Insurance Predictive Modeling Risk Testing 
DataRobot Blog
APRIL 29, 2022
With the big data revolution of recent years, predictive models are being rapidly integrated into more and more business processes. This provides a great amount of benefit, but it also exposes institutions to greater risk and consequent exposure to operational losses.
O'Reilly on Data
MAY 18, 2020
This article answers these questions, based on our combined experience as both a lawyer and a data scientist responding to cybersecurity incidents, crafting legal frameworks to manage the risks of AI, and building sophisticated interpretable models to mitigate risk. All predictive models are wrong at times?—just
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CIO Business Intelligence
JUNE 7, 2022
Predictive analytics is often considered a type of “advanced analytics,” and frequently depends on machine learning and/or deep learning. Prescriptive analytics is a type of advanced analytics that involves the application of testing and other techniques to recommend specific solutions that will deliver desired outcomes.
IBM Big Data Hub
FEBRUARY 14, 2024
Automotive With applications of AI, automotive manufacturers are able to more effectively predict and adjust production to respond to changes in supply and demand. They can streamline workflows to increase efficiency and reduce time-consuming tasks and the risk of error in production, support, procurement and other areas.
Domino Data Lab
JULY 28, 2021
There are many software packages that allow anyone to build a predictive model, but without expertise in math and statistics, a practitioner runs the risk of creating a faulty, unethical, and even possibly illegal data science application. All models are not made equal.
Cloudera
SEPTEMBER 7, 2023
With AI, financial institutions and insurance companies now have the ability to automate or augment complex decision-making processes, deliver highly personalized client experiences, create individualized customer education materials, and match the appropriate financial and investment products to each customer’s needs.
Birst BI
OCTOBER 30, 2018
A personal crystal ball that predicts your days ahead is what financial services firms everywhere want. 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? Will this next trade return a profit?
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