Recent years have witnessed rapid increases in financial and healthcare data, due in part to advancements in financial data analytics tools, medical imaging, and the increasing availability of real-time data to infer most-probable narratives (see example use cases here and here). Professionals in these areas are making more decisions and must navigate increasingly complex systems. Significant investments are being made to deliver the right data and powerful insights. However, accounting for the exponential possibilities arising from this new data is stretching the capabilities of classical computing systems.

Enter quantum computing. It has been proven that quantum computing can have an advantage over classical approaches. Quantum computing does not merely provide an incremental speedup. It is the only known technology that can be exponentially faster than classical computers for certain tasks, potentially reducing calculation times from years to seconds. Quantum computing harnesses a different way of thinking, and necessities new and highly sought-after skills, distinct IT architectures, and novel strategies.

The potential applications of AI-quantum hybrid methods in solving highly-complex optimisation problems are drawing attention. In finance and healthcare, the use of quantum computing in parallel with classical computers is likely to bestow substantial advantages that classical computing alone cannot deliver. This is mainly due to the existence of complex multi-criteria decision-making scenarios in these two fields. Some potential quantum use cases include: banking security; financial optimisation, and; public health decision making scenarios, such as those required for large-scale pandemics.

The project funding is awarded by Nottingham Trent University's Strategic Research Fund.