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Purpose: The purpose of the study is to determine the significant difference between the performance of the Indian banks in pre coronavirus disease (COVID 19) and post COVID 19 periods. Further, it explores the impact of COVID 19 on the profitability of the Indian banks by investigating variation between the non-performing assets (NPAs) and the net profit of the banks during pre and post COVID 19 periods.

Need of the study: The COVID 19 outbreak has affected various industries including Indian banks which reported an increase in NPAs, and demand for credit which in turn impacted profitability. This study was carried out to examine the impact of COVID 19 outbreak on Indian banking sector.

Methodology: This study uses different banks’ NPA and net profits performance to examine the effect of COVID 19 on banks’ overall performance. The data have been collected from secondary sources, commercial websites, and websites of Indian banks (private and public sectors). t-Test was used to analyse the data.

Findings: Among public sector banks, Canara Bank was found to have a significant difference in net profit in the pre and post COVID 19 periods. In private sector banks, HDFC Bank showed a significant difference in the net profit in pre and post COVID 19 periods. For NPAs, all private banks showed no significant difference in pre and post COVID 19 period results.

Implications: The study revealed that both private and public sector banks in India were mildly affected by pandemic and most of them are significantly reporting no difference in net profit and NPAs during pre and post COVID 19 periods.

Purpose: This chapter discusses the role and use of chatbots adopted by the different categories of banks (private and public sector banks) in India. The chapter presents brief essential services offered by Indian chatbots regarding accuracy, technology providers and virtual assistance, ways to connect, etc. This chapter concluded that most of the questions answered by the Indian chatbots are already available on the banks’ websites, and there is a need for enhancement in the capabilities of Indian chatbots.

Need for the Study: The need for the study is based on the working of banking chatbots, customer query handling, and the efficiency of the chatbots in India. The chapter helps to analyze the services offered by various banks.

Methodology: This chapter is based on secondary data collected from banks’ websites and articles from various journals. The study is based on nine banks (both private and public sectors) those are having working chatbots (SBI, HDFC Bank, ICICI Bank, Yes Bank, IndusInd Bank, Kotak Mahindra Bank, Axis Bank, Andhra Bank, Bank of Baroda). The present study is focused on chatbots, their services, and software applications for various customer-handling capacities.

Findings: The research concluded that Indian banks are investing a small amount in using chatbots, yet Indian chatbots are deficient regarding far too provincial administrations as they are adequate just for standard and basic inquiries. Also, Indian customers are not properly aware of chatbots and virtual assistance.

Practical Implications: This study provides an overview of the working chatbots in India (for both public and private sector banks) and their functions, as well as the capacities of these chatbots. The previous conducted studies are based on the uses, importance, and working of chatbots/artificial intelligence (AI) in banking. In this study, after discussing the different services, it is found that Indian banks need to update their AI/Virtual assistance with more features.

Non-performing assets (NPAs) are classified as loans and advances which are in default, either refund of principal or interest payments are not duly met. This not only leads to dishonour of loan agreement from the recipients' point of view but also huge NPAs result macroeconomic instability and economic crisis. The financial crisis may create hindrances towards achievement of sustainable development of an economy. Keeping NPA in balance sheet portrays lacunae in management of the lender. The non-recovery of interest and principal reduces the lender's operating cash flow, which upsets the budget and drops the earnings. Statutory provisions, set aside to cover probable losses, reduce the income further. When the non-recovery is determined to be definite in nature, they are written off against earnings of the lending institution. Thus, presence of NPAs in balance sheet gives a distress signal to the stakeholders of the lending institution. Under this consideration, the present study will look upon some of these issues related to NPA management in Indian banking sector. The main objective of this study is to discuss the nexus between the NPA of Indian scheduled banks for priority sector, non-priority sector and public sector and the gross domestic product (GDP) of Indian economy for the time period 2005–2020. To study this objective, the ratio analysis and the trend analysis of NPA of three sectors and GDP of Indian economy over the given time frame have been done. Finally, some policy prescriptions regarding achievement of sustainable development after taking into account NPA management of an economy have also been proposed.

