AI Innovation in Capital Markets
In this episode of FinTech Focus TV, recorded live at the AI in Capital Markets Summit in New York City, Toby Babb sits down with Theo Bell, Head of AI Product at Rimes, to explore the cutting-edge convergence of artificial intelligence and capital markets. As a FinTech recruitment business deeply invested in advancing technology conversations, Harrington Starr brings you this in-depth dialogue with one of the industry’s most insightful AI leaders.
From Theo’s deep experience at Palantir and Goldman Sachs to her transformative work at Rimes, this conversation reveals how AI is reshaping enterprise data management, revolutionising operational efficiency, and transforming the future of work across FinTech. For clients and candidates in FinTech recruitment, this is essential listening and reading.
FinTech Recruitment Meets AI Leadership
Theo Bell, Head of AI Product at Rimes, brings together a unique blend of experience in data, finance, and artificial intelligence. With an eight-year tenure at Palantir and formative years at Goldman Sachs in electronic equities trading, Theo’s journey to leading AI product innovation at Rimes reflects the evolution of FinTech talent: data-driven, agile, and innovation-obsessed.
Rimes, a longstanding force in enterprise data management, originally built its reputation in benchmark and index data. Today, the company offers a full-service investment management platform, helping clients master and manage data across the front, middle, and back office. This expansion mirrors a broader trend in FinTech recruitment, where roles are increasingly converging across data, infrastructure, and product leadership.
Why FinTech Hiring Is Prioritising AI and Data Quality
One of the key themes in this episode is data quality, a subject often overlooked in the past but now mission-critical for AI success. Theo notes how data issues like improper corporate actions are immediately surfaced when AI models are applied. As organisations accelerate AI adoption, poor-quality data becomes a blocker to success.
From a FinTech hiring perspective, this shift is monumental. Demand is rising for professionals who not only understand AI but can also ensure the integrity of datasets that feed into machine learning systems. As Theo puts it, AI is “a really good way of finding all the holes in your data.” This elevates data governance, ownership, and transparency from back-office concerns to strategic imperatives.
This is where businesses like Rimes provide value, offering “AI-ready” data that ensures organisations can trust the outputs of their models. And trust is vital, especially when considering the growing concerns around hallucination in generative AI. For FinTech staffing firms and capital markets employers, the focus is increasingly on finding talent who can both build and interrogate these systems with confidence.
Product Innovation at Pace: AI Product Leadership in FinTech
Toby highlights the rapid acceleration of AI as “a pace that we’ve never seen before in the history of all tech.” For Theo, this creates a challenging yet exhilarating environment. Her remit isn’t about pivoting Rimes’ entire business model; it’s about integrating AI to enhance product relevance and performance.
This pragmatic approach resonates strongly within FinTech recruitment. Organisations aren’t necessarily looking for flashy AI projects; they want to embed AI into existing products in a way that’s sustainable, measurable, and valuable. Theo shares that the worst option is “doing nothing,” which can paralyse businesses overwhelmed by the breadth of AI options. Instead, Rimes created an AI lab to foster experimentation and rapid prototyping, a strategy that allowed them to try, fail, and refine.
Initially, the lab was a ring-fenced team focused on isolated testing. However, Theo quickly realised that AI engineers needed to be embedded directly within product teams to unlock meaningful impact. By aligning domain experts with AI talent, Rimes is now producing tools and models that are rooted in business value, a playbook many FinTechs are now adopting.
Building the Future with Agentic AI: FinTech Jobs of Tomorrow
Theo predicts that 2025 will be “the year of agentic AI.” Rather than relying on massive, general-purpose models that are difficult to test, Rimes is now building small, fine-tuned AI agents that perform specific tasks with precision and reliability. These agents are designed to work together, forming intelligent systems that can be scaled incrementally.
This modular strategy offers critical insights for those hiring in FinTech. The market is evolving toward roles that combine niche technical expertise with domain-specific understanding. It’s no longer just about hiring AI engineers; it’s about hiring individuals who can embed AI into core business functions, from customer service to compliance and portfolio management.
Theo shares her experience embedding AI agents into Rimes’ operations, such as analysing incoming support tickets, routing them based on complexity, and monitoring service delivery. These aren’t experiments, they’re early-stage implementations driving measurable efficiency. In recruitment terms, it’s a clear signal that future talent will need to work across silos, blending AI fluency with practical business awareness.
