By Samantha Barnesinternational banker
OWe are now seeing a massive adoption of quantum computing research and application on Wall Street. Indeed, companies such as JPMorgan Chase, Goldman Sachs, Citigroup and Wells Fargo, alongside the biggest banks in Europe and Asia, are spending far more than just a few years ago to pursue quantum solutions that will give them distinct computing advantages. on their rivals. And as research continues, we are on the brink of a quantum arms race within the banking industry.
Quantum computers can hold more data than the “classical” computers we use today primarily via qubits (quantum bits). They can also handle a wide range of complex computational problems with much more speed and less power consumption; as such, they can solve several problems in seconds that are beyond the capabilities of conventional computers or will take them an inordinate amount of time.
Thus, the global banking system, among a number of key industries, may well see significant performance gains over the next few years, thanks to the adoption of quantum computing. “In theory, quantum futures banks could build trading strategies that offer better returns, quickly analyze different combinations of portfolios to find the best mix of investments, and optimize risk analysis for tasks like issuing credits,” noted technology market intelligence firm CB Insights. in November. “Although quantum computers aren’t best at everything – and the machines still face formidable technical challenges – they are expected to excel at performing day-to-day mathematical banking tasks quickly, such as Monte Carlo simulations (used to make predictions that better account for chance) and optimization problems.
Indeed, Monte Carlo simulation is among the most anticipated specific beneficiaries of quantum computing. Research from Goldman Sachs and quantum start-up QC Ware published in September 2021 found that quantum computers are now powerful enough to demonstrate a quantum algorithm that could dramatically speed up such simulations, which, in turn, can be used to improve the often complex resource. – intensive and costly process of pricing derivative contracts. “As part of our firm’s drive to deliver ever-increasing value to our clients, our research group has made fundamental contributions to quantum technology. We are working on enterprise use cases that could have a significant impact on strategic investment decisions,” said William Zeng, head of quantum research at Goldman Sachs. “Working with IonQ has been key to accessing the best quantum technology and accelerating our timeline.”
As such, progress may well be imminent allowing a bank to offer quotes over the phone to clients seeking to trade derivatives, according to Paul Burchard, head of research in Goldman’s Research and Development division, instead. than having to wait several hours for computational tasks to be executed, as is currently the case. “There is a very big IT bill that we pay every year to price these derivatives and take risks on them,” Burchard told the FinancialTimes in April 2021.
Banks are therefore already realizing the potential efficiencies and problem-solving capability offered by quantum computing. And rather than simply waiting for the emergence of “quantum supremacy” – that is, when a quantum computer can perform a calculation that a classical computer can hardly solve – they recognize that investing in quantum research today and trying to derive marginal results improvements in subsequent practical applications will be essential to gaining a competitive advantage over their peers. “Because of their far greater power, quantum computers could offer extraordinary developments for the banking industry in areas such as risk analytics, machine learning, and cybersecurity. Most experts believe we are at least 10 years away from commercially viable general-purpose quantum computers, although recent advances suggest potential breakthroughs sooner,” noted Gustavo Ordonez-Sanz, former lead analyst. economic capital, innovation and quantum computing at HSBC. “We need to embrace this technology, in line with the bank’s innovation agenda, keeping abreast of the latest developments and building our internal knowledge to be better prepared for the post-quantum world.”
However, one of the biggest concerns about quantum computing is the power these machines have that could eventually allow them to launch successful cyberattacks on financial systems, perhaps even some of the most encrypted banking security infrastructure in the world. world. JPMorgan, however, is already looking to fend off this potentially disastrous eventuality. In February, a team of quantum engineers from the largest bank in the United States, joined by colleagues from Japanese multinational conglomerate Toshiba and the American telecommunications company Ciena, announced that they had developed a powerful encryption network of quantum key distribution (QKD) to protect blockchains from quantum attacks. -computer attacks. “Security is paramount to JPMorgan Chase,” said Marco Pistoia, head of JPMorgan Chase’s Future Lab for Applied Research and Engineering (FLARE) group and one of the research leaders. “This work comes … as we continue to prepare for the introduction of production-grade quantum computers, which will change the security landscape of technologies such as blockchain and cryptocurrency for the foreseeable future.”
According to a January report from Inside Quantum Technology, which provides insight into quantum technology markets, global spending by financial institutions on quantum computing will exceed $630 million by 2027 and $2.2 billion by by 2030. The report also predicts a major evolution in quantum computing. in the financial services industry, from the “proof of concept” stage at present to widespread use in about a decade, with significant use in portfolio management and construction, currency arbitrage, fraud detection, trade settlements, analytics-based CRM (customer relationship management), credit scoring, risk modeling, tax loss harvesting and derivatives pricing.
“Financial services firms have invested significantly in identifying specific use cases that will be most beneficial when quantum computing reaches commercial scale. Officials at banks and related institutions see machine learning as a vehicle of early value because it can fit into a hybrid computing model that combines quantum and classical computing,” according to the Inside Quantum Technology report. “Gradually, more applications for quantum computing will show how they can translate into value stream for the financial industry. In other words, as part of the sales process, potential end users need to understand that buying the quantum technology will benefit them.”
But the report also cites hardware limitations as a major barrier to widespread adoption of quantum computing in the current climate. “There is enough proof of concept to establish that quantum code works and provides significant value. The production use of quantum computing in financial services is currently hardware-limited, according to our interviews. Financial services want their code to be hardware independent. This requires independent software stacks supporting familiar languages like Python, C++, etc.
IBM expects quantum computing to play a central role in driving “the most significant computing revolution in 60 years” and has repeatedly asserted that it will deliver its 1,121-qubit Quantum Condor processor to by 2023, which should, in turn, lead to practical application “characterised by systems running error-corrected circuits and widespread adoption” by 2030. ‘IBM for Corporate Security, Jamie Thomas, the company is on schedule.’In terms of the hardware roadmap, we’ve put ourselves forward,’ Thomas recently told CUBE, the tech channel in direct from SiliconANGLE “We said we were going to get to a 1000+ qubit machine and in 2023. So that’s our milestone, and we have a number of milestones that we’ve outlined along the way.”
Such estimates can prove useful for financial institutions in terms of the pace of research and development of this technology. “Identify concrete areas of application!” Venture into simulators with Qiskit, program with Silq, use Quantum Learning Machines (QLM) and cloud services to familiarize yourself with the use, programming and behavior of quantum computers! Daniel Fasnacht, managing director and founder of Swiss financial advisory firm EcosystemPartners AG, advised in an article he wrote for Finextra in May 2021. “Most importantly, prepare your computing landscape accordingly, as legacy concepts and architectures typically do not provide the flexibility and connectivity needed to make sense of quantum computing capabilities delivered ‘as a service’ meaningfully and effectively. ”
Goldman Sachs, however, predicts that quantum computing could make its debut helping solve some of the most complex calculations in financial markets within five years. His joint research with QC Ware suggests that programmers would be happy to give up much of the huge performance gains promised by quantum systems to see practical improvements registered much sooner than expected. Thus, it would seem that the race to generate quantum advantages within the banking sector is now well and truly on.