Title: Pre and Post Merger Performance through CAMEL Rating Approach: A Case Study of ICICI Bank Ltd
Abstract: The CAMEL approach is a useful tool to examine the safety and soundness of banking sectors in India. It also highlights the risks being faced by banks and helps mitigate the potential risks which may lead to bank failures. In the present study, an attempt is made to evaluate the pre and post merger performance & financial soundness of ICICI banks using CAMEL approach. And this paper also observes financial ratios are considered to reflect profitability of banking sector using the following parameters such as, capital adequacy, asset quality, management efficiency, earning quality and liquidity under globally accepted parameters of CAMEL rating model and their consistency over the study period of 2007–08 to 2016–17. The main objective of this paper is to highlight the theoretical background of CAMEL model and overview of ICICI Bank Ltd. And to examine the shareholders capital adequacy ratios of pre and post merger performance in ICICI Bank Ltd. and also to study the asset quality, earning quality, liquidity ratios and management efficiency ratios of pre and post merger performance in ICICI Bank Ltd. The data has been collected from secondary sources and to measure the reliability of data and for financial ratios of pre-merger data and post merger data. Therefore this study can be concluded though there has been an improvement in the capital adequacy and asset quality in pre merger performance of the acquiring banks. But in the case of post merger performances of management efficiency and earnings quality failed to reflect the ability of the bank to effectively and assets quality generating increased income for the bank and thereby its profitability. And also the liquidity positions has been indicate changes good liquidity position in the post merger period compared to the pre merger period of ICICI Bank Ltd.
Publication Year: 2017
Publication Date: 2017-01-01
Language: en
Type: article
Access and Citation
Cited By Count: 2
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot