zanke Project Manager, Progressive Insurance, Cleveland, Ohio, USA
  • Dipti Sontakke Consultant, Capgemini Inc, Atlanta, GA, USA

Keywords:

Artificial Intelligence, Predictive Underwriting, Commercial Lines Insurance, Neural Networks, Decision Trees, Risk Selection, Pricing Strategies, Data Analysis, InsurTech, Industry Transformation

Abstract

Artificial intelligence (AI) has emerged as a transformative force in the insurance industry, revolutionizing traditional underwriting processes. This paper investigates the application of AI techniques, including neural networks and decision trees, in predictive underwriting for commercial lines insurance. By leveraging vast amounts of data, AI models enhance risk selection and pricing strategies, leading to more accurate assessments of potential liabilities and improved profitability for insurers. This research explores the theoretical foundations of AI in underwriting, examines real-world case studies, and evaluates the benefits and challenges associated with its implementation. Through a comprehensive analysis, this paper aims to provide insights into the opportunities presented by AI in commercial lines insurance underwriting and its implications for the industry's future.

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Published

25-05-2021

How to Cite

[1]
“Artificial Intelligence Applications in Predictive Underwriting for Commercial Lines Insurance”, Adv. in Deep Learning Techniques, vol. 1, no. 1, pp. 23–38, May 2021, Accessed: Mar. 07, 2026. [Online]. Available: https://thesciencebrigade.org/adlt/article/view/181

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