The Fintech Talents Festival returned for another year of fintech networking, discussions and deep dives into industry problems at the Brewery in London. To get a better view of the current UK fintech landscape, we followed the involvement of Rise, created by Barclays, the global community of global financial services innovators.
Established in 2015, Rise was introduced to the world with one aim: to fuse the speed, agility and innovation of fintechs with the security and scale of Barclays. Since then, the global fintech platform’s programmes have achieved a range of milestones.
Now, in 2023, the UK’s fintech sector needs support more than ever. Following difficult macroeconomic conditions for all industries, the sector has needed to fight to consolidate the position it has done so well to build throughout the last decade.
With this in mind, Rise is continuing its efforts to help give fintechs the boost they need, including with presence at events like the Fintech Talents Festival.
Rise fintech mentoring
To kick things off, Rise hosted a ‘fintech mentorship series’, in which several expert fintech mentors offered advice to startups. The event enabled startups to schedule one-to-one meetings with prominent fintech leaders.
Each startup representative was given half an hour to speak and connect with four of the eight expert mentors in a setup likened to ‘speed dating’.
Priya Guliani, CEO of decentralised identity platform EarthID and part of the Rise Growth Academy cohort, discussed her experience speaking to various mentors with The Fintech Times: “Above all, it was a very good experience. Primarily, my goal was to run through our value proposition and the challenges that we’re facing, from an extraction and scalability perspective, and get some insights into that.
“These meetings were centred around getting to know people, the introductions and making sure that you can build a connection and arrange a follow-up meeting and I managed to do that with all four mentors.”
We also sat down with Andrew Horton, CTO of Cairo-based data and analytics firm Zeal, who also explained the importance of making connections: “I met four mentors and I’ve left with things to do next and I’ve got connections that I can follow up with.
“When I look at the work I do today, so much of it involves going through people who know people that I met once upon a time, wherever that might be – so I’m always happy to talk. The mentors were very generous with what they told me and what they shared with me.”
Discussing AI use cases
Dimitrios Emmanoulopoulos, director and head of machine learning (ML) technologies for Barclays, also took to the ‘FTT AI Transformation Stage’ to give his talk titled ‘AI use cases for Financial Services‘. Emmanoulopoulos covered various methods to benchmark AI and ML technologies, as well as the impact generative AI could have in finance.
“What my team does in Barclays is review new technologies that come into the bank from an advanced analytics point of view – meaning everything beyond the reporting tools – starting from ML, traditional ML, AI and generative AI,” he explained.
Emmanoulopoulos also discussed the concept of graph neural networks supporting anti-money laundering efforts: “The graph shows who is interacting with whom. In this case, we don’t have structured tabular data; we have graph data training the algorithm from the top to be able to detect that graph’s features.
“So for example, in anti-money laundering, the feature could be one customer spreading equal amounts of money to 12 different accounts in a second. This can be depicted very well in a graph, so you need an algorithm to depict this and flag it as a fraudulent or non-fraudulent transaction.
“Again, this requires AI and ML at every level and the more real-time we go requires more and more expensive infrastructure.”
Taking a step back
On day two of the Fintech Talents Festival, Anastasiya Kizima, head of global ecosystem partnerships at Rise, was joined by Mariya Brown, head of EMEA innovation at BNY Mellon, the investment banking services holding company, on the ‘Fintech Talents Stage’.
Focusing on wealthtech, the session entitled ‘A new era of financial empowerment‘ covered closing the wealth gap, utilising artificial intelligence, regulation, developments and predictions for the future.
Brown explained her view that before firms engage with AI, many need to tackle fundamental issues first: “There have been quite a number of panels on AI. Coming more from the institutional background, I have to say we have to get a lot of the basics right before we move into AI.
“In the wealth world, or at least the bit that I see, a lot of it is legacy software, with a host of problems that have to be resolved: some of them are on the data side and others on the usability side. Regarding this, we have been making lots of progress. The reason I joined Pershing is because there was a transformation programme in place that’s reinventing everything we do.“
Banks working with fintechs
Brown also gave some advice of her own to aspiring fintechs: “I think, in all honesty, large institutions can’t innovate as quickly as small fintechs. But for the small fintechs, my advice would be to focus on a very narrow area. It’s very rarely that we go out looking for like a blanket solution because there are so many systems in place.
“But it is quite often that we go out looking for compliance solution that just addresses five points, or we’ll go looking for certain onboarding functionality. We’re very happy to integrate various fintechs and we have in the past, so for example, for portfolio management, we use a third party, and we have a very close partnership with them that works really well.”
Kizima also asked Brown about which area she is most interested in for the future: “A lot of people talk about the ageing population and I’m curious to see what solutions will appear in that space. Obviously, there’s a lot of noise around inclusion and serving the underserved and potentially a lot of that is related to education.
“Whereas when you’re talking about retirement age, a lot more intricate tools are required for that. How do you figure out what sort of decumulation is best for you if you take out a certain part of your portfolio every month, what does that mean? I think modelling that is very interesting.”
