Hayatta kalma analizi kullanarak çevrimiçi ödeme sektöründe kayıp tahmini

Online payment systems are rapidly becoming a vital component of fintech world. With the entry of numerous firms into the sector, competition has become intense, and customers can easily switch providers without prior notice. As a result, churn has emerged as a critical topic for organizations seeking to remain competitive. The study focuses on the key factors that influence churn in an online payment company, specifically, a well-known payment service provider in Turkiye. One of the other objectives of the study is to find out which churn period and which input variables combination is more suitable with company's business model and customer's behavior. To arrive at this conclusion, we have developed a survival model that can answer both questions. We analyzed the customers who had been using the services and identified them as churn and non-churn based on three different methods. We examined various variables that could influence churn, including demographic factors, payment history, and usage patterns, to build three different models with different target variables. The results of these models were compared to determine which variables were most significant in predicting churn and which type of churn period is more suitable to answer the question in hand. All the statistical models exhibited similar performance indicators and variable importance rankings. The findings indicate that commission rate change, refund rate, payment count, volume, merchant type, merchant source name, and merchant sector were significant predictors of customer churn, while settlement period and working area of the merchant were not significantly associated with churn. Moreover, the second model, which defined the churn event as occurring within a one-month period, outperformed the other models. Additionally, the results suggest that the risk of customer churn increases after 25 months of doing business with the company.