In the last couple of weeks I’ve had the great opportunity to spend time with IT architects of various sorts both inside and outside of the insurance industry. The discussions have been illuminating and offer different visions and futures both for technology that supports insurers and for the future of the architecture function in insurers.
One of the main events that allowed for this conversation was a round table held in London with architects from insurers. The main topics were the relevance of microservices style architectures to insurance, the role of the architects in AI and InsurTech and the future role of architects at insurers. Another event that offered an interesting contrast was the inaugural London Software Architecture Conference which I'll call SACon below (Twitter feed).
I won't fully define microservices here but briefly it’s an approach to delivering software where each service is built as it’s own application which can be scaled independently from other services.
Microservices as a way of delivering software was the default approach at the SACon. There were sessions where architects sharing stories about why sometimes you had to work with a monolith or even making the case for not having the services in discrete applications. Meanwhile at the round table the monolith was the default still with the case being made for microservices in some parts of the architecture.
There are use cases where microservices make a great deal of sense, particularly in already distributed systems where a great deal of data is being streamed between applications. Here the infrastructure of microservices and the libraries supporting the reactive manifesto such as Hysterix and Rx* (e.g. RxJava) and indeed one insurer related their use of microservices to support IoT. Others discussed using this style of approach and the tooling surrounding these architectures to launch new products and increase change throughput but in all cases these were far from replacing the core architecture.
For now microservices is not the default for insurer software but is certainly a tool in the box. An observation or two from SACon from those looking to adopt: First it doesn’t solve the question of how big a service or a component is, something architects need to discuss and refine and; Second, microservices needs a great deal of automation to make work, a topic covered in our DevOps report to be published shortly.
Architects and AI
I have a background with training and experience both in computer science, AI and machine learning. One thing that I noticed going to the analytics conferences where AI is discussed is the absence of IT representation – plenty of actuaries, MI/BI folks, marketing folks – was this a place for architects?
Most insurers present at the round table had activity within the organisation for AI. For the most part only data architects are involved in this discussion – AI being distinct from business and applications architecture for now. It’s my opinion that AI components will form part of the wider applications architecture in the future, with AI components being as common place as programmed ones.
Architects and InsurTech
Here is an area where architects can more immediately contribute in a meaningful way both in reviewing opportunities and unique capabilities from InsurTech firms and in discussing integration where acquisition rather than investment is the goal.
The challenge here of course is the age old challenge for architects – to have a seat in the discussion the architect function needs to demonstrate the value it can bring and it’s internal expertise.
Finally, one amusing discussion I had was with a few architects from startups. As I discussed legacy systems they also related seeing legacy systems in their organisations – albeit the legacy systems were 2 or 4 years old rather than 20 or 40 years old. The intriguing thing here was the reasons for them becoming legacy were the same as insurers – availability of skills, supportability and responsiveness to changing demands. It may hearten architects at insurers that start ups aren’t immune to legacy issues!
As noted in our prior research insurance has always been an industry that relies on advanced analytics and has always sought to predict the future (as it pertains to risk) based on the past. (For research on advanced analytics in insurers see here, here and here).
As observed in the last post here analytics, AI and automation has been a key focus of InsurTech firms but do not assume that the investment is limited to newbies and start-ups. I have for a few years now been attending and following the Strata+Hadoop conferences and others focused on advanced analytics and the broad range of tools and opportunities coming out of the big data organisations. This last week I attended a conference focused on the insurance industry and was surprised to see the two worlds have finally, genuinely overlapped – just take a look at the sponsors.
As Nicolas Michellod and I have noted in the past, insurers have already been investing in these technologies but only those that have made the effort to speak “insurance”. What the conversations at Insurance Analytics Europe (twitter feed) demonstrated was a new focus on core data science tools and capabilities. This continued the theme from DIA Barcelona (twitter) earlier in the year.
The event followed InsTech London’s meeting (Twitter) looking at data innovation and it’s opportunities for Lloyd’s, the London market and the TOM initiative. Here the focus was on InsurTech firms that would partner on analytics, would sell data or would enable non-data scientists to benefit from advances in machine learning, predictive analytics and other advanced analytics disciplines.
While this trend of democratising advanced analytics was discussed by analytics heads and CDO’s at the analytics conference the focus was much more on communicating value, surfacing existing capability and tools within the organisation and to put it bluntly, getting better at managing data.
In short – AI, Analytics, Machine Learning, Automation – these were all hot topics at InsurTech Connect and similar events but for the insurers out there – don’t assume these are purely the domain of InsurTech. Insurers are increasingly investing in these capabilities which in turn is attracting firms with a great deal to offer our industry. For those big data firms that ruled out insurance as a target market a couple of years ago – look again, the appetite is here.
As a techy and AI guy of old I am deeply enthused by this focus and excited to see what new offerings come out of the incumbent insurers and not just InsurTech.
Do have a look at the aware machine report and the blog too. We’re increasing our coverage in this area so if you have a solution focused on this space please reach out to Nicolas, Mike or myself so we can include you and for the insurers look out for a report shortly.
- Efficiencies and platform rationalization–aka “let’s figure out what is the right number of core systems, which core systems will be the survivors, and how data conversion and integration will work”
- Cloud, SaaS, data management/stores, and analytics
- Professional service and SI support capabilities that can scale to the new Chubb
- Which systems will best support a digital roadmap
- Design highly configurable and agile systems that feature ease of integration
- Have enough scale to meet the needs of bigger and bigger insurer customers—grow, merge, or wither
- Are we headed for a new AI winter?
- Or an AI apocalypse?
- Also, will I still be cleaning my home in 2020?