This insights piece is by David Prejeant, Executive Vice President at Alacrity Solutions
I’ve always loved learning and building high-performance teams, so I was delighted when Lee Boyd, our Chief Operating Officer at Alacrity Solutions, asked me to support our recently launched UK operation. It’s an expansion of my current role and, with it, an exciting opportunity to build and shape Alacrity in the historic Lloyd’s of London market. I recently attended a Lloyd’s of London Academy boot camp here in the US, and while I know it’s no substitute for being there in person, it was a valuable introduction to how the market works. It reinforced the opportunity to help build Alacrity’s UK business at a time when the insurance sector is working out how it embraces artificial intelligence (AI).
It’s a topic that’s front of mind for executives globally, but in London it raises a particularly interesting question: how does a marketplace established in the 1600s, which still conducts so much business in person, evolve for the AI era? I recently read a KPMG study that found 77% of UK insurance executives believe failing to respond to AI will undermine their competitiveness within the next five years. Despite this, only 11% have the data foundations and governance needed to scale AI beyond pilots. Fragmented and poor-quality data, unclear ownership and legacy systems were cited as the key issues holding them back.
The gap between ambition and readiness is a defining challenge for the sector right now. Globally yes, but I think it’s more pronounced in London for a couple of reasons. The first being how much business gets done face to face, and the second being how risk is shared. Both fragment data, and if London wants to continue leading in specialised risk, it’s something that must be addressed. The good news is that if met head-on, it’s a very solvable problem.
The innovation advantage on London’s doorstep
Before we get into these challenges, it’s worth saying that London has a real head start. One of the things that struck me most at the boot camp was Lloyd’s Lab. Technology companies set up right next to the market and build for it, while talking to those it serves. We don’t really have an equivalent in the US, where most of our technology gets built somewhere across town and pitched to us afterwards.
For a market as unique as Lloyd’s, that’s a huge advantage. It means systems can be designed around the needs of the business from the outset, rather than being bolted on afterwards and retrofitted into existing operations. For many insurance and claims organisations today, getting the most out of AI technology means rethinking their operating model. A recent survey by The Insurance Network found 54% of UK claims professionals believe redesigning their operating model is a high or critical priority.
The challenge is that many firms aren’t ready to take advantage of it. KPMG found 92% of insurers in the UK are looking at AI as a way of reducing cost, but only 25% are focusing on how it can drive revenue through new products, services and AI-enabled offerings.
For me, that’s a missed opportunity. Firms that only think of AI as a cost-cutting exercise will find some efficiency gains, but they’ll miss the bigger prize of using it to create better products and better outcomes for their customers. With only 11% having strong data foundations, this is where the work needs to start, because whether the goal is cutting cost or creating new products, both depend on having access to data you can trust.
The room vs. the system
One of the things I admire most about the London market is how much of its business is still done face to face.
As someone who’s spent a lot of time thinking about how connection and trust drive high-performing teams, I love the culture of people working together in person: an ecosystem built on trust, human judgement and a willingness to cooperate, whether you’re a broker, insurer or claims administrator. It’s a big part of the market’s heritage, and arguably the reason London remains the global leader in specialised risk, because people are used to having conversations and working through complex issues together. It’s quite different from the US, where we rely far more on technology platforms and email.
But that same strength also helps explain why fragmented data is such a persistent challenge in UK insurance. When so much happens in conversation, information passes between brokers, TPAs and insurers in whatever form it happens to arrive. The fix, therefore, is connecting people and processes, not just plugging in new software.
How risk gets shared
The way risk is structured adds another layer of data complexity. In London, it’s common for one risk to be split across several syndicates, with a lead and followers behind it. Here in the US, one carrier usually holds the whole thing. That structural difference changes how information moves, with every additional party becoming another opportunity for data to get stuck or missed.
I often hear that in the UK it’s not unusual for a follow market to find out about a loss months after the lead, simply because the information sits across brokers, TPAs and insurers with no shared standard connecting any of it. Interestingly, research from AutoRek found UK insurers manage an average of 17 separate data sources feeding their premium processes alone. Coming from a claims background, I know that if premium data looks like that, claims are likely to be messier still. That’s not a problem better technology can solve on its own; it’s an operating challenge the whole sector needs to address together.
Fixing the data foundations first
As I think about the use of AI in UK insurance, I keep coming back to the fact that AI won’t replace the judgement of people in the London market, but it can give them better information, faster, once the data underneath it is in order.
That means the first step is getting the foundations right. In practice, that means:
· Agreeing shared data standards between leads, followers and their partners.
· Being clear about who owns data and AI decisions across the business (rather than leaving them with the technology team).
· Judging AI by the outcomes it creates for brokers and policyholders, not just the costs it takes out.
It’s something we’re thinking about lots at Alacrity in the UK. Setting up a new office gives us the chance to design our processes around the needs of the market and our customers from day one. Borrowing from Lloyd’s Lab, it means putting the people who build the technology in the same room as the people who will use it, before anything goes live.
The good news is that London already has a culture built on conversation and trust, something many other insurance markets envy. The challenge now is to build the data infrastructure that will help the market evolve and continue to thrive in the AI era.
Be the first to comment