The Use of Artificial Intelligence in Credit Risk Management at BBVA
The Use of Artificial Intelligence in Credit Risk Management at BBVA

Author(s): Ana Lorenzo
Subject(s): Economy, Business Economy / Management, Financial Markets, ICT Information and Communications Technologies
Published by: Университет за национално и световно стопанство (УНСС)
Keywords: Artificial Intelligence; Credit Risk Management; BBVA; Machine Learning; Banking Regulation
Summary/Abstract: This paper examines the integration of Artificial Intelligence (AI) into credit risk management at BBVA, one of Europe’s leading digitally oriented banks. As financial institutions increasingly rely on data-driven tools to ensure resilience and competitiveness, AI offers new capabilities for predicting defaults, optimizing credit scoring, and monitoring portfolios in real time. The study explores how machine learning (ML) models, big data analytics, and cloud architectures enable BBVA to enhance decision-making accuracy and operational efficiency while reducing non-performing loan ratios and improving capital allocation. The analysis identifies AI’s main contributions to credit risk management: improved predictive performance, faster and more consistent credit decisions, and dynamic monitoring through real-time data integration. It also highlights how BBVA’s digital transformation strategy — including the development of centralized data platforms and multidisciplinary governance frameworks — supports the responsible deployment of AI across business lines. However, the paper also emphasizes the challenges associated with AI adoption. Issues such as algorithmic bias, lack of transparency, data protection, and compliance with evolving regulations (e.g., GDPR and the EU AI Act) require careful governance and ethical oversight. BBVA’s approach combines model explainability, human-inthe-loop controls, and rigorous validation processes to ensure fairness and accountability in automated decision-making. The findings suggest that AI fundamentally reshapes credit risk management by complementing — not replacing — human expertise. The successful implementation of AI at BBVA demonstrates that technological innovation, when guided by ethical principles and strong regulatory alignment, can strengthen both risk resilience and financial inclusion. The study concludes that responsible AI integration represents not only a competitive advantage but also a necessity for sustainable banking in the digital era.

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