Impact of Artificial Intelligence and Machine Learning Adoption in Finance - Kakde, Hrishikesh; Lad, Kaveri (Indian Journal of Computer Science, 2024)
The present explores the impact of Artificial Intelligence (AI) and Machine Learning (ML) in banking, emphasizing advantages in fraud prevention, cost savings, and efficiency. Concerns about the competitiveness of traditional financial institutions against Fintech companies are highlighted. AI’s ability to analyze vast data instantly aids investment tracking and risk assessment, utilizing personal information for insurance evaluation. The COVID-19 pandemic has accelerated digitalization, strengthening AI’s role in big data analytics and alternative data sources. ML models autonomously improve performance through data analysis, presenting a transformative era in financial depth and efficiency. The present article discusses the potential for a widening digital gap between developed and developing countries, recognizing AI’s revolutionary impact on banking productivity and risk management. It underscores the rapid shift of banking services online during pandemics, facilitating substantial digitalization gains. AI holds the promise to revolutionize the workplace, significantly enhancing productivity and profitability while reshaping banking services.