Remove Insurance Remove Measurement Remove Metrics Remove Predictive Modeling
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80% of insurance carriers aren’t delivering high impact analytics. Here’s how you can do better.

Decision Management Solutions

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.

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How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

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. You can collect metrics and events and analyze them for operational efficiency.

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Seven Steps to Success for Predictive Analytics in Financial Services

Birst BI

Descriptive analytics techniques are often used to summarize important business metrics such as account balance growth, average claim amount and year-over-year trade volumes. The credit scores generated by the predictive model are then used to approve or deny credit cards or loans to customers. Accounts in use.

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The Impact of Healthcare BI Tools on Decision-Making and Patient Care

FineReport

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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CIO 100 Award winners prove the transformative value of IT

CIO Business Intelligence

In increasingly politicized times, easily performing RLAs can provide a measure of confidence to the interested voter that elections are being run properly.” And it yields multiple business metric improvements, such as limiting surplus inventory. The project also ensures technicians’ comfort and safety as they service customers.

IT 98
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Explaining black-box models using attribute importance, PDPs, and LIME

Domino Data Lab

Intrinsic methods – this technique is based on ANNs that have been designed to output an explanation alongside the standard prediction. Because of its architecture, intrinsically explainable ANNs can be optimised not just on its prediction performance, but also on its explainability metric. See Wei et al.

Modeling 139