Although quantum computing technology is still new, JP Morgan Chase, Ally Bank, Credit Agricole and other banks are actively testing it and, in some cases, using it, according to speakers at the HPC+AI on Wall Street conference at New York this week.
“We realize that if a company is not doing anything for the market right now and is just waiting for the quantum advantage to become a reality, when the quantum advantage becomes real, it may be too late,” said Marco Pistoia, Director General, Distinguished Engineer, Head of Global Technology Applied Research and Head of Quantum Computing at JPMorgan Chase: “We want to be ready when quantum advantage becomes possible at a higher level.”
These banks do not attempt to buy and use quantum computers directly. They use cloud-based quantum computing-as-a-service offerings from companies such as D-Wave, IBM, Google, Amazon, Rigetti, Microsoft, and QC Ware. They test advanced computing power for complex problems such as portfolio optimization and index tracking.
Banks are looking for improvements in speed, as well as greater precision in simulations and calculations for risk analysis, fraud detection and pricing of complex derivatives.
“The financial services industry is responsible for computing large models that integrate massive amounts of data fairly quickly,” said Heather West, research manager, infrastructure systems, platforms and technologies at IDC. “However, using a typical computing infrastructure, these models are limited in the number of variables that can be included and the time required to run these models.”
Using quantum computing, “financial institutions will be able to produce better and more accurate forecasts and risk assessments in near real time,” she said.
In a survey of West financial institution executives conducted in 2021, 25% said they were currently investing in quantum computing technology and 43% said they planned to invest in 2022. Bankers surveyed are experimenting with the use of quantum computing for a wide variety of use cases that include ATM cash allocation, credit scoring, derivatives pricing, fraud detection, compliance and settlement of transactions.
“While today’s quantum computing technology is nascent, it is well suited to experiment with optimization problems, making this a prime time for financial institutions to begin experimenting and identify use cases. suitable for running on quantum computing systems,” West said. Banks should also develop the quantum algorithms and applications that will be needed to solve such problems once quantum systems scale to a point where quantum advantage can be achieved, she said.
Quantum computing directly harnesses quantum mechanics, the laws of physics that govern the smallest particles in the universe, to solve problems at high speed. Traditional computers only allow bits of information to live in one state (0 or 1) at a time. A quantum computer uses qubits (quantum bits) which allow bits of information to be 1, 0 or both 0 and 1 simultaneously. The result is a computing system capable of manipulating and evaluating many combinations of information simultaneously.
A quantum computer can jump from 10 to 154 potential power responses to a problem in microseconds.
But the technology still has challenges ahead. McKinsey analysts noted in a recent white paper that manufacturers are always trying to scale the number of qubits in a quantum computer while achieving a sufficient level of qubit quality.
“The most important step will be the achievement of fully error-corrected and fault-tolerant quantum computing, without which a quantum computer cannot provide exact and mathematically precise results,” the authors said. “Five manufacturers have announced plans to have fault-tolerant quantum computing hardware by 2030. If this timeline holds, the industry will likely establish a clear quantum advantage for many use cases by then.”
In the same whitepaper, McKinsey analysts said the most promising use cases for quantum computing in finance are in portfolio and risk management. “For example, quantum-efficiently optimized collateral-focused loan portfolios could allow lenders to improve their offerings, potentially lowering interest rates and freeing up capital,” the authors said.
“In finance, you have a lot of use cases with exponential complexity,” Pistoia said. “As the level of complexity explodes and the data set becomes large enough, classical computing can no longer solve this problem.”
Another reason the financial sector needs quantum computing is for speed, he said.
“In finance, we need answers right away because the market is moving so quickly,” Pistoia pointed out. “The market is volatile and a calculation that takes three days is totally unnecessary. So we need answers right away and we need precise answers.”
JPMorgan Chase’s quantum computing research and engineering team explores the use of quantum computing for risk analysis, option pricing, portfolio optimization, fraud detection and analytics mergers.
The bank is still in the research phase.
“I think quantum computing is very important,” Pistoia said. “It’s not quite at the stage yet where it can be used in production. Quantum computers are not yet powerful enough. When we are at the scientific stage with a certain technology, it is the best time to collaborate really with other companies and publishing our results and forming partnerships so that we can learn from other groups and other groups can learn from us.”
Vendors at the conference, even traditional computer and chip companies like Dell and Intel, also seemed to think a shift from high-performance computing technology to quantum computing was inevitable and felt compelled to investing in quantum technology.
“You have no choice,” said Jay Boisseau, HPC and AI technology strategist at Dell Technologies. “It happens whether you like it or not.”
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