Generative Artificial Intelligence: Positive Impact on American Financial Institutions - Nagvekar, Ravindra (Digital Repository of Theses, 2025)
Generative Artificial intelligence (GenAI) has played a significant role in influencing the operations of the financial institutions through monitoring market risks and credit risks. The purpose of this study is to determine the positive impacts of Generative AI on the American financial institutions. “Generative adversarial network” of the GenAI streamline the process of content development that supports managers of financial institutions for personalised advice. Additionally, analysis of historical data giddies up the process of decision making by analysing the sentiment of the current market. Furthermore, GenAI develop simulation based on the current data that assists in the evaluating different scenario that ease the process of decision making for financial institution. Literature review chapter has reviewed the positive impacts of the GenAI within the financial institutions. It has been found that the theories like technology acceptance model and theory of reasoned action are beneficial for determining the behaviour of the financial institutions at the time of using GenAI. Implication of theories has effectively paved the way of conducting research within the context of implication of GenAI in financial institutions. Developing in-depth comparing between Predictive AI and Generative AI has also determined accessibility of GenAI capabilities in financial institutions. Methodology chapter has supported this study to identify the most suitable methods for this research such as philosophy, approach, design of this research, data collection, and review of the research problem, questions, sampling, and data analysis. Primary quantitative research design helped this study to gather relevant information related to the positive impacts of GenAI on the financial institutions of North America through reliable primary sources. Positivism research philosophy was integrated for designing the research methodology as it views the phenomenon of Gen AI’s impact on financial institutions of North America. Additionally, integration of deductive research approach ensure evaluation of GAI’s impacts like risk assessment, investment decision through evaluating empirical evidence. Based upon the factors of philosophy and approach, quantitative strategy was undertaken to gain better visualisation on Gen AI’s impacts in finance. Apart from this, questionnaire was used as research instrument for collection of relevant information through closed ended questions. Therefore, survey of 35 participants allows opportunity to capture’s it’s their experience on the impact of Gen AI within financial institute of North America. Use of Generative AI has played a major role for developing customer services of financial institutions for offering virtual assistants to customers with the use of AI chat bots. The study focuses on the outcome of the survey question that young adults are most aware about the application of modern technologies along with its impacts due to the exposures of technology in American Financial Institutions. Financial institutions of North America can focus on proactive risk management with the integration of Generative AI due to the ability for improving risk management strategy in customer satisfaction. From the data analysis, generative artificial intelligence in managing financial institution activity along with opening new avenues in managing decision making, and predictive capability of American Financial Institution has obtained. It is seen that most of the respondents agreed that generative AI is effective in managing financial facilities in reducing issues regarding intellectual property. Discussion on primary data analysis and previous theoretical framework helped to address an inclusion of GenAI over financial decision-making for North American institutions. Meeting research questions was an important part of this chapter to incorporate financial planning for organisations. Meaningful insight creation from vast amount of data set helps to banking employee to overcome banking operational challenges like employee abuse, intellectual property pressure.