Quantum computing in finance is emerging as a transformative force with profound implications for the industry. This cutting-edge technology holds the potential to revolutionize how banks operate in three critical areas: optimizing complex financial processes, enhancing the power of machine learning, and strengthening secure communications.
Quantum computing is a new approach to calculation that uses principles of fundamental physics to solve extremely complex problems very quickly.1 It excels at solving problems that are currently too intricate or time-consuming for even the most powerful traditional computers. This includes finding the best solutions in scenarios with an overwhelming number of possibilities, extracting deeper insights from vast data sets, and creating fundamentally new ways to protect digital information. While quantum computing in finance is still maturing, leading institutions are actively exploring and demonstrating how these capabilities can deliver significant business advantages, from making more-informed investment decisions to protecting against future cyberthreats. This article examines how banks are already using and advancing quantum computing and offers guidance for others who want to start.
Optimization: Unlocking peak financial performance
Optimization problems involve finding the best possible solution from a vast number of possibilities. Compared with classical methods, which try different paths one at a time, quantum algorithms, such as annealing, can find solutions much faster by using laws of quantum physics.2 Tasks such as optimizing portfolios, assessing credit risk, and managing collateral could greatly benefit from quantum computing’s capacity to process complex scenarios quickly. Its applicability to various problems and the magnitude of the advantage is still being researched.
Portfolio optimization: Refining asset allocations and boosting returns
Quantum computing in finance is expected to help identify optimal asset allocations significantly faster and more efficiently than conventional computational techniques. This can allow financial institutions to develop more-sophisticated and successful investment strategies by quickly determining the ideal investment mix within a portfolio, enabling faster responses to market fluctuations and a more dynamic approach to managing investment risks and opportunities.
Citi Innovation Labs partnered with Classiq, a quantum computing software company, to explore how quantum computing in finance can improve portfolio optimization. The partnership applied quantum approximate optimization algorithms (QAOAs) to portfolio optimization to see if they offered advantages over classical methods.3 They specifically examined how changes to the algorithm’s penalty factor affected its performance. Citi believes this work could lead to improved results for this and other complex challenges in the financial industry.4
Credit risk evaluation: Enhancing risk assessment and capital efficiency
Quantum methods such as quantum Monte Carlo are faster and more efficient than classical approaches. Because quantum computers can process multiple scenarios simultaneously, they can achieve accurate results that would take a classical computer an impractically long time to calculate. They are expected to enable significantly better credit risk models, resulting in more-comprehensive evaluations and more-informed loan offers. They are also more efficient for calculating essential metrics, such as economic capital requirements, which are vital for a bank’s financial stability and strategic planning.
The Bank of Canada has researched these methods for bank stress testing. Their studies model the impact of credit shocks and scenarios involving rapid asset sales to see how quantum capabilities could provide computational advantages to improve financial resilience and ensure regulatory compliance.5
Collateral optimization: Reducing costs and improving liquidity
Quantum computing provides a powerful new way to optimize collateral allocation, a critical task for banks that aims to reduce costs, manage risk, and boost liquidity. Unlike traditional approaches, quantum algorithms can efficiently handle the complex constraints involved in deploying collateralized assets.
Multiverse Computing, a quantum software company, has shown this potential in partnership with European financial institutions, including Crédit Agricole CIB and BBVA. They combined tensor networks—a mathematical tool for efficiently representing and manipulating highly complex systems with many variables—with quantum annealing to enhance capital allocation and reduce computation time.6
Quantum machine learning: Powering smarter decisions
Quantum machine learning (QML) is expected to detect fraud, predict churn, and generate synthetic data better than classical computing or AI and machine learning.
Fraud detection: Improving accuracy and strengthening financial security
Quantum computing can significantly enhance fraud detection through QML, which enables the rapid and precise analysis of large, complex data sets of transaction data. By improving the accuracy and speed of identifying subtle patterns and anomalies, banks can detect fraud earlier and more accurately, reducing financial losses and enhancing security for institutions and customers.
Intesa Sanpaolo, a major Italian banking group, is collaborating with IBM to explore QML for improving the accuracy and speed of fraud detection.7 The bank is using a QML algorithm that can classify and identify patterns in data that are too complex for traditional methods. In their initial tests, the quantum model was able to identify fraudulent transactions with greater accuracy and efficiency, reducing the number of legitimate transactions flagged as false positives and negatives.
Churn prediction: Forecasting customer behavior and boosting retention
Quantum computing offers a powerful new capability for predicting churn. By leveraging quantum algorithms, institutions can more accurately identify which customers are at risk of leaving and gain deeper insights into the underlying reasons. This enhanced predictive power enables banks to develop and implement more-effective customer retention strategies, thereby improving loyalty and safeguarding revenue.
