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      TitleA Study on Income Recognition & Asset Classification of New Private Sector Banks in 2014
      Publication TypeJournal
      Year of Publication2014
      AuthorsJACOB, SAJINI, Kumar, S
      KeywordsCredit Risk, NPAs
      Abstract

       

      Credit Risk is the potential that a bank borrower/counter party fails to meet the obligations on agreed terms. These losses could take the form of outright default or alternatively, losses from changes in portfolio value arising from actual or perceived deterioration in credit quality that is short of default. An asset is classified as non-performing asset if dues in the form of principal & interest are not paid by the borrower for a period of 180 days. However with effect from March 2004, default status would be given to a borrower if dues are not paid for 90 days. The importance of Non Performing Assets is increasing day by day from the formation of Shri M. Narsimham Committee. It is the second land mark in banking sector in India after nationalization of banks. Reserve Bank of India had advised all commercial banks on 7th November, 1987 to introduce the health classification indicating the quality of individual advances in the following eight categories with Health Code assigned to each borrower account namely Satisfactory, Irregular, Sick – viable, Sick – non – viable / sticky, Advances – recalled, Suit – file – accounts and Decreed debts. The high level of NPAs in banks and financial institutions has been a matter of grave concern to the public as bank credit is the catalyst to economic growth of the country. NPAs are not therefore the concern of only lenders. The purpose of this study is to understand the performing assets and non – performing assets of new private sector banks in India and also study about the rating of banks on NPA management. Impact of NPAs on performance of a Bank may be either Interest income reduction due to non – performance of assets and/or Desirable yield not achieved etc . This paper also attempts to study the impact of NPA’s on Banks. Statistical techniques used are Mean (x), Standard deviation (б), T-Test and Correlation.

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