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Ways in Which AI can Improve Enterprise Risk Management

bridgei2i

However, risk management is no way lagging. ERM or Enterprise Risk Management is being used to identify crises long before it blows up into a huge problem. AI is being used to assess, prioritize, and mitigate risks in the enterprise so that the business operations do not take a hit. Risk Management Model.

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Managing risk in machine learning

O'Reilly on Data

Fortunately there are members of our data community who have been thinking about these problems. One important change outlined in the report is the need for a set of data scientists who are independent from this model-building team. “How How to build analytic products in an age when data privacy has become critical”.

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Data Loss: Hazards, Risks and Strategies for Prevention

Smart Data Collective

Regular saving of work and plans for the systematic backing up of data should be part of the workflow procedures of any enterprise. However, enterprises should be prepared for the worst-case scenario, such as a catastrophic network failure, which can cause the entire data collection of a company to disappear completely.

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The Foundations of a Modern Data-Driven Organisation: Change from Within (part 2 of 2)

Cloudera

The report classified employees’ reasons for leaving into six broad categories such as growth opportunity and job security, demonstrating the importance of using performance data, data collected from voluntary departures and historical data to reduce attrition for strong performers and enhance employees’ well-being.

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Make data protection a 2023 competitive differentiator

IBM Big Data Hub

They have been exceedingly clear in communicating with consumers what data is collected, why they’re collecting that data, and whether they’re making any revenue from it. They go to great lengths to integrate trust, transparency and risk management into the DNA of the company culture and the customer experience.

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Vendor management: The key to productive partnerships

CIO Business Intelligence

While working with IT vendors can help ease the burden on IT, it also raises concerns, especially around data, risk, and security. Vendor management can better support IT governance, helping organizations keep a close eye on compliance and risk management. Vendor management certifications.

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Discovering Data Monetization Opportunities in Financial Services

Cloudera

Data has become an essential driver for new monetization initiatives in the financial services industry. Wealth managers can monetize their data by selling analytics and insights to their clients, such as customized investment recommendations based on an individual’s financial goals and risk profile.