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Optimizing Risk and Exposure Management – Roundtable Highlights

Cloudera

We recently hosted a roundtable focused on o ptimizing risk and exposure management with data insights. For financial institutions and insurers, risk and exposure management has always been a fundamental tenet of the business. Now, risk management has become exponentially complicated in multiple dimensions. .

Risk 102
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Ways in Which AI can Improve Enterprise Risk Management

bridgei2i

In dynamic markets, enterprises need to keep looking for ways to gain an edge over competitors to retain their position and stride forward to the top place. However, risk management is no way lagging. ERM or Enterprise Risk Management is being used to identify crises long before it blows up into a huge problem.

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Cloudera wins Risk Markets Technology Award for Data Management Product of the year

Cloudera

Financial services institutions need the ability to analyze and act on massive volumes of data from diverse sources in order to monitor, model, and manage risk across the enterprise. They need a comprehensive data and analytics platform to model risk exposures on-demand. Cloudera is that platform. End-to-end Data Lifecycle.

Risk 90
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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. IRM technology product leaders will need to develop IRM capabilities that are capable of addressing the IRM market insights outlined in this blog post. Key Findings.

Marketing 110
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Bringing Financial Services Business Use Cases to Life: Leveraging Data Analytics, ML/AI, and Gen AI

Cloudera

In this context, Cloudera and TAI Solutions have partnered to help financial services customers accelerate their data-driven transformation, improve customer centricity, ensure compliance with regulations, enhance risk management, and drive innovation. Regulation and risk are a big focus for financial institutions.

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Optimizing PCI compliance in financial institutions

CIO Business Intelligence

That, in turn, reduces IT cost, the time it takes staff to learn the environment, and the time to market. All other needs, for example, authentication, encryption, log management, system configuration, would be treated the same—by using the architectural patterns available.

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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 ML in many real-world contexts, optimizing statistical or business metics alone will not suffice. Data collection and data markets in the age of privacy and machine learning”. Culture and organization.