Purpose: Worldwide economies have been shattered by the alarming increase in Non-Performing Assets (NPAs) in Banking Sector. In India, the rise in NPA levels gives a clear insight into the health of industry and state. This study aims to determine how NPAs in India impact the profitability of eight banks chosen from the public and private sectors; specifically: Punjab National Bank (PNB), Bank of India (BOI), UCO Bank, Punjab and Sind Bank (PSB), HDFC Bank, Axis Bank, ICICI Bank, and Yes Bank; during the period 2009/2010 to 2017/2018.

Design/methodology/approach: The study utilised IBM SPSS version 20 application to carry out our statistical analysis of measures of central location (mean and median), measures of dispersion (standard deviation), to carry out the Kolmogorov–Smirnov test to check the normality of data, the Mann–Whitney U test (for two groups) for median comparison between private and public sector banks and the Kruskal–Wallis test (for more than two groups) for median comparison for more than two banks. p ≤0.01 and p ≤0.05 were the two-tailed significance level used for determining the significance of all statistical tests.

Findings: Trend analysis and statistical tests show that the trend in public sector banks to have NPAs is higher compared to private sector banks, and losses arising from NPA impact the banks’ profitability.

Practical implications: It is apparent that NPAs are a large threat to banks in India as it reflects the state of the Indian economy. The growth of the economic cycle is predominantly dependent on the smooth and profitable functioning of private and public sector banks. This current study focusses on and compares the impact of NPAs on the profitability of public and private sector banks. NPAs have grown exponentially more in the case of public sector banks than private sector banks, which has affected the former banks’ financial health and performance. Increases in the level of NPAs adversely affect the working style and long-term stability of public and private sector banks in the economy.

Social Implications: NPAs have a negative influence on the profitability of the banks as well as on the economic growth of the country too. However, it is recommended that management in the banking sector, particularly the public banks, should use various preventive and recovery strategies to reduce the risk of failure and to keep track of NPAs to stay safe.

Originality/value: This study aims to determine how NPAs in India impact the profitability of eight banks chosen from the public and private sectors; specifically: PNB, BOI, UCO Bank, PSB, HDFC Bank, Axis Bank, ICICI Bank, and Yes Bank; during the period 2009/2010 to 2017/2018.

The study aims to evaluate the financial distress position of selected sample banks in India. The top 10 banks with the highest levels of gross non-performing assets (NPA) under both public and private sector ownerships have been chosen for the study. Application of the Altman Z-score model has been used to compare both ownership banks’ financial distress for five years from 2017 to 2021. Based on the study’s findings, it was found that private sector banks demonstrated better financial stability than their public sector counterparts. Specifically, the average Z-score of the selected sample banks was higher than the safe zone threshold of 2.9 during the study period.

Recalling that the introductory chapter (Chapter 1) wanted to carry out similar types of analysis for the major states in India. Thus, the present chapter tries to examine the trends of a bank branch, deposit, credit, the credit–deposit ratio, sectoral shares of credit, magnitudes of banking transactions, credit concentration, etc., for the selected 15 states and Delhi as the only union territory for the period 1972–2019. The study period covers the pre-reform period from 1972 to 1992 and the post-reform period 1993–2019. The observations show that the branch, deposit and credit did not grow significantly during the post-reform period. As a result, the credit–deposit ratio did not increase significantly during the reform period. But, the magnitude of banking transactions increased in most of the states during the reform period. Regarding the sector-wise share of credit, AP, Maharashtra, UP and TN are the leading states in agricultural credit, WB, Gujarat and Maharashtra are in industrial credit and Kerala, Assam and Delhi are in the service sector. On the other hand, the study finds rising magnitudes credit concentrations of the states during the post-reform period in contrast to the declining concentration in the pre-reform period. Maharashtra is the state which holds around 25 per cent of all states’ credit throughout the entire period of 1972–2019. Hence, there are the notions of rising disparity and inequality in credit as well as incomes of the states and all India levels.

