Building a World First Financial Autopilot
27 August, 2025
How Banqora is Reshaping Capital Markets with AI
In a compelling episode of FinTech Focus TV, Toby sits down with Ernst Dolce, Co-Founder and CEO at Banqora, to explore the real-world challenges and opportunities facing capital markets infrastructure today. This conversation offers a rich exploration into how artificial intelligence (AI), data insight, and robust infrastructure are not only reshaping financial services but also redefining what's possible.
With over 20 years of experience spanning quant trading, risk management, structuring, and heading a trading book worth over $300 billion, Ernst brings both technical expertise and leadership insight to this rapidly evolving sector. From his early frustrations with outdated processes to building Banqora with a clear mission, his journey is a testament to why technology and talent go hand-in-hand when driving true innovation in FinTech.
As a FinTech recruitment firm with global reach, Harrington Starr is committed to connecting high-impact talent with game-changing businesses like Banqora. This episode shines a spotlight on the types of visionaries shaping the future, and the kinds of career paths emerging from such innovation.
The Origins of Banqora: From Industry Frustration to Founding Vision
Toby begins the interview by noting that Ernst is operating in “possibly the most exciting space within the sector at the moment.” Introduced by mutual friend and former guest Kevin Marcus, Ernst shares that Banqora was built to help financial institutions generate revenue, reduce operational costs, and increase efficiency, particularly across the often-ignored middle and back office.
His career journey began as a quant on a fixed income trading desk, where he enjoyed building models. He later moved into risk management but found the role overly focused on oversight. Seeking more dynamic involvement, he transitioned into structuring, where he built client solutions and eventually led large trading books focused on repo and securities lending.
The real turning point came when he was managing a vast book of transactions and constantly confronted by inefficiencies. From corporate actions to cost-heavy, error-prone back-office processes, Ernst found himself burdened by inefficiencies that cost both time and money. These challenges were common across asset managers, hedge funds, and banks, so Ernst decided to solve them at scale.
AI Before the Trend: Forecasting the Future in 2017
Ernst’s journey into AI began not in 2023, but back in 2017. During a Christmas trip to the US, he found himself drawn to the potential of AI to revolutionise finance. He wrote himself an email forecasting a 10-year shift toward AI-led infrastructure, predicting it would outpace blockchain in terms of applicability and speed. What made AI particularly compelling was its ability to operate as a layer on top of existing infrastructure, avoiding the collective dependency that slows blockchain adoption.
By January 2018, Ernst had made a personal commitment to enter the AI space in finance. Partnering with co-founder Dr Nicola Solden, the pair spent four years exploring how to reduce infrastructure costs, eliminate repetitive operations, and address global time zone inefficiencies for institutions operating across the US, Europe, and Asia.
The Cost of Inefficiency: Why AI Is Not Optional
Ernst describes the challenges he faced managing a large trading team, including receiving between 200 and 3,000 emails per day, maintaining 50 Bloomberg chat threads, and using seven to eight tools just to complete one repo transaction. Each transaction, representing billions in liquidity and value, was vulnerable to delays and mistakes.
One of the most staggering figures Ernst shares is the market-wide annual loss of $100 billion due to settlement failures. As the financial industry shifts from T+2 to T+1 settlement cycles, the window to resolve transactions has effectively been cut in half. Firms sticking with legacy infrastructure risk being left behind or facing costly disasters.
When the US transitioned to T+1, it reportedly resulted in a $30 billion loss in its first year, an ominous preview for European markets soon to follow. For Ernst, this change only strengthens the case for using AI to solve critical infrastructure challenges, particularly in trade settlement, asset recall, and time-sensitive operations.
The Role of FinTech in Closing the Innovation Gap
A recurring theme throughout the episode is the slow pace of innovation on the buy side. Ernst notes that 80% of asset managers’ technology budgets are spent on maintaining legacy systems, tools that provide little to no competitive edge. Meanwhile, asset management fees have dropped by 30% over the past decade in both the UK and Europe, pressuring firms to streamline costs and modernise systems.
Buy-side firms also face growing pressure from passive investment vehicles like ETFs. The expectation for faster, on-demand fund access means that inefficiencies and delays are no longer tolerable.
Ernst makes a powerful point: leaders in asset management now have two choices. They can embrace technology to unlock operational scale or continue with outdated systems and risk irrelevance. There’s no in-between.
Overcoming Resistance: The Reality of AI Adoption in Financial Services
While AI adoption is growing, estimated at 70% in the UK and projected to reach 80% by next year, Ernst cautions against mistaking adoption for transformation. Many organisations adopt AI superficially, lacking the discipline to integrate it meaningfully.
