INTERNATIONAL JOURNAL OF BUSINESS INNOVATION AND RESEARCH, cilt.1, sa.1, ss.1-20, 2025 (Scopus)
Abstract: The insurance industry heavily relies on customer relationships and loyalty for sustained business performance. However, most interactions between insurance companies and their customers are limited to financial matters and short-term. Insurance companies need to enhance customer loyalty and retention to stand out in the highly competitive market. In this study, we aim to identify the key factors that lead to customer churn in the insurance market during the complaint process. Our analysis utilises machine learning algorithms to examine how complaint parameters affect customer decisions. Results indicate that ensemble and SVM are the best-performing algorithms chosen for this study. However, all implemented models demonstrate a reliable level of accuracy. The customer satisfaction score emerge as the most impactful factor on customer churns overall, whereas the other parameters' significance varies according to the model used.