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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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CIOs weigh where to place AI bets — and how to de-risk them

CIO Business Intelligence

Amid the turbulence of AI, technologies are emerging rapidly, startups are clamoring for attention, and hyperscalers are scrambling to corral market share. There are a lot of risks and a lot of land mines to navigate,” says the analyst. It’s an environment that taxes the decision-making skills of the even the most savvy CIOs.

Risk 133
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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. Data collection and data markets in the age of privacy and machine learning”.

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

AWS Big Data

Additionally, they need streaming architectures to handle growing trade volumes, market volatility, and regulatory demands. We also used FactSet’s market data solutions for historical and streaming market quotes and trades.

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How to Gain Greater Confidence in your Climate Risk Models

Cloudera

As governments gather to push forward climate and renewable energy initiatives aligned with the Paris Agreement and the UN Framework Convention on Climate Change, financial institutions and asset managers will monitor the event with keen interest. What are the key climate risk measurements and impacts? They need to understand; .

Risk 79
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Automating Model Risk Compliance: Model Monitoring

DataRobot Blog

If the assumptions are being breached due to fundamental changes in the process being modeled, the deployed system is not likely to serve its intended purpose, thereby creating further model risk that the institution must manage. Monitoring Model Metrics. Figure 1: Data drift tab of a deployed DataRobot model.

Risk 59
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IBM’s watsonx.governance takes aim at AI auditing

CIO Business Intelligence

It focuses on three core areas of documentation: compliance, risk management, and model lifecycle management — processes IBM says are intertwined. Post risk analysis, the enterprise then compares models to see which model best suits the use case at hand, Gentile said. per resource unit.

Risk 120