Banca Intesa Sanpaolo doubled models from under 300 to nearly 700 since 2020 with rising AI and ML adoption

Independent validation coverage fell below 70% driving framework transformation

New risk methodology scores inherent and residual risk adding AI factors like fairness explainability and hyperparameter robustness

Central inventory includes all AI systems proprietary and third party

Digital automation tool integrates methods testing and code reducing manual effort and backlog

Generative AI used in controlled closed knowledge base to assist code conversion testing and report drafting with human oversight

ML credit risk model framework evaluates overfitting interpretability and hyperparameter sensitivity balancing performance and risk

Regulatory focus including EU AI Act leads to tiered oversight for high risk AI and future expansion to compliance and ESG models