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Case Studies

Wells Fargo: Interpretable Machine Learning

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"Managing machine learning model risk is of the utmost importance in heavily regulated industries such as finance; in particular, to manage potential risks due to bias/fairness, conceptual soundness, implementation, and model change control."

Agus Sudjianto
EVP, Head of Corporate Model Risk

Use Cases

Explainable AI

Overview of the Challenge

Transparency, accountability, and trustworthiness of data-driven decision support systems based on AI and machine learning, or more traditional statistical or rule-based approaches, are serious regulatory mandates in banking, insurance, healthcare, and other industries. From pertinent regulations to increasing customer trust, data scientists and business decision-makers need to understand the challenges and opportunities with explainable AI.