Redefining Productivity and Efficiency in Capital Markets
Throughout the conversation, Toby and Theo explore the interplay between efficiency and productivity, two buzzwords that dominate AI discussions. At Rimes, AI is being used to optimise internal operations, not by replacing people, but by augmenting them.
Theo describes how a digital twin of Rimes’ data environment enables AI to streamline workflows, triage client tickets, and enhance training decisions. For instance, AI agents can determine whether a support ticket should go to a junior analyst or a senior expert. They can also flag trends in service quality that suggest a need for additional training or resources.
This isn’t just a story of automation; it’s about creating a more fulfilling work environment. By eliminating repetitive tasks like copy-pasting into Excel or refreshing dashboards, employees can focus on high-impact, strategic work. From a FinTech recruitment lens, it underscores a powerful shift: employers want people who can think creatively, work alongside machines, and drive strategic value.
AI, Collaboration, and the Rise of a New FinTech Culture
One of the most refreshing insights Theo shares is how collaborative the AI space has become. Events like the AI in Capital Markets Summit are no longer about grandstanding, they’re about knowledge-sharing, openness, and collective innovation. According to Theo, the AI community is more open about failures than ever before, fostering a culture where experimentation is not only accepted but encouraged.
This cultural shift aligns perfectly with how FinTech recruitment is changing. Technical skills alone are no longer enough. Companies are looking for adaptable individuals who embrace learning, engage with peers, and can navigate the uncertainties of an ever-evolving space. In Theo’s words, “The only certainty here is uncertainty.”
Her prediction? As AI agents begin talking to each other, across systems, departments, and even organisations, the industry will need a shared language or protocol (such as the emerging “Model Context Protocol”) to facilitate seamless communication. This trend is set to redefine enterprise architecture, job roles, and inter-company workflows alike.
Capital Markets and AI: Human-Centric Innovation at the Core
Despite all the technological advancement, Theo remains grounded in a human-centric view of innovation. She emphasises that AI’s role is to enable people to do the work that really matters, strategic, value-driven, and intellectually engaging tasks.
Even as armies of AI agents begin transforming capital markets, she doesn’t foresee a world without humans. Instead, she sees a future where professionals are empowered, not replaced. In FinTech hiring, this perspective is crucial. The most successful companies in 2025 will be those that balance technical innovation with cultural evolution, giving employees the tools and space to excel.
Toby and Theo also reflect on the near future. While there’s been a lot of talk about AI, she believes that by the end of 2025, we’ll see real agents in production. This is a watershed moment for FinTech, where the hype is giving way to tangible outcomes. And with businesses like Rimes leading the charge, the expectations for enterprise AI are only growing.
Rimes at 30: A FinTech Legacy Reinvented with AI
As Rimes approaches its 30th anniversary, the company is not resting on its laurels. Theo reveals that part of her mission is to help clients understand that Rimes is more than just a benchmark and index provider. With market-leading capabilities in data mastering, investment management, and now AI-powered solutions, Rimes is positioning itself as a thought partner for capital markets firms on their digital transformation journeys.
For FinTech staffing businesses like Harrington Starr, this offers a blueprint for the future of client engagement. Thought leadership, innovation partnerships, and long-term support are increasingly valued over point solutions. And the demand for AI-savvy professionals who can facilitate these transitions has never been higher.
Theo’s final message is a call to collaboration. Whether it’s sharing AI expertise, helping clients make sense of their data, or embedding engineers into cross-functional teams, success in FinTech depends on trust, experimentation, and a shared vision of progress.
Conclusion: AI Talent, Trustworthy Data, and the Future of FinTech Recruitment
This episode of FinTech Focus TV offers a masterclass in AI leadership from one of the industry’s brightest minds. Theo Bell’s practical, human-centric approach to AI product development at Rimes provides a roadmap for any FinTech firm seeking to stay ahead in the data-driven age.
For Harrington Starr and other FinTech recruitment businesses, the key takeaways are clear: the market is evolving rapidly, AI is moving from concept to production, and the demand for forward-thinking talent is surging. Clients need teams who can build and trust AI. Candidates need to combine technical fluency with adaptability and domain expertise.
As FinTech enters the next phase of intelligent automation, partnerships between agents, people, teams, and technology will define success. And at the centre of it all is talent: the human intelligence powering artificial intelligence.
