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What is Model Risk and Why Does it Matter?

DataRobot Blog

This provides a great amount of benefit, but it also exposes institutions to greater risk and consequent exposure to operational losses. The stakes in managing model risk are at an all-time high, but luckily automated machine learning provides an effective way to reduce these risks.

Risk 111
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How to Gain Greater Confidence in your Climate Risk Models

Cloudera

As part of these efforts, disclosure requirements will mandate that firms provide “the impact of a company’s activities on the environment and society, as well as the business and financial risks faced by a company due to its sustainability exposures.” What are the key climate risk measurements and impacts? They need to understand;

Risk 79
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Cloudera wins Risk Markets Technology Award for Data Management Product of the year

Cloudera

Financial services institutions need the ability to analyze and act on massive volumes of data from diverse sources in order to monitor, model, and manage risk across the enterprise. They need a comprehensive data and analytics platform to model risk exposures on-demand. Cloudera is that platform. End-to-end Data Lifecycle.

Risk 87
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AI for Human Capital Management

DataRobot Blog

For instance, in 2019, the Government Acquisition Office (GAO) researched and identified 35 high-risk hiring areas. The Office of Personnel Management (OPM) began tracking time-to-hire (T2H) requirements in 2008 and found that the average government hire took around 100 days. A variety of factors combine to create this situation.

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How to Follow New OECD Guidance on Transfer Pricing

Jet Global

Given this timeframe, the OECD has recently published a report with the aim of assisting transfer pricing teams on best practices to follow given the current climate. For both, the risks and costs associated with disputes are high. This is a key factor when considering and interpreting the content of the report.

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How Data Ethics Supports Governance & Monetisation

Alation

I recently led an online session, Data Monetisation and Governance , looking at the evolution of data governance , defining data ethics (from the Turing Institute ), and touching on the balancing act between using data to monetise (by increasing revenue, decreasing spend, or mitigating risk) and meeting ethical obligations. In Conclusion.

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Banking on mainframe-led digital transformation for financial services

IBM Big Data Hub

Why mainframe application modernization stalls We’ve experienced global economic uncertainties in recent memory, from the 2008 “too big to fail” crisis to our current post-pandemic high interest rates causing overexposure and insolvency of certain large depositor banks. Why did they fail to launch a new mobile app?