From Bloomberg, April 26:
As a breakthrough proves elusive in the quest to deploy the nascent technology and boost earnings, global finance is divided on how to proceed.
Roughly three years ago, Goldman Sachs Group Inc. looked like it had an edge in Wall Street’s race to master quantum computing.
The banking giant had assembled a handful of highly specialized scientists and partnered with Amazon.com to figure out how the nascent technology could be used to juice better returns for its raft of wealthy clients. They were shocked by what they found.
Goldman’s researchers discovered they would have to run an algorithm for millions of years in order to solve the problem. What’s more, the processor would need to have at least 8 million so-called logical qubits — a set of quantum bits that form the building blocks of quantum computers. Current machines consist of fewer than 100.
Shortly after, Goldman’s quantum team evaporated amid the bank’s widespread cost cutting program. While it now employs next to none, its rival JPMorgan Chase & Co., on the other hand, has persisted with a team of well over 50 physicists, computer scientists and mathematicians, exploring applications in optimization problems, machine learning and cryptography.
The contrast between the two of the world’s largest lenders is emblematic of the split among global financial firms debating ways to harness what’s touted to be the next big thing after artificial intelligence. Experts say quantum computing can reshape areas ranging from new drug discovery to machine learning and risk modeling in finance, with the potential to add billions of dollars in revenue. But it’s also thought to be still years away from offering many practical solutions, raising questions about its near-term value.
Unlike pharmaceutical, defense or material sciences firms — which appear to have a clearer understanding of where they would like to use quantum computing — banks, insurers and asset managers are chasing fixes to a myriad of complex problems: transaction fraud, risk management, how to maximize returns from a portfolio and asset price prediction, to name just a few. The wide array of issues they want to tackle and the limitations imposed by currently available hardware have made it more difficult for them to pinpoint potential benefits.
Wary of these challenges, many financial firms have largely stayed on the sidelines, happy to let others take the lead in exploring these machines that are exponentially more powerful than existing supercomputers. But some like JPMorgan are pouring resources in the hope that one day the technology would give them an edge over competitors.
“We’re positioning ourselves so we can take advantage by understanding what the problem space is across our portfolio,” said Rob Otter, JPMorgan’s head of global technology applied research who earlier ran State Street Corp.’s digital technology department, including quantum research.
While JPMorgan declined to reveal the exact size of the team, Otter said his crew is seeking ways to resolve performance issues and bottlenecks using a quantum computer across the business — including the investment bank — working with colleagues covering portfolio analytics, asset and mortgage pricing.
In November, the bank said it had developed a method to process and analyze large, fast-arriving datasets more efficiently using Quantinuum Ltd.’s Helios processor, which would enable the bank to perform complex tasks like anomaly detection, fraud monitoring, or network analysis quicker. In March last year, it demonstrated an algorithm on a quantum processor with Amazon.com that could make portfolio selection easier by identifying large sets of uncorrelated assets, enhancing diversification and risk management.
Otter said his team may be able to start running useful algorithms on a quantum processing unit in the next couple of years. Now, “we’re waiting for the hardware to be more commercially viable in order to use them,” he said.
Still largely in the domain of academic research, the technology is based on the complex principles underpinning quantum mechanics. Just like traditional computers, quantum computers also use tiny circuits to perform calculations, but they do that simultaneously, rather than in sequence. That allows for complex problems to be solved at vastly faster speeds than those of classical processors.
Business consultants even have some early estimates for its potential. Research by McKinsey & Co. last year said revenue from quantum computing is likely to surge to as much as $72 billion by 2035, from about $4 billion in 2024, fueled by developments in industries such as chemicals, life sciences and finance.
Read More: Quantum Computing Is Finally Here. But What Is It?
Given the stakes, others in the world of finance — besides JPMorgan and Goldman — have been poking around as well, but with varying intensity.
UBS Group AG is upskilling around 50 of their quant analysts in the basics of quantum computing. Spanish lender BBVA SA has worked with Multiverse Computing SL on speeding up ways to optimize portfolio management, and also with other firms. Credit Agricole SA has looked at how quantum algorithms can anticipate credit downgrades better. Many lenders are also racing to upgrade their cryptography, wary that the immense power of the emerging technology may enable it to break encryption standards.
But most of the action is currently led by tech titans including Alphabet Inc.’s Google and International Business Machines Corp., plus a raft of startups, as they build and test software and hardware, like Google’s Willow and IBM’s Heron processors. Though current models are too small and unreliable to be useful, they have been collaborating with companies across industries to explore potential applications by offering their services on the cloud.
Read More: Google’s Quantum Computer Solves Septillion-Year Task in Minutes
For instance, BMW is working with Nvidia Corp. and quantum software firm Classiq to find ways to improve drivetrains and cooling systems; Novo Nordisk A/S and Roche Holding AG are looking at modeling molecular interactions for new discoveries; and, Exxon Mobil Corp. is working with IBM to map the most efficient routes for its tanker fleets.
But for financial firms, developing solutions for risk tolerance and portfolio diversification gets trickier.
Plus, when it comes to applications for finance, “there’s a lot of confusion” about the direction, further complicated by differences in system architectures and technologies used to build them, said Subodh Kulkarni, chief executive of quantum computer builders Rigetti Computing Inc. — one of a growing number of listed companies in this area. That could mean one bank may have to work with multiple quantum computing companies to meet its needs instead of just one.
“We certainly see increased interest from various different higher-end financial companies,” Kulkarni said. “We certainly see them hiring quantum physicists, exploring algorithms and doing research with companies like us, IBM and a few others.”....
....MUCH MORE
