Optimising Digital Health Insurance Products: The Role of AI-Driven Personalisation in Enhancing Customer Satisfaction and Cost Efficiency

Abstract

Background: The use of artificial intelligence (AI) in digital health insurance has enhanced traditional insurance models by providing customised insurance, efficient and fast claim processing, and financial savings. By leveraging the strength of AI, insurance companies will be able to determine the risk level and offer personalised insurance policies in real-time, tailored to the health conditions and activities of policyholders. Yet, there are specific objections to algorithms, including concerns about data privacy and secrecy. Objective: The study aimed to evaluate the efficacy of AI-based personalisation in the framework of digital health insurance. Key aspects to be examined included satisfaction rates, costs, and the ethical and compliance issues surrounding these. Methodology: A qualitative research technique was employed in this study, involving 16 policyholders, insurance industry officers and staff. Thematic analysis was used to analyse the data in an attempt to determine pertinent themes and topics, such as the trustworthiness, transparency, affordability, the relevance of AI in claim processing, and ethical concerns, such as unconscious bias and data safety. Findings: The discussion reveals that the coverage of AI in the insurance can be defined in terms of pleasing the clients with accessibility, automation, and flexibility of prices. Nevertheless, the data protection, balance of data, and, thus, the role of algorithms in decision-making can still be considered severely problematic. Conclusion: AI can break the traditional form of health insurance in the times of the digital revolution, but the dilemma and the challenges related to the ethical use of AI and legal regulations of their application must be taken into account to achieve equality and to generate the required element of trust and accountability in the new models of insurance.