[WiS Seminar Series]: Complexity, Interpretability, and Trust. Lessons from Quantitative Finance
Bush House, Strand Campus, London
Abstract
Quantitative finance operates at the intersection of mathematics, computation, and decision-making under uncertainty, in settings where models must be both technically sound and operationally usable. In this talk, Dr Dialid Santiago will draw on examples from quantitative finance to discuss three lessons that are increasingly relevant across computational disciplines: the limits imposed by computation, the enduring value of interpretable models, and the challenge of communicating uncertainty.
Dialid will also draw on examples from quantitative finance to highlight three related themes. First, she will discuss practical computational challenges such as intraday full revaluation and real-time Greek calculation, illustrating how algorithmic complexity, numerical stability, and time constraints shape model design and deployment. Second, she will revisit the Black–Scholes model to explore why simple and analytically tractable frameworks continue to play an important role alongside more complex alternatives, and what their transparency reveals about assumptions and limitations. Finally, Dialid will consider approaches to communicating uncertainty, using examples such as inflation fan charts and visualisations of stochastic processes.
Biography
Dr Dialid Santiago (also known as _Quant Girl_) is a mathematician and Quantitative researcher working at the intersection of mathematical modelling, computation, and financial decision-making under uncertainty. She has nine years of experience as a quantitative analyst, designing and implementing models for pricing and risk management across multiple asset classes, including equities, credit, commodities, and rates.
She holds a PhD in Statistics from the University of Warwick, where her research focused on non-linear stochastic processes, as well as degrees in mathematics and statistics. She currently works in the Commodities Front Office Quant team at Bank of America, and has previously held roles at Citigroup, Barclays, and The Co-operative Bank. Her interests include computational modelling, interpretability, and the use of data visualisation to communicate uncertainty in complex systems.
Attending the event
For external visitors, please email Alfie Abdul-Rahman (alfie.abdulrahman@kcl.ac.uk) to arrange access.
Location: Bush House Centre Block, (S)5.01
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