Performance Assessment of State Bank of India During Post Merger for Sustainability – An Application of CAMEL & LSTM Models
Keywords:
State Bank of India, Merger, CAMEL Model, Capital Adequacy, Return on Equity and Liquidity, LSTM etc.,Abstract
Themain aim of the paper isto appraise the performance of the State Bank of India (SBI) during the post-merger. Many research studies have contributed to the performance of the State Bank of India during the pre-merger period. After the mergerof SBI,the specific studies regarding performance evaluation by application of particular tools as well as Artificial Intelligence (AI) are scanty. This kind of study is required by large public sector banks in the country like the State Bank of India, hence, this specific study has been undertaken. A CAMEL Model and Artificial Intelligence (AI), LSTM have been used to evaluate the performance of SBI during post-merger. The performance evaluation process has been assessed by adopting indicators like Capital Adequacy, Asset Quality, Management Efficiency, Earnings Capacity, and Liquidity of SBI post-merger period.
After reviewing the past studies some questions havearisen in the authors' minds. Is it merging SBI associate banks and Bharathiya Mahila Bank with SBIthe correct decision? Didthe post-merger of SBI give good results? By taking these queries the researchers have assessed the study based on the secondary data only with some of thetenets by offering AI.During the post-merger period a five-year data has been undertaken i.e., from 2017-18 to 2021-22 forstudy purposes. The secondary data was gathered from books, standard international journals, annual reports from SBI, and authenticated websites. To analyse the data so as to get concrete inferences to be drawn from the studysome statistical tools have been used wherever is required.
