Author
Listed:
- Sita Rama Praveen Madugula
- Nihar Malali
Abstract
Artificial Intelligence (AI) and Machine Learning (ML) enable the adoption of AI and ML in actuarial functions to revolutionize the life and annuity insurance industry by enhancing risk assessment and policy pricing and also offering improvement of operational efficiency. Traditional actuarial models use historical data and rule-based approaches, which are, in most cases, not flexible or accurate in terms of prediction. Using AI-powered tools like deep learning, natural language processing, and predictive analytics, insurance companies can better use large datasets for fraud detection, new policy offers, and better decision-making. In addition, automated underwriting and AI-based claims management make processes easier and, therefore, cheaper and better for customer experience. Also, AI has helped in integrating the dynamic pricing models which change as the risk factor changes in real time. Nevertheless, responsibilities posed for responsible AI adoption remain unmet as some of them are data privacy concerns, model interpretability, regulatory constraints, and ethical considerations. This study discusses how AI/ML is utilized in actuarial science, assesses the savings potential and effect on efficiency, and outlines methods for measuring ROI for such methods.
Suggested Citation
Sita Rama Praveen Madugula & Nihar Malali, 2025.
"The Economic Impact and ROI of AI/ML Adoption in Life and Annuity Actuarial Functions,"
International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 11(2), pages 2323-2335, March.
Handle:
RePEc:jbh:ijsrcs:v11:y2025:i2:id:1285
DOI: 10.32628/CSEIT23112570
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT23112570
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