Empowering Financial Services: The Transformative Impact of AI on FinTech Innovation

Tayyab Muhammad (), Asad Yaseen () and Kriya Shah ()

American Journal of Computing and Engineering, 2024, vol. 7, issue 4, 35 - 49

Abstract: Purpose: This study examines the transformative role of Artificial Intelligence (AI) in the financial services industry, particularly in the FinTech sector. By exploring AI applications such as personalized banking, fraud detection, credit scoring, and algorithmic trading, the paper analyzes how AI enhances operational efficiency and customer experience. Material and Methods: Using case studies from leading financial institutions, the paper highlights both opportunities and ethical concerns, such as data privacy and algorithmic bias. Findings: The study found that AI enhances detection by analyzing vast datasets to spot suspicious patterns and anomalies that human auditors may miss, improving compliance and reducing financial crime risks. AI streamlines loan underwriting processes by evaluating a broader range of data, such as payment history and social media behavior, providing more accurate risk assessments. The study also revealed that algorithmic trading uses AI to automate and optimize trades at speeds and scales impossible for human traders. AI systems analyze real-time market data and execute trades within milliseconds, capitalizing on fleeting opportunities in the stock market. By incorporating machine learning, these systems can adapt and improve over time, becoming more effective in predicting market trends and managing risk. Implications to Theory, Practice and Policy: It expands the understanding of how AI can reshape financial interactions, enhancing personalization, fraud detection, and credit assessment. From a practical standpoint, it highlights real-world applications, such as robo-advisors and algorithmic trading, offering insights into how institutions can implement AI responsibly. On a policy level, the study underscores the importance of regulatory frameworks addressing data privacy, algorithmic fairness, and transparency, advocating for collaboration between regulators and financial institutions to ensure ethical AI deployment.

Keywords: Artificial Intelligence; FinTech; Fraud Detection; Credit Scoring; Algorithmic Trading; Financial Innovation. (search for similar items in EconPapers)
Date: 2024
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