AI in Insurance Use Cases & Benefits

Use Cases & Projects Rose Wijnberg

When it comes to the use of AI in insurance, a Dataiku-sponsored survey of executives revealed that insurers still have room to grow — only 7% of insurance companies surveyed are considered leaders.  This despite the fact that AI applications in insurance and the benefits of AI in insurance are many, and the industry already has a long history of leveraging data via actuarial science to assess risk. What gives?

→ AI in Insurance: Top Use Cases, Challenges, and Trends

AI & Us, the new web series from Dataiku, looks at how AI is changing our everyday lives. The most recent episode, which you can watch below, explores how AI cuts through complexity and impacts customers in insurance. In the episode, representatives from Zurich Insurance delve into top insurance AI use cases and, in particular, the benefits of AI in insurance for process efficiency.


“The term ‘AI’ seems to have a negative connotation sometimes. You know, computers are generating their own rules and doing their own thing. But in reality, it’s a tool.”

 — Phil Knowles, Group Audit @ Zurich Insurance

AI in Insurance Use Cases

According to Phil Knowles, Group Audit at Zurich Insurance, AI can be deployed in any of the insurance processes, including product design, underwriting, pricing, claims handling, claims management, and more. One of the unique benefits of AI in insurance is that the industry in particular has massive amounts of data, more than any human brain could process. So AI can not only bring new insights, but it can also help cut through complexity and yield massive efficiencies (both huge wins anytime, but especially in a tough economic climate).

Taking this one step further, here are some specific examples of AI in insurance use cases among Dataiku customers:

AI in Insurance Claims Processing 

One insurance company uses Dataiku to build and run more than 70 models for general insurance claims. These models have fundamentally changed the way the business handles claims, reducing reliance on individual expertise and introducing more consistency for a better customer (and, ultimately, handler) experience.

AI for Stronger Customer Experience and Marketing

Aviva has created ADA, an algorithmic decision agent, which is a customer-first AI powering omni-channel, hyper-personalized marketing. But it’s not just about front-end, user-facing impact — Aviva’s Customer Data Science Team is also making strides with AI when it comes to cutting complexity. The team is 5x more efficient in developing data projects from beginning (building a model) to end (pushing into production) with Dataiku.

AI for Improved Fraud Detection

Insurance organizations are all exposed to fraud risks, and given the complexity of data sources involved, introducing machine learning and AI is a great opportunity to improve fraud models. Santéclair is doing just that, detecting fraudulent claims more effectively with Dataiku.

AI for New Insurance Product Development

Envelop Risk is using machine learning and AI to build the next generation of insurance products. They took a holistic approach to characterising the cyber risk economy, deploying dozens of machine learning models to predict behavior, incentives, and diffusion, and more.

AI & Deep Learning for Mail Processing and Manual Task Automation

Even as we continue to reach new technological milestones and solve the world's most demanding problems, many insurance companies are still confronted with the oldest of administrative nightmares: piles and piles of mail. Dataiku worked with one insurance customer to deliver a production-ready tool that could be used to automatically sort any letters received (including determining if the letter is handwritten or typed and parsing that letter) and send them to their appropriate departments. Traditionally, this would have to be done by hand — an expensive and time-consuming task.

AI in Insurance Benefits

AI in insurance benefits include are innumerous, including increased revenue, risk mitigation, cost optimization, efficiency, and bringing a competitive edge. Watch the latest episode of AI & Us for more about the potential in of data science, machine learning, and AI technology in this industry.

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