This study investigates the customer churn in banking sector and explores application of machine learning models to predict rates. paper starts by providing a comprehensive definition or attrition. Furthermore, review prior studies conducted field rate detection prediction within is .It encompasses an examination diverse datasets employed, including their origins, sizes, sources, specific utili...

Customer churn may be a critical issue for banks. The extant literature on statistical and machine learning for customer churn focuses on the problem of correctly predicting that a customer is about to switch bank, while very rarely considers the problem of generating personalized actions to improve the customer retention rate. However, these decisions are at least as critical as the correct id...

The paper presents model based on fuzzy methods for churn prediction in retail banking. The study was done on the real, anonymised data of 5000 clients of a retail bank. Real data are great strength of the study, as a lot of studies often use old, irrelevant or artificial data. Canonical discriminant analysis was applied to reveal variables that provide maximal separation between clusters of ch...

Churn prediction is essential for the survival of every business as it allows proactive action planning, whereas customer segmentation an effective grouping approach commonly used product marketing and relationship management. This paper analyzes current development attrition telecommunications (telco) industry, explores integration both approaches that results in actionable matrix framework re...

BACKGROUND Online health communities (OHCs) have become a major source of social support for people with health problems. Members of OHCs interact online with similar peers to seek, receive, and provide different types of social support, such as informational support, emotional support, and companionship. As active participations in an OHC are beneficial to both the OHC and its users, it is imp...

This paper illustrates the similarities between the problems of customer churn and employee turnover. An example of employee turnover prediction model leveraging classical machine learning techniques is developed. Model outputs are then discussed to design & test employee retention policies. This type of retention discussion is, to our knowledge, innovative and constitutes the main value of thi...

In the telco industry, attracting new customers is no longer a good strategy since cost of retaining existing much lower. Churn management becomes instrumental in industry. As there limited study combining churn prediction and customer segmentation, this paper aims to propose an integrated analytics framework for management. There are six components framework, including data pre-processing, exp...

Churn prediction is an important topic in the free online game industry. Reducing churn rate of a significantly helps with success game. operator identify possible churning players and keep them engaged via appropriate operational strategies, marketing and/or incentives. Playtime-related features are some widely used universal for most models. In this article, we consider developing new predict...

This chapter proposes an integrated methodological system of telecommunication customer detainment management, including telecommunication customer churn prediction and strategy formulation of customer detainment management. The formulation of churn customer detainment management strategy includes customer detainment value assessment, customer detainment level determination, enterprise-attribut...