Quantum computers will eventually present the threat of breaking the encryption algorithms that banks and credit unions use today. But this is a mitigatable threat, and banks have many uses for quantum computers that have prompted the world’s largest institutions to invest in the technology.
These uses of quantum computing are currently purely hypothetical, according to one expert, who said no quantum computer today can solve real-world problems faster than a classical computer can. But as tests of the technology continue, small and medium-sized banks can expect a clearer list of potential ways they can use quantum computing in the future.
So far, the list of potential applications includes risk analysis, building investment portfolios and monitoring financial crime, and it could grow over time.
In recent years, JP Morgan Chase, Bank of America, Barclays and Morgan Stanley have created teams to study quantum computing technology and its applications. Ally announced last year was testing the use of technology to bring efficiency to investment portfolio construction. Well Fargo announced a partnership with IBM and MIT in 2019 to study quantum computing technology and HSBC has achieved a similar announcement Next year.
“We must embrace this technology, in line with the bank’s innovation agenda, keeping abreast of the latest developments and growing our internal knowledge to increase our readiness for the post-quantum world,” said Gustavo Ordonez-Sanz, head of economic capital responsible for global risk analytics and innovation for HSBC.
Many observers track the advances of quantum computers by how quickly their limitations are eliminated. For example, the number of qubits, the quantum equivalent of the bits used by classical computers that a quantum computer can manipulate, has increased over time.
THE current register for qubits in a quantum computer it equals 433, which IBM achieved last year. This broke the record of 127 qubits set by IBM the previous year. However, IBM’s quantum computers (and all others with large numbers of qubits so far) have an error rate that makes them ineffective for many uses.
The observers also monitor this error rate to gauge when quantum computers might reliably outperform classical computers in various tasks. According to a Feb blog posts from Google’s Quantum AI team, error-correcting quantum computers will require error rates of about one in a million, but today’s quantum computers typically have an error rate of about one in a thousand.
Once quantum computing hardware has achieved an adequate level of error correction, qubits and other metrics, banks will have a new concern to grapple with: how to actually program a quantum computer.
The quantum computer software used in laboratories today differs greatly from the programming currently taught in schools and colleges. While companies like Google and IBM use familiar programming languages like Python to allow people to experiment with their quantum computers, these programming languages simply act as a wrapper around a very different set of instructions that would be foreign to any programmer who doesn’t specifically studied quantum computers.
Some companies offer services that help bridge the knowledge gap that programmers have between classical programming and quantum programming. One such company is Singapore-based Horizon Computing, founded and led by Joe Fitzsimons.
The lack of quantum computing skills and education today could pose a challenge as the technology develops, Fitzsimons said, and that will present smaller banks with a unique challenge.
“Places like JP Morgan Chase and Goldman Sachs have quantum teams,” Fitzsimons said, and those teams are made up of “expert people who have been in the quantum computing community for a significant amount of time.” However, for smaller institutions, building those teams “isn’t necessarily an option” because “there certainly will be and there is currently a significant talent bottleneck. There just aren’t enough people with experience.”
However, banks won’t need to replace all of their classical computers with quantum computers. They won’t be able to speed up every computational task, Fitzsimons said. But for a variety of computational tasks, the acceleration offered by quantum computers will be significant and, in some cases, exponential.
Quantum computers will enable banks to improve their loan underwriting models, more accurately calculate loan prepayment and default risks, and process more data input into their marketing models, according to a blog post released this month by the American Bankers Association. Quantum computing could also help banks improve their risk profiling, optimize their trading strategies and increase their ability to detect fraud and other financial crimes. according to IBM.
In general, problems involving mathematical optimizations and repeated random sampling are the most feasible for quantum acceleration, according to Fitzsimons, but quantum computers that can collect large amounts of data are expected to take a long time to develop.
“Understanding how to take advantage of quantum computing is a major problem, and it’s not something you can solve in a hurry,” Fitzsimons said.
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