How JPMorgan Chase and other banks plan to use quantum computing

Although quantum computing technology is still new, JPMorgan 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 conference on Wall Street in New York this week.

We realize that if a company does nothing for the market right now, and just waits for the quantum advantage to become a reality, when the quantum advantage becomes real, it may be too late, “said Marco Pistoia, CEO, illustrious engineer, head of applied research on global technology and head of quantum computing at JPMorgan Chase. “We want to be ready when quantum advantage becomes possible at a higher level.”

These banks are not attempting to purchase and use quantum computers directly. They are using cloud-based quantum computing-as-a-service offerings from companies such as D-Wave, IBM, Google, Amazon, Rigetti, Microsoft and QC Ware. They are testing advanced computer power for complex problems like portfolio optimization and index tracking.

Banks are looking for improvements in speed, as well as greater accuracy in simulations and calculations for risk analysis, fraud detection and pricing of complex derivatives.

“The financial services industry is responsible for processing large models that embed huge amounts of data fairly quickly,” said Heather West, head of research, infrastructure systems, platforms and technologies at IDC. “However, using classical computing infrastructure, these models are limited in the number of variables that can be included and in the time it takes to run these models.”

Using quantum computing, “financial institutions will be able to produce better and more accurate risk predictions and assessments in near real time,” he said.

In a 2021 survey of leaders of West financial institutions, 25% said they invest in quantum computing technology and 43% said they want to invest in 2022. The bankers surveyed are experimenting with the use of quantum computing to a wide variety of use cases including ATM cash allocation, credit scoring, derivative pricing, fraud detection, compliance and transaction settlement.

“Although today’s quantum computing technology is nascent, it is suitable for experimenting with optimization problems, making this a prime time for financial institutions to begin experimenting and identifying use cases suitable for running on quantum computing systems.” West said. Banks should also develop quantum algorithms and applications that will be needed to perform such problems once quantum systems are scaled to a point where the quantum advantage can be achieved, she said.

Quantum computing directly exploits 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) that allow bits of information to be 1, 0, or both 0 and 1 at the same time. The result is a computational system capable of manipulating and evaluating many combinations of information simultaneously.

A quantum computer can scroll from 10 to 154a power potential responses to a problem in microseconds.

But technology still has challenges to overcome. McKinsey analysts noted in a recent White paper that manufacturers are still trying to scale the number of qubits in a quantum computer by achieving a sufficient level of qubit quality.

“The most important milestone will be the achievement of a completely correct and error-tolerant quantum computation, without which a quantum computer cannot provide exact and mathematically accurate results,” said the authors. “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 white paper, McKinsey analysts said the most promising use cases for quantum computing in finance are in portfolio and risk management. “For example, efficiently optimized loan portfolios that focus on collateral could allow lenders to improve their offerings, possibly by lowering interest rates and freeing up capital,” the authors said.

“In finance, there are many use cases with exponential complexity,” Pistoia said. “As the level of complexity explodes and the dataset becomes large enough, classical computing can no longer solve that 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 changing so quickly,” Pistoia said. “The market is volatile and a calculation that takes three days is totally useless. So we need answers now and we need accurate answers.”

JPMorgan Chase’s quantum computing research and engineering team is exploring the use of quantum computing for risk analysis, option pricing, portfolio optimization, fraud detection and merger analysis .

The bank is still in the research phase.

“I think quantum computing is very important,” Pistoia said. “It is not yet fully at the stage where it can be used in production. Quantum computers are not yet powerful enough. When we are in a scientific phase with a certain technology, that is the best time to actually collaborate with other companies and publish our own. achievements and form partnerships so that we can learn from other groups and other groups can learn from us. “

Even vendors attending the conference, even from traditional computer and chip companies like Dell and Intel, seemed to believe a shift from high-performance computing to quantum computing technology was inevitable and felt compelled to invest in quantum technology.

“You have no choice,” said Jay Boisseau, HPC and AI technology strategist at Dell Technologies. “Here it comes, whether you want it or not.”


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