IMPROVING CLAIMS SETTLEMENT EFFICIENCY WITH ARTIFICIAL INTELLIGENCE (AI) - DRIVEN DATA ANALYTICS IN INSURANCE

Abstract

The insurance industry is undergoing significant transformation with the adoption of artificial intelligence (AI) and data analytics. These technologies offer promising solutions to long-standing inefficiencies in claims settlement, a critical process for insurers. This paper explores the application of AI-driven data analytics in improving claims settlement efficiency within the insurance industry. Traditional claims processing methods are often slow, labor-intensive, and prone to errors, leading to increased operational costs and customer dissatisfaction. By integrating AI technologies such as machine learning, natural language processing (NLP), and predictive analytics, insurers can automate routine tasks, reduce fraud, and expedite decision-making. The analysis reveals that AI implementation reduces claims processing times by up to 50% and decreases operational costs by 20-30%. The paper also examines the implications for key stakeholders, including insurers, policyholders, and regulators, and highlights the ethical considerations surrounding AI adoption. AI offers a promising future for the insurance industry, though regulatory frameworks must evolve to address challenges related to transparency, fairness, and data privacy.