How JPMorgan Chase and other banks plan to use quantum computers

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 this week’s HPC + AI on Wall Street conference in New York.

We realize that if a company is currently doing nothing for the market and just waiting for quantum advantage to become a reality, when quantum advantage becomes real, it could be too late,” said Marco Pistoia, Managing Director and Distinguished Engineer, Head of Global Technology Applied Research and Head of Quantum Computing at JPMorgan Chase: “We want to be ready when quantum advances become possible at a higher level.”

These banks are not trying 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 like portfolio optimization and index tracking.

Banks are seeking improvements in speed and precision in simulations and calculations for risk analysis, fraud detection and pricing of complex derivatives.

“The financial services sector is responsible for computing large models that integrate a massive amount of data fairly quickly,” said Heather West, research manager for 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 the time it takes to run these models.”

With the help of quantum computing, “financial institutions will be able to make better and more accurate forecasts and risk assessments in near real time,” she said.

In a 2021 survey of West’s top financial institutions, 25% said they are currently investing in quantum computing technology, and 43% said they plan to invest in 2022. Bankers surveyed are experimenting with using quantum computing for a variety of use cases such as cash allocation at ATMs, credit scoring, derivatives pricing, fraud detection, compliance and transaction processing.

“While today’s quantum computing technology is still nascent, it lends itself well to experimenting with optimization problems, making this an ideal time for financial institutions to start experimenting and identify use cases that make it possible to operate on quantum computing systems.” are suitable,” said West. Banks should also develop the quantum algorithms and applications needed to solve such problems once quantum systems are scaled to a point where quantum advantages can be realized, she said.

Quantum computing directly uses quantum mechanics, the laws of physics that govern the smallest particles in the universe, to solve problems at high speed. Conventional 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 a 1, 0, or both 0 and 1 at the same time. The result is a computational system that can manipulate and evaluate many combinations of information simultaneously.

A quantum computer can cycle through 10 to 154 power potential responses to a problem in microseconds.

But the technology still has challenges to overcome. McKinsey analysts recently stated in a report White paper that manufacturers are still trying to scale the number of qubits in a quantum computer while still achieving sufficient qubit quality.

“The most important milestone will be the achievement of a fully error-corrected, fault-tolerant quantum computer, without which a quantum computer cannot provide exact, mathematically accurate 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 create a clear quantum advantage for many use cases by then.”

In the same white paper, McKinsey analysts said that the most promising use cases for quantum computing in finance are in portfolio and risk management. “Efficiently quantum-optimized loan portfolios focused on collateral, for example, could allow lenders to upgrade their offerings, potentially lowering interest rates and freeing up capital,” the authors said.

“In finance, there are many use cases with exponential complexity,” said Pistoia. “When the complexity explodes and the data set becomes large enough, classical computing can no longer solve this problem.”

Another reason the financial industry needs quantum computing is for speed, he said.

“In finance, we need answers now because the market is changing so quickly,” Pistoia said. “The market is volatile and a calculation that takes three days is completely useless. So we need answers immediately and we need accurate answers.”

The quantum computing research and engineering team at JPMorgan Chase investigates 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’s not quite ready to be used in production yet. Quantum computers are not yet powerful enough. When we’re at a scientific stage with a given technology, that’s the best moment to actually collaborate with other companies and get our results out there and partner up so we can learn from other groups and other groups from us.”

Vendors at the conference, even from traditional computer and chip companies like Dell and Intel, also seemed to believe that a shift from high-performance computing technology to quantum computing was inevitable and that they felt compelled to invest in quantum technology.

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

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