Finborn nabs $70M for tech that turns financial data dust into AI gold


Companies in sectors such as financial services and insurance live and die by their data — specifically, how well they can use it to understand what people and businesses will do next, a process that’s increasingly dominated by AI. Now, a startup called Finnborn, based in London’s financial hub, has built a platform to help financial firms organize and make more use of their data in AI and other models. It’s announcing £55 million ($70 million) in funding, which it will use to expand its reach beyond the Square Mile.

Highland Europe and strategic backer AVP (the venture arm of insurance giant AXA) are co-leading the Series B, which values ​​the company at around £280 million ($356 million).

Finborn co-founder CEO Thomas McHugh told TechCrunch that he got the idea for the startup after working for several years as a senior quant in the City, most of which was spent at the Royal Bank of Scotland. One of those years was 2008, the year when RBS, then the world’s largest bank, was dramatically pushed to the brink of collapse after being overly exposed to subprime loan contagion.

The major change came in the form of a massive reorganization internally.

Previously, the entire bank was organised into a series of business silos, which in turn affected not just how people worked, but also how data worked within them. All of these cost a lot to run, costs that needed to be reduced urgently. “We had to take out crores of costs from the business in a very short period of time,” he recalls.

They decided to take a page from the nascent but rapidly growing world of cloud services. AWS, founded in 2006, had only been around for two years at this point, but the data teams could see that it presented a compelling and comparable model for how the bank could store and use data. So it too took an integrated and federated approach to the problem.

“We basically managed to build a lot of technology that worked across every asset class. Until then, people had said it wasn’t really possible. But we had an incredible reason to make the change and from that we knew we could build better technology, much more scalable technology,” McHugh said. He added that equity systems, fixed income and credit, all previously run as separate systems, were now on one platform.

The 2008 U.K. financial crisis was a rollercoaster that, if you didn’t get through it unscathed, would certainly have left you believing you could handle any kind of challenge. So McHugh embarked on what was surely the riskiest thing in business: a startup.

Finborn may have its roots in how McHugh and others on his team approached the challenge of building more efficient data services at their bank, but it has also evolved into an idea that reflects and shapes how financial services companies buy IT today. Just as companies with extensive sales operations might use Salesforce (or a competing platform) rather than building their own software, Finborn believes financial companies will increasingly do the same: work with outside companies for the tools to run their operations, rather than building their own software.

This also inevitably aligns with how banks and others in financial services are increasingly working with AI.

Today the company’s products include the LUSID operational data store; investment and accounting record books (used in asset management analysis); a portfolio management platform that tracks positions, cash, P&L and risk; and a data virtualization tool. McHugh said Finborn is also helping manage how companies handle their data for training models, an area where it is likely to become more involved.

It seems that the main conclusion here is that there is no clear leader, and banks do not want to share data with other banks, so are training on ways to prevent this from happening – a process that also helps customers control the results more tightly and prevent “confusion” from entering the picture. Open source is playing an important role in presenting more flexible options for end users.

“What we’ve seen is that customers don’t want any of the models we write or use to be trained on someone else’s data,” he said. “We look at this very strongly. We do this because by not having permission to use someone else’s picture, those models are less confused.”

Finborn currently has many competitors. For example, asset manager competitors include Aladdin by BlackRock, SimCorp, State Street Alpha and GoldenSource; alternative asset manager competitors include Broadridge, Enfusion, SS&C Eaze and Maia. BNY Mellon Eagle, RIMS, Clearwater Analytics and IHS Markit all offer tools for asset owners; and asset services include companies such as FIS, Temenos, Denodo, SS&C Advent and NeoXam.

The fact that there are so many companies may force one to take the more simplified approach of dealing with just one – a route being taken by companies such as Fidelity International, London Stock Exchange Group, Baillie Gifford, Northern Trust and the Pension Insurance Corporation (PIC).

“Over the past few years, Finnborn has built a revolutionary SaaS platform that is enabling many of the world’s largest financial institutions to move from legacy solutions to modern data architectures that enable full real-time visibility and optimal decision making,” Tony Zappala, partner at Highland Europe, said in a statement.

“When the team first showed me in 2020 that they could integrate investment data from the entire universe of assets held by managers onto a single platform, they wowed me,” said Imran Akram, general partner at AXA Venture Partners. “Today this is a clear differentiator and is especially important for the emerging AI wave.”


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