A stochastic approach for valuing customers in banking industry: A case study

Hamid Bekamiri, Mohammad Mehraeen*, Alireza Pooya, Hossein Sharif

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

5 Citations (Scopus)

Abstract

This study provides a stochastic dynamic programming model with a Markov chain that explicitly focuses on the customer as well as a new model for valuing the customers in the banking industry. The proposed framework calculates individual customer’s lifetime value dynamically. The study follows a stochastic dynamic programming model that is based on the Markov chain. The deduced findings are illustrated with supplementary context from an outstanding case study. The findings underline the importance of the stochastic model for calculating customer lifetime value based on customer behavior. The presented framework provides a beneficial way for future research and valuable insight for allocating promotional marketing strategies to customer groups. The presented framework provides a dynamic model for calculating the individual customer’s lifetime value. The main contribution of the study is the explicit calculation of individual customer’s lifetime value in the banking industry. Thus, this study provides a stochastic framework for customer segmentation and allocates appropriate marketing promotion strategies. Furthermore, the results of this study were supported by real customer data of one of the largest banks in the MENA region.
Original languageEnglish
JournalIndustrial Engineering and Management Systems
Volume19
Issue number4
Pages (from-to)744-757
Number of pages14
ISSN1598-7248
DOIs
Publication statusPublished - Dec 2020
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2020 KIIE

Keywords

  • Bank
  • Customer Lifetime Value
  • Customer Profitability
  • Markov Chain Model

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