Where the money is: Exploring finance’s quantum use cases
Bank robber Willie Sutton supposedly said the reason he robbed banks was “that’s where the money is.” Quantum computing companies may feel the same way about finance. There could be lucrative paydays for companies that can help financial firms of various kinds apply quantum computing to their use cases.
Finance is believed by IQT Research to have a higher level of interest in quantum than other industries, and it’s not hard to imagine why. Finance firms have an acute need for state-of-the-art encryption and security. Also, fast processing makes a difference in finance, with that difference sometimes measured in millions of dollars. Plus, the finance sector always has been on the cutting edge adopting new technology, and as a result have a wealth of their own internal technology knowledge and talent that may be comfortable aggressively pursuing quantum computing long before other sectors wrap their heads around it.
A series of sessions during IQT Fall last week focused on quantum computing for finance use cases. Investment optimization, not surprisingly, was mentioned as a potential popular application in finance. Samuel Mugel, CTO of Multiverse Computing, called it the “low-hanging fruit” of quantum finance apps.
Sonika Johri, lead quantum applications research scientist at IonQ talked about her company’s work with the Fidelity Center for Applied Technology, in which they have used IonQ’s trapped ion quantum computers to model correlations between the performance of two stocks to determine probability of future performance. In the experiment, quantum machines out-performed classical machines on the basis of speed, quality of results and quantitative analysis.
While processing speed was key to determine the value of quantum computing applied to the model, result quality also was very important. A Johri noted, “Missing rare events can be quite dangerous because the 2008 financial crash is blamed on the use of… functions which did not accurately capture risk occurring from rare events in the distribution fields.”
Johri also said IonQ had worked with Goldman Sachs and QCware on a project involving Monte Carlo analysis, a type of finance simulation that helps financial managers calculate risk. “Our use of quantum computing in this simulation paves the way for quantum-based risk analysis and price simulation,” she said.
Meanwhile, using quantum-based encryption and security techniques seems like another obvious potential arena of finance use case, and Stuart Nicol, chief investment officer at Quantum Exponential suggested that security applications should take precedence over some others that are more opportunistic trading tools.
“If we don’t get encryption right then our financial systems are in serious danger,” he said. “This is not Y2K concerns; this is very real and present danger, and we need to make sure we are ahead of states and other nefarious wrongdoers who would like to steal and interrupt our systems a whole lot if we don’t get it right.”
He added, “Personally I don’t want this to be another arms race about trading efficiencies. I hope humanity can do a bit better than that.”
Ultimately, the most valuable applications for quantum in finance will identify themselves as problems and challenges that financial firms have not been able to otherwise solve using classical computers.
Markus Braun, founder and managing director at JoS Quantum suggested that “just the existence of quantum computers will open up the possibilities” of how they could be used as individual businesses figure out on their own how they might benefit.
Peter Bordow, SVP & Principal Systems Architect for Advanced Technologies at Wells Fargo said that in addition to what “we know that we know” about obvious quantum finance applications, and what “we know we don’t know” about problems quantum may be able to solve, “there’s a vast field where we don’t know what we don’t know yet about the applications of quantum computing in finance.”