ARTIFICIAL INTELLIGENCE AND CYBER RESILIENCE IN THE BANKING SECTOR. A NEW ERA IN RISK MANAGEMENT AND FINANCIAL PROTECTION
Abstract
Artificial Intelligence (AI) has become a crucial component in enhancing cyber resilience within the European banking sector. The rapid digital transformation has brought about significant cyber risks, necessitating advanced solutions for data protection, business continuity, and maintaining customer trust.
AI plays a vital role in real-time anomaly detection, risk anticipation, and automated incident response, thereby optimizing threat defence and financial risk management through predictive analytics. Despite its benefits, AI's integration poses challenges related to data protection and ethical decision-making, requiring strict compliance with European and international legislation such as GDPR, NIS2 Directive, Basel III regulations, and the AI Regulation.
This study offers a descriptive analysis and examines AI's impact on cyber resilience, highlighting its technological advantages and legal implications in the banking sector. Innovative models for AI implementation are explored to develop effective security and financial risk management mechanisms, emphasizing the need for proactive threat detection, operational efficiency, and adaptability to evolving cyber threats.
AI plays a vital role in real-time anomaly detection, risk anticipation, and automated incident response, thereby optimizing threat defence and financial risk management through predictive analytics. Despite its benefits, AI's integration poses challenges related to data protection and ethical decision-making, requiring strict compliance with European and international legislation such as GDPR, NIS2 Directive, Basel III regulations, and the AI Regulation.
This study offers a descriptive analysis and examines AI's impact on cyber resilience, highlighting its technological advantages and legal implications in the banking sector. Innovative models for AI implementation are explored to develop effective security and financial risk management mechanisms, emphasizing the need for proactive threat detection, operational efficiency, and adaptability to evolving cyber threats.
Keywords
artificial intelligence, resilience, risk management, efficiency, adaptability
AI Summary
JEL Classification
G32, K24, O33
