Author : Nihar Malali

Artificial intelligence is altering the face of actuarial profession by improving the risk assessment, the financial forecast, and decision-making with the help of advanced Explainable AI, natural language processing, and machine learning methods. While traditional actuarial methods based on statistical models are still common, the use of AI-specific methods to process data more rapidly and to discover and leverage hidden patterns of risk that are not apparent in statistical models leads actuaries to do a greater use of their time in higher value strategic analysis. Adoption of AI has smaller obstacles, such as model openness, data bias, regulatory compliance, and moral dilemmas with automated decision-making. Taking actuarial and AI collaboration as an example, this study explores the latest actuarial involvement in AI, discusses how an actuary will need to gain competency in AI governance, data science and algorithmic auditing and what impact it might have on present and future life insurance in insurance. It studies the impact of AI to underwriting/ pricing, claims processing and financial risk modeling in terms of efficiency and the accuracy of the decision taken. Finally, the study takes into consideration the ethical and regulatory aspects of AI uptake focusing on fairness, accountability and transparency within application of AI in the actuary field. By taking AI as a collaborative tool, not a replacement for human expertise, actuaries can improve decision-making, drive innovation, and create trust in a growing data-driven world of financial risk management.

Keywords: Actuarial Science, Machine Learning, Predictive Analytics, Risk Assessment, Underwriting Automation.