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Marketing Optimization in Retail Banking

Author

Listed:
  • Ramasubramanian Sundararajan

    (GE Global Research, Bangalore 560 066, India)

  • Tarun Bhaskar

    (GE Global Research, Bangalore 560 066, India)

  • Abhinanda Sarkar

    (GE Global Research, Bangalore 560 066, India)

  • Sridhar Dasaratha

    (GE Global Research, Bangalore 560 066, India)

  • Debasis Bal

    (GE Global Research, Bangalore 560 066, India)

  • Jayanth K. Marasanapalle

    (GE Global Research, Bangalore 560 066, India)

  • Beata Zmudzka

    (Bank BPH, GE Capital, 80-387 Gdansk, Poland)

  • Karolina Bak

    (Bank BPH, GE Capital, 80-387 Gdansk, Poland)

Abstract

In this paper, we address the problem of making optimal product offers to customers of a retail bank by using techniques including Markov chains, genetic algorithms, mathematical programming, and design of experiments. Our challenges were large problem size, uncertainty about estimates of customer responses to product offers, and practical issues in training and implementation. The solution had an estimated financial impact of around $20 million; it also provided other intangible benefits, including structured decision making, the capability of performing what-if analysis, and portability to other markets and portfolios.

Suggested Citation

  • Ramasubramanian Sundararajan & Tarun Bhaskar & Abhinanda Sarkar & Sridhar Dasaratha & Debasis Bal & Jayanth K. Marasanapalle & Beata Zmudzka & Karolina Bak, 2011. "Marketing Optimization in Retail Banking," Interfaces, INFORMS, vol. 41(5), pages 485-505, October.
  • Handle: RePEc:inm:orinte:v:41:y:2011:i:5:p:485-505
    DOI: 10.1287/inte.1110.0597
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    References listed on IDEAS

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    2. Bigler, T. & Kammermann, M. & Baumann, P., 2023. "A matheuristic for a customer assignment problem in direct marketing," European Journal of Operational Research, Elsevier, vol. 304(2), pages 689-708.

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