On the path towards a quantum economy

Rapid technical innovation in quantum computing has yielded an array of hardware platforms that can run increasingly sophisticated algorithms. In the real world, however, such technical advances will remain little more than a curiosity if they are not adopted by businesses and the public sector to drive positive change. As a result, one key priority for the UK’s National Quantum Computing Centre (NQCC) has been to help companies and other organizations to gain an early understanding of the value that quantum computing can offer for improving performance and enhancing outcomes.
To meet that objective the NQCC has supported several feasibility studies that enable commercial organizations in the UK to work alongside quantum specialists to investigate specific use cases where quantum computing could have a significant impact within their industry. One prime example is a project involving the high-street bank HSBC, which has been exploring the potential of quantum technologies for spotting the signs of fraud in financial transactions. Such fraudulent activity, which affects millions of people every year, now accounts for about 40% of all criminal offences in the UK and in 2023 generated total losses of more than £2.3 bn across all sectors of the economy.
Banks like HSBC currently exploit classical machine learning to detect fraudulent transactions, but these techniques require a large computational overhead to train the models and deliver accurate results. Quantum specialists at the bank have therefore been working with the NQCC, along with hardware provider Rigetti and the Quantum Software Lab at the University of Edinburgh, to investigate the capabilities of quantum machine learning (QML) for identifying the tell-tale indicators of fraud.
“HSBC’s involvement in this project has brought transactional fraud detection into the realm of cutting-edge technology, demonstrating our commitment to pushing the boundaries of quantum-inspired solutions for near-term benefit,” comments Philip Intallura, Group Head of Quantum Technologies at HSBC. “Our philosophy is to innovate today while preparing for the quantum advantage of tomorrow.”
Another study focused on a key problem in the aviation industry that has a direct impact on fuel consumption and the amount of carbon emissions produced during a flight. In this logistical challenge, the aim was to find the optimal way to load cargo containers onto a commercial aircraft. One motivation was to maximize the amount of cargo that can be carried, the other was to balance the weight of the cargo to reduce drag and improve fuel efficiency.
“Even a small shift in the centre of gravity can have a big effect,” explains Salvatore Sinno of technology solutions company Unisys, who worked on the project along with applications engineers at the NQCC and mathematicians at the University of Newcastle. “On a Boeing 747 a displacement of just 75 cm can increase the carbon emissions on a flight of 10,000 miles by four tonnes, and also increases the fuel costs for the airline company.”

With such a large number of possible loading combinations, classical computers cannot produce an exact solution for the optimal arrangement of cargo containers. In their project the team improved the precision of the solution by combining quantum annealing with high-performance computing, a hybrid approach that Unisys believes can offer immediate value for complex optimization problems. “We have reached the limit of what we can achieve with classical computing, and with this work we have shown the benefit of incorporating an element of quantum processing into our solution,” explains Sinno.
The HSBC project team also found that a hybrid quantum–classical solution could provide an immediate performance boost for detecting anomalous transactions. In this case, a quantum simulator running on a classical computer was used to run quantum algorithms for machine learning. “These simulators allow us to execute simple QML programmes, even though they can’t be run to the same level of complexity as we could achieve with a physical quantum processor,” explains Marco Paini, the project lead for Rigetti. “These simulations show the potential of these low-depth QML programmes for fraud detection in the near term.”
The team also simulated more complex QML approaches using a similar but smaller-scale problem, demonstrating a further improvement in performance. This outcome suggests that running deeper QML algorithms on a physical quantum processor could deliver an advantage for detecting anomalies in larger datasets, even though the hardware does not yet provide the performance needed to achieve reliable results. “This initiative not only showcases the near-term applicability of advanced fraud models, but it also equips us with the expertise to leverage QML methods as quantum computing scales,” comments Intellura.
Indeed, the results obtained so far have enabled the project partners to develop a roadmap that will guide their ongoing development work as the hardware matures. One key insight, for example, is that even a fault-tolerant quantum computer would struggle to process the huge financial datasets produced by a bank like HSBC, since a finite amount of time is needed to run the quantum calculation for each data point. “From the simulations we found that the hybrid quantum–classical solution produces more false positives than classical methods,” says Paini. “One approach we can explore would be to use the simulations to flag suspicious transactions and then run the deeper algorithms on a quantum processor to analyse the filtered results.”
This particular project also highlighted the need for agreed protocols to navigate the strict rules on data security within the banking sector. For this project the HSBC team was able to run the QML simulations on its existing computing infrastructure, avoiding the need to share sensitive financial data with external partners. In the longer term, however, banks will need reassurance that their customer information can be protected when processed using a quantum computer. Anticipating this need, the NQCC has already started to work with regulators such as the Financial Conduct Authority, which is exploring some of the key considerations around privacy and data security, with that initial work feeding into international initiatives that are starting to consider the regulatory frameworks for using quantum computing within the financial sector.
For the cargo-loading project, meanwhile, Sinno says that an important learning point has been the need to formulate the problem in a way that can be tackled by the current generation of quantum computers. In practical terms that means defining constraints that reduce the complexity of the problem, but that still reflect the requirements of the real-world scenario. “Working with the applications engineers at the NQCC has helped us to understand what is possible with today’s quantum hardware, and how to make the quantum algorithms more viable for our particular problem,” he says. “Participating in these studies is a great way to learn and has allowed us to start using these emerging quantum technologies without taking a huge risk.”
Indeed, one key feature of these feasibility studies is the opportunity they offer for different project partners to learn from each other. Each project includes an end-user organization with a deep knowledge of the problem, quantum specialists who understand the capabilities and limitations of present-day solutions, and academic experts who offer an insight into emerging theoretical approaches as well as methodologies for benchmarking the results. The domain knowledge provided by the end users is particularly important, says Paini, to guide ongoing development work within the quantum sector. “If we only focused on the hardware for the next few years, we might come up with a better technical solution but it might not address the right problem,” he says. “We need to know where quantum computing will be useful, and to find that convergence we need to develop the applications alongside the algorithms and the hardware.”
Another major outcome from these projects has been the ability to make new connections and identify opportunities for future collaborations. As a national facility NQCC has played an important role in providing networking opportunities that bring diverse stakeholders together, creating a community of end users and technology providers, and supporting project partners with an expert and independent view of emerging quantum technologies. The NQCC has also helped the project teams to share their results more widely, generating positive feedback from the wider community that has already sparked new ideas and interactions.
“We have been able to network with start-up companies and larger enterprise firms, and with the NQCC we are already working with them to develop some proof-of-concept projects,” says Sinno. “Having access to that wider network will be really important as we continue to develop our expertise and capability in quantum computing.”
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