Purpose: The study is conducted to evaluate the adaptability of artificial intelligence in recruitment and to assess the effect of this technology on the performance of the employees. Design/Methodology/Approach: Standard Multiple Linear regression model is used to predict the performance of the employees and one-way ANOVA is used to compare the artificial intelligence based recruitment with performance indicating variables namely reliability, productivity, Automation, Gamification & Training using SPSS. Snowball sampling method has been adopted for a sample size of 440 respondents working in leading recruitment consultancies in urban Bangalore. Findings: There is a greater association between the recruitment and performance variables when artificial intelligence is adopted as it is significant at 0.001 per cent level and productivity being the maximum. However, the impact of implementing gamification for recruitment doesn't have a significant impact on the output due to partial significant effect on the adoption as (p = 0.046 < 0.05). Value of "R" is 0.604 and the coefficient of determination is 0.365. Productivity, Training, Automation & Reliability are the significant predictors of the performance in employees. Originality/Value: Artificial intelligence has emerged as a boon to the recruiters by automating the repetitive tasks, administrative tasks. Intelligent screening helps in automating resume screening, recruiter Chatbots for real-time candidate engagement, and digitization of interviews. This promotes pro-active strategic decision making better by the recruiters.

Purpose: Human resource plays a pivotal role in the overall development of any organization irrespective of technological changes taking the lead. The study aims to analyze the role of human resource in the Merchant banks that facilitate in offering quality services rendered based on the decision making comprising of confidentiality, analytical skills, and problem-solving ability. Design/Methodology/Approach: 50 respondents from the Merchant banks operating in urban Bangalore were surveyed to collect the primary data collected based on a structured questionnaire using a stratified sampling method. Confidentiality, analytical skills, problem-solving ability, technology & service are the variables used to test the Structural Equation Model (SEM) using SPSS AMOS (Analysis of Movement variance). Findings: SEM has been applied to validate the model fit to test if there is a significant effect of human resource in the decision making for the Merchant banking services rendered. The findings resulted that confidentiality is the most influencing path in the model with standardized coefficients being 0.986 and followed by problem-solving ability being 0.972. Originality/Value: Artificial Intelligence has been taking over every aspect of the business reducing the workforce in the modern era of globalization as technology-enabled systems can be more accurate and useful in decision making, and human resource plays a pivotal role in interpreting the systems.

Purpose: The study aims to identify the reasons for the increase in the number of captive operations in urban Bangalore, which earlier was confined only to middle office and back end office but now venturing into front end office. Design/Methodology/Approach: The study includes 50 respondents, employees in the leading foreign-based investment banks operating in urban Bangalore, applying the snowball sampling method through a structured questionnaire. Business model, strategy, database, customized product, market research, operating cost, and employment are the variables. SPSS has been used to test the hypothesis through One-way ANOVA (Analysis of Variance). Findings: Employment, operating cost, and analytical skills are the key human resource factors impacting the performance. Business models, strategies, and customer database, are the significant factors of asset management. Attractive business avenues, eminent personnel, customer database are the formative factors of quality management. Job roles, portfolio seeding, segment business are the most highly influencing performance factors in offering excellent service to the clients by these banks as they are significant at 0.001 per cent level. Originality/Value: Investment banking reflects being one of the distinct segments which facilitates in capital formation, financial consultancies, advisory services, security trading, custodian services, investment management services, corporate actions, etc. This sector has transformed into a promising one in boosting the economy and financial services post-globalization. Most of the Asian nations are promising to be a silver line for the US and UK based Investment banks operating in Bangalore.

Banks are automating their processes, migrating their infrastructure and applications to the cloud to create a seamless customer journey. Transformative technology has enabled banks and financial institutions to automate their operations based on advanced data-driven. Banks are adopting AI based anti-money-laundering, anti-fraud, compliance, credit-underwriting and smart contracts technology in their operations. These applications have been embraced by the investment banks as regulatory framework are failing to combat conventional way in combating against money laundering. Artificial Intelligence will focus on cognitive application in functional areas of business along with investment and compliance sectors of financial services industry. Adopting AI based anti-money-laundering, anti-fraud, compliance, credit-underwriting and smart contracts technology in their operations.

Purpose This study aims to analyze the importance of disruptive technological innovations on qualitative service delivery and their impact on the investment banks’ employee performance. Design/methodology/approach The cluster sampling method has been used to collect the primary data from the 250 respondents from foreign investment banks. Variables used are employee performance, service delivery, technology, security, operations, strategy and quality through chi-square, linear stepwise multiple regression analysis and correlation. Findings Storage network, operating cost, client reporting, cloud system and money laundering are the highest and most significant predictors of employee performance. Employee performance multiplies every unit with a strategic solution owing to positive and robust correlation (0.944). Fusion technology-based banks offer quality service to their clients. Originality/value A combination of artificial intelligence and blockchain ensures increasing automation to improve efficiency and reduce the operating cost creating a seamless integration in fraud detection, customer support, risk management, security, digitization and automation process, algorithmic trading, wealth management, etc.