Celina Insurance’s Predictive Analytics Initiative: The Machine Learning Factor

by Nicolas Michellod, September 17, 2014
Case Studies
North America

Abstract

Predictive analytics is an investment insurers need to consider going forward, and we think insurance-based machine learning represents a key factor they need to take into consideration when evaluating vendors.

In the report, Celina Insurance’s Predictive Analytics Initiative: The Machine Learning Factor, Celent details how Celina Insurance, a US mutual insurance company, came to the decision to invest in a modern predictive analytics solution, and why machine learning has been a crucial factor driving its decision.

Machine learning is a technique that leverages algorithms that learn how to improve a model through experiences in performing data observations without human intervention. Automation is key to machine learning because the objective is to define algorithms that are able to learn without human assistance. For instance a machine learning algorithm will be able to learn which data sources would add value in a model or determine the impact of a variable on the result of a calculation.

“New techniques and emerging technologies enable business innovation or at least improvements in insurance,” says Nicolas Michellod, Senior Analyst in the Celent insurance practice and author of the report. “Celina Insurance’s curiosity and interest in what’s new on the market allowed them to identify how machine learning could add value to their business.”

After a short introduction of Celina Insurance Group, this report describes how the mutual enterprise has identified and prioritized predictive analytics business applications and communicated the potential value that can be derived from such a tool internally. The report also describes the process used by Celina Insurance to select a predictive analytics vendor and explain why and how machine learning has been a key factor influencing Celina Insurance decision.

Celent is a research and advisory firm dedicated to helping financial institutions formulate comprehensive business and technology strategies. Celent publishes reports identifying trends and best practices in financial services technology and conducts consulting engagements for financial institutions looking to use technology to enhance existing business processes or launch new business strategies. With a team of internationally based analysts, Celent is uniquely positioned to offer strategic advice and market insights on a global basis. Celent is a member of the Oliver Wyman Group, which is a wholly-owned operating unit of Marsh & McLennan Companies [NYSE: MMC].

Media Contacts

North America
Michele Pace
mpace@celent.com
Tel: +1 212 345 1366

Europe (London)
Chris Williams
cwilliams@celent.com
Tel: +44 (0)782 448 3336

Asia (Tokyo)
Yumi Nagaoka
ynagaoka@celent.com
Tel.: +81 3 3500 3023

Table of Contents

Executive Summary

1

Introducing the Celina Insurance Group

2

 

Snapshot

2

 

Recent Performance

3

 

Investing in Predictive Analytics

3

Identifying the Need for Predictive Analytics

5

 

Comparison with Peers

5

 

Giving Project Stakeholders a Sense of the Importance of Predictive Analytics in Insurance

5

 

Prioritizing Business Applications

6

Predictive Analytics Vendor Selection

8

 

Vendor Assessment Framework

8

 

Proof of Concept and Demonstration Phase

9

 

Challenging Vendor Offerings with Existing Capabilities

9

 

Final Decision

10

Machine Learning Applied to Insurance

11

 

What Is Machine Learning?

11

 

What Value Does Machine Learning Bring to Celina Insurance?

12

Lessons Learned

16

 

Lessons Learned by Celina Insurance

16

 

Celent Considerations

16

Leveraging Celent’s Expertise

18

 

Support for Financial Institutions

18

 

Support for Vendors

18

Related Celent Research

19

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