At Proclaim we have been keeping a close eye on developments in technology in the claims space. Insurtech has certainly created some buzz in the industry – not sure we are getting to the frenzy in 
the early 2000s tech boom when a fish and chip shop with a computer was declaring itself a dotcom, but there certainly is a raft of activity in the insurance tech space.
Given how slowly insurance moves as an industry, there will be those who are cynical, but we have seen enough to know that the advances in data analytics and machine learning will, in time, transform the insurance claim space. As for now, it seems the broad focus initially has been on the distribution end – creating a model that has less friction for the direct to market space (which is mainly domestic insurance at this stage). Some of the new players in this space like Lemonade and Metromile in the USA are undoubtedly innovative in both the distribution and claim space and could claim to be disruptors. While a fair degree of focus in Insurtech has been in how to disrupt the insurance industry, most of the new innovations are in the domestic space. This is only a small portion of the overall insurance market, so there isn’t an UBER or Air BnB that has currently come to grips with disrupting the larger insurance market.
The commercial insurance space would be the main prize for a disruptor. But it has capital intensity, heavy regulation and complexity to boot so disruption on a large scale seems less likely. The consensus seems to be that as the new tech matures we will see innovation come from partnerships between the new tech companies and the established commercial insurance market. This is in areas like Data Analytics, automated processing, smart bots/robotics and machine learning.
What about claims? Usually (and unfortunately) the last thing thought of, we don’t see any evidence Insurtech will change that sequence. Currently the focus of new tech in claims seems to also be in domestic motor and property, where players like Lemonade use automated processing to get their ‘three second claim payment’. We do have a sense that the commercial lines of business will follow, a little later, leading to change in this space that should be positive for the customer experience. We have already seem some insurers try and innovate to align themselves more closely with a digital experience – digital forms, bots and straight through processing – and expect that soon to be a wider choice for customers in how they submit claims.
So what are we doing to confront this brave new world? While we will continue to try and improve efficiency in processing, we are focused on being more data driven. In that regard, we feel we need to invest in a data driven innovation strategy to support three main areas:
- Advanced business intelligence for our clients
- Decision science
- Machine learning
We are looking to Data Analysis as a key changer to do two things initially – the first is to offer our clients more advanced insights into their claims. Better analysis and better visualisation tools. Second, we want our Data Analysis to provide and explain correlations between variables, such that we can confidently advance or adapt our business models to statistically proven methods. And if we can confidently correlate certain variables, the next step is to help with prediction. This extends to assisting with flagging claims with potential high cost or duration for instance, or flagging claims that have fraud indicators.
If we can truly understand the drivers for the best decisions, we hope to build machine learning tools that can help us to achieve better outcomes for our clients.
The claims world is largely built around prediction. We understand that machine learning can, and will, assist us in reserving and in early identification of potentially problematic claims. We don’t think this tech will be like driverless cars though – we still think the skill and expertise of the Account Manager driving a claim will be critical. The danger with this technology is that some Insurers may think predictive machines can replace human decision makers; the reality is that the best results will come from a combination of machine prediction coupled with human expertise and intuition.
So it does appear the focus of Insurtech has shifted from disruption to partnerships, which is also how we see our future relationship with tech. It isn’t a replacement for expertise – we can continue to invest in people while innovating in tech, as together we can create a formidable partnership.
Written by Jon Broome
