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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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Automating Model Risk Compliance: Model Validation

DataRobot Blog

To start with, SR 11-7 lays out the criticality of model validation in an effective model risk management practice: Model validation is the set of processes and activities intended to verify that models are performing as expected, in line with their design objectives and business uses.

Risk 52
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PODCAST: Exploring Data, Digital and Artificial Intelligence through a Holistic Lens

bridgei2i

A Masters in Quantitative Economics from the Indian Statistical Institute (ISI), Calcutta, Prithvijit founded BRIDGEi2i in May 2011. Pritam Kanti Paul, CTO and Co-Founder of BRIDGEi2i Analytics, is a Gold Medalist in his batch of Masters in Statistics at the Indian Statistical Institute Calcutta.

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4 Key Elements of Enterprise AI Strategy

bridgei2i

A Masters in Quantitative Economics from the Indian Statistical Institute (ISI), Calcutta, Prithvijit founded BRIDGEi2i in May 2011. Pritam Kanti Paul, CTO and Co-Founder of BRIDGEi2i Analytics, is a Gold Medalist in his batch of Masters in Statistics at the Indian Statistical Institute Calcutta.

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What Are the Most Important Steps to Protect Your Organization’s Data?

Smart Data Collective

Based on figures from Statista , the volume of data breaches increased from 2005 to 2008, then dropped in 2009 and rose again in 2010 until it dropped again in 2011. They can use AI and data-driven cybersecurity technology to address these risks. The instances of data breaches in the United States are rather interesting. In summary.

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PODCAST: COVID19 | Redefining Digital Enterprises – Episode 6: The Impact of COVID-19 on Supply Chain Management

bridgei2i

It is even more essential now that supply chains are empowered with a high standard of data and analytics sophistication to be able to cost-effectively serve the company’s purpose and combat risks at the same time. You know, Chief Risk Officers, for example, will no longer be confined to the credit industry. Anushruti: Perfect.

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Our quest for robust time series forecasting at scale

The Unofficial Google Data Science Blog

In the first plot, the raw weekly actuals (in red) are adjusted for a level change in September 2011 and an anomalous spike near October 2012. Such a model risks conflating important aspects, notably the growth trend, with other less critical aspects.