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How A Data Catalog Enhances Data Risk Management

Alation

Alation joined with Ortecha , a data management consultancy, to publish a white paper providing insights and guidance to stakeholders and decision-makers charged with implementing or modernising data risk management functions. The Increasing Focus On Data Risk Management. Download the complete white paper now.

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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. An enterprise starts by using a framework to formalize its processes and procedures, which gets increasingly difficult as data science programs grow. What Is Model Risk? Types of Model Risk.

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What is GRC? The rising importance of governance, risk, and compliance

CIO Business Intelligence

The need to manage risk, adhere to regulations, and establish processes to govern those tasks has been part of running an organization as long as there have been businesses to run. Furthermore, the State of Risk & Compliance Report, from GRC software maker NAVEX, found that 20% described their programs as early stage.

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How to build an intelligent enterprise

CIO Business Intelligence

Ensure representation from various departments such as operations, IT, finance, legal/risk, human resources, and customer service. Establish a risk management framework. Develop strategies for mitigating risks and handling unexpected challenges. Select committee members with a mix of technical and business expertise.

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ERM Program Fundamentals for Success in the Banking Industry

Speaker: William Hord, Senior VP of Risk & Professional Services

Enterprise Risk Management (ERM) is critical for industry growth in today’s fast-paced and ever-changing risk landscape. When building your ERM program foundation, you need to answer questions like: Do we have robust board and management support? Register today!

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How to become an AI+ enterprise

IBM Big Data Hub

While many organizations have implemented AI, the need to keep a competitive edge and foster business growth demands new approaches: simultaneously evolving AI strategies, showcasing their value, enhancing risk postures and adopting new engineering capabilities. This requires a holistic enterprise transformation. times higher ROI.

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CIOs are worried about the informal rise of generative AI in the enterprise

CIO Business Intelligence

In my previous column in May, when I wrote about generative AI uses and the cybersecurity risks they could pose , CISOs noted that their organizations hadn’t deployed many (if any) generative AI-based solutions at scale. Today, it is, as they create a mysterious new risk and attack surface to defend against.