Demystifying Artificial Intelligence in Insurance: The Tools Supporting Data Science and the Rise of DataOps

Create a vendor selection project & run comparison reports
Click to express your interest in this report
Indication of coverage against your requirements
A subscription is required to activate this feature. Contact us for more info.
Celent have reviewed this profile and believe it to be accurate.
4 July 2018
Craig Beattie, Nicolas Michellod, and Zao Wu

Artificial Intelligence is of increasing importance in insurance and insurers are hiring for or creating Data Scientist position to leverage this opportunity. The route to creating AI applications relies on Data Science.

Key research questions

  • What is the data science pipeline, and why is it important for an AI strategy?
  • What is DataOps and what benefits does it bring?
  • How can the insurance industry reap the full benefits of Data Science?


Note: A webinar that draws on this presentation is available here.

In this report, we discuss the Data Science workflow, from gathering requirements for the activity through to deploying the output and monitoring it. This workflow is amenable to automation, a topic increasingly referred to as DataOps. DataOps is a sibling of DevOps for Data Science, which aims to allow more effective industrialisation of Data Science in practice, through:

  • Improved repeatability of findings
  • Reduced time to identifying actionable insights
  • Decreased time to impact

Subscription required

Access to this content requires a Celent research subscription.

Subscribers should sign in to access this research.

If you are not a subscriber, register now or contact us to find out more about our subscription options.

sign in or sign up to read more

Insight details

Life & Health Insurance, Property & Casualty Insurance
Subscription(s) required to access this Insight:
Insurance, >>Life/Annuities Insurance, >>Property / Casualty Insurance
Insight Format
Geographic Focus
Asia-Pacific, EMEA, LATAM, North America