{"title":"银行运用Altman Z分数和Merton模型预测印度企业破产","authors":"Anjala Kalsie, Ashima Arora","doi":"10.18701/IMSMANTHAN.V11I01.6873","DOIUrl":null,"url":null,"abstract":"There has been a recent increase in the financial distress in\nassets of the banking industry. Constant defaults by corporate houses have led banks reach gross NPA levels of 5%.One major\nreason for this rise can be improper risk assessment by banks while giving out loans and improper monitoring of their portfolio\ncompanies. And further Indian banks do not use the most robust risk assessment tools and fail in taking early warning action.\nThe paper tries to use two popular models, namely the Altman Zscore model and the Merton Model to predict financial distress\nin companies which have been the top defaulters in the recent past.The paper tried to determine whether such models are\neffective in predicting financial distress and how much before the occurrence of the actual event. Financial ratios and other\nquantitative data from March 2009- March 2013 forms the sample for the study for Kingfisher Airlines, MoserBaer, Gammon\nIndia, Educomp Solutions and Deccan Chronicles. The study found Merton model to be a better indicator of financial distress\n(of companies) than Altman Z score model. However, none of the models were able to judge the possibility of default at the time\nof issuance of loan indicating at its limitation. Nevertheless, these models which essentially are data driven for assessing the\ncredit risk must widely be used by banks more often, replacing the existing reliance on simple ratios and intuition method.","PeriodicalId":135569,"journal":{"name":"The Journal of Innovations","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Use of Altman’s Z score and Merton Model by Banks to Predict Bankruptcy in Indian Corporates\",\"authors\":\"Anjala Kalsie, Ashima Arora\",\"doi\":\"10.18701/IMSMANTHAN.V11I01.6873\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There has been a recent increase in the financial distress in\\nassets of the banking industry. Constant defaults by corporate houses have led banks reach gross NPA levels of 5%.One major\\nreason for this rise can be improper risk assessment by banks while giving out loans and improper monitoring of their portfolio\\ncompanies. And further Indian banks do not use the most robust risk assessment tools and fail in taking early warning action.\\nThe paper tries to use two popular models, namely the Altman Zscore model and the Merton Model to predict financial distress\\nin companies which have been the top defaulters in the recent past.The paper tried to determine whether such models are\\neffective in predicting financial distress and how much before the occurrence of the actual event. Financial ratios and other\\nquantitative data from March 2009- March 2013 forms the sample for the study for Kingfisher Airlines, MoserBaer, Gammon\\nIndia, Educomp Solutions and Deccan Chronicles. The study found Merton model to be a better indicator of financial distress\\n(of companies) than Altman Z score model. However, none of the models were able to judge the possibility of default at the time\\nof issuance of loan indicating at its limitation. Nevertheless, these models which essentially are data driven for assessing the\\ncredit risk must widely be used by banks more often, replacing the existing reliance on simple ratios and intuition method.\",\"PeriodicalId\":135569,\"journal\":{\"name\":\"The Journal of Innovations\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Journal of Innovations\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18701/IMSMANTHAN.V11I01.6873\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of Innovations","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18701/IMSMANTHAN.V11I01.6873","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Use of Altman’s Z score and Merton Model by Banks to Predict Bankruptcy in Indian Corporates
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.