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Applied Insurance Analytics: A Framework for Driving More Value from Data Assets, Technologies, and Tools Hardcover - 2014 - 1st Edition
by Patricia Saporito
From the rear cover
Most insurers fail to fully exploit their greatest asset: data. Why? Because their use of analytics is largely limited to stovepiped operational areas such as underwriting, claims, marketing, or risk management. To unleash the value buried in your data, you need an analytics strategy that is enterprise-wide, business driven, and performance-focused.
In this book, industry thought leader Patricia L. Saporito explains why such a strategy is so important-and how to plan, implement, and profit from yours. Drawing on 25+ years of insurance experience, she presents a complete framework for customizing an analytics strategy based on your business model, capabilities, and goals. Saporito reviews common analytic applications by functional area, offering specific use cases and examples and helping you build on the analytics you're already doing. She presents insurance-specific data and governance models for effectively organizing and integrating your data, ensuring its quality and privacy and maximizing the value it creates. Finally, she provides tools and frameworks for improving the "analytic IQ" of your entire organization, from business users to IT developers.- Crafting your optimal analytics strategy and execution framework
Defining needs, prioritizing initiatives, and organizing for success
- Deepening skills, transforming culture
Building the truly analytics-driven, performance-based organization
- Selecting and applying insurance-specific analytics metrics
Making the most of KPIs, leading indicators, and correlation metrics
- Choosing the right tools for the right jobs
Selecting tools for reporting, visualizing, and predicting
THE INSURER'S BEST-PRACTICE GUIDE TO DRIVING BUSINESS VALUE FROM ANALYTICS "Finally... a data analytics roadmap for insurance industry decision makers-not just research, but applied research to our industry."
-John A. Cherba, Past President, Society of Insurance Research "As we move into a time with big data and cognitive computing, we are very fortunate as an industry to have thought leadership that brings front and center-as Pat has discussed in her book-topics that we must incorporate and look to as points of reference and, most importantly, lessons learned. Great reference materials and perspectives!"
-Cindy Maike, Associate Partner, Insurance, Global Business Services, IBM "In her book, Pat connects the dots between business challenges and analytics capabilities in the insurance industry and provides a roadmap on how to optimize analytics in practice."
- Dwight McNeill, Professor and Author of A Framework for Applying Analytics in Healthcare: What Can Be Learned from the Best Practices in Retail, Banking, Politics, and Sports Today, many insurers radically underutilize their data, leaving them vulnerable to traditional and non-traditional competitors alike. In Applied Insurance Analytics, industry thought leader Patricia L. Saporito helps you change that by leveraging analytics to improve business performance and customer satisfaction throughout your business. Saporito shows how to use analytics to systematically improve operations ranging from underwriting and risk management to claims. Through use cases, case studies, tools, and templates, you'll learn how to assess where you stand, choose new applications that offer the greatest value, gain more value from existing investments, and master best practices from throughout the industry and beyond.
Details
- Title Applied Insurance Analytics: A Framework for Driving More Value from Data Assets, Technologies, and Tools
- Author Patricia Saporito
- Binding Hardcover
- Edition number 1st
- Edition 1
- Pages 208
- Volumes 1
- Language ENG
- Publisher Pearson FT Press, Upper Saddle River, NJ, U.S.A.
- Date 2014-07
- Illustrated Yes
- Features Bibliography, Dust Cover, Glossary, Illustrated, Index, Price on Product - Canadian, Table of Contents
- ISBN 9780133760361 / 0133760367
- Weight 0.95 lbs (0.43 kg)
- Dimensions 9.44 x 6.01 x 0.51 in (23.98 x 15.27 x 1.30 cm)
- Library of Congress Catalog Number 2014937548
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