Vol. 3 No. 1 (2023): African Journal of Artificial Intelligence and Sustainable Development
Articles

Artificial Intelligence for Predictive Underwriting in P&C Insurance

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  • Ravi Teja Madhala
Ravi Teja Madhala
Senior Software Developer Analyst at Mercury Insurance Services, LLC, USA
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Published 02-03-2023

Keywords

  • Insurance technology,
  • predictive analytics
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

How to Cite

[1]
Ravi Teja Madhala, “Artificial Intelligence for Predictive Underwriting in P&C Insurance”, African J. of Artificial Int. and Sust. Dev., vol. 3, no. 1, pp. 513–537, Mar. 2023, Accessed: Dec. 29, 2024. [Online]. Available: https://africansciencegroup.com/index.php/AJAISD/article/view/233

Abstract

Artificial Intelligence (AI) and machine learning (ML) are fundamentally transforming underwriting in the Property and Casualty (P&C) insurance sector, shifting the industry from reliance on manual processes and static historical data to advanced, automated, and data-driven decision-making. Traditional underwriting often faced challenges such as inefficiencies, human errors, and biases, which limited scalability and accuracy. AI-powered predictive underwriting overcomes these limitations by leveraging various structured & unstructured data sources, including demographic details, behavioural insights, geographic patterns, & historical claims. Through sophisticated algorithms, AI can identify intricate correlations and patterns that human analysis might miss, enabling insurers to assess risks with unmatched precision and efficiency. Automating the underwriting process reduces operational costs, accelerates turnaround times, and ensures consistency in decision-making. Moreover, predictive models continuously evolve and adapt to changes in risk landscapes, allowing insurers to address emerging risks and market dynamics proactively. This adaptability is crucial in designing personalized policies that cater to individual customer needs, enhancing customer satisfaction & loyalty. Despite challenges such as data privacy concerns, algorithmic transparency, regulatory compliance, and mitigating biases in AI models, the benefits of predictive underwriting are immense. It empowers insurers to optimize risk evaluation, improve pricing strategies, & streamline operations, ultimately fostering innovation & competitiveness in the industry. Additionally, AI-driven underwriting enables insurers to create a more customer-centric ecosystem by offering tailored solutions that align closely with customer preferences and needs. As the adoption of AI in underwriting continues to grow, it is clear that its integration will play a pivotal role in shaping the future of P&C insurance, driving efficiency, accuracy, and innovation while addressing the evolving expectations of customers in a rapidly changing insurance landscape.

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