Abstract

Article history: Received December 16, 2011 Received in Revised form January, 3, 2012 Accepted 10 January 2012 Available online 16 January 2012 One of the most basic requirements of financial institutes, governmental and private banks in the present age is to have a good understanding on customers' behaviors of bank network. It helps banks determine customer loyalty, which yields profit making for bank. On the other hand, it is important to know about credit risk of customers with the goal of decreasing loss and better allocation of bank resources to applicants of receiving loan. According to nature of customer loyalty discussion and credit risk, these two issues are separately studied. The present article deals with studying customer loyalty and prioritizing based one private bank in Kurdistan province. The proposed model of this paper studies customer loyalty by using Recency Frequency Monetary (RFM) factor for prioritizing customer based on loyalty properties and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). In addition, in order to calculate the relative importance coefficient or weight of loyalty properties in RFM method, the pair wise comparison matrix based on analytical hierarchy process (AHP) is used. Results show that in the present study, necessarily customers having higher average monetary value during a specified time period does not have much higher priority compared with other customers. © 2012 Growing Science Ltd. All rights reserved.

Highlights

  • Nowadays experts for banking research believe that developing global trade depends on developing electronic trade

  • The present article deals with offering weighted Recency Frequency Monetary (RFM) method and so for calculating weights, pairwise comparison matrix based on analytical hierarchy process (AHP) model has been used

  • Calculating variables of RFM Mmodel for customer under study. As it was described at RFM model, variables including recency (R) frequency (F) and monetary value (M) are regarded as basis for customer loyalty to banking network

Read more

Summary

Introduction

Nowadays experts for banking research believe that developing global trade depends on developing electronic trade. It is obvious that those banks are more successful, in addition to attempt for keeping their present customers, that they attempt to offer suitable service to attract new customer and obtain profitability. According to different values of each customer at bank network, it is required to recognize valuable customers, compiling suitable plans and strategies for offering better services attempting to improve customer loyalty. Obtaining this goal; results in increasing profitability and long-term success of bank. Bank shall continue depending on their competitive advantage and meeting requirement of their customer in order to be successful to continue their survival

Problem definition
Conceptual model of research
RFM Model
Pair wise Comparison Matrix and AHP Method
Calculating variables of RFM Mmodel for customer under study
Calculating importance coefficient or weight of RFM variables
Ranking customer based on properties of customer loyalty at RFM model
Findings
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.