Retail Banking Loan Portfolio Equilibrium Mix : A Markov Chain Model Analysis
The variance analysis of actual loan sanctions with the non-documented method of loan allocation of the selected retail bank, over a period of 24 months, revealed that there is a scope to improve their income earnings. Realizing its importance Markov Chain Market Share model was applied to inter temporal data of loan disbursements of the selected bank. By applying Estimate Transition Matrix, scope for probability of loan switching among its types was calculated to suggest the probable mix of loan portfolio. From the results it was suggested that the loan proportions among various types were as follows: Housing (32.0 %), Others (28.1 %), Business (20.0 %) and Education (19.7 %). These proportions can be taken as guideline percentage within the government norms for the priority sector. Simulation studies were also done to calculate the expected income of interest using Markov proportions and compared with the actual interest earnings to prove the superiority of the model.
Copyright: © 2005 V. Thyagarajan and Saiful Maznan Bin Mohamed. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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- Markov Chain Market Share Model
- Loan Portfolio
- Model Superiority