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Straight Through Processing, AI and the Process of Innovation

Thu, 08 Oct 2026 11:15:35 GMT

Straight Through Processing (STP) transformed capital markets by replacing fragmented, manual trade-processing workflows with connected systems capable of confirming and settling transactions electronically. Drawing on a discussion with James Karat, the article traces how STP emerged from a practical operational problem and helped reduce settlement times, errors, fraud risk and manual intervention across financial markets. It also examines the role of AI in improving modern STP processes, highlighting the value of machine learning for identifying root causes of transaction breaks while warning that generative AI can introduce unacceptable risks into high-stakes financial operations. More broadly, the article argues that meaningful innovation is most effective when it begins with real problems, strong domain knowledge and practical implementation rather than technology in search of a use case.

From the romance of disruption to the discipline of infrastructure: the end of Fintech innocence.

Wed, 07 Oct 2026 16:05:00 GMT

Fintech is entering a more mature phase. Rather than replacing traditional finance, emerging technologies such as tokenisation, stablecoins, CBDCs and blockchain are increasingly being integrated into regulated financial systems. Drawing on research presented at the 4th Annual Business of Blockchain & Tokenization Conference in Miami, this article explores why access does not always mean inclusion, why decentralisation does not remove power, and why tokenisation can sometimes distort user behaviour. It argues that the future of finance is likely to be hybrid—combining innovation and programmability with governance, resilience, consumer protection and trust.

Are AI Models as Irrationally Human as We Are? Inside Tomer Geva’s Seminar on LLM Cognitive Biases

Fri, 08 May 2026 15:00:00 GMT

This blog post summarizes a seminar by Professor Tomer Geva (Tel Aviv University) hosted at the Gillmore Centre. It explores a new systematic framework for evaluating cognitive biases in Large Language Models (LLMs). The post details how LLMs often mirror human irrationality but can also bypass it when they "recognize" the bias in play. It also covers Professor Geva’s visit to the Gillmore Lab, where he discussed the alignment between his research and the Centre's work on AI-driven decision-making and bias reduction.

Remaking Public Service: Can AI Celebrities Save Lives?

Fri, 01 May 2026 16:00:00 GMT

This blog post explores a recent seminar hosted by our research centre featuring Professor Alan Dennis (Indiana University), a world-renowned expert in Information Systems. The post examines the shift from traditional, one-way Public Service Announcements (PSAs) to interactive, AI-driven "Celebrity-as-a-Service" (CaaS). By leveraging Large Language Models (LLMs) and digital human technology, Professor Dennis demonstrates how "digital twins" of celebrities can provide scalable, one-on-one interactions that significantly increase public trust and health compliance. Additionally, the post highlights Professor Dennis’s subsequent visit to our Gillmore Lab, where he engaged with our researchers to discuss the future of AI-driven communication and its alignment with our centre’s current projects.

The future of real estate: Learning from the past

Thu, 11 Dec 2025 00:00:00 GMT

Professor Andrew Baum looks ahead to the future of real estate, arguing the industry needs to absorb the lessons of the past while adopting the tools of tomorrow.

Think bigger, Grow together

Wed, 07 May 2025 23:00:00 GMT

The UK has been acknowledged as a global FinTech powerhouse. Heather Xiao argues that future growth requires a shift in mindset, and that the industry must embrace 'Ecosystem Thinking.'