Insurance is, at its heart, a data driven industry. Across just the big four comparison websites in the UK (Compare the Market, Money Supermarket, Go Compare and Confused) nearly a million car insurance quotes are delivered every day. In this industry, delivering deep insight from data, in real-time, is now key to staying ahead of the crowd.

Adopting a data-first approach to insurance can reap enormous benefits and with very little effort. Cloud services, such as Microsoft Azure, are starting to offer ever more powerful tools straight off the shelf that allow you to make faster, data driven decisions to enhance your business. Here are just a few examples of how artificial intelligence (AI) and data are critical for the insurance industry.

Data foundations

Before introducing AI into a system, businesses need to build better and more accurate data foundations. For example, if you were trying to work out if a particular group of customers are spending a lot of time in your service centre or phoning support – with access to customer journey analytics and insights, an insurance company would be able to create a predicted lifetime value score which could be used to drive a better quote.

Once AI is introduced, any previous actions and the customer’s information can be sent to the machine-learning model to improve future outcomes and ensure that the sales and marketing teams are targeting the most profitable customers — and avoiding those likely to be unprofitable and detrimental to the business.

Getting information to people quicker

In insurance, there’s so much data and so many ways to look at it that it is often very difficult to know where to start.  What’s more, data volumes can be so large and pipelines so convoluted that it requires expert knowledge to get the exact information required. You don’t want your key decision makers to require a degree in computer science to get the information they need.

Building a robust data pipeline often means simplifying the data extraction, transfer and analysis process. Gone are the days of logins, downloads and spreadsheets getting emailed around the business (and the potential governance, GDPR, security risks this can lead to). Through the likes of Power BI, analysis can be fully automated and delivered through reports and dashboards, in real-time, to the decision makers that need it most, enabling everyone to get a better understanding of the business. This empowers people to make more informed, data-driven decisions.

ML and enhanced modelling – improving predictions with ML

There’s a reason many of the challenges on the leading AI/ML/Data Science competition site come from the insurance industry. On Kaggle data scientists battle it out for cash prizes to build the best models possible – models which can then be put into production by the sponsoring company.

Machine learning (ML) models frequently outperform traditional statistical models as was the case in the Deloitte churn prediction competition. Churn plays an important part of any pricing decision, here actuaries may typically use generalised linear models on samples of customer data to predict the likelihood of churn for a customer over a number of years.

In this competition, machine learning methods were employed that were far better at predicting whether or not a customer would churn in the next 12 months, when compared to traditional statistical techniques. The tools used to develop them are better suited to, and in-fact thrive on, larger data volumes which allow them to capture more complex patterns in behaviour.

Catching fraud with AI

Through the use of AI and analysis of typical fraud patterns, insurance firms are now able to identify future fraud much faster and more accurately – much faster than a human ever could.

When a fraudulent pattern is recognised, this claim can be routed to an investigations department. The feedback and research they undertake can then be fed back into the fraud model, enabling the model to continuously improve by becoming smarter and more accurate with every new claim.


Each and every insurance company should be looking to incorporate AI into their daily work, especially in terms of generating quotes and detecting fraud. By delivering the right information to the right people and more data-driven decisions overall, AI will enable insurance firms to clearly differentiate themselves from their competition and better deliver for their current and future customers.

Watch our webinar Data Science 101 for Professional Services to discover the other impacts we are seeing AI make to the insurance industry.