Abstract
This paper is aimed at designing an optimal product portfolio recommendation framework for banking or financial institution customers factoring individual situations and member financial readiness aspects. The analytical framework is expected to factor in not only member behavior and related dimensions but also external dynamics like demographic changes, economic landscape, and information technology advancements in a dynamic setup. The framework could be used to empower product line leaders with the right strategy to provide personalized customer experience with right product mix. It could also be used to report portfolio level revenue changes over time and demonstrate customer migration across segments and product adoption changes. These insights are expected to help organizations achieve enhanced customer retention and engagement and quickly adapt to varying external and internal trends.
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© 2019 Springer Nature Singapore Pte Ltd.
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Mukherjee, D. (2019). Portfolio Optimization Framework—Recommending Optimal Products and Services in a Dynamic Setup. In: Balas, V., Sharma, N., Chakrabarti, A. (eds) Data Management, Analytics and Innovation. Advances in Intelligent Systems and Computing, vol 839. Springer, Singapore. https://doi.org/10.1007/978-981-13-1274-8_21
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DOI: https://doi.org/10.1007/978-981-13-1274-8_21
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Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-1273-1
Online ISBN: 978-981-13-1274-8
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