Remove Metrics Remove Reporting Remove Risk Management
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Data Scalability Raises Considerable Risk Management Concerns

Smart Data Collective

A report by China’s International Data Corporation showed that global data would rise to 175 Zettabyte by 2025. The Relationship between Big Data and Risk Management. While the sophisticated Internet of Things can positively impact your business, it also carries a significant risk of data misuse. Well, you aren’t alone!

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PODCAST: Making AI Real – Episode 2: AI enabled Risk Management for FS powered by BRIDGEi2i Watchtower

bridgei2i

Episode 2: AI enabled Risk Management for FS powered by BRIDGEi2i Watchtower. AI enabled Risk Management for FS powered by BRIDGEi2i Watchtower. Today the Chief Risk Officers(CROs) struggle with the critical task of monitoring and assessing key risks in real time and firefight to mitigate any critical issues that arise.

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Project Management Report: Structure, Examples & Free Templates

FineReport

What is Project Management Report? A project management report is a high-level overview of the current status of a project. Why is project management report critical? Depending on the project’s size and complexity, the project management reporting content and frequency may vary.

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5 tips for better business value from gen AI

CIO Business Intelligence

According to AI at Wartons report on navigating gen AIs early years, 72% of enterprises predict gen AI budget growth over the next 12 months but slower increases over the next two to five years. CIOs should return to basics, zero in on metrics that will improve through gen AI investments, and estimate targets and timeframes.

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Combine transactional, streaming, and third-party data on Amazon Redshift for financial services

AWS Big Data

The following are some of the key business use cases that highlight this need: Trade reporting – Since the global financial crisis of 2007–2008, regulators have increased their demands and scrutiny on regulatory reporting. You can run a direct query from QuickSight for BI reporting and dashboards.

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Managing risk in machine learning

O'Reilly on Data

There are also many important considerations that go beyond optimizing a statistical or quantitative metric. As we deploy more models, it’s becoming clear that we will need to think beyond optimizing statistical and business metrics. Real modeling begins once in production. Culture and organization.

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Why you should care about debugging machine learning models

O'Reilly on Data

In addition to newer innovations, the practice borrows from model risk management, traditional model diagnostics, and software testing. The study of security in ML is a growing field—and a growing problem, as we documented in a recent Future of Privacy Forum report. [8]. Currency amounts reported in Taiwan dollars.