September 26, 2023


Be life confident

Practical implications in Payments and Banking

5 min read

I know, I know, Quantum computing is still nascent, but it’s already sparking a revolution in technology.

Funding to quantum tech start-ups soared to record levels in 2021. Media interest in the space has continued to climb. New milestones and scientific breakthroughs are being announced at a quickening pace.

Against this backdrop, big tech companies Google, Microsoft, Amazon, IBM, and Intel are investing heavily in building their own quantum computers and developing applications around enterprise use cases.

With enormous prizes on the horizon, none of these big tech companies want to be left behind.

But what are the implications for payments?

Quantum computing technology is set to revolutionise computing, providing exponential gains in processing power.

The easiest way to understand it is to start with traditional computing, which encodes data as a series of zeroes and ones. Quantum computing exploits the quirky behaviour of sub-atomic particles, which can be in two states at the same time (a property that is called “superposition“).

This means that a quantum bit – or qubit – can be a one and a zero at the same time. But of course you all know that…so lets get to the good bit.

Combining large numbers of qubits means that the number of states they could represent rises exponentially, making it possible to compute millions of possibilities instantaneously. That’s why quantum computing speeds up data processing, making it possible to solve problems far beyond the reach of traditional computers.

To give a simple example, imagine you want to program a computer to find a specific individual in a phone book containing 100 million names. A traditional search algorithm would take 50 million operations, on average, to locate them; a quantum search algorithm would only need 10,000.

What practical applications are there?

In banking, for instance, quantum computing could be used to create risk management systems that are better at modelling a bank’s financial exposures and calculating potential losses.

Another application could be in the field of artificial intelligence, where quantum computers could help machine-learning algorithms to master complex tasks much more quickly than they currently can.

Quantum quandary

The added processing power provided by quantum computing will inevitably be used by some people for unethical purposes, and it will undoubtedly make it easier to break some cryptographic algorithms.

On the plus side, quantum computing can also be used to strengthen security. In a recent article, Gemalto cryptographic expert Aline Gouget wrote: “We are working on the design of products embedding so-called crypto agility capability. This enables software to be loaded that could replace keys and algorithms, as and when they become deprecated. This powerful mechanism enables a fleet of resistant products to be maintained, even as algorithms are found to be vulnerable.”​

The Dutch Payments Association has already organised four expert sessions with participants from universities, banks and payment companies and experts in the field of quantum and crypto.

“These sessions taught us that the computing power of existing quantum computers is still very limited. Nevertheless, two known quantum algorithms pose a threat to a number of widely used encryption algorithms, if implemented on future powerful quantum computers,” says Oscar Covers, Cybersecurity Analyst at the Dutch Payments Association

“We expect the first practical quantum computers to be deployed in the chemical and medical industries. These applications provide an early warning because to break current encryption algorithms, still more quantum computing power will be needed.

Our approach is to define ‘low regret moves’: steps we can take now without regretting them later on. Quantum key distribution will assure secure communication in a quantum computer era but the solution must also fit economically with business processes.

In addition, it is preferable to introduce modifications through regular replacement, as accelerated replacement incurs more expenses.”

What business lines will benefit most?

According to Mckinsey, in late 2019, a Bank of America strategist said quantum computing would be “as revolutionary in the 2020s as smartphones were in the 2010s.”4 However, from a business line perspective, the most promising use cases are likely to be those that require highly complex and/or exceptionally fast models.

In valuation, for example, the ability to speedily identify an optimal risk-adjusted portfolio is likely to create significant competitive advantage. For loan and bond portfolios, more precise estimates of credit exposures should lead to better optimization decisions.

More broadly, capital allocation across a range of corporate finance activities can be improved by insights into the size and materiality of risks, while payments and transfers can be protected through better encryption.

Equity and FX trading offer significant possibilities, amid demand for ever-more accurate market risk and scenario calculations, and growing appreciation of the utility of raw computing power in smart routing and trade matching. Some large banks already expend large amounts of computational resources optimising private interbank trading, suggesting it makes sense to seek an edge in this area.

Finally, sales, marketing, and distribution can benefit from sharper decision making, for example in relation to resource allocation and tailored services. This holds true for most organisations with large and diverse customer bases but especially for banks, which still spend a large proportion of their operating expenditure on branches and call centres.

As of now, the major Wall Street banks are leading the charge in the quantum realm. A Goldman Sachs researcher in January 2020 said quantum has the potential to become a critical technology.

Still, Goldman’s efforts are at an early stage. In its early experiments, the bank found that Monte Carlo simulations, which require significant amounts of conventional computing power, cannot yet be parallelized on a quantum system. It therefore refocused on developing approaches to decrease the depth of quantum circuits required to do these calculations.

JPMorgan and Citigroup, meanwhile, have set up quantum computing initiatives and even bought stakes in computing start-ups. JPMorgan also experimented with Honeywell’s quantum computer in an effort to ease mathematical operations that involve Fibonacci numbers.

In late 2019, Wells Fargo joined the IBM Q program, a community of companies, start-ups, academic institutions, and research labs working to explore practical applications.

European banks are also exploring quantum computing opportunities. BBVA has formed a partnership to explore portfolio optimisation and more efficient Monte Carlo modelling.

Also in Spain, Caixa Bank is running a trial hybrid framework of quantum and conventional computing with the aim of better classifying credit risk profiles.

In mid-2020, UK’s Standard Chartered revealed its exploration of quantum computing applications, such as portfolio simulation, in collaboration with US-based Universities Space Research Association.

These initiatives make sense because they allow financial firms to test quantum algorithms on simulators or the cloud without acquiring full-scale quantum computers.

This appears to be a sensible strategy as long as quantum computers remain subcritical for practical applications and there is no dominant design for scaling quantum capabilities.


Source Article | Newsphere by AF themes.