Combined rough set theory and flow network graph to predict customer churn in credit card accounts

Connectivity of covering approximation spaces and its applications on epidemiological issue

“…For example, Hybrid Rough Set Theory (HRST), RST combine with DEMATEL-based flow graph, formal concept analysis, etc ( [7,22,35,43]), which are worthy of consideration in coming work.…”

A Prudent Based Approach for Customer Churn Prediction

“…Several methodologies and approaches have been proposed which mainly leverage both static and dynamic analysis for churn prediction modeling. Although, Churn analysis problem is an alarming issue for various domains such as Credit cards accounts [17], Banks & Financial Services [27], Human resource management [22], Insurance & subscription services [25], games [26] and social networks [28], this section represents various related studies about customer churn prediction modeling in telecommunication sector.…”

“…The prediction of such customer churn is highly important for project managers because losing a customer is a low cost opportunity for competitors to gain customer [17,10]. It has been reported that the associated cost with acquisition of new customers is ten times more than retaining the existing customers [14].…”

A hybrid KMV model, random forests and rough set theory approach for credit rating

“…In addition, it is a tool suitable for analyzing quantitative and qualitative attributes. RST has been successfully applied in many different fields, such as controlling industrial processes [9,29], diagnosis analysis [42,51], image processing [43], market decision-making [1,16,49], environmental problem detection [11,39], knowledge acquisition [17,56,57], web and text categorization [12,18,30] and early warning [7,55]. Unfortunately, it is rarely applied to the prediction problem of credit rating [10].…”