Remove Finance Remove Measurement Remove Risk Management
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Managing machine learning in the enterprise: Lessons from banking and health care

O'Reilly on Data

In our experience, many of the most popular conference talks on model explainability and interpretability are those given by speakers from finance. After the 2008 financial crisis, the Federal Reserve issued a new set of guidelines governing models— SR 11-7 : Guidance on Model Risk Management. Sources of model risk.

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The 10 most in-demand IT jobs in finance

CIO Business Intelligence

But financial services companies need skilled IT professionals to help manage the integration of new and emerging technology, while modernizing legacy finance tech. As demand for tech skills grows in the finance industry, certain IT jobs are becoming more sought-after than others. Back-end software engineer. Data engineer.

Finance 98
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The 10 most in-demand IT jobs in finance

CIO Business Intelligence

But financial services companies need skilled IT professionals to help manage the integration of new and emerging technology, while modernizing legacy finance tech. As demand for tech skills grows in the finance industry, certain IT jobs are becoming more sought-after than others. Back-end software engineer. Data engineer.

Finance 98
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New Regulatory Requirements Will Help Shape Cybersecurity for Finance

CIO Business Intelligence

Policy makers around the world have been recognizing this heightened risk, which has been further amplified by the recent geopolitical tensions. The European Union (EU) has pulled together a proposal for a unified framework to regulate risk management for financial institutions.

Finance 98
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Making an AI Investment: How Finance Institutions are Harnessing the Power of AI and Generative AI

Cloudera

Traditional machine learning (ML) models enhance risk management, credit scoring, anti-money laundering efforts and process automation. Some of the biggest and well-known financial institutions are already realizing value from AI and GenAI: JPMorgan Chase uses AI for personalized virtual assistants and ML models for risk management.

Finance 77
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CDOs: Your AI is smart, but your ESG is dumb. Here’s how to fix it

CIO Business Intelligence

Most data management conferences and forums focus on AI, governance and security, with little emphasis on ESG-related data strategies. If sustainability-related data projects fail to demonstrate a clear financial impact, they risk being deprioritized in favor of more immediate business concerns.

IT 59
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What Is Model Risk Management and How is it Supported by Enterprise MLOps?

Domino Data Lab

Model Risk Management is about reducing bad consequences of decisions caused by trusting incorrect or misused model outputs. Systematically enabling model development and production deployment at scale entails use of an Enterprise MLOps platform, which addresses the full lifecycle including Model Risk Management.