This chapter explores the transformative impact of digitalization on risk management within the banking sector, emphasizing how emerging technologies—particularly AI and other digital tools—are redefining risk mitigation strategies and operational frameworks. Digitalization presents substantial opportunities to improve risk assessment, enhance fraud detection, and strengthen the overall resilience of financial institutions. However, it also introduces significant challenges, including heightened cyber threats, increased regulatory complexity, and ethical concerns surrounding the use of AI. To provide a comprehensive and evidence-based analysis, this chapter employs a systematic bibliometric review of 70 peer-reviewed papers, selected from an initial pool of 390 articles retrieved from the Web of Science database. The findings highlight the transformative potential of technologies such as machine learning and blockchain in addressing various dimensions of financial risk. Simultaneously, the chapter emphasizes the critical need for robust governance structures and ethical frameworks to guide the responsible adoption of these technologies. By identifying key research gaps and emerging trends, this chapter offers valuable insights for advancing the understanding of digital banking and risk management. It aims to support the development of more resilient, adaptive, and ethically grounded financial systems in an increasingly digital landscape.

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Banking Digital Drifts: What Are the Opportunities for Risk Assessment?

  • Phuong Le,
  • Thao Ngoc Nguyen

摘要

This chapter explores the transformative impact of digitalization on risk management within the banking sector, emphasizing how emerging technologies—particularly AI and other digital tools—are redefining risk mitigation strategies and operational frameworks. Digitalization presents substantial opportunities to improve risk assessment, enhance fraud detection, and strengthen the overall resilience of financial institutions. However, it also introduces significant challenges, including heightened cyber threats, increased regulatory complexity, and ethical concerns surrounding the use of AI. To provide a comprehensive and evidence-based analysis, this chapter employs a systematic bibliometric review of 70 peer-reviewed papers, selected from an initial pool of 390 articles retrieved from the Web of Science database. The findings highlight the transformative potential of technologies such as machine learning and blockchain in addressing various dimensions of financial risk. Simultaneously, the chapter emphasizes the critical need for robust governance structures and ethical frameworks to guide the responsible adoption of these technologies. By identifying key research gaps and emerging trends, this chapter offers valuable insights for advancing the understanding of digital banking and risk management. It aims to support the development of more resilient, adaptive, and ethically grounded financial systems in an increasingly digital landscape.