ALTMAN MODEL AND FINANCIAL SOUNDNESS OF INDIAN BANKS

Transcription

1 International Journal of Accounting and Financial Management Research (IJAFMR) ISSN Vol. 3, Issue 2, June 2013, TJPRC Pvt. Ltd. ALTMAN MODEL AND FINANCIAL SOUNDNESS OF INDIAN BANKS NISHI SHARMA & MAYANKA University Institute of Applied Management Sciences, Panjab University, Chandigarh, India ABSTRACT Financial soundness of banking sector is undoubtedly a backbone of every economy. Failure of giant banks may traumatize not only the domestic economy but can also put the globe at stake. Collapse of Lehman brothers is recent evidence to this contagious effect. In this context, it is very crucial to analyse the financial soundness of domestic banks. At present there are various methods which may be helpful to analyse financial position of banks like capital adequacy ratio, profitability, liquidity or hybrid model like CAMEL rating. An important model to analyse financial soundness / distress of any corporate house is Altman Z score model. But unfortunately it was least explored by researchers while studying financial soundness of banks. In this reference the present study attempts to apply Altman model to Indian banking industry. The study found that with only two exceptions the financial position of Indian banks found satisfactory. The two banks found somehow in distress position are Canara bank among public sector banks and Kotak Mahindra bank among private sector banks. However, capital adequacy ratio of both of these banks was sound enough as compared to its peer banks. The study suggests the use of hybrid model to make any conclusive remark to the soundness of any company. KEYWORDS: Altman Model, Financial Position, Hybrid Model, Private Sector Banks and Public Sector Banks INTRODUCTION Global financial crisis blessed with growing inflation, currency depreciation, fiscal uncertainty, high level of interest rates and subdued industrial production was strong enough to break down the resilience of financial sector. The collapse of financial giants Lehman brothers and Merrill Lynch bought distress to many financial institutions across the globe. There are different methods of measuring this distress like capital adequacy ratio, profitability, liquidity or hybrid model like CAMEL rating. An important model to analyse financial soundness / distress of any corporate house is Altman Z score model. The model scores the financial soundness of corporate house in terms of Z values. Z score has originally been devised by Edward Altman to signal the possibility of financial bankruptcy of manufacturing units. But since then it has been frequently updated to make it applicable to private companies, non-manufacturers and entities indulge in emerging credit. The model claims for more than 70% accuracy in predicting corporate bankruptcy. But unfortunately it was least explored by researchers while studying financial soundness of banks. In this context, the present study tests the efficacy of Altman model in Indian banking sector. REVIEW OF RELATED LITERATURE The study of financial soundness / distress of banking sector is totally inevitable to ensure economic growth but the issue could not get extensive anatomisation. Though there are studies in this field applying capital adequacy ratio, profitability, liquidity or hybrid model like CAMEL rating, yet the distress position has not extensively studied. Particularly there is a great dearth of studies applying Altman financial distress model to banking industry which has already shown significant result for manufacturing sector. Some of the studies conducted in the arena may be discussed as further. A study conducted by Chaitanya (2005) measured financial distress of IDBI using Altman Z-Score Model. The

