Pricing and revenue management for bank home loans: a mathematical approach

Sumeetha Natesan (), Deepika Thakur (), Goutam Dutta () and Manoj Kumar Tiwari ()
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Sumeetha Natesan: Indian Institute of Management
Deepika Thakur: McKinsey & Company
Goutam Dutta: Indian Institute of Management
Manoj Kumar Tiwari: National Institute of Industrial Engineering

OPSEARCH, 2023, vol. 60, issue 2, No 3, 656-687

Abstract: Abstract In this study, we formulate both dynamic and static pricing models for home loans for a bank. These models optimize the net present value of money available at the end of 15 years, subject to pricing limits and cash flows. We collected actual data from a leading nationalized bank in India to develop a relationship between interest rate (price) and number of loans sanctioned (demand). We then assume different versions of the demand function (linear, exponential and rectangular hyperbola). We also develop the relationship of default probability as a function of interest rate. For the three demand functions, we evaluate the expected revenue at the end of the nth period for both static and dynamic pricing models for home loans and compare the results. We also discuss the sensitivity of the study result to changes in the parameters of the demand equations for dynamic pricing model.

Keywords: Revenue management; Pricing; OR in banking; Demand estimation; Non-linear optimization (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s12597-023-00624-5

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