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AI Governance for Legal, Risk, & Compliance Leaders

Ensure AI initiatives effectively uphold legal standards, manage risks prudently, and maintain robust compliance across all AI deployments across the organization

AI Governance Use Cases for Legal, Risk, & Compliance Leaders

Regulatory Compliance

Ensuring that AI systems comply with all applicable laws and regulations is paramount. This includes local, national, and international regulations that govern data privacy, consumer protection, and sector-specific rules. Leaders focus on maintaining an up-to-date understanding of these regulatory landscapes and implementing governance structures that ensure AI tools do not breach legal requirements.

Risk Management

Identifying, assessing, and mitigating risks associated with AI deployments is a key concern. This includes technological risks (such as system failures or security breaches), ethical risks (like biases in AI models leading to unfair treatment), and operational risks (impacting the reliability and efficiency of AI systems). Leaders work to establish processes that monitor these risks continuously and develop strategies to mitigate them effectively.

Data Security and Privacy

Protecting sensitive data utilized by AI systems from unauthorized access and breaches is crucial. Compliance leaders focus on implementing strict data governance practices that include secure data storage, controlled access, and robust encryption methods. Ensuring data privacy not only complies with laws like GDPR but also builds trust with customers and other stakeholders.

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ModelOp Customers Rapidly Establish and Effectively Address AI Governance

2/2/2024

BBSI Achieves Near Real-time Credit Scoring Updates with ModelOp

BBSI chose ModelOp to automate the model life cycle of their models with ModelOp to ensure accuracy and timely business outcomes.

Royal Bank of Canada Capital Markets optimizes bond trading with AI and ModelOp Center

Royal Bank of Canada Capital Markets optimizes bond trading with AI and ModelOp Center (as published in “ModelOps for Dummies”).

F500 Financial Services Company Reduces Fraud and Bootstrap with ModelOps Enterprise Solution

Recognizing the potential of AI to address the fraud challenge, the company’s data scientists developed a composite fraud detection model.

Frequently Asked Questions

How does ModelOp's software ensure compliance with international and industry-specific regulations?

ModelOp comes pre-packaged with templates for many common regulatory requirements such as SR 11-7, Dodd-Frank Act, GDPR, and the EU AI Act. Furthermore, ModelOp provides regular updates to these templates as policies change and new regulations are enacted. Second, ModelOp provides the ability to enforce requirements on metadata, documentation, testing, ongoing monitoring, configuration, peer review, and approvals. Together, this enables our customers to quickly “become compliant” and easily “stay compliant."

What risk management features does ModelOp include to identify and mitigate risks associated with AI deployments?

Response coming soon

How does the software handle data security and privacy, particularly sensitive and personal data?

Response coming soon

Accelerate innovation and safeguard all your enterprise AI initiatives with ModelOp

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