CIO Business Intelligence
NOVEMBER 21, 2023
After all, 41% of employees acquire, modify, or create technology outside of IT’s visibility , and 52% of respondents to EY’s Global Third-Party Risk Management Survey had an outage — and 38% reported a data breach — caused by third parties over the past two years.
O'Reilly on Data
MAY 18, 2020
Materiality is a widely used concept in the world of model risk management , a regulatory field that governs how financial institutions document, test, and monitor the models they deploy. NIST’s Computer Security Incident Handling Guide which, while not tailored to the risks of AI specifically, provides one good starting point.
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CIO Business Intelligence
OCTOBER 4, 2023
At the lowest layer is the infrastructure, made up of databases and data lakes. These applications live on innumerable servers, yet some technology is hosted in the public cloud. User data is also housed in this layer, including profile, behavior, transactions, and risk.
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. 8] Data about individuals can be decoded from ML models long after they’ve trained on that data (through what’s known as inversion or extraction attacks, for example).
datapine
MARCH 31, 2022
On the flip side, if you enjoy diving deep into the technical side of things, with the right mix of skills for business intelligence you can work a host of incredibly interesting problems that will keep you in flow for hours on end. A background in (or a firm grasp of) data warehousing and mining. BI Data Scientist.
Domino Data Lab
APRIL 3, 2019
The top three items are essentially “the devil you know” for firms which want to invest in data science: data platform, integration, data prep. Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. Rinse, lather, repeat.
bridgei2i
APRIL 23, 2020
How much will the bank’s bottom line be impacted depends on a host of unknowns. One of the specific AI use case in FS has been Fraud Management, which triggers alerts when seemingly contradictory spending patterns are observed. BRIDGEi2i implemented a fraud-monitoring-and-prevention solution for a leading US bank. Learn MORE. “We
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