2 56 Nishi Sharma & Mayanka model reported that the financial position of the bank was not satisfactory and it also gave indications about the possible bankruptcy of the bank. Blank et., al. (2009) conducted a study on German banks. The study established the relationship between size distribution and financial stability of the banks. Carapeto (2010) attempted to devise most accurate, consistent & simple accounting measure that can be used to distinguish between healthy & financially unsound institutions. The study took a sample of 1175 banks and exposed the ratio of non-performing loans to total loans as the most appropriate accounting measure of distress is the ratio of nonperforming loans to total loans. Nayak and Nahak (2011) studied the performance of Indian public sector banks during post-liberalization period. The study devised performance index for banks based upon the financial ratios of profitability, financial efficiency, operational efficiency and financial soundness. The paper applied Principal Component Analysis method to construct index and ranked different banks over the last 10 years using Edward Altman Model. The study ranked State Bank of India continues at first position to be followed by other banks like Punjab National Bank, Canara Bank, Bank of India and Bank of Baroda etc. Husna and Rahman (2012), attempted to predict possible bankruptcy of Islamic Banks through the CAMEL rating. The study examined asset quality, liquidity ratios, ratio of volatile liability to total source of funds, ratio of primary capital to average assets and current-quarter ratio. Subramnayam and Venkateswarlu (2012) found that the percentage to total of public sectors banks share is decreasing year to year and foreign sector banks share is fluctuating. The study reported that the operating profit percentage of public sector banks to total has decreased from percent to percent during to The operating profit percent to total percent of private sector banks has increased from percent to percent during to and the operating profit percent to total of foreign banks fluctuated during to period. Mishra et., al. (2013) studied the stability of Indian banking sector. The study applied Value at Risk measures, Granger s Causality test and Regression analysis. The results reveal the symptoms of moderate rise in instability in the banking sector in coming periods due to the instability in the asset quality. As shown from the review, Altman model has not been much applied by the researchers. Alternatively capital adequacy ratios, assets quality, ratio of non-performing assets, liquidity, and profitability have been opted as suitable measures to depict the financial soundness. However, after the lessons from recent financial crisis, the study of survival / insolvency probability should be of paramount concern for all related parties. In this context, the present paper attempts to analyse the financial distress of Indian banks through testing the Altman model. RESEARCH METHODOLOGY The present study estimates Z score for 36 Indian commercial banks for a period of five years from These banks comprise of 20 Indian public sector banks and 16 Indian private sector banks. The study applies Altman Z score model to Indian banking industry. This model is a hybrid model which calculates Z score for the corporate house on the basis of four variables viz., working capital, retained earnings, earnings before interest and tax, book value of equity, total liability and total assets. The data used in the study is a secondary data collected from economics times and Reserve bank of India. The calculation of Z score has been done with the help of following equation: Z = 6.56X X X X 4 Where,

3 Altman Model and Financial Soundness of Indian Banks 57 X 1 is the ratio of Working Capital to Total assets. It estimates company's ability to cover financial obligations. X 2 is the proportion of Retained Earning to Total Asset. This ratio measures cumulative profitability over time as a proportion of total assets. X 3 is the ratio of Operating profit to Total Assets. It depicts the managerial efficiency in terms of profitability of the business. Earnings before interest and tax (EBIT) have been used as a proxy to operating profit. X 4 is the ratio of Book value of equity to Total Liabilities of the corporate house. It expresses the financial leverage i.e. the proportion of equity. A high value of ratio depicts firm s aggressiveness in financing its growth with debt. If the cost of the debt financing outweighs the return that the company generates on the debt, it could even lead to the possible bankruptcy. Altman model suggests that if a financial institute secure more than 2.6 score, it should be placed in safe zone. But if it is unable to secure even 1.1 Z score it should be assumed in distress zone and it is more prone to bankruptcy. If the value of Z score is in between 1.1 and 2.6, it should be treated in grey zone. The present study computes Z score for all 36 banks during a period of 5 years from It assigns ranks to public and private sector banks separately. The study also ranks these banks on the basis of liquidity, profitability and capital adequacy ratio so as to analyse whether the hybrid model has an edge over the others or it produces the same results. RESULTS AND FINDINGS Table 1 depicts the descriptive statistics of different variables used in the study. Table 1: Descriptive Statistics Particulars Working Retained Market Total Total EBIT Capital Earnings Equity Assets Liability Public Sector Banks Number of Observations Mean Maximum Minimum Private Sector Banks Number of Observations Mean Maximum Minimum The descriptive statistics of selected public sector and private sector bank reveal that average liquidity (ratio of working capital to total assets) of Bank of Baroda is highest at and lowest for Canara bank at In case of private banks it is highest for city Union Bank at and worst for Kotak Mahindra at The profitability (percentage of EBIT to total assets) is highest in case of Allahabad Bank at 8.65% and 4.19% of Axis Bank of respectively for public sector and private sector banks. Average Profitability ratio is lowest for Syndicate Bank at 1.05% in case of public sector and 0.58% for DCB in case of private sector banks. Table 2 and 3 demonstrate the Z score of Indian commercial banks. Table 2: Z Score of Public Sector Banks S.No. Public Sector Banks Average Z Score 1 Allahabad Andhra Bank