Purpose: Progression is an unpreventable reality of presence, and banking is no exclusion. Cash transformers and moneylenders from times gone past are great agents today. Cash held in trust became store taking, and money advancing became credit making; over an extended time, banks transformed into a need, and the occupation of banks, transformed into a critical piece of monetary reality. Banks’ turn of events and headway has been mind-boggling, with the latest frenzy being intuitive media banking. The chapter additionally framed the amazing open doors and dangers for banks because of the presentation of innovations and how banks are making the most of the open doors and endeavouring to cure the risks. The financial area in India is a lifesaver for the country. Indian banks could become the fifth most prominent on earth by 2020 and the third most prominent by 2025.

Methodology: This study has given auxiliary information. Furthermore, it’s gathered from the holding bank of India concerning utilisation by various banks. Which utilised graphic review including mean mode middle.

Finding: After the review, we find that sight, sound, and green banking have become fantastic assets for the baking area. During COVID-19, the utilisation of mixed media expanded in contrast to a year ago.

Significance: The review featured sight and sound and green banking sealed spine in COVID -19 and is utilised expanded after this pandemic.

Purpose: This chapter aims to unveil the challenges of adopting and using banking chatbots in India and identify the challenges of Chat Generative Pre-trained Transformer (ChatGPT) for future banking.

Need for the study: Unveiling the challenges of chatbots and ChatGPT in the banking industry in India is crucial to understand the limitations and areas of improvement to enhance customer experience, ensure data security, and maintain regulatory compliance.

Methodology: The researchers conducted a narrative review systematically summarising and analysing existing literature on chatbots and ChatGPT, providing a comprehensive overview of the challenges faced in the industry.

Findings: The authors identify perceived risk, platform quality, connectivity and infrastructure, data privacy and security, user education and acceptance, existing legacy systems, and regulatory guidelines as the challenges of adopting chatbots. Additionally, the findings reveal that the challenges posed by ChatGPT in future banking include the potential reduction of traditional banking jobs, linguistic diversity, data privacy and security, ethical considerations and bias mitigation, explainability and accountability, integration with existing banking systems, and user trust and acceptance. However, implementing these new technologies also presents opportunities for individuals with unique human skills, such as critical thinking, empathy, and creativity, which are difficult to replace with technology.

Practical implications: By minimising the challenges of ChatGPT and chatbots, the banking industry could achieve improved customer service, cost efficiency, automation of routine tasks, and 24/7 availability, leading to enhanced customer satisfaction and operational efficiency in the banking industry. Additionally, these artificial intelligence (AI) tools enable data-driven insights, personalised experiences, scalability, and efficient handling of large customer volumes, contributing to better decision-making and enhanced customer engagement.

The values and trends of the credit–deposit (C-D) ratio in countries and the states within them depend on several factors. Two such factors that the present study considers are the banks’ loanable funds locked under the heads of non-performing assets (NPA) and governments’ securities investments. Increases in the amounts of NPA and securities investments usually lead to a decrease in the allocations of bank credit to real investment purposes, such as industrial, service and agricultural activities and vice versa. On this background, this chapter examines the trends in bank credit in relation to the NPA and securities investments in the states of India and tries to find out the real cause of concern on the falling trends in the C-D ratio in the post-banking reform phase. We may now summarize that the falling C-D ratio or the rising quantity of flight of credit to the real sectors is closely associated with the banks’ investment of extra amount on securities over their statutory limits. This study finds that the NPA ratio at all-India levels is gradually declining while the investments on securities are increasing during the post-reform period. Such a craze behind this investment has an inevitable effect on the magnitude of credit delivery to the commodity-producing sectors. This means that the NPA threat is not a real threat to explain the downward trend of C-D ratio but the magnitude of security investments in both the central and state governments is a real threat and the downward trend of the C-D ratio is the result of this fact. Even though banks are safe in terms of their returns, the scenarios are not good for the rest of the economy as it creels their sustainability.