Citation :

Nkolo Rove Bekono, Dr. Ahmed Nabih Zaki, 2025. "A Comparative Survey of Artificial Intelligence Applications in Finance" International Journal of Computer Science & Information Technology  Volume 1, Issue 1: 1-8.

Abstract :

Artificial intelligence (AI) has profoundly revolutionised the financial industry by improving customer service, cutting running expenses, and increasing security. Artificial intelligence finds use in a wide range from automated trading to fraud detection to robo-advisory services to risk management underwriting, credit scoring, and regulatory compliance. Financial firms have been able to get real-time, actionable insights from vast volumes by aggregating machine learning (ML), natural language processing (NLP), computer vision, and robotic process automation (RPA). Furthermore enabled by artificial intelligence are creative financial goods, improved financial procedures, and hyperpersonalized customer experiences. Artificial intelligence also enables real-time financial transaction monitoring feasible, enhances anti-money laundering (AML) systems, and supports predictive analytics for income projection. Moreover helping ESG (Environmental, Social, Governance) analysis by means of AI-driven solutions are streamlining supply chain financing efficiency and corporate audit processes. Notwithstanding its significant benefits, the use of artificial intelligence in banking also raises important issues of data privacy, algorithmic bias, explainability, and the need of robust rules. This paper presents a comparison of artificial intelligence applications in numerous financial sectors: banking, investment, insurance, and financial advice services. By means of study of the technologies, use cases, benefits, and challenges, this assessment stresses the existing impact, maturity level, and future potential of artificial intelligence in banking.

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Keywords :

Artificial intelligence, machine learning, financial services, banking, investment management, fraud detection, credit scoring, risk management, financial advisory, natural language processing, robotic process automation, financial rules, data privacy, algorithmeric bias, customer experience, regulatory compliance.