DataRobot Blog
APRIL 29, 2022
The stakes in managing model risk are at an all-time high, but luckily automated machine learning provides an effective way to reduce these risks. However, after the financial crisis, financial regulators around the world stepped up to the challenge of reigning in model risk across the financial industry.
Smart Data Collective
MAY 4, 2023
However, the Identity Theft Resource Center reports a 68% increase in data breaches at corporations in 2021, surpassing the previous record rise of 23% in 2017. As a result, third-party risk management (TPRM) has become a crucial aspect of enterprise risk management.
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IBM Big Data Hub
FEBRUARY 8, 2024
However, it wasn’t until the 1990s that ESG considerations started to appear in mainstream investment strategies. 1 Slowly but surely, institutional investors started to recognize that companies could potentially improve financial performance and risk management by focusing on ESG issues like greenhouse gas emissions.
John Wheeler
JULY 15, 2019
Gartner kicked-off it’s global series of 2019 Security & Risk Management Summit Conferences last month in Washington, DC. It’s here where we receive direct feedback from both technology providers as well as end-users on emerging trends and technologies for security and risk management.
IBM Big Data Hub
AUGUST 1, 2023
Delivering high levels of resiliency It’s essential for clients to be able to securely manage mission-critical workloads and enable business continuity as they implement strategies to reduce risk and keep pace with market demands.
CIO Business Intelligence
DECEMBER 19, 2022
We’ve already seen what happened when HPE bought hyperconverged infrastructure vendor SimpliVity back in January 2017. If not, then you immediately have to start figuring out your exit strategy,” says Tony Harvey, a senior director and analyst at Gartner who advises on vendor selection. If that’s true, then you’re in a better position.
O'Reilly on Data
JANUARY 22, 2019
Whether financial models are based on academic theories or empirical data mining strategies, they are all subject to the trinity of modeling errors explained below. All financial models, whether based on academic theories or data mining strategies, are at the mercy of the trinity of modeling errors. Nobels For Nonsense , by J.R.
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