An interview between Carl Christensen, Global Head L&H Solutions at Swiss Re and Stephen Yap, Research Director at Insurtech Insights
Q:
I’m delighted to be joined by Carl Christensen from Swiss Re. Hello Carl. I’d love to learn about what you do.
A:
Pleasure to be here, thank you. I’ve been at Swiss Re for almost nine years and am leading our Life and Health Solutions globally (link: L&H Business solutions | Swiss Re). That’s where we provide technical expertise in conjunction with risk knowledge to our clients. I have a 20+ year long history in primary (insurance) since I’ve worked in different areas of the industry.
Q:
Swiss Re is now coming up to 160 years, a long time for any organization to be in business. What’s the secret of the company’s longevity?
A:
We’re fortunate to have weathered a lot of natural and man-made catastrophes over the years. Resilience is our secret sauce. We’ve perfected the recipe over the years, learned from the data and this learning, combined with expert knowledge, is what helped us weather multiple storms and become who we are today. It also continues to inform our corporate culture and the way we do business. We’re a knowledge company. The voluminous amounts of data we have helps us to not only predict the future but keep us on top of innovation. Our ambition is to continue this path and stand side by side with our clients, helping them advance and bring forward-thinking views to them.
Q:
Innovation is happening faster than ever in the history of Life and Health (L&H). I’d like to hear what you consider to be the biggest topics that are shaping the future of L&H insurance.
A:
We’ve talked about acceleration of innovation for a long time, there have been different visions of it, but only select few remained. One of the themes is digitalisation of distribution. Today it’s picking up speed in terms of the real tangible value it creates. Another theme is data and analytics. What can we do with the existing data we have? How can we combine new and existing data? And how can we draw predictive models using them both? All of this is supported by the evolution of AI (Artificial Intelligence), which plays a key role, but still has quite a way to go. The other big industry trend – destined to become more prominent – is ecosystems: different parties within the industry collaborating to provide innovative and trail-blazing solutions and products for the market.
Q:
How does Swiss Re help enable primaries in the L&H space in these areas?
A:
We started with various solutions a while ago, providing specific systems in different areas of the insurance value chain. One such flagship solution is Magnum, a globally recognized leader of underwriting automation engines. Magnum allows clients to unlock growth opportunities by cutting down the application time from weeks to minutes, increasing point-of-sale conversion and achieving operational efficiencies while delivering an enhanced, easy, and engaging customer experience to the end user. It’s been around for 15 years and constantly evolving, as we continue to invest in data-driven underwriting.
Another solution is CARE, a rising star building up on our excellence in automation to support claims processing. Point-of-claim is where the insurance promise delivers for the customer and will enhance or detract from an insurer’s brand and reputation. As an automation tool it delivers operational efficiencies while helping increase customer satisfaction which is a known driver for growth.
We also now provide data analytics services, both from a platform perspective and for distinct analytics insights.
Q:
What are some problems that can be resolved through innovations that are now available from Swiss Re? Perhaps some of the historical pain points, either for the customer or for the underwriter or another department within a carrier, which we can now address using these tools?
A:
Digital distribution has been a key evolution for life and health, but still small as a proportion of the overall market. When you go digital, all the distribution value chain components also need to be digitalized. For example, you need a tool, like Magnum – our automated underwriting engine, that perfects interactions with consumers and allows the decision to be taken on the spot. You will not get there using manual shortcuts.
The other thing is analytics. A lot of primaries have realised they are sitting on large portfolios of insurance, and that distribution is expensive. Acquisition costs are high. How can we use analytics within an existing portfolio to retain clients, offer upsell and cross-sell opportunities and create engagement moments? We have developed several risk utilities to provide those insights for our clients and this has already proven to be highly valuable.
Q:
I’m interested in learning more about the tools that you provide to help carriers upsell, cross sell, and retain. Can you share more details of what they do and how they work?
A:
Let’s look at a concrete example: in Germany, automated underwriting was hovering around 50% of the total. With Magnum, in many cases, we’ve been able to increase that up to 75% by categorizing risks down to a lot of detail. By working closely with our primaries and finding data insights early in the engagement, we were able to create an impact.
There’s still pressure on underwriters to make decisions with regard to things that cannot be automated. There are opportunities to provide appropriate data at the right time to re-run rule-based algorithms to define the right output. All of this makes things much more streamlined for the carrier and the customer.
Q:
I’ve heard a lot about the industry improving its ability to provide insurance to people with pre-existing conditions, who historically may have found it more difficult to get superior quality L&H cover. What are you seeing in this area?
A:
That’s a great question. Our ambition is to make the world more resilient. The recurring questions are: How do we cover risks in the population in diverse ways? How can we provide that cover to everybody whilst keeping premiums affordable?
We find supporting data points, look at different underwriting processes to help support clients who have a goal to improve underlying pre-conditions. How can we use data and analytics to find ways to manage these conditions? That’s where we combine data with risk knowledge to support distinct products or embed them into existing products.
Q:
From a technical perspective, as a primary carrier working with Swiss Re, how complex is it to connect and integrate with your data and analytics capabilities? Is it something that takes a long time, or can it be done relatively quickly?
A:
From a few days to several weeks, depending on several factors. We strive to make the integration as simple as possible, so we’ve developed models which are API (Application Programming Interface) based, cloud-based solutions with noticeably clear and stringent data security protocols. With companies that have the right frameworks in place, it can be a very quick process, as in just days to get analytics in place and to start to see outputs based on the risk utilities we’ve developed.
The process is more complex in companies where data is highly fragmented, sometimes hosted in many different systems, many of which are legacy systems. When legacy systems are a factor, we focus on areas where we can drive benefits early on, rather than try large data-consolidation initiatives with a substantial risk of failure.
Q:
I’d love to hear more about the use cases of AI within L&H.
A:
We’re at a stage where a lot is rule based in underwriting, whether it’s risk utilities or underwriting method itself. This is still highly effective, but we are doing a lot in the AI space because we recognise the potential for teams to be able to use the benefits of more automated processes. We need to train the machines so we can rely upon them. With Magnum, for example, we have defined AI utilities that are distinct to underwriting philosophies, where we are training the machines and testing with clients. AI can be extraordinarily powerful, however in life insurance you need to be conscious of how you teach the machine as you embark on that journey.
Q:
Have we already seen the big gains? Are future gains more incremental? Or are there more game changers still to come?
A:
Out of all available tech areas, the industry is investing more in analytics, which is a clear sign of future value creation. We also need to recognise big data and data analytics are complex topics. Right now, everyone is trying to do their own thing. As a reinsurer we are actively playing a consolidation role. We want to partner with the industry and our primaries to create a shared ecosystem of learning, and scalability of optimal cost for analytics services. The industry needs to be conscious of the cost of ownership as we move into these analytical investments. I think we’re in an early stage of evolution.
We’re also seeing a lot of acceleration in terms of digital distribution and automation. We’ve already supplied a lot of tools to support that evolution, but I think we’re going to see an accelerated growth trajectory in the years to come. There’s still much more room for the development of digitalisation, distribution and supporting intermediary channels, alongside direct-to-consumer channels with data and analytics.
Q:
Thank you very much, Carl.
