Impact of artificial intelligence on finance

The integration of Artificial Intelligence (AI) within the finance industry has yielded a transformative wave, forever altering its structural and operational landscapes. This thesis embarks on a meticulous exploration into the nuanced impacts, delineating the symbiotic yet occasionally contentious relationship between AI technologies and financial paradigms. In particular, it interrogates how machine learning, predictive analytics, and robotic process automation have revolutionized facets of the finance sector such as algorithmic trading, risk management, customer service, and compliance. Through the lens of varied case studies and empirical analysis, this investigation unveils the profound capabilities of AI in enhancing predictive accuracy, optimizing trading algorithms, and personalizing client interactions while streamlining multifarious financial processes. Paralleling these advancements, it profoundly scrutinizes challenges and ethical dilemmas emergent from this digital shift, encompassing aspects of employment displacement, data privacy concerns, and potential algorithmic biases. Thus, through a confluence of theoretical frameworks and analytical scrutiny, this research elucidates the pervasive impacts of AI on the finance industry, weaving a narrative that contemplates the transformative benefits against the tapestry of ethical and operational challenges. Ultimately, this dissertation aims to serve as a linchpin for discourse and decision-making among policymakers, practitioners, and academicians, provoking reflection on strategies for harnessing AI’s potentials while mitigating its pitfalls within the financial realm.