Quantum computing will redefine geopolitical advantage

In less than a fortnight Sibos 2026 kicks off in Miami, Florida. High on the agenda is how artificial intelligence (AI) will reshape financial services when combined with quantum computing.

These two geostrategic innovations may become symbiotic: with AI serving to stabilise fragile quantum hardware, and quantum computing accelerating complex data processing.

In an exclusive interview with Finextra, Lionel Martellini, founding director of the EDHEC Quantum Institute, and Dr Dimitrios Salampasis, associate dean and associate professor, emerging technologies and fintech at Swinburne University of Technology, unpacked how quantum computing could create genuine competitive advantage in financial services, and where the hype runs ahead of the results.

AI, quantum computing, and finance

Quantum physics is characterised by the mechanics of waves. It theorises that until observed, the velocity and position of a subatomic particle — such as a photon or electron — occupies a ‘cloud of probability’ in space and time, as opposed to a defined point, à la classical mechanics. This counterintuitive state of matter is known as a superposition, meaning particles can exist in more than one position in spacetime at a given moment. Once observed, the waveform collapses. 

While this may sound like the stuff of science fiction, the theory of Quantum Electrodynamics (QED) has proven to be one of the most precise scientific theories ever written down, and has supported technological innovations from lasers to GPS.

However, the latest technology powered by quantum physics — quantum computing — could be the most transformative yet. The potential of subatomic particles, or information, to exist not just in binary states but in superpositions, has radical implications for computation. No longer must the language of machines rely on either zeros or ones; it can use quantum bits, or qbits, to represent a combination of these numbers simultaneously. This exponentially increases computational power, enabling problems to be solved that are too complex for classical computers.

Dr Salampasis explained that quantum computing is currently in an early commercial experimentation phase, with companies around the globe testing whether quantum computers can deliver measurable advantages to real business problems:

“Banks and financial institutions are currently exploring quantum computing in areas including portfolio optimisation, risk management, derivative pricing, fraud detection, trading and financial modelling,” he said. “Many of these use cases involve evaluating massive volumes possible outcomes or identifying optimal solutions within very complex systems.”

In September 2025, for example, HSBC and IBM reported results from an experiment using real European corporate bond trading data. Their quantum-assisted approach achieved up to a 34% improvement in predicting whether a client would accept a quoted bond price compared with the classical approaches used as benchmarks.

“This was significant because it involved an actual financial-market problem rather than an artificial laboratory exercise,” Dr Salampasis pointed out.

Regarding portfolio optimisation, Martellini asserted that quantum computing will bring considerable benefits — notwithstanding the success rates using classical methods.

“Quantum computing to some looks like a solution desperately in search of a problem,” he said. “But in portfolio optimisation it can add real value, not just to the allocation stage but to the universe selection stage. Most right now are using heuristics to select securities that align with their investment plans, whether it be big stocks or low-carbon exposure, et cetera. Quantum computing can make a big difference here, once the hardware matures.”

The reason this technology will be so powerful in the universe selection stage, Martellini explained, is that investors often have a plethora of constraints to satisfy. The constraints could be ethical or ESG-related, sector-related, or purely financial. With such specifications in mind, in order to calculate the optimal subset of 100 securities from 500, for example, the possible combinations are inconceivably vast. In fact, the figure would be “greater than the number of atoms in the visible universe,” Martellini said. Whereas classical computers would take more than a millennia to run a calculation like this, quantum computers could do it near-instantly.

Martellini predicted that, once quantum hardware is mature, financial services may adopt a hybrid approach to portfolio optimisation, whereby quantum methods are deployed for selecting the universe, while classical methods — refined by AI — are deployed at the allocation stage.   

Quantum’s technical challenges

Before the full potential of AI and quantum computing can be unlocked, the financial services industry has several challenges to address, the most fundamental being an engineering feat.

“The biggest challenge is building quantum computers that are sufficiently stable, reliable and financially viable to solve useful problems consistently,” Dr Salampasis explained. “As machines, quantum computers are extraordinarily sensitive. Small environmental disturbances can introduce errors into calculations. As the machines become larger and calculations become more complicated, managing those errors becomes substantially more difficult.”

