The Future of Technology: AI in Trading & Workflows

Building the Future of FinTech with AI

In a landmark episode of FinTech Focus TV, recorded live at the FIX EMEA Trading Conference, Toby Babb sits down with Paul Brennan, Chief Strategy Officer at Imandra, to discuss one of the most pressing and transformative topics in financial services: the adoption and integration of artificial intelligence (AI). With the financial technology landscape evolving at an unprecedented pace, the conversation brings fresh insight into how symbolic AI and reasoning engines are helping capital markets shift from traditional systems to intelligent, data-driven operations.

Harrington Starr, as a leading FinTech recruitment business, recognises that meaningful discussions like this help shape the direction of the sector. From recruiting the next wave of AI talent to understanding how firms are reimagining their technology strategies, this episode offers valuable guidance for companies preparing for the future of financial services.

Imandra’s Role in FinTech: Elevating AI Through Symbolic Reasoning

Paul Brennan begins by introducing Imandra as an “automated reasoning” company—an organisation at the forefront of symbolic AI. Unlike the more widely discussed generative AI tools powered by neural networks and machine learning, symbolic AI is grounded in mathematical logic. This means Imandra builds systems that are deterministic, auditable, and designed to avoid the opaque decision-making that often troubles traditional large language models.

In the context of capital markets, where trust, accuracy and regulation are paramount, symbolic AI presents a significant opportunity. Paul explains that many people at the FIX EMEA Trading Conference may not yet be familiar with the term “automated reasoning,” but that’s precisely why this conversation is so vital. Imandra’s AI engines are built for mission-critical use cases—those where correctness is non-negotiable.

With an approach rooted in verifiability and transparency, Imandra’s technology allows firms to confidently integrate AI into workflows that demand high precision. These use cases are increasingly relevant as financial institutions seek to evolve while maintaining compliance and governance standards.

Practical Use Cases of AI in Financial Services and Trading

The discussion moves quickly into practical territory, with Paul offering a compelling overview of how AI is being used across the FinTech and trading ecosystem. He notes that the adoption of AI in financial services varies drastically between organisations. Some firms are still at the beginning stages—experimenting with tools like ChatGPT to summarise emails—while others are using advanced AI systems to analyse massive datasets and generate novel trade ideas that elude human analysts.

Paul makes it clear that this is not a debate about whether firms should buy or build their AI solutions, nor is it about cloud versus on-premise. Those questions are largely in the past. What matters now is how firms can apply AI tools effectively. Each company has its own unique requirements and goals, and successful integration depends on personalisation and thoughtful implementation.

This theme of real-world AI usage is echoed throughout the conversation. Financial organisations are no longer just exploring AI—they are starting to demand tangible returns on investment. By assembling the right combination of AI tools, firms can accelerate their productivity and find competitive advantages in areas such as trade execution, compliance, client engagement and risk management.

Enhancing FinTech Recruitment Through AI Awareness

As FinTech recruitment specialists, Harrington Starr recognises that talent strategy must evolve in parallel with technological innovation. With firms adopting more complex AI systems, there is growing demand for professionals who understand not only data science and engineering, but also symbolic AI, automated reasoning, and agentic systems.

Paul’s perspective reinforces the importance of hiring strategically. He notes that some firms are building entire networks of AI agents—systems composed of multiple autonomous components, each driven by a large language model. These agents are designed to replicate human workflows, particularly those that are monotonous and repetitive. Often, a central coordinating agent—likened to a “chief of staff”—oversees the network, ensuring that each component works harmoniously to deliver outcomes.

This development marks a fundamental shift in how FinTech firms will structure their technology teams going forward. The future will require a hybrid skillset—professionals who understand both the technical underpinnings of AI and the business context in which these tools are deployed. Harrington Starr is actively guiding clients in building teams capable of navigating this complexity.

Productivity and Efficiency: The Driving Forces Behind AI Adoption

One of the most significant themes that emerges from the episode is the importance of productivity and efficiency in modern financial services. With global markets becoming increasingly volatile and competitive, the ability to do more with less is essential.

Toby and Paul discuss how AI is no longer simply about enhancing speed. Instead, the focus has shifted to quality—using AI to improve accuracy, transparency and value delivery. As AI systems become more advanced, they are able to support better decision-making, automate routine tasks, and unlock deeper insights from data.

Paul reflects on how firms are using AI agents to replace labour-intensive manual processes with intelligent automation. These agentic systems can understand tasks, execute workflows, and even create content or analysis on demand. The benefits are clear: increased speed, better accuracy, and more time for humans to focus on high-impact work.

This is particularly relevant for financial recruitment. Firms seeking to improve operational efficiency will increasingly look to hire professionals who can deploy, manage and evolve AI systems. Harrington Starr is committed to connecting companies with talent that understands the strategic role of AI in business transformation.

