What are the challenges of implementing quantum computing? It’s a young technology that was first studied in the early 1980s. Quantum computers are generally designed to solve very specific problems, and they are sensitive to any kind of disturbance, like noise and dust. Banks also face some hurdles in seamlessly implementing the technology.
- Because quantum computers are finicky, banks will likely tap into the machines through a partnership with a quantum computing fintech that’s able to maintain them. This means banks will need a flexible tech stack that most likely runs via APIs and the cloud and can handle common coding languages like Python and C++.
- Banks also function under tight regulatory scrutiny. Using quantum models will require banks to have a firm grasp on what exactly the models are doing and how they’re using customer information.
Which banks are using quantum computing? Worldwide spending on quantum computing is expected to reach $630 million by 2027 and $2.2 billion by 2030, according to Inside Quantum Technology. Here are some banks that have already jumped in, and what they are doing:
Our take: Many experts estimate commercialized use of quantum computing is still about a decade away. The hurdles banks face in its adoption will resemble the challenges they’ve had to overcome when migrating their mainframe system to the cloud—like service disruptions, legacy technology barriers, and resistance to buy-in for long-term projects. That means banks need to start preparing for the technology now.
This article originally appeared in Insider Intelligence’s Banking Innovation Briefing—a daily recap of top stories reshaping the banking industry. Subscribe to have more hard-hitting takeaways delivered to your inbox daily.