Assessing the Potential of Robo-Advisors in Transforming Indonesia’s Insurance Sector

This study aims to investigate the adoption of robo-advisors in the Indonesian insurance sector, focusing on key factors influencing their acceptance, such as trust, anxiety, performance expectancy, preference for human advisors, attitude, and perceived privacy. The research employed a quantitative approach using a structural equation modeling (SEM) technique through Partial Least Squares (PLS). Data were collected via a Google Forms survey distributed to 442 valid respondents using purposive sampling, with the study conducted in Jakarta, Indonesia. The findings revealed that performance expectancy, anxiety, preference for human advisors, and perceived privacy significantly impact the intention to use robo-advisors, whereas trust and attitude showed limited influence. The study concludes that while robo-advisors hold potential in enhancing efficiency and personalization, concerns such as user privacy and the need for human interaction remain critical. Insurance companies should prioritize robust data privacy measures and consider hybrid models combining robo-advisors with human advisors to enhance user trust and satisfaction. Implications for practice include fostering user trust through transparent data handling policies and providing educational resources to mitigate technology-related anxiety. Limitations of this research include its focus on respondents in a single geographic region and its reliance on self-reported data, which may introduce biases. Future research should explore the application of robo-advisors in broader insurance markets and examine their long-term impact on user behavior and financial decision-making.