Are Indian Banks Heading Towards ‘Financial Embarrassment’?

The manner in which US Federal & other central banks of advanced countries are shaping their monetary policies in order to avoid another economic downturn, is going to precisely result in that – claimed Mr. Raghuram Rajan, RBI Governor at LBS last week (Refer Box-1). The practice of zero-lower-bound interest rates of Fed and ECB in order to fuel industrial growth is unconventional and exposing other markets as well to the macro-economic risks. While saying this, Mr. Rajan also ensures to sound confident on the prospects of India and Indian Banks despite the external influences like these.

 

Box 1:The Economic Times 27-June-2015

While the Central Bank and the Government will dwell upon to ensure the external risks of the above-kind, the banks per se, operating in India need to ensure that they are operationally covered to sustain themselves. Ceteris paribus, especially the external risks, how do the Indian banks cope with distress?

Objective of this Analysis: This analysis aims to test the possibility of Commercial Banks in India going bankrupt in the next 2-3 years, purely based on their operational efficacy. 

Methodology: Various ready-made methods of bankruptcy prediction are available, that take the form of survival approach, option-valuation, neural-network models and other sophisticated approaches. These methods focus on risks emanating from externalities as well as internal affairs of a firm. As the aim of this study is to predict possibility of financial distress caused by operational dimensions of the firm, Altman’s Z-Score Model is applied. Edward I. Altman published his Z-Score formula in 1968, which uses multiple financial ratios of the firm to predict the bankruptcy chances in the next two years. Altman had- applied multiple discriminant analysis to a set of public manufacturing firms and arrived at coefficients for different ratios, those when summed,  give a score, based on which one can derive conclusions on the state of distress. Over a period of time, the formula has been modified to suit different set of firms, viz., public-owned companies, privately-owned firms, non-manufacturing firms, firms from emerging markets etc. This analysis uses the Z-Score formula proposed to be suitable for non-manufacturing firms in emerging markets, which is presented below.

Altman Z-Score For Non-Manufacturers & Emerging Markets: Z = 6.56X1 + 3.26X2 + 6.72X3 + 1.05X4 X1 = Net Working Capital / Total Assets X2 = Retained Earnings / Total Assets X3 = EBIT / Total Assets X4 = Book Value of Equity / Total Liabilities Zones of Discrimination: Z > 2.6 “Safe” 1.1 < Z < 2.6 “Grey” Z < 1.1 “Distress” Analysis & Results:  Constituents of BSE Bankex Index were taken as sample (12 banks), data pertaining to their financials were collected from their respective annual reports for the year ended 31-March-2015 and requisite ratios and Z-Score are computed. The data and their computations are presented in the below table (Box-2)   (Figures In) Total Assets Working Capital Retained Earnings Earnings Equity Total Liabilities TA NWC RE EBIT EQ TL Bank Of India In Lakhs 62528474 502170 3185720 754949 3252285 4009869 Axis Bank In Crores 467243 60163 44475 7358 44950 84394 Bank Of Baroda In Crores 676114 11076 37416 4931 37847 36976 Canara Bank In Crores 553152 -26040 26611 2703 27086 25763 Federal Bank In Crores 82908 -2474 7529 1012 7700 2393 HDFC Bank In Crores 607097 37433 62653 10216 63154 59478 ICICI Bank In Crores 826079 109891 83537 11175 84697 211252 Indusind Bank In Lakhs 10911592 1767533 1010103 309822 1063048 2061806 Kotak Mahindra Bank In Crores 148561 42639 21752 3065 22138 31415 Punjab National Bank In Crores 636011 19757 42217 3341 42588 59205 State Bank Of India In Crores 2700110 51323 160641 17517 161388 244663 Yes Bank In Crores 136170 14279 11262 1997 11680 26220   Box 2: Financial Data of BSE Bankex Constituents Altman’s Z-Scores computed for the respective banks, along with the zone they fall, are presented in the below chart (Box-3)  Box 4: Altman Z-Score for BSE Bankex Constituents Kotak Mahindra Bank and Federal Bank were found to be in safe zone. Canara Bank and State Bank of India are in distress zone. All other banks are in the grey zone. Going by Altman’s model we may predict distress zone banks to go into bankruptcy in the near future; grey zone banks need to exercise caution and relook into their operational strategies; whereas banks in safe zone need to maintain status quo. In the context of a probable economic downturn, as discussed above and when considered as a whole, it can be observed that most of the banks in India fall under grey zone, which is not so immune state to be in, (even though it’s not a distress state).  Conclusion: The above results need to be viewed with caution, as Altman model is developed primarily on manufacturing firms and applicability of the same on non-manufacturing firms, especially banking and financial firms are yet to be proven by researchers. Lack of literature on the same is a big limitation for this analysis. As an academic attempt, this study can remain as a record and unfolding of the future can lead to further research in the area and development of a model meant for banking companies. There is no evidence to suggest computation of a Z-Score is a better means of analyzing long-term solvency. Rather, it can be asserted that use of these ratios as predictors of distress is best in complementing a rigorous analysis of financial statements. Evidence from literature does suggest the Z-Score is a useful screening, monitoring and attention-directing device.   Going by the results, it can be concluded that banks of India, have as an undercurrent, a not-so-satisfactory operational efficacy, and unless these are fixed for better, financial embarrassment - in the event of Mr. Rajan’s prediction coming true - is something that could be a reality. References Altman Z-Score. (2015). Retrieved from Wikipedia - The Free Encyclopedia: https://en.wikipedia.org/wiki/Altman_Z-score Altman, E. (2000). Predicting Financial Distress of Companies: Revisiting the Z-Score and ZETA Models. Altman, E. I. (1968). Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy. Journal of Finance. Economic Times Mumbai Bureau. (2015, June 27). Rajan Rings the Alarm Bell: Chances of Global Depression. The Economic Times, p. 1. Retrieved from http://epaperbeta.timesofindia.com/Article.aspx?eid=31815&articlexml=Rajan-Rings-the-Alarm-Bell-Chances-of-Global-27062015001030 Wild, J. J., Subramanyam, K. R., & Halsey, R. F. (2007). Credit Analysis. In J. J. Wild, K. R. Subramanyam, & R. F. Halsey, Financial Statement Analysis (pp. 540-541). Tata Mc-Graw Hill.