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Optimizing Risk and Exposure Management – Roundtable Highlights

Cloudera

We recently hosted a roundtable focused on o ptimizing risk and exposure management with data insights. For financial institutions and insurers, risk and exposure management has always been a fundamental tenet of the business. Now, risk management has become exponentially complicated in multiple dimensions. .

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Generative AI: 5 enterprise predictions for AI and security — for 2023, 2024, and beyond

CIO Business Intelligence

From IT, to finance, marketing, engineering, and more, AI advances are causing enterprises to re-evaluate their traditional approaches to unlock the transformative potential of AI. What can enterprises learn from these trends, and what future enterprise developments can we expect around generative AI?

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Generative AI use cases for the enterprise

IBM Big Data Hub

Demystifying generative AI At the heart of Generative AI lie massive databases of texts, images, code and other data types. This data is fed into generational models, and there are a few to choose from, each developed to excel at a specific task. Imagine each data point as a glowing orb placed on a vast, multi-dimensional landscape.

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ANZ Bank’s Advances Data-Driven Analytics With Cloudera

Cloudera

Data and analytics are the essential engines in this strategy which entails upgrading the bank’s core banking technology to deliver reliable, efficient, and secure services for their customers while safeguarding critical data. The approach offered lower risks and allowed for comprehensive platform and application testing.

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Building Tax Planning into Enterprise Risk Management Strategies

Jet Global

Tax planning is playing an increasingly important part in corporates’ enterprise resource management (ERM) strategies, driven by the many uncertainties created by political, economic, and pandemic-related trends. Take Responsibility for Risk Oversight. Take Responsibility for Risk Oversight.

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12 most popular AI use cases in the enterprise today

CIO Business Intelligence

Organizations all around the globe are implementing AI in a variety of ways to streamline processes, optimize costs, prevent human error, assist customers, manage IT systems, and alleviate repetitive tasks, among other uses. And with the rise of generative AI, artificial intelligence use cases in the enterprise will only expand.

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Know before you go: 6 lessons for enterprise GenAI adoption

CIO Business Intelligence

That quote aptly describes what Dell Technologies and Intel are doing to help our enterprise customers quickly, effectively, and securely deploy generative AI and large language models (LLMs).Many Knowing these lessons before generative AI adoption will likely save time, improve outcomes, and reduce risks and potential costs.