Decision Management Solutions
NOVEMBER 13, 2018
80% of data and analytics leaders with global life insurance and property & casualty carriers surveyed by McKinsey reported that their analytics investments are not delivering high impact. Insurance companies, like other companies, want their analytics investments to be strategic – to have a strategic impact.
CIO Business Intelligence
JUNE 7, 2022
It can be used to reveal structures in data — insurance firms might use cluster analysis to investigate why certain locations are associated with particular insurance claims, for instance. It is often used to understand how customers feel about a brand, product, or service. Data analytics vs. business analytics.
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John Wheeler
OCTOBER 20, 2020
banking, insurance and securities) measure risk on a quantitative basis. Other quantitative analysis methods are used to develop more precise predictive models to determine the potential for digital risk events, such as product/service liability, fraud or theft.
O'Reilly on Data
MAY 18, 2020
All predictive models are wrong at times?—just As the renowned statistician George Box once quipped , “All models are wrong, but some are useful.” If, however, the impact of this type of failure was diminished–by, for example, the model being used as one of several overlapping diagnostic tools–materiality would decrease.
Cloudera
SEPTEMBER 7, 2023
But these measures alone may not be sufficient to protect proprietary information. The Danger of Black-Box AI Solutions We believe the best, most pragmatic solution for AI in financial services and insurance is what we call–“Trusted AI.”
AWS Big Data
MARCH 7, 2023
It covers how to use a conceptual, logical architecture for some of the most popular gaming industry use cases like event analysis, in-game purchase recommendations, measuring player satisfaction, telemetry data analysis, and more.
FineReport
APRIL 9, 2024
Furthermore, maintaining data security and compliance requires continuous vigilance and proactive measures to safeguard against potential vulnerabilities. The integration of clinical data analysis tools empowers healthcare providers to leverage predictive analytics for proactive decision-making.
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