The objective of this study is to Analyze the Financial Position and Performance of the Axis and Kotak Mahindra Bank in India based on their financial characteristics. We have chosen the CAMEL model and t-test which measures the performance of bank from each of the important parameter like capital adequacy, asset quality, management efficiency, earning quality, liquidity and Sensitivity. The present study is conducted analyze the consistency of the profitability of the Axis and Kotak Mahindra bank’s. It is analyses that (...) the ratio of credit deposit is maximum of Kotak Mahindra Bank Ltd and it shows efficient management of the bank. The ratio of earning per share is maximum for Axis Bank Ltd i.e. 50.28 and the ratio of return on Assets is minimum for Axis Bank Ltd. The CAMELS’ analysis and t-test concludes that there is no significance difference between the Axis and Kotak Mahindra bank’s financial performance but the Kotak Mahindra bank performance is slightly less compared with Axis Bank. (shrink)

The rapid advancement of Artificial Intelligence (AI) and the developments of Large Language Models (LLMs) like Generative Pretrained Transformers (GPTs) have significantly influenced content creation in scholarly communication and across various fields. This paper presents a comparative analysis of the content reliability between human-generated and GPT-generated scholarly articles. Recent developments in AI suggest that GPTs have become capable in generating content that can mimic human language to a greater extent. This highlights and raises questions about the quality, accuracy, and reliability (...) of such content, especially in academic contexts. Statistical evaluations and quantitative assessments conducted in this study uncover key differences in content accuracy, coherence, citation usage, and overall reliability between human and GPT-generated articles. The paper also examines the potential biases, the role of context, and the implications of AI-generated content for the future of scholarly communication. The study concludes with framework for predictive model indicating the potential future impact of GPT-driven content creation and recommendations for ensuring content quality and ethical considerations in AI usage. (shrink)