Referencing a joint survey from the Bank of England and FCA, Ernst explains that 60% of surveyed firms abandoned their AI projects due to a lack of visible value. The problem, he argues, isn’t the technology, it’s the implementation strategy. Firms fail to define clear use cases, leading to expensive and fruitless experiments.
At Banqora, AI is not a product in itself, it’s a means to an end. The team helps clients identify high-impact pain points and focuses AI efforts accordingly. Whether it’s automating collateral tracking or reducing manual spreadsheet work, the goal is to free up skilled employees to do more meaningful, revenue-generating tasks.
Democratising Access: How AI Levels the Playing Field for Small Firms
Another insight Ernst shares is how AI is helping smaller financial firms compete with much larger players. In the past, only big institutions could afford robust infrastructure and teams to manage high-volume transactions. Today, with the right AI tools, small to mid-sized firms can operate with speed, accuracy, and insight on par with the giants.
He urges smaller firms to view AI not as a luxury, but as a necessity. Many market opportunities, such as niche loans or products unprofitable for larger players, are now accessible thanks to AI-enabled efficiency. With fewer barriers to entry and no excuse not to adopt, the time for smaller players to act is now.
Data First: The Foundation of Any FinTech Strategy
According to Ernst, finance can be boiled down to four elements: data, infrastructure, tools, and decision-making. If the data is poor, the rest collapses.
Banqora prioritises data quality in every implementation. Clean, reliable data allows for better tooling, faster decisions, and competitive differentiation. However, many firms struggle to get their data house in order. This is particularly problematic in AI initiatives, where data integrity directly impacts outcomes.
Ernst underscores that firms must begin with the basics. Before launching any AI project, organisations need to identify where data can be used to solve concrete problems and invest in those areas first. From our perspective, building the right team is just as important as building the right systems; specialist data recruitment gives firms the talent needed to manage, govern, and innovate with their data.
Go-to-Market Challenges: Facing Feedback and Finding Product-Market Fit
Toby and Ernst discuss the difficulty of bringing a product to market in the FinTech space. One particularly vivid anecdote Ernst shares is the day he received 15 client rejections, including a final “no” at 7 pm from a client he had spent weeks courting. The blow was so severe that he walked home for 45 minutes just to clear his mind.
But these rejections were valuable. Each one refined Banqora’s product, improved the pitch, and clarified where clients found the most value. Today, what once took a month to validate now takes as little as two days, thanks to better tooling, client understanding, and internal processes.
Building the Right Team: People, Culture, and the Pursuit of Excellence
As a FinTech recruitment firm, Harrington Starr knows that building the right team is fundamental to any company’s success. Ernst reinforces this by explaining how critical it was to hire people with domain expertise, client empathy, and the ability to deliver high-quality solutions from day one.
He shares that Banqora deliberately avoided “mom and pop” investors, opting instead for a cap table composed of venture capitalists, private equity, and senior executives from hedge funds, banks, and asset managers. These backers brought not just funding, but deep understanding of the problem Banqora is solving.
Ernst also speaks passionately about company culture. Fun is a core component. The Banqora team travels together, dines together, and deliberately sets aside time to connect outside of work. Building trust and personal connection, he believes, leads to stronger collaboration and more resilient teams.
What’s Next for Banqora: Scale, Consistency, and Customer Trust
The future of Banqora is about consistency and discipline. The team is focused on repeating its early successes, continuing to deliver measurable value, and expanding its customer base through trust and performance.
Ernst recognises that FinTech innovation isn’t a sprint, it’s a marathon. With settlement cycles shrinking, client expectations rising, and infrastructure costs becoming unsustainable, firms need trusted partners who can deliver at scale. Banqora’s mission is to be that partner.
Words of Advice: What Ernst Would Tell His 2018 Self
As the episode draws to a close, Toby asks Ernst what advice he’d give to his 2018 self. Ernst is clear: don’t beat yourself up. Leaving a high-paying, secure job in finance to start a company is terrifying. And even when you believe in your vision, the reality is always harder than expected.
He notes that the startup journey involves learning about HR, compliance, cybersecurity, and more, all areas he didn’t manage directly in his previous roles. He advises founders to ensure their support systems are in place. Friends who challenge you, advisors who guide you, and investors who demand rigour are essential to survival.
He also credits advisors like Jed and Adam, early backers from a venture firm called Ler, for helping shape Banqora’s strategy and expectations. Their continued involvement has been pivotal to the company’s growth.
At Harrington Starr, we believe that transformative FinTech businesses like Banqora require the right talent to fuel growth and innovation. Whether you're building AI infrastructure, scaling a trading platform, or digitising the middle and back office, we specialise in connecting forward-thinking firms with top-tier professionals.
