Finbourne nabs $70 million for technology that turns financial data dust into AI gold | TechCrunch

Companies in fields like 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 is increasingly dominated by from him. Now, a startup called Finbourne, founded out of London’s financial hub, has built a platform to help financial companies organize and use more of their data in AI and other models. It is announcing £55m ($70m) in funding, which it will use to expand its reach outside 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 just over £280 million ($356 million) post-cash.

Thomas McHugh, the CEO who co-founded Finbourne, told TechCrunch that he came up with the idea for the startup after many years working as a senior executive in the City, most of those spent at the Royal Bank of Scotland. One of those years was 2008, the year RBS, then the world’s largest bank, came dramatically to the brink of collapse after becoming overexposed to the subprime loan spread.

The major shift took place from within in the form of a major reorganization.

Previously, the entire bank was organized into a series of business silos, which affected not only how the people worked, but also how the data worked within them. All this cost a fortune to run, costs that urgently needed to be cut. “We had to cut hundreds of millions of costs out of the business in a very short time,” he recalled.

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

“We were able to build basically an awful lot of technology that worked in every asset class. People until then said that this was not really possible. But we had a tremendous reason to change, and from that, we knew we could build better technology, much more scalable technology,” McHugh said. Equity, fixed income and credit systems, he said, all previously operated as separate systems were now on one platform.

The UK financial crisis of 2008 was a rollercoaster that, if you didn’t jump right in, you’d be blown away by the belief that you can face and meet any kind of challenge. So of course that eventually led McHugh to take on the riskiest thing in business: a startup.

Finbourne 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 the idea, reflecting and shaping how companies financial services buy IT today. Just as companies with extensive sales operations may use Salesforce or a competing platform instead of building their own software, Finbourne’s bet is that financial companies will increasingly do the same: outsource for tools to run their operations instead of building their own.

This is also inevitably linked to 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 books (used in asset management analysis); a portfolio management platform that tracks positions, cash, P&L and exposure; and a data virtualization tool. McHugh said Finbourne is also helping manage how companies handle their data for training models, an area where it is likely to become more involved.

It seems like the key takeaways here are that there is no clear leader and banks don’t want to share data with other banks, so they’re training themselves in ways not to be – a process that also helps customers more tightly control outcomes and keep the “hallucinations” from creeping into the picture. Open source is playing an important role in how it presents 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 see this very strongly. We do this because by not allowing them to use someone else’s photo, those models are less able to hallucinate.”

Finbourne has a whole range of competitors at present. Rival asset managers, for example, include Aladdin from Blackrock, SimCorp, State Street Alpha and Goldensource; Alternative asset manager competitors include Broadridge, Enfusion, SS&C Eze and Maia. BNY Mellon Eagle, Rimes, Clearwater Analytics and IHS Markit all offer tools for asset owners; and asset services include the likes of FIS, Temenos, Denodo, SS&C Advent and NeoXam.

The fact that there are so many can be a compelling reason for someone to take a more streamlined approach to working with just one – a route that companies such as Fidelity International, London Stock Exchange Group, Baillie Gifford, Northern Trust and the Pension Insurance Corporation. PIC) are receiving.

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