Skip to main content
main content, press tab to continue
Article | Insurer Insights

Five guiding principles for successfully automating insurance pricing

By Serhat Guven and Neil Chapman | January 27, 2023

Automating insurance pricing certainly has its merits, but what are some of the contributing factors to a successful automation process?
Insurance Consulting and Technology
Insurer Solutions|InsurTech

For all the talk and, we would say, undoubted benefits of automating insurance pricing, our experience with implementing WTW Radar for clients shows that successful projects aren’t just a matter of throwing some technology at a problem. Here are five points that we think can help contribute to success.

Streamlining versus automation

Streamlining and automation often get talked about in the same breath, but there’s a big difference between them, albeit some streamlining of pricing processes might accompany an automation project. Streamlining is essentially simplifying an existing process, typically by removing some unnecessary workflows from the larger effort.

By comparison, we like a quote from Haresh Sippy, Chief Founder of Tema India, who has described automation as “cost cutting by tightening the corners and not cutting them”.

In the context of insurance pricing, that will typically mean connecting disparate systems and data flows more seamlessly, bringing some overall structure and governance to the workflow, enabling some scheduling and triggering of activity, and creating some reports to monitor progress.

Automation shouldn’t just be a matter of saving some time – important as that often is – it should pave the way to bring new sources of value to pricing.

Automation has to be done responsibly

Another phrase you will hear widely used in relation to automation is along the lines of “do more with less”. That is often the case but, equally, automation applied to an inefficient operation will simply magnify the inefficiency.

If we look at traditional machine learning models, for example, they have to effectively ‘fail’ to learn. But, will they learn fast enough for certain pricing applications? In other words, automation has to be appropriate to the pricing circumstances for which it is intended.

When looking at how to apply automation responsibly, the six standards recommended by Microsoft are, we would suggest, a good starting point: accountability; transparency; fairness; reliability and safety; privacy and security; and inclusiveness.

Improvement has to be relative to something relevant

Insurers come at the insurance pricing cycle of AnalyseDecideDeploy in a multitude of ways, so no two automation projects are going to be the same.

For example, companies working with traditional generalised linear models could make significant improvements (up to 40% resource savings in our experience) by automating the process of simplifying, grouping and curve fitting factors that could lead to more competitive or segmented pricing.

A next step could be the automated tuning of factor parameters and interactions, leading on to applications that assist the interpretation of results.

The key is to identify where automation can improve your pricing process and deliver the most value.

It’s also worth remembering that automation may do more than just replace what previously would have been done manually. Machines may also reveal pricing insights that wouldn’t typically have been uncovered. Often, automation can also serve to triage the value of making rating updates, as we have seen recently with some companies automating the tracking of potential inflation effects on their books of business.

Be ready for the question – “Who’s going to be impacted by a pricing action and by how much?”

In just about every pricing automation project we’ve worked on, where companies are, for example, using technology to integrate and update data from multiple systems to adjust their pricing and are perhaps aiming to get new pricing to market quicker, the question arises: “Which customers are going to be most impacted, and by how much?”

In the fairly safe knowledge that the question is coming, automate the response. Particularly as impact analysis can be extremely time consuming if done manually.

Another reason for being ready for the question is increasing interest from regulators in understanding how machine learning and automation are influencing factors that drive pricing decisions.

The key challenges are often cultural

Automation doesn’t necessarily always sit easily with established pricing practices. So, it pays to determine what those most involved are prepared to let go and the acceptable levels of scrutiny and review of automated processes at the outset.

There is likely to be a need to introduce and bed in new working practices, because breaks or barriers in an automation-enhanced workflow can limit the benefits of automation. For example, a company that aspires to automated delivery of pricing updates can face real problems if the handoff from pricing/product teams to IT/rate deployment team is overly manual and complex.


If you would like to discuss these points more or find out how WTW is supporting insurers around the world to bring and develop automation in their pricing process using Radar, please contact us.

Authors


Global Proposition Leader, Pricing, Product, Claims and Underwriting, WTW
email Email

Senior Director and Global Leadership, Pricing, Product, Claims and Underwriting, WTW
email Email

Contact us