skip to main content
Close Icon We use cookies to improve your website experience.  To learn about our use of cookies and how you can manage your cookie settings, please see our Cookie Policy.  By continuing to use the website, you consent to our use of cookies.
Global Search Configuration

Introduction

This report provides a snapshot of machine learning adoption in the global insurance sector. It also examines the key investment priorities and use case for machine learning over the next 24 months.

Highlights

  • Overall, 12% of insurers are currently deploying ML within their organization compared to 17% across all industries. Wider adoption of ML by insurers is being hindered by regulatory issues.

Features and Benefits

  • Allows insurers to benchmark their machine learning strategy against their peers.
  • Analyzes trends in machine learning spending in the insurance industry.

Key questions answered

  • What are the key machine learning investment priorities for the insurance sector?
  • What are the key challenges of machine learning adoption within the insurance sector?

Table of contents

Summary

  • Catalyst
  • Ovum view
  • Key messages

Recommendations

  • Recommendations for insurers
  • Recommendations for vendors targeting the insurance sector

Insurers lag other verticals in the deployment of ML but are addressing the gap

  • Some insurance sectors currently lag many verticals in their deployment of ML
  • Regulation and data architectures are limiting ML adoption in the insurance industry
  • Accelerating the use of ML is a key priority for insurers

Fraud and digital channels are the most important use cases for machine learning in insurance

  • Improving loss ratios is the immediate use case for ML
  • ML is a critical element of insurers becoming fully "digital"

Insurers will use a range of machine learning technologies to deliver digital transformation

  • ML is being used to exploit the value of existing data across all insurance sectors
  • NLP and chatbots projects are a priority for the non-life sector
  • Life insurers are adopting intelligent RPA to streamline complex processes
  • Image recognition and analysis will become an important component of insurance

Appendix

  • Methodology
  • Further reading
  • Author

Recommended Articles

;

Have any questions? Speak to a Specialist

Europe, Middle East & Africa team: +44 7771 980316


Asia-Pacific team: +61 (0)3 960 16700

US team: +1 212-652-5335

Email us at ClientServices@ovum.com

You can also contact your named/allocated Client Services Executive using their direct dial.
PR enquiries - Email us at pr@ovum.com

Contact marketing - 
marketingdepartment@ovum.com

Already an Ovum client? Login to the Knowledge Center now