One way to manage extremely complex quantum hardwire could be AI. Dr Salampasis argued that it would help identify errors, optimise performance and potentially discover better ways of performing quantum calculations. Google DeepMind’s AI system, AlphaQubit, for example, is designed to improve the identification of errors in quantum computers. In this way it is possible that AI technology will become symbiotic with quantum computers — forming part of the infrastructure needed for them to run effectively.

Another key challenge will be preparing financial services’ security infrastructure for a future in which today’s public-key cryptography is no longer safe.

“Powerful quantum computers could undermine some of the encryption methods currently used to protect financial transactions and sensitive information,” Salampasis precited. “Governments and technology organisations are therefore already introducing new encryption standards designed to withstand quantum attacks.”

J.P. Morgan is among the few currently preparing for future decryption threats by studying post-quantum encryption algorithms to protect sensitive financial data. Meanwhile, the European Securities and Markets Authority (ESMA) has published a report characterising the rise of quantum computing as a strategic threat to the cryptographic protocols securing global financial markets.

Martellini argued that the institutions not already investing in post-quantum cryptography are late:

“Even though we don’t have a clear timeline for when this threat will materialise, we are seeing new developments all the time that require fewer and fewer qbits to run these computations. The deadline is approaching fast. It could be the end of this decade or just after. There is no way that waiting is a good strategy in the face of these threats.”

Already, the giants of the tech world are shoring up their defences. Google, for its part, is has scheduled its post-quantum cryptography migration to 2029, and the US administration has asked that all sensitive systems be upgraded by 2030.  

A geopolitical race

Much like AI semiconductors, quantum computing is increasingly being treated as a strategic national technology. Though geopolitical competition is focused on the US, China, and Europe, each region’s strengths are different.

According to Dr Salampasis, the US, for its part, has “the strongest commercial quantum-computing ecosystem, combining research, private capital, technology companies, cloud infrastructure, defence investment and large corporate customers.”

China, meanwhile, is a major strategic competitor of the US, having been investing heavily in quantum computing, quantum communications and related technologies, while simultaneously developing more of the underlying technology domestically.

“China’s broader advantage is that quantum technology forms part of a much larger national strategy around technological self-sufficiency and strategic industries,” Dr Salampasis noted.

Europe and the UK, on the other hand, have strong expertise in several technologies that quantum computers depend upon, including precision engineering, lasers, specialised cooling systems, photonics and semiconductor equipment.

“The UK has a significant quantum research ecosystem and has identified quantum technologies as strategically important,” Salampasis said.

With regard to quantum computing’s supply chain, it is more complicated than that of the AI semiconductor:

“There is currently no single country or company occupying a position equivalent to Taiwan's role in advanced semiconductor manufacturing,” Dr Salampasis contested. “Different types of quantum computers require different specialised materials and equipment…In this context, quantum computing is potentially less dependent on one geographical chokepoint. Rather, more dependent on a strategically important network of highly specialised suppliers.”

Martellini agreed: “I don’t think there is any short-term risk of Europe or the US being deprived of the kinds of parts needed to develop quantum computing. Whereas AI relies on raw materials, quantum computing needs complex hardware like lasers. The West is well-equipped in that domain.”

Once again, like the Manhattan project, it seems as though all sides are compelled to develop a treacherous technology at speed, in order to guarantee their own national security.  

Finding the commercial advantage

The simultaneous emergence of AI and quantum computing is serendipitous. As industries around the world spiral around an event horizon of uncertainty, it could be that at least one invisible boundary sits between the realisation of quantum computing and its current, experimental state. To help cross this boundary, AI may step in to perform the intellectual heavy lifting.

For Dr Salampasis, AI is at the very least likely to help quantum computing become commercially viable:

“Over the longer term, the convergence of these two technologies could be very significant, since AI provides intelligence and automation, and quantum computing provides a new form of specialised computational power. The forward-looking and innovative organisations that learn how to combine those capabilities effectively may ultimately capture more value than those focusing on either technology in isolation.”

But will quantum computing get the attention it needs with all the oxygen being sucked from the room by AI?

“I’m not sure how the threats posed by AI will interact with quantum computing,” Martellini concluded. “So far, they are unrelated. But what I am sure of is that at some point they will become entangled.”