Trust, Transparency, and Risk in AI Systems

Despite the promise of AI, Paul acknowledges that there is still scepticism in the market. Trust is a major hurdle. Firms are cautious about integrating AI into critical systems because of concerns around transparency, hallucinations, and bias—particularly when using generative models.

Imandra’s approach to this challenge is to build reasoning engines that are inherently trustworthy. Symbolic AI, by design, does not rely on opaque training data or probabilistic outputs. Instead, it operates on logic and rules that can be verified, audited and understood. This makes it well-suited for financial services, where regulation, compliance and auditability are essential.

Paul explains that this is not just about risk mitigation—it’s also about creating systems that users and stakeholders can trust. By integrating reasoning engines into larger AI frameworks, firms can ensure that their decision-making processes are both efficient and accountable.

This is a vital point for hiring managers. As more firms look to deploy AI, there will be greater demand for professionals with expertise in governance, compliance and ethical AI. Harrington Starr is helping clients identify and attract the next generation of FinTech leaders who can drive responsible innovation.

A Global View on AI Adoption in Financial Services

Toby raises the question of whether there is a significant difference between AI adoption in the US and Europe. While the US is often viewed as a leader in AI innovation, particularly in terms of building infrastructure and foundational models, Paul offers a more nuanced perspective.

He argues that the actual implementation of AI—using it within organisations for real-world purposes—is progressing at a similar pace across both regions. Financial firms in the US and Europe face comparable challenges around regulation, data security, fiduciary responsibility, and change management. As such, the journey toward meaningful AI adoption is shared.

This insight is essential for international recruitment. Harrington Starr operates across multiple markets, and understanding these dynamics allows the firm to advise clients on where to find the right talent and how to build diverse, globally aware teams that can navigate the evolving FinTech landscape.

Moving Beyond the Proof-of-Concept: Building AI that Scales

A critical point discussed in the episode is the need for financial firms to move beyond proof-of-concept (POC) initiatives. Paul believes that many organisations stall at the experimentation stage because they lack a clear roadmap for scaling AI systems.

To succeed, firms must identify clear objectives, assess ROI, and build frameworks that allow for quick iteration and “failing fast.” This means breaking down internal barriers—such as data access restrictions and procurement challenges—and creating space for experimentation.

Leadership buy-in is also essential. Paul explains that many POCs fail because they lack sponsorship from senior executives. True AI adoption requires not just investment but cultural commitment—a willingness to embrace continuous learning and innovation.

For FinTech recruiters, this shift means focusing not just on technical skills but also on leadership, communication and change management. Harrington Starr works with firms to find individuals who can champion AI from both a technical and strategic standpoint.

Augmentation Over Replacement: AI’s Role in the Future of Work

One of the most important messages from this conversation is that AI is not here to replace people—it’s here to empower them. Paul draws a powerful analogy: modern aircraft have autopilot systems, but they still require human pilots. Similarly, AI in trading is about augmentation, not displacement.

By automating low-value tasks, AI allows humans to focus on creative, strategic and impactful work. It gives professionals the tools to be more effective, not redundant. The key is to retrain and upskill, to embrace the change rather than resist it.

This philosophy is at the heart of Harrington Starr’s recruitment approach. Helping professionals transition into new roles, acquire new skills, and adapt to a changing landscape is essential to building a resilient FinTech workforce. AI is not a threat—it’s a partner in progress.

What’s Next for Imandra and AI Builders in 2025

As the episode wraps up, Paul offers a glimpse into what’s next for Imandra. The company is preparing to launch a new product designed specifically for AI builders—engineers and developers working in languages like Python who are creating agentic frameworks for enterprise applications.

This tooling will enable teams to explore what their code does, validate system behaviours, and ensure robustness in critical functions. It’s aimed at those building the next generation of AI systems—intelligent, transparent, and trustworthy.

The emergence of this kind of specialised tooling signals a new era in FinTech. As demand grows for systems that combine performance with precision, so too does the need for skilled professionals who can build and manage them. Harrington Starr is already working with clients to identify these talent needs and ensure that the right people are in place to support the next wave of innovation.

Embracing the Future of FinTech With the Right Talent

This live episode of FinTech Focus TV from the FIX EMEA Trading Conference offers a timely and insightful look into how AI is shaping the future of financial services. With Paul Brennan offering clarity on symbolic AI, agentic systems, and trustworthy automation, and Toby Babb guiding the discussion with insight and relevance, it is a conversation that reflects the real momentum building across the sector.

As the FinTech industry evolves, so must the strategies for sourcing, attracting and retaining top talent. Harrington Starr remains at the forefront of this transformation—supporting organisations as they adopt new technologies, build intelligent systems, and prepare for the future of work.

AI is no longer a distant concept—it’s here, and it’s happening now. The firms that embrace it thoughtfully, and the professionals who learn to work alongside it, will be the ones who define the next chapter of FinTech success.