Mark joined Carbon in November 2020 as Head of Data Architecture. In this interview, Mark talks about what attracted him to the business, the diverse nature of his role and why Carbon’s proprietary platform, Graphene, is a real game-changer in the market
Please can you provide some colour about how you got into the world of ‘new technologies and data’ – what particularly interested you about these disciplines?
I’ve always been interested in the nuts and bolts of how things work, with the fundamental building blocks of any system being data. It’s been pretty fascinating, to me at least, to have witnessed the tech landscape evolve from the pre-internet era to the vast amount of on-demand computing power now at the fingertips of anyone in an instant.
What in particular attracted you to Carbon?
Across many industries, superior analysis, management and sharing of data leads to better informed business decisions and more efficient and cost-effective processes. For an innovative business to succeed, however, it requires those running it to have deep market understanding and product knowledge along with the passion to grow and develop.
As soon as I met the team at Carbon, it was clear those qualities were there in abundance, along with the pragmatism that Rome wasn’t built in a day. The opportunity to build something truly innovative in the delegated authority space without the handcuffs of legacy systems and mindsets was too strong to ignore.
What are the key elements of your role as Head of Data Architecture?
In essence, my role encompasses the design, operation and management of our evolving technical ecosystem with the ultimate aim of delivering timely and accurate data across all facets of the business.
By way of example, initiatives completed by the team include near real time consumption of claims and risk data and the ability to consume a wide set of external data sources.
There’s also a healthy amount of client interaction to ensure Graphene remains on point and highly relevant – and we hold regular product workshops to ensure this happens.
Tell us more about Graphene specifically and what your role is in the management and development of the platform?
Graphene is a bespoke technology ecosystem, designed specifically for the management of binder business. Moving away from linear mono-directional communication, it shares underwriting conclusions with all contract parties, while providing insight that underpins corrective strategies and proactive risk management. Importantly, it combines both underwriting and claims data; live portfolio segmentation; mid-term portfolio adjustments and reduces claim leakage, all while improving data quality, communications, and therefore, underwriting results.
I lead the Graphene team across its three key pillars – data cleansing / ingestion, analytics, and core development. The depth of talent we’re building in each area is incredible and we’re currently in an exciting growth period with new faces joining on a regular basis.
We are particularly proud of the fact that all development is done in-house – and we’ve purposely brought in talent from a variety of industries bringing with them fresh ideas and perspectives.
Carbon talks about new technologies such as Graphene “allowing the business to provide superior data analysis and management for coverholders while giving us deep insights into our clients’ businesses”. What does this mean in practice?
Graphene continually gets cited as a key factor in the decision to trade with Carbon, with a key example being our ability to consume and link data in ways that may otherwise have been deemed irrelevant or too challenging, allowing us to forensically dissect a portfolio.
This in turn enables early identification and monitoring of underperforming classes and crucially also over-performing classes – keeping conversations transparent and the ability to tweak the portfolio as required for the benefit of all parties.
Other providers in the market talk about leading the way in terms of new technologies. Do you think that Graphene is genuinely different and if so, what sets it apart in terms of differentiation and relevance?
“New technologies” is great marketing speak but what sets an analytics system apart is its core dataset and the way that is stored and structured. We’ve invested a significant amount of time and resources to ensure that a solid foundation is in place, which in turn allows us to run a wide array of technologies and models in a scalable and repeatable manner.
But all this would be for nothing if the analytics aren’t relevant to the business – this is where the deep product knowledge of the industry experts at Carbon comes in and allows us to curate a suite of analytics that tells the real story of the portfolio.
What really sets Graphene apart in the market is its suite of predictive analytics. While traditional analytics display data in a rigid format requiring the user to seek out insights, Graphene applies machine learning to actively point the end user to trends and patterns that may otherwise have been missed or buried within the data.
A recent example was when Graphene pre-emptively alerted an underwriter to a potential opportunity whereby Graphene had calculated that additional risk appetite was available in a particular geographical area to buildings that had a specific wall and roof construction type. The book was subsequently adjusted to the suggested risk profile which has benefitted all the parties involved and really highlighted the power of the platform.
What are your plans and goals for Graphene and other new technologies?
We’re building Graphene from the ground up with connectivity in mind and the mantra of straight-through-processing (STP), the concept that every data touch and transfer point should be automated with manual interaction kept to a minimum.
With that in mind, a major goal of ours is to foster an ecosystem, both within the immediate Graphene sphere and wider industry, that enables this seamless and instant transfer of data. Combine that with a host of innovations around predictive analytics, advanced search capabilities and enrichment of the core dataset with insightful external data – then we have a very exciting and busy time ahead.
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