AI MODEL RISK MANAGEMENT FRAMEWORK

AI Model Risk Management Framework

An AI Model Risk Management Framework (MRM) is a structured approach used by organizations to identify, assess, monitor, and control risks associated with artificial intelligence and machine learning models.

As AI systems become more integrated into finance, healthcare, cybersecurity, and enterprise decision-making, managing risks such as bias, security vulnerabilities, and incorrect predictions becomes essential.

📘 What is Model Risk?

Model risk occurs when an AI or machine learning model produces incorrect, biased, or harmful outcomes, which may lead to:

⚠ Poor business decisions

⚠ Financial losses

⚠ Regulatory violations

⚠ Security or privacy issues

⚠ Reputational damage

Organizations use risk management frameworks to ensure AI systems remain reliable, transparent, and safe.

🧩 Key Components of an AI Model Risk Management Framework

1️⃣ Model Governance

Establishing policies and oversight for AI systems.

Key elements:

• AI governance policies

• Model ownership and accountability

• Documentation and audit trails

• Compliance with regulations