ARTIFICIAL INTELLIGENCE IN INSURANCE PROCESSES: FRAUD DETECTION AND RISK MITIGATION

The integration of Artificial Intelligence (AI) in insurance processes has revolutionized fraud detection and risk mitigation. AI-driven systems enhance predictive accuracy, operational efficiency, and scalability while enabling real-time monitoring of insured assets. Machine learning models, deep learning algorithms, and data analytics tools detect anomalous patterns, prevent fraudulent activities, and optimize claims management. Despite these advancements, challenges remain in data quality, model transparency, ethical considerations, and regulatory compliance. Future developments, including explainable AI, blockchain integration, cross-sector data collaboration, and adaptive self-learning models, promise to further strengthen risk assessment frameworks. This study demonstrates that AI is not merely a technological tool but a transformative paradigm, enabling insurers to manage risk proactively, ethically, and in a globally interconnected environment.

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