Technology Risks, Insurtech Innovation, and Their Influence on the Classification of Insurance Company Performance

Abstract

This study evaluates the influence of technology risks on insurance company performance through Insurtech innovation, focusing on the roles of Data Privacy (DP), Skill Gaps (SG), and Financial Risks (FR) in predicting Insurance Performance (IP). Employing a questionnaire survey approach, the research extended historical empirical studies, capturing demographic profiles and study variables measured on a 5-point Likert scale. A pilot study refined the questionnaire, achieving an 80% response rate, and minor adjustments were made to enhance clarity. The dataset included 243 responses from employees of Jordanian insurance companies, with 37 excluded due to incomplete data. Validity and reliability were assessed using Average Variance Extracted (AVE), Composite Reliability (CR), and Cronbach's Alpha, confirming the robustness of the measurement model. Multicollinearity was tested using Tolerance, and Variance Inflation Factor (VIF), with no significant issues detected. A multiple regression model demonstrated that DP and FR positively impact IP, while SG has a negative effect. To further predict IP, the dataset was split into 80 20% and a Multilayer Perceptron (MLP) model was employed. The MLP neural network model, using the Rprop method, highlights the importance of DP, SG, and FR in predicting IP, achieving an accuracy of up to 72%. These findings highlight the importance of addressing technology risks and leveraging Insurtech innovations to enhance insurance company performance, providing valuable insights for industry stakeholders and policymakers.​