Finbourne Puts Even More Humans in the Loop to Build Client Confidence and Business

In an age when many firms are handing over ever more functions to artificial intelligence, Finbourne Technology is going all-out with investment in human engineers to take the company’s investment management data and technology capabilities to its customers.

While the FinTech industry is hailing its ability to create agentic processes that enable people to tell technology to solve problems for them, Finbourne is banking on the human touch and generations of hands-on expertise to bring a qualitative approach to problem solving. In effect, FDE is a two-way project: it ensures that the financial minds that work on client accounts also have the technical ability to help with technology while at the same time teaching engineers the soft skills of dealing with customers on a one-to-one basis, including investment management.

Finbourne Chief Technology Officer Elliot Hurdiss, who was tasked with putting the programme together, admitted it was an unusual brief, given the proliferation of autonomous AI tools.

“When I was first learning to be an engineer, engineers were the people who had beards and sat the back of the room and you wouldn’t let them anywhere near a client,” Hurdiss told Data Management Insight.

“So it seems slightly strange that we’re talking about engineers being our interface.”

Complex Kit

The genesis of the project was the recognition that FINBOURNE’s suite is a ‘complex piece of kit’, and that clients often prefer to have engineers who know the platform closely working alongside their own teams.

In response, the company’s leadership tasked Hurdiss with finding a solution. Over the following 12 months he put together a team of engineers and investment management experts and had them learn each other’s jobs.

“I slowly realised that this is an inherently technical domain that we live in and that the people who are facing off to our clients should be more technical by their very nature,” Hurdiss said.

FDE aims to ensure that clients are able to derive full value from the services they buy from Finbourne. The engineers are able to work with the company’s AI, its Candela agentic layer and its platform tooling to build production solutions at speed, Finbourne said.

Engineers will help clients connect legacy systems and fragmented data silos; embed governance, audit and controls; and formulate agentic AI solutions across the trading lifecycle.

By embedding staff into client’s workflows as an extension of its own team, Finbourne anticipates it can configure architectures to production stage within three-to-six months instead of the multiple-year timeframes that typically characterise such tasks.

“They try and get client lanyards and badges and sit with them and live their problems,” said Hurdiss. “They have the industry expertise to understand that problem and then the technical expertise to have that implemented within our data platform.”

The expectation is that the FDE engineers will spend a relatively short amount of time within clients’ teams, getting them set-up and operational. They will also show client staff how to take on challenges and operationalise the systems themselves.

“Our hope is that our engineers can come in and, in a short space of time, find out what the problems are, implement the platform such that it solves those problems, train the users and hopefully fold themselves out of the customer and hence get them to run on their own,” Hurdiss said.

Skills Gap

Finbourne went into the project fully aware of the shortage of the technical, data and AI skills necessary to achieve its goals. A slew of reports in the past couple of years have highlighted how the FinTech industry is at risk of slower development amid a skills gap. The challenge is being acutely felt in regulatory compliance, where an absence of talent is contributing to banks inability to meet some key obligations.

Consequently, Finbourne embarked on an ambitious training strategy to create its army of outreach experts. About half of the development programme’s participants were trained new skills to take into the heart of clients’ operations.

“Every which way you look at it, it’s a training problem,” Hurdiss said. “It’s not just going to be about churning out code out; it’s going to be around delivering a product for someone that they can easily use and solves all the business needs. There are engineering skills. There are very complex industry knowledge that they’ll need to have.

“You need to have engineers that can have softer skills and speak to clients and have architectural problem solving skills. Finding someone who has that off the bat is difficult,” he added.

Finbourne hasn’t simply plucked new recruits from its mail room and trained them to be highly expert engineers, but the basement-to-boardroom analogy isn’t entirely without merit.

“We’re taking engineers who might not have much business context, and training them up, and we’re taking consultants who have got a ton of of business expertise and experience in investments and accounting and training them up technically,” Hurdiss said.

“Then we’re putting them all together and deploying them out to do what is quite a difficult but very valuable job.”

Return on Investment

Economics would suggest that taking on a team of humans to do work that others are trying to get AI to execute could be expensive. But Hurdiss argues that AI is enabling Finbourne to make the numbers work as it reduces the manual tasks they need to carry out.

As well, Finbourne regards the programme as an “investment in customer service” that will bring greater returns as clients become better able to use the firm’s technologies and remain loyal to them.

Importantly, Hurdiss sees FDE as a differentiating factor over its competitors that will help it win more business.

“In a world where AI is disrupting software, having human beings in the loop, having human beings to help with the creative problem solving is something that is only increasingly rare, but increasingly valuable for our clients,” he said.