Quantum computing in finance: steampunk chandeliers have their uses

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Achieving alpha – outperforming the market – is a never-ending goal in finance, and it explains why leading firms keep a keen eye on opportunities for technology to forge a path ahead of the competition. The use of quantum computing in finance has long been talked about as one such differentiator. And what’s noticeable now is the long list of financial institutions with practical examples to report.

For example, companies using quantum computing in finance, include Crédit Agricole, Barclays, Goldman Sachs, HSBC, JP Morgan Chase, Mastercard, Nomura, and Wells Fargo, to name just a few.

What is quantum computing?

Without getting too deep in the weeds, it’s useful to picture quantum computers as being able to find the low-energy point in a multi-dimensional landscape, to borrow the description given by D-Wave’s CEO, Alan Baratz. And this property allows systems such as quantum annealers to quickly solve problems such as the shortest path out of a maze, or – more practically for industry –find the most efficient delivery route for complex logistics, optimize scheduling, and tackle supply and demand puzzles.

It’s often said that quantum bits, or qubits, can represent many states at the same time – a property dubbed superposition. What’s more, these states can be entangled so that their information is shared, or correlated, and can no longer be described independently. And this gets to the heart of how quantum computers work.

“In the quantum computer, all possible solutions are considered simultaneously with the highest probability of the correct solution surfacing through the results,” explained Peter Bordow, who leads the Quantum Technology Research Team at Wells Fargo, in a recent Mastercard Foundry webinar on quantum computing in finance.

Rather than having to take a trial-and-error approach common to classical computing, stepping through various permutations one by one, quantum computers can instead consider all possibilities at once. And, as hardware and software continue to improve, so will the accuracy of those most probable, lowest energy solutions.

In the financial sector, applications include portfolio optimization and time-series predictions examining securities risk and performance. But there are gains too that might open up on the networking side – for example, helping payment providers to make the settlement process more efficient by optimizing the connections between merchants and banks.

In case you are curious about what #quantum computing can or cannot do for #finance then this review in @NatRevPhys might be a good starting point.
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— Andreas Wallraff (@AndreasAtETH) July 14, 2023

Dylan Herman, a member of JP Morgan’s Global Technology Applied Research team, is lead author of A Survey of Quantum Computing for Finance, published this month in Nature Reviews Physics. And, in the review, he points out that quantum computing can help financial institutions meet the challenges of three macroeconomic trends – keeping up with regulations, addressing customer expectations driven by big data, and ensuring data security.

One advantage that the financial sector has over other industries when it comes to adopting quantum computing is that results can still prove to be valuable even if they are an approximation. In drug discovery, another application area being explored for quantum computing, developers will want to know the exact chemical formula.

However, if quantum computing in finance can narrow the uncertainty of how assets will respond to future market conditions then traders will gladly take that information on board.

Quantum computing in finance

“We are in the early stages of the quantum revolution, yet we are already observing a strong potential for quantum technology to transform the financial industry,” writes Herman and co-authors in their review paper. “So far, the community has developed potential quantum solutions for portfolio optimization, derivatives pricing, risk modeling, and several problems in the realm of artificial intelligence and machine learning, such as fraud detection and natural language processing.”

At the top of the article we spoke about alpha, which implies profiting from beating the market, but companies adopting quantum computing in finance could also improve their positions by reducing fraud. Mastercard estimates that its systems have saved around $30 billion in fraud over the past two years.

And there’s anti-money laundering technology to consider too. AML efforts are valuable for society in limiting the funding of criminal activity.

Fraud detection schemes have to balance real-time performance against the number of features that can be utilized to determine the likelihood of financial transactions being legitimate. And quantum computing can help to optimize that basket of features to make sure that the strongest indicators are being used to combat fraud most effectively.

“We’re looking at this as a combination of offline quantum-driven or quantum-supported activity, ultimately leading to an online real-time classical solution,” comments Steve Flinter, VP of R&D at Mastercard.

Hidden flow discovery – using quantum computers to beat crypto mixers

Ideally, digital ledgers will improve the future of finance by making it more straightforward to track transactions and determine the origin of funds. But obfuscation systems known as crypto mixers or crypto tumblers (or even bitcoin blenders) have thrown a spanner in the works, helping adversaries to try and beat the system.

Having identified crypto wallets that could be related to criminal activity, law enforcement officers will want to trace the origin of those funds linked to accounts by their respective blockchains. Unfortunately, analysts may find that the information has been scrambled using a crypto mixing service that breaks the link between the cryptocurrency wallet and the origin of the funds.

However, despite being advertised as a ‘bridge to anonymity’, crypto mixers could turn out to be vulnerable to the all-seeing eye of a quantum computer. Mastercard’s R&D team – dubbed Mastercard Foundry – believes that quantum computers in finance could play a key role in hidden flow discovery to boost AML efforts.

One of the properties of quantum circuits is that they are reversible. In other words, if crypto mixing is tractable as a quantum system then it may be possible to unwind the obfuscation steps applied and identify the most probable wallet origin of the cryptocurrency activity after all.

And this is by no means the end of the story. You can expect a long list of real-world applications for quantum computers as users are finding that commercially available qubits offer an advantage over their classical cousins in solving hard problems.