Use of Altman’s Z score and Merton Model by Banks to Predict Bankruptcy in Indian Corporates

Anjala Kalsie, Ashima Arora
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Abstract

There has been a recent increase in the financial distress in assets of the banking industry. Constant defaults by corporate houses have led banks reach gross NPA levels of 5%.One major reason for this rise can be improper risk assessment by banks while giving out loans and improper monitoring of their portfolio companies. And further Indian banks do not use the most robust risk assessment tools and fail in taking early warning action. The paper tries to use two popular models, namely the Altman Zscore model and the Merton Model to predict financial distress in companies which have been the top defaulters in the recent past.The paper tried to determine whether such models are effective in predicting financial distress and how much before the occurrence of the actual event. Financial ratios and other quantitative data from March 2009- March 2013 forms the sample for the study for Kingfisher Airlines, MoserBaer, Gammon India, Educomp Solutions and Deccan Chronicles. The study found Merton model to be a better indicator of financial distress (of companies) than Altman Z score model. However, none of the models were able to judge the possibility of default at the time of issuance of loan indicating at its limitation. Nevertheless, these models which essentially are data driven for assessing the credit risk must widely be used by banks more often, replacing the existing reliance on simple ratios and intuition method.
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银行运用Altman Z分数和Merton模型预测印度企业破产
最近,银行业资产的财务困境有所增加。企业房屋的持续违约导致银行的总不良资产比率达到5%。这种上升的一个主要原因可能是银行在发放贷款时进行的风险评估不当,以及对其投资组合公司的监管不当。此外,印度的银行没有使用最强大的风险评估工具,也没有采取早期预警行动。本文试图使用两种流行的模型,即Altman Zscore模型和Merton模型来预测最近一直是顶级违约公司的财务困境。本文试图确定这些模型在预测财务危机方面是否有效,以及在实际事件发生之前预测财务危机的程度。2009年3月至2013年3月的财务比率和其他定量数据构成了翠鸟航空公司、MoserBaer、GammonIndia、Educomp Solutions和Deccan Chronicles的研究样本。研究发现,默顿模型比奥特曼Z分数模型更能反映公司的财务困境。然而,没有一个模型能够在贷款发放时判断违约的可能性,表明其局限性。然而,这些模型本质上是评估信贷风险的数据驱动,必须被银行更频繁地广泛使用,取代现有对简单比率和直觉方法的依赖。
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