What quantum computing may mean for the finance industry
Some banks are testing technology’s applications. Quantum computing has implications for high-value challenges in finance, according to an industry expert.
Quantum computing can be used to measure credit decay, increase training speed for machine learning algorithms, including accelerating Monte Carlo calculations, and to optimize portfolios, explains Sam Mugel, who holds a Ph.D. in quantum computing, in this episode of Bank Automation News’ podcast, the Buzz.
Quantum computing has implications for high-value challenges in finance, according to an industry expert.
Quantum computing can be used to measure credit decay, increase training speed for machine learning algorithms, including accelerating Monte Carlo calculations, and to optimize portfolios, explains Sam Mugel, who holds a Ph.D. in quantum computing, in this episode of Bank Automation News’ podcast, the Buzz.
"We'll use classical for some things and quantum for some things,” Mugel tells BAN. “Quantum computing is good at things like training machine learning models, which right now is costing an awful lot of energy and awful lots of our computational power. It's really good at things like really difficult optimization problems, which are everywhere, particularly in finance.”
Mugel serves as chief technology officer at Multiverse Computing, a fintech specializing in quantum computing. He helped develop Multiverse’s Singularity, a spreadsheet application for quantum investment optimization that makes quantum algorithms accessible.
Mugel explains how quantum computing compares to traditional computing and what the technology means for the financial services industry. He also shares how banks are already leveraging quantum computing, including the Bank of Canada. BBVA and Credit Agricole also are early Multiverse customers and early adopters of quantum computing.