@article{article_895069, title={A Case Study on Building a Cross-Selling Model through Machine Learning in the Insurance Industry}, journal={Avrupa Bilim ve Teknoloji Dergisi}, pages={364–372}, year={2022}, DOI={10.31590/ejosat.895069}, author={Özdemir, Yunus Emre and Bayraklı, Selim}, keywords={machine learning, cross-selling model, decision trees}, abstract={Cross-selling, has become widespread in recent years and has increased in importance, is a strategy of selling interrelated products or services to the customer by analyzing the general buying trend. In this study, firstly, its usage in data-based marketing and insurance is explained. As known, possibilities are very important in the insurance industry. For example, premiums to be determined in the next year in life insurance are based on the number of deaths (mortality) in the past years among certain age groups. Accordingly, the probability of customers with private pension contracts to obtain life insurance will be estimated. While making this estimation, besides the personal information of the customers, their behavior in the past periods of 1-3-6 months and the various traces they left on the system will be used. Machine learning, decision trees, and Cross Sales have been studied in detail. Customer data of an insurance company in Turkey is used in the implementation of the project. Then, it was examined whether a product can be purchased based on the past behavior of individual customers with the Chaid, C5.0 and Crt algorithms used in decision trees. Finally, it will analyzed that this study does not contribute to company sales, and new generation sales techniques will be used instead of traditional sales methods.}, number={35}, publisher={Osman SAĞDIÇ}