Insurance Measurement Prescriptive Analytics Risk 
CIO Business Intelligence
JUNE 7, 2022
More specifically: Descriptive analytics uses historical and current data from multiple sources to describe the present state, or a specified historical state, by identifying trends and patterns. Predictive analytics is often considered a type of “advanced analytics,” and frequently depends on machine learning and/or deep learning.
Birst BI
OCTOBER 30, 2018
Every day, these companies pose questions such as: Will this new client provide a good return on investment, relative to the potential risk? Is this existing client a termination risk? A well-designed credit scoring algorithm will properly predict both the low- and high-risk customers. Will this next trade return a profit?
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Domino Data Lab
JUNE 2, 2019
Trying to dissect a model to divine an interpretation of its results is a good way to throw away much of the crucial information – especially about non-automated inputs and decisions going into our workflows – that will be required to mitigate existential risk. Measure how these decisions vary across your population.
Andrew White
JANUARY 11, 2021
As such banking, finance, insurance and media are good examples of information-based industries compared to manufacturing, retail, and so on. Some data is more a risk than valuable. What are you seeing as the differences between a Chief Analytics Officer and the Chief Data Officer? GI-GO of course we all know. Governance.
Alation
AUGUST 26, 2021
Privacy, Risk and Compliance. Augmented Analytics. DI empowers analysts to apply augmented analytics to applications, supporting predictive and prescriptive analytics use cases. Similarly, retailers and other less regulated industries are boosting defensive measures to ensure compliance with GDPR and CCPA.
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