Evaluating the Impact of Artificial Intelligence on Risk Assessment in Digital Banking

Abstract

The introduction of AI has revolutionized how risk assessments are carried out in digital banking, through providing advanced means for fraud detection, credit scoring and real-time monitoring. This study considers the impact of artificial intelligence technologies on credit scoring models in digital banking. By using mixed techniques of qualitative and quantitative analysis alongside case studies and examination of the latest developments, the research explores to what extent the accuracy and efficiency of risk management is enhanced through machine learning, natural language processing and predictive analytics. The findings demonstrate that AI-based approaches can improve efficiency and scalability of RAs, yet also raise new issues as ensuring interpretability and as of regulation and ethics testing. Recommendations for Financial Institutions Conclusion The final section of the paper presents a set of practical recommendations on how to leverage AI solutions responsibly by financial institutions that need to reconcile being innovative with being compliant in the ever-changing landscape of digital finance.