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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;

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Driving 15 years of IT transformation in 5

CIO Business Intelligence

Through this strategy, Lovelady and his team have struck the often difficult to balance attributes of business unit flexibility with enterprise scale. “At These include network management, help desk, establishing and enforcing policies related to information security and risk management, and several other IT functions.

IT 111
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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. Apart from generating regulatory reports, these teams require visibility into the health of the reporting systems.

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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?

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Can Machine Learning Address Risk Parity Concerns?

Smart Data Collective

One of the most important changes pertains to risk parity management. We are going to provide some insights on the benefits of using machine learning for risk parity analysis. However, before we get started, we will provide an overview of the concept of risk parity. What is risk parity? What is risk parity?

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Managing machine learning in the enterprise: Lessons from banking and health care

O'Reilly on Data

A look at how guidelines from regulated industries can help shape your ML strategy. After the 2008 financial crisis, the Federal Reserve issued a new set of guidelines governing models— SR 11-7 : Guidance on Model Risk Management. Note that the emphasis of SR 11-7 is on risk management.).