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Modular architecture drives productivity and risk management at Gilbane

CIO Business Intelligence

In my view, companies that split up these functions are seeing second-order consequences around communication, costs, and conflict, and are bringing these roles back together. We’re piloting a way to do automated payments to subcontractors based on work in place that’s been identified with photo and video documentation,” Higgins-Carter says.

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What Is Model Risk Management and How is it Supported by Enterprise MLOps?

Domino Data Lab

Model Risk Management is about reducing bad consequences of decisions caused by trusting incorrect or misused model outputs. Systematically enabling model development and production deployment at scale entails use of an Enterprise MLOps platform, which addresses the full lifecycle including Model Risk Management.

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How to use foundation models and trusted governance to manage AI workflow risk

IBM Big Data Hub

As more businesses use AI systems and the technology continues to mature and change, improper use could expose a company to significant financial, operational, regulatory and reputational risks. AI governance refers to the practice of directing, managing and monitoring an organization’s AI activities.

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Automating Model Risk Compliance: Model Development

DataRobot Blog

Addressing the Key Mandates of a Modern Model Risk Management Framework (MRM) When Leveraging Machine Learning . The regulatory guidance presented in these documents laid the foundation for evaluating and managing model risk for financial institutions across the United States. To reference SR 11-7: .

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Data protection strategy: Key components and best practices

IBM Big Data Hub

According to IBM’s Cost of a Data Breach , the global average cost to remediate a data breach in 2023 was USD 4.45 These data breaches can cost their victims in many ways. It can also help them reduce vulnerabilities and ensure data is efficiently managed, compliant with regulations, and not at risk of misuse or loss.

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7 steps for turning shadow IT into a competitive edge

CIO Business Intelligence

Ask IT leaders about their challenges with shadow IT, and most will cite the kinds of security, operational, and integration risks that give shadow IT its bad rep. That’s not to downplay the inherent risks of shadow IT.

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The Value of Data Governance and How to Quantify It

erwin

And with many competing projects and activities vying for people’s time, it must be clear to people why choosing data governance activities will have a direct benefit to them. Usually we talk about benefits which are rather qualitative measures, but what we need for decision-making processes are values,” Pörschmann says. “We