CIO Business Intelligence
JANUARY 11, 2024
CIOs are under increasing pressure to deliver AI across their enterprises – a new reality that, despite the hype, requires pragmatic approaches to testing, deploying, and managing the technologies responsibly to help their organizations work faster and smarter. The top brass is paying close attention.
CIO Business Intelligence
MARCH 18, 2024
Like Gudipati and Nafde, Menon and her team are planning to use hyperscalers as a relatively low-risk option. Though a multicloud environment, the agency has most of its cloud implementations hosted on Microsoft Azure, with some on AWS and some on ServiceNow’s 311 citizen information platform.
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Cloudera
OCTOBER 20, 2021
Understanding a firm’s exposure to climate risk begins with creating scenarios and gaining better visibility to the impact of a variety of variables on the book of business. Stress testing was heavily scrutinized in the post 2008 financial crisis. The climate risk model makes robust scenarios possible. Assess Variables.
IBM Big Data Hub
AUGUST 18, 2023
The Digital Operational Resilience Act , or DORA, is a European Union (EU) regulation that created a binding, comprehensive information and communication technology (ICT) risk-management framework for the EU financial sector. It offers more control and flexibility for comprehensive testing and validation.
CIO Business Intelligence
MARCH 13, 2024
We did side-by-side testing,” he says. In testing, gen AI was also particularly good at generating test cases and creating dummy data for testing. We got 600 people together to test gen AI in a sandbox to try different use cases in 54 different categories.” It’s not about reducing headcount, he adds.
O'Reilly on Data
DECEMBER 12, 2019
In addition to newer innovations, the practice borrows from model risk management, traditional model diagnostics, and software testing. While our analysis of each method may appear technical, we believe that understanding the tools available, and how to use them, is critical for all risk management teams.
O'Reilly on Data
MAY 18, 2020
If our model generates false negative predictions for tumor detection, organizations could combine automated imaging results with activities like follow up radiologist reviews or blood tests to catch any potentially incorrect predictions—and even improve the accuracy of the combined human and machine efforts. How Material Is the Threat?
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