Model Risk
Risk of adverse consequences from incorrect or misused model outputs.
Definitions (3)
The risk of financial, operational, reputational or legal adverse outcomes arising from model design, development, deployment, change, misuse, data issues, or incorrect assumptions and outputs; includes harms from bias, drift, or other model performance degradations.
The set of harms and failure modes that can arise from an AI model’s architecture, training data, evaluation, or operational deployment — including bias, poor generalization, safety failures, adversarial vulnerability, and unintended behaviours — which must be identified, assessed and mitigated through testing, documentation and governance measures.
Model risk is the potential for adverse consequences arising from decisions based on models that are either incorrect or misused. This can result in financial loss, suboptimal business decisions, or reputational damage, stemming from errors within the model or its improper application.
Related Terms
Model-intrinsic risk
Risk stemming from a model's inherent capabilities or behaviours....
Systemic or correlated risk
Risk from model homogeneity causing market shocks....
Model Risk Management (MRM)
Lifecycle controls for development, validation and use of models....
Risk Management
Systematic process of managing AI-related risks....
Model Documentation
Records of model development, assumptions, and validation....