Exploring Artificial Intelligence for Enhanced Financial Decision-Making in Treasury Management and Risk Mitigation

Abstract

The present study aims to identify the effect of factors of Artificial Intelligence on the financial decision making processes in treasury management; the impact of factors of Artificial Intelligence in making financial decisions related to risk mitigation; challenges related to the implementation of AI in the treasury and risk management processes; opportunities that are linked with the implementation of AI into the treasury and risk management functions and the suggestions associated with AI implementation that can improve the accuracy, efficiency, and the strategic quality of financial decision. There are three cities namely, Bangalore, Delhi and Hyderabad taken for survey. Therefore, Bangalore, Delhi and Hyderabad are universe for current research. In this study respondents are randomly selected using purposive sampling techniques. Sample size for the study includes 600 employees working in 4 commercial banks, namely, State Bank of India, Canara Bank and HDFC Bank and ICICI Bank. this research underscores that the benefits of AI in treasury and risk management are substantial and multifaceted. However,
realizing these benefits requires careful attention to organizational readiness, governance, regulatory compliance, data quality, and human expertise. The findings provide empirical support for integrating AI as a core component of treasury operations while simultaneously highlighting the need for a balanced approach that combines technological advancement with effective human and organizational controls. As AI continues to evolve, organizations that strategically adopt and manage these technologies will be better positioned to enhance financial decision-making, mitigate risks, and achieve long-term sustainability and competitive advantage in the dynamic financial environment.
Keywords: artificial intelligence (AI), commercial banks, financial decision-making, risk mitigation, treasury management