Predictive modelling of the impact of insurtech adoption on financial stability in global insurance companies

Khaw, Elaine Xiang Ling (2025) Predictive modelling of the impact of insurtech adoption on financial stability in global insurance companies. Final Year Project, UTAR.

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Abstract

While the rapid adoption of InsurTech is reshaping the global insurance industry by enhancing operational efficiency, it also introducing new risks and challenging traditional regulatory frameworks such as Solvency II. This study aims to explore the impact of InsurTech adoption on the financial stability of global insurance companies. This study utilizes a dataset of the top 100 global insurance companies by market capitalization from 2017 to 2024. InsurTech Adoption Index is constructed to measure the degree of technology integration through principal component analysis (PCA) and textual analysis of annual reports. The analysis employs a series of machine learning algorithms to predict financial stability and utilizes LASSO regression to rigorously address feature selection and mitigate multicollinearity. Our results indicate that InsurTech adoption is not merely a trend, but a significant driver of financial stability and operational resilience, with Return on Equity (ROE) playing a primary defensive role. The findings show that while excessive capital accumulation increases risk, active leverage can promote stability. Furthermore, the result shown that inflation remains a major destabilizing factor, and increased stability and market concentration has challenged the concentration vulnerability hypothesis. Methodologically, the XGBoost algorithm has proven to be the most robust predictive model, outperforming linear models and capturing the complex nonlinear relationships revealed by SHAP analysis. These findings suggest that regulators should incorporate predictive analytics into their regulatory frameworks. Insurers should prioritize operational efficiency as well as proactive capital allocation over defensive capital hoarding. Keywords: InsurTech Adoption; Financial Stability; Predictive Modelling; Global Insurance Companies; Machine Learning

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