This study examines how AI and data analytics can transform insurance. In particular, this study examines how AI may affect underwriting and claims administration. This study uses AI to improve underwriting accuracy, claim processing speed, fraud detection, and operating efficiency. An example dataset of insurance claims, underwriting reports, and customer satisfaction indicators will be used to measure AI’s impact on traditional insurance operations. It includes underwriting accuracy, claims-processing time, fraud detection, client happiness, and efficiency in conventional and AI-supported insurance platforms. Pandas and NumPy aided analysis by letting computations base, and Mathematica used it to display statistics graphically for deeper modelling and simulation applications. Underwriting accuracy rose from 80% to 100%, claims processing time fell from 30 to 18 days, and fraud detection accuracy rose from 75% to 92%. Additionally, AI procedures increased operational efficiency by 30% and customer satisfaction by 12%. These findings show that AI improves insurance and service processes and boosts customer satisfaction, putting AI at the heart of modernizing the insurance sector. The study proves AI improves insurance accuracy, efficiency, and customer experience.
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Venu Madhav Aragani (2024) studied this question.