Scott Buchholz is the CTO of Deloitte Consulting LLP‘s Government and Public Services practice.
Information is the lifeblood of the financial services industry, which means the faster and more accurately players can analyze complex information, the more they stand to gain. That’s why the industry is uniquely positioned to be transformed by quantum computing, a technology that processes information like nothing we’ve seen before.
As quantum computers graduate from research labs and become real business tools, leaders in the financial services industry need to start preparing today to avoid being left behind.
Key Use Cases For Quantum Computing In The Financial Services Industry
Quantum computers may impact financial services in various areas by accelerating the time it takes to generate results, improving calculation accuracy and identifying novel patterns. In a recent report Deloitte published, we identified the key financial services use cases for quantum computing to be derivative pricing, liquidity optimization, portfolio optimization, risk analysis and supervised anomaly detection.
Supervised anomaly detection can transform how financial institutions identify fraud, and quantum optimization techniques can improve liquidity. Anomaly detection encompasses, but is not limited to, fraud detection. Quantum machine learning can train to higher accuracy with less data than comparable classical models, helping financial services institutions swiftly uncover patterns, predict behaviors and make real-time decisions possible. These improvements can help financial institutions more efficiently pinpoint patterns that warrant further investigation—which can reveal mistakes, new trends and fraud.
Moreover, my team and I have observed that some organizations these days are finding value in “quantum-inspired” approaches (the idea of taking inspiration from quantum computers to run on today’s technology). For instance, based on our analysis, some organizations are using quantum-inspired machine learning techniques, running on today’s CPUs and GPUs, to improve their ability to identify fraudulent transactions. Some of these techniques can be evaluated for today’s production systems and can migrate to quantum hardware as it matures.
Another potential use case is improving liquidity by optimizing transaction sequencing. This leverages a quantum computer’s ability to rapidly evaluate and optimize varied scenarios. For instance, research published by the Bank of Canada in 2022 showed that a hybrid quantum-classical algorithm vastly improved a “payments system’s efficiency by reducing the required liquidity to process payments with minimal added settlement delay.” The researchers found “liquidity savings in 26% of them, providing an average daily savings of C$240 million.”
Challenges Of Leveraging Quantum Computing In Financial Services
Quantum computers will inherit existing challenges and likely create new ones in financial services. Running a machine learning algorithm on a classical computer versus a quantum computer does not change many of the underlying challenges that exist. So, challenges such as bias, as well as incorrect assessments, decisions and predictions, will likely remain. However, one unique new risk that quantum computing poses is its ability to quickly decrypt encrypted information. While the National Institute of Standards and Technology (NIST) released new standards in August 2024 to mitigate this risk, financial services providers must be especially cognizant of this potential threat, given the vast amounts of sensitive consumer data they work with.
That being said, however, arguably the most pressing challenges financial institutions may face when leveraging quantum computing revolve around integrating a fundamentally new technology into their organizations. While financial institutions have robust technology adoption procedures that should suffice, the leap to quantum computing is a major one that requires proficiency in quantum information science—a subject area with a significant skills shortage. Many organizations will likely struggle to find the right talent in a timely manner.
Why Financial Services Institutions Should Get Ready For The Quantum Future Now
A number of the world’s largest financial institutions have already made substantial investments in quantum computing. Others are working to investigate what value “quantum-inspired” algorithms running on today’s machines can bring. And yet others are testing proofs-of-concept or developing roadmaps to know when and where to start.
Quantum computing is not yet widespread. However, financial institutions that treat quantum computing as a far-off event could risk falling behind, missing out on top talent and losing their competitive edge. Expertise is not as readily available as some leaders in the financial world might think, and they should take steps now to develop and secure the right talent. As for gaining a competitive edge, there’s a first-mover advantage. Time is money. For instance, one quantum use case in the financial world is calculating the value of exotic derivatives more quickly—imagine how that might become a trading advantage.
Financial leaders don’t have to spend inordinate amounts of time and money to jumpstart their quantum efforts. They just need to take some level of action now, be it learning about quantum computing, engaging with potential vendors and system integrators or putting together a strategy and roadmap, to name a few steps. What matters most is movement. With quantum on the horizon in the financial services industry, doing nothing is no longer an option.
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