4 58 Nishi Sharma & Mayanka Table 2:Contd., 3 Bank of Baroda Bank of India Bank of Maharashtra Canara Bank Corporation bank Dena Bank IDBI Indian bank Indian overseas bank Oriental Bank of Commerce Punjab and Sind Bank Punjab National Bank State Bank of India Syndicate bank UCO Union Bank of India United Bank of India Vijaya bank Average Annual Z score Altman model assigns least rank to Canara bank and put it in distress zone. However, other public sector banks were found to be in safe zone as they secured more than 2.6 score. Z score of Bank of Baroda was highest which was followed by Andhra Bank. Z score was best in the year 2009 and was least in 2010 and This may probably be due to the later repercussions of global financial crisis. But even in that phase, public sector banks were found capable enough to get way from any financial distress. Table 3: Z Score of Private Sector Banks S.No. Private Sector Banks Average Z Score 1 Axis bank City union bank Dhanlaxmi Bank Development credit bank Federal Bank HDFC BANK ICICI IndusInd Bank ING Vsysya bank Jammu Kashmir Bank Karnataka Bank Karur Vsya Bank Kotak Mahindra Bank Laxmi Villas Bank South Indian Bank Yes Bank Average Annual Z score

5 Altman Model and Financial Soundness of Indian Banks 59 The financial position of Kotak Mahindra bank was found to be in distress zone by Altman Z score model. The model also reported that soundness of Indusind bank has shown remarkable improvement after The model ranked City Union Bank as the best performer which was followed by Laxmi Vilas bank. Table 4 and Table 5 provides brief description of ranking of public sector and private sector banks respectively on the basis of profitability, liquidity, capital adequacy ratio and Z score. Table 4: Ranking of Public Sector Banks S.No Bank Profitability Based Liquidity CAR Based Z Score Based Ranks Based Ranks Ranks Ranks 1 Allahabad Bank Andhra Bank Bank of Baroda Bank of India Bank of Maharashtra Canara bank Corporation bank Dena Bank IDBI Indian bank Indian overseas bank OBC Punjab and Sind Bank Punjab National Bank SBI Syndicate bank UCO Union Bank of India United Bank of India Vijaya bank Poor working capital ratio to total assets and Z score of Canara bank place it on the last position. However the same put on second rank on the basis of capital adequacy ratio. Profitability and capital adequacy ratio ranked Syndicate Bank on last position. Bank of Baroda has been ranked first on the basis of liquidity, capital adequacy ratio and Z score. Allahabad bank has been ranked first on the basis of profitability. Andhra Bank has been ranked second on the basis of three categories viz., profitability, liquidity and Z score. However, capital adequacy ratio assigns tenth rank to it. Table 5: Ranking of Private Sector Banks Bank Profitability Based Ranks Liquidity Based Ranks CAR Based Ranks Z score Based Ranks Axis bank City Union bank Dhanlaxmi Bank Development Credit Bank Federal Bank HDFC bank ICICI Bank IndusInd Bank ING Vsysya bank JK bank Karnataka bank Karur Vysya bank Kotak Mahindra bank Laxmi Vilas Bank

6 60 Nishi Sharma & Mayanka Table 5: Contd. South Indian Bank Yes Bank Axis bank was ranked highest on the basis of profitability. Liquidity and Z score both criteria have ranked City Union bank the best performer. Kotak Mahindra bank could not secure good position on the basis of profitability, liquidity and Z score. However its capital adequacy ratio was good enough to enable it to have second position among private sector banks. CONCLUSIONS The study concluded that with only two exceptions the financial position of Indian banks found satisfactory as per the Altman model. The two banks found somehow in distress position are Canara bank among public sector banks and Kotak Mahindra bank among private sector banks. However, capital adequacy ratio of both of these banks was sound enough as compared to its peer banks. This analysis also derive a very important conclusion that capital adequacy ratio cannot be treated as a whole sole indicator of financial soundness and should be considered along with other parameters. The study is expected to provide good framework to policymakers as well as bank managers while designing their investment outlay. REFERENCES 1. Carapeto et., at. (2010). Distress Classification Measures in the Banking Sector. Mergers and Acquisitions Research Centre, Cass Business School, City University of London, 1-30, retrieved from 2. Nayak B. and Nahak C (2011). Benchmarking Performance of Public Sector Banks in India. The IUP Journal of Bank Management, IUP Publications, 2, Blank et., al. (2009). Shocks at large banks and banking sector distress: The Banking Granular Residual. Journal of Financial Stability, Elsevier, 5(4), Husna and Rahman (2012). Financial Distress- Detection Model for Islamic Bank. International Journal of Trade Economics and Finance, 3(3), Subramnayam and Venkateswarlu M.(2012). Financial performance of scheduled commercial banks in India-a study.,indian journal of research, 1(12), Chaitanya (2005). Measuring Financial Distress of IDBI Using Altman Z-Score Model. IUP Journal of Bank Management, IV (3), Mishra, Majumdar and Bhandia(2013). Banking Stability- A Precursor to Financial Stability. Department of Economy& Policy Research, retrieved from