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CIO Applications Weekly Brief

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Editor's Pick (1 - 4 of 8)
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Lies, Damn Lies, and Data Visualization

Lies, Damn Lies, and Data Visualization
Douglas Duncan, CIO, Columbia Insurance Group

Predictive Analytics in Healthcare: It's Not Happening

Predictive Analytics in Healthcare: It's Not Happening
Kirk Kirksey, VP & CIO, UT Southwestern Medical Center

Predictive Analytics Key Component of Customer Experience Management

Predictive Analytics Key Component of Customer Experience Management
Richard Barton, CIO, American Management Association

Predictive Analytics in Higher Education

Predictive Analytics in Higher Education
Linda Hartford, CIO, Northeast Wisconsin Technical College

Revitalizing Data Collection with Next- Gen Technology

Revitalizing Data Collection with Next- Gen Technology
Marci Augustine, Director, Business Intelligence & Analytics, Xo Group Inc.

The Numbers Game: Making Hospital Data User-Friendly

The Numbers Game: Making Hospital Data User-Friendly
William Feaster, M.D., VP, Chief Health Information Officer, Choc Children’s

Predictive Analytics in the Insurance Industry

Predictive Analytics in the Insurance Industry
Hongyuan Wang, PhD & MAS, Director of Predictive Analytics, Data and Analytics, Employers

Three Types of Analytics Used in Practice and Their Links

Three Types of Analytics Used in Practice and Their Links
Victor S.Y. Lo, PhD A.I. and Data Science Center of Excellence Leader, Workplace Investing, Fidelity Investments

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Why is Predictive Analytics the Cornerstone for Insurers?

By CIO Applications| Monday, November 16, 2020
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FREMONT, CA: The rising adoption level of predictive analytics-based tools and applications across the insurance industry results in a reduction of underwriting expenses and claim-processing duration. Predictive analytics help the insurers to fully utilize continuously generating customer data from multiple sources and standardize the operations of insurance businesses. In recent years, predictive analytics has become an essential part of the industry with a promise to let the industry professionals explore more innovative solutions to bring complete transparency and operational accuracy between insurers and customers.

• Identifying the Risk of Fraud

Predictive analytics holds the potential to minimize insurance forgery by effectively identifying and preventing potential fraud. Predictive analytics-based tools and applications allow the insurers to monitor their clients and customers across social media and help them detect signs of fraudulent behavior. Such abilities allow the insurers to investigate claims processes more accurate and save a huge amount from payments.

• Pricing and Risk Selection

Advanced data insights help the insurers understand customers’ intentions, like the potential to canceling or lowering the coverage. Here predictive analytics enables insurers to give personalized attention to different customers by analyzing their satisfaction with the coverage.

• Improvising Claims Processes

Predictive analytics helps insurers identify claims that become heavy losses unexpectedly. This feature can alert claims specialists in advance and let the insurance companies cut down outlier claims. By referring to previous cases and accurately analyzing claims data and provided documents, predictive analytics helps the insurance companies develop plans for managing similar claims in the future. The technology contributes to streamlining processes, allowing the insurers to run claim analyses based on historical data and informed decisions for high efficiency.

With numerous more benefits, predictive analytics promises to bring transformation across insurance businesses. The technology allows industry professionals to create strategic plans for effective operations and long-term business solutions.

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