International Journal of Science, Engineering and TechnologyAuthors: Chetan Prakash Ratnawat
Abstract: The insurance sector is experiencing a considerable change that is Artificial intelligence (AI), data analytics, and automation. Past AI deployments mainly targeted separate insurance functions like underwriting, claims processing, and regulatory compliance that have resulted in hardly any benefit for the overall organization. This paper suggests an AI-driven insurance model that interconnects risk assessment, operational activities, financial reporting, and regulatory adherence into one well-organized multi-layered structure. After studying a variety of sources including peer-reviewed articles, industry standards, and regulatory documents, the findings indicated that AI has the biggest impact when it comes to low-risk, high-exposure tasks such as claims triaging, document processing, and workflow automation. On the other hand, tasks that require human expertise like the underwriting decision-making should not be done by AI alone. The results also show that AI integration at an ecosystem level enhances the decision consistency, operational efficiency, and governance transparency compared to isolated implementations. Besides, the research underscored the improvements that prior studies have been able to quantify – for instance, the faster processing of claims, better fraud detection, and more stringent compliance monitoring. This research adds to the body of InsurTech literature by advocating for the creation of a compliance-focused AI governance framework, which fully adheres to legal and ethical principles. The proposed model acts as a guide, balancing practicality with retaining transparency, accountability, and trust within insurance companies.
DOI: http://doi.org/10.5281/zenodo.21700751
