Banking

How JPMorgan Chase and other banks plan to use quantum computing

Though quantum computing technology is still new, JPMorgan Chase, Ally Bank, Credit Agricole and other banks are actively testing and in some cases using it, according to speakers at the HPC + AI on Wall Street conference in New York this week.

We realize that if a company doesn’t do anything about the market right now, and just waits for quantum advantage to become a reality, when quantum advantage becomes real, it might be too late,” said Marco Pistoia, managing director, 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 on a higher level.”

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

The banks are seeking 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 sector is responsible for computing large models that incorporate a massive amount of data fairly quickly,” said Heather West, research manager, infrastructure systems, platforms and technologies at IDC. “However, using classical computer infrastructure, these models are limited in the number of variables that can be included and the time in which it takes to run these models.”

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

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

“While today’s quantum computing technology is nascent, it is well suited 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 be developing the quantum algorithms and applications that will be needed to run such problems once quantum systems are scaled to a point where quantum advantage can be achieved, she said.

Quantum computing directly leverages quantum mechanics, the laws of physics that govern the smallest particles in the universe, to solve problems at high speeds. 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 enable bits of information to be a 1, 0 or both 0 and 1 simultaneously. The result is a computation system that can manipulate and assess many combinations of information concurrently.

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

But the 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 while achieving a sufficient level of qubit quality. 

“The most important milestone will be the achievement of fully error-corrected, fault-tolerant quantum computing, 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 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 quantum-optimized loan portfolios that focus on collateral could allow lenders to improve their offerings, possibly lowering interest rates and freeing up capital,” the authors stated. 

“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 big enough, classical computing cannot solve that problem anymore.”

Another reason the financial industry 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 computation that takes three days is totally useless. So we need answers right away and we need accurate answers.”

The quantum computing research and engineering team at JPMorgan Chase 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’s not yet completely at the stage at which it can be used in production. Quantum computers are not yet powerful enough. When we are in a scientific stage with a certain technology, that’s the best moment to actually collaborate with other companies and publish our results and form partnerships so that we can learn from other groups and other groups can learn from us.”

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

“You don’t have a choice,” said Jay Boisseau, HPC and AI technology strategist at Dell Technologies. “It’s coming whether you want it to or not.”

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