What's the most promising insurance technology in the market? | Insurance Business America
Insurance organisations are scaling up their modernisation processes by embracing artificial intelligence and machine learning tools – and tech companies are seizing the opportunities. Out of all the cutting-edge tools available to help solve insurance’s most pressing problems, which ones have the power to accelerate change in the industry?
Insurance Business spoke to leading insurance professionals on the sidelines of the Earnix Excelerate 2022 conference in London this week. Here’s what they said:
Brad Middleton, director, pricing & rating, Deloitte Canada
I’ve found Earnix to be quite good for the marketplace. One of the challenges that insurers consistently face is reducing the cycle time between starting a rate change and deploying it into production. Tools from Earnix have helped insurers manage a more tightly coupled rating and modelling system that bridges part of that gap.
I’m excited to hear about the partnership that Earnix is making with Guidewire. Up to this point, it has been challenging for many clients to integrate their systems. The cost of integration – to take a product like Earnix when you’re already on Guidewire and have them start talking to each other – could be prohibitive, especially for smaller carriers.
A pre-configured tool will allow more carriers access to Earnix by reducing the implementation costs [of integration]. It will help them fully realise the benefits they’ve been striving for, such as time-to-market price sophistication. It will help them take their current rating system and add a complexity that they haven’t been able to achieve before.
Milan Chavda, head of pricing, INSHUR
When I first used Earnix, it was just about dynamic pricing, which I thought was ahead of its time. Now that I’ve started using it again, I see it’s added much more. I think it’s an exciting technology because users can integrate a lot into it.
Claims is an important area of the insurance lifecycle that isn’t touched on that much. One of the companies we work with is Five Sigma, whose claims platform is good. They’re probably one of the most exciting technologies that I’ve seen.
With Earnix, it’s easy to use and quick to make changes. Being able to input data instantly gives us that competitive advantage because we react to the market much faster. With Five Sigma, I like all the data you get out of it; there’s a lot of information, and it integrates with our technology stack well.
Edward Hill, SVP, European markets, INSHUR
It’s technology around agile data ingestion and management. There’s a symbiotic relationship between pricing, underwriting, and claims; technology can help deliver better results by bringing them together. In traditional firms, these areas are often very siloed. But technology around data management makes it possible for other areas of the insurance business to work in unison to achieve company objectives.
For our business, we work in an on-demand, gig economy sector, which is a booming industry. For us, it’s all about making agile changes to the pricing and underwriting model and being quick with claims management. So technology for data ingestion, making sure we get notifications on the claims front, is important.
James Rawstron, head of pricing at Digital Partners, Munich Re
The most promising insurance technologies are the ones that enable you to maximise value from the data you’re collecting and integrate data from external sources. There’s so much data available that we are leveraging across different parts of the business. That means not just using pricing data for pricing, but also using it at the claim stage to help serve customers better.
Technology that lets you collect data, aggregate it, and make it visible so that you can get actionable insights for customers is exciting because [those tasks are] difficult to do. It sounds simple, but there aren’t many platforms or companies doing it.
Nick McCowan, head of general insurance, UK Post Office Management Services
I don’t think it’s about a specific piece of technology. In a time of inflation and regulatory pressure, one of the big challenges in the industry is using what you’ve got more effectively, rather than necessarily reinventing everything or buying lots of new kit. How do you use different sets of customer data with more traditional pricing data to create insight that allows you to personalise propositions, drive your channel strategy, improve your operation and your omni-channel experience for customers?
Digitisation in insurance has often been about reducing cost. Now, I think it is much more about helping customers who want to do certain transactions in one place, but also want to talk to us in other ways. We must be guided by that, rather than saying, “I’m going to digitise my business, full stop.” For me, it’s about being responsive to customers.
Harrison Jones, senior manager, Deloitte Canada
If you ask that question to most actuaries, I assume they will say something about machine learning and artificial intelligence. I agree with that, but what I get most excited about is the enabling software around that.
Most actuaries can build a new, sophisticated machine learning model, but not many can deploy it. Actuaries typically struggle with API integration or machine learning DevOps, so any technology that facilitates that for actuaries is interesting. Earnix is an excellent example because you can bring your own model to the table, even build it yourself directly into the software, but deploying and managing [the model] is also easy. It’s sophisticated and makes the whole process much more manageable.