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What is Model Risk and Why Does it Matter?

DataRobot Blog

With the big data revolution of recent years, predictive models are being rapidly integrated into more and more business processes. This provides a great amount of benefit, but it also exposes institutions to greater risk and consequent exposure to operational losses. Model Validation – Prior to the use of a model (i.e.,

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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

Banks have the most to gain if they succeed (and the most to lose if they fail) at bringing their mainframe application and data estates up to modern standards of cloud-like flexibility, agility and innovation to meet customer demand.

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Emerging Trends: 4 IRM Market Insights to Aid COVID-19 Business Recovery

John Wheeler

Integrated risk management (IRM) technology is uniquely suited to address the myriad of risks arising from the current crisis and future COVID-19 recovery. Provide a full view of business operations by delivering forward-looking measures of related risk to help customers successfully navigate the COVID-19 recovery.

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FRTB: Will 2023 Finally be the Year?

Cloudera

The Fundamental Review of the Trading Book (FRTB), introduced by the Basel Committee on Banking Supervision (BCBS), will transform how banks measure risk. FRTB is designed to address some fundamental weaknesses that did not get addressed in the post-2008 financial crisis regulatory reforms.

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