Measurement Risk Management Software 
CIO Business Intelligence
DECEMBER 18, 2024
This year saw emerging risks posed by AI , disastrous outages like the CrowdStrike incident , and surmounting software supply chain frailties , as well as the risk of cyberattacks and quantum computing breaking todays most advanced encryption algorithms. Furthermore, the software supply chain is also under increasing threat.
CIO Business Intelligence
DECEMBER 10, 2024
Set clear, measurable metrics around what you want to improve with generative AI, including the pain points and the opportunities, says Shaown Nandi, director of technology at AWS. In HR, measure time-to-hire and candidate quality to ensure AI-driven recruitment aligns with business goals.
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O'Reilly on Data
JULY 15, 2019
After the 2008 financial crisis, the Federal Reserve issued a new set of guidelines governing models— SR 11-7 : Guidance on Model Risk Management. Note that the emphasis of SR 11-7 is on risk management.). Sources of model risk. Model risk management. AI projects in financial services and health care.
O'Reilly on Data
MAY 18, 2020
Before we get into the details of AI incident response, it’s worth raising these baseline questions: What makes AI different from traditional software systems? The answers boil down to three major reasons, which may also exist in other large software systems but are exacerbated in AI. All predictive models are wrong at times?—just
CIO Business Intelligence
FEBRUARY 21, 2025
Birmingham City Councils (BCC) troubled enterprise resource planning (ERP) system, built on Oracle software, has become a case study of how large-scale IT projects can go awry. There are multiple reports including one from a manager at BCC highlighting the discrepancies at the Council, way back in June 2023.
O'Reilly on Data
NOVEMBER 13, 2018
The main bottleneck here is speed: many researchers are actively investigating hardware and software tools that can speed up model inference (and perhaps even model building) on encrypted data. Classification parity means that one or more of the standard performance measures (e.g., What machine learning means for software development”.
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.
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