An example of this application is Itau Unibanco’s collaboration with QCWare, which demonstrated the use of quantum-inspired algorithms to improve financial forecasting, with the specific goal of reducing customer churn. Applied to a data set of approximately 180,000 anonymized customer data points, the quantum-inspired model improved overall precision to 77.5 percent, from 71.0 percent, and increased the number of captured customer withdrawals by 2.0 percent.8
Synthetic data generation: Creating realistic data and empowering model training
Quantum computing researchers are investigating methods to create synthetic financial data sets that mirror real data patterns. They aim to lessen reliance on actual data in machine learning and safeguard sensitive customer information. While these techniques are still in early development and mostly tested on small problems, they promise to make machine learning in finance quicker and more precise.
The Fidelity Center for Applied Technology collaborated with IonQ to develop and train sophisticated quantum models capable of producing realistic synthetic financial data.9 These models accurately reflect complex market behaviors and intervariable relationships, producing more realistic and accurate synthetic financial data than traditional methods. This advancement enables improved testing and validation of financial models, helping institutions improve portfolio management, risk assessment, and trading strategies.
Communications: Fortifying the digital frontier
Quantum computing presents significant risks as well as opportunities. The immense computational power of future quantum computers poses a direct threat to cryptographic systems that currently secure digital communication and financial transactions. However, it also enables the development of post-quantum cryptography (PQC) and quantum key distribution (QKD) to protect information.
PQC: Securing future financial transactions
Current public-key cryptography relies on mathematical problems that would be easily solvable by a sufficiently powerful quantum computer. PQC uses a new class of mathematical problems that are sufficiently complex to defeat the computational advantages of quantum systems. For financial institutions, therefore, it will be crucial to adopt PQC to maintain the integrity and confidentiality of digital communications.
QKD: Ensuring ultrasecure communications channels
While PQC comprises cryptographic algorithms that run on classical computers, QKD is a hardware-based solution. It uses the laws of quantum physics to enable a verifiably secure exchange of cryptographic keys and can detect any attempt to eavesdrop. It provides a level of protection that is theoretically resistant to future attacks from quantum computers, making it essential for safeguarding highly sensitive financial information and critical infrastructure. PQC and QKD could be used together to create a multilayered defense against future cyberthreats.
As part of OpenQKD, an EU-funded initiative to build a quantum communications infrastructure across Europe, financial institutions are piloting QKD to secure critical data links. Danske Bank in Denmark has successfully completed a live QKD-protected transfer between simulated data centers, representing the first quantum-safe data exchange in the Nordics outside a lab environment.10 Meanwhile, Mt Pelerin, a Swiss crypto-focused institution, has used QKD to test ultrasecure digital asset custody under real-world banking conditions. These pilots—advanced by institutions such as ID Quantique (a Swiss company specializing in quantum cryptography) and DTU (the Technical University of Denmark), which provides research expertise—demonstrate QKD’s potential to future-proof financial communications.11
Also, HSBC has partnered with Quantinuum to explore how quantum computing can enhance the security of digital assets and distributed ledger systems. HSBC is testing quantum-generated cryptographic keys to secure tokenized gold transactions on its Orion blockchain platform.12 This works like a lock that changes its combination randomly and continuously, making it far harder for attackers to break in, even with future quantum computers. Early results indicate that quantum-safe encryption can be seamlessly integrated into existing blockchain systems without disrupting them, thereby offering a practical path to protect digital assets against future cyberthreats.
Quantum money: Enabling unforgeable digital currencies
Quantum money is a revolutionary concept that allows quantum systems to create unforgeable digital currencies, enhancing financial security and preventing counterfeiting. Unlike traditional currencies, it uses quantum mechanics to embed security features that render replication or forgery physically impossible, providing an unprecedented level of trust in digital transactions.
A cutting-edge example of this emerging capability was a joint demonstration by Mitsui, NEC, and Quantinuum of the transmission of unforgeable quantum tokens, a practical version of quantum money, across a ten-kilometer fiber-optic QKD network in Japan.13
The outlook and prospects for quantum computing in financial services
McKinsey estimates that the potential economic value from quantum computing in the finance industry is between $400 billion and $600 billion by 2035.14 Financial services companies are rapidly increasing their exploration of and strategic investments in quantum computing. Leading research firms project a sharp rise in spending on quantum capabilities, with some predicting more than 200-fold growth from 2022 to 2032, at a CAGR of 72 percent.15
This trend is driven by the understanding that quantum computing can fundamentally transform how financial institutions manage risk, optimize operations, detect fraud, and secure vital data. The early applications, often using hybrid quantum–classical methods, are already showing clear benefits in specific cases. Although fully fault-tolerant quantum computers are still years away, industry leaders are increasingly aware that the quantum era is an emerging reality expected to bring transformative results over the next decade or so, making it crucial for leaders to give their attention to it now.
What banks can do now to position themselves for quantum computing
Financial institutions can take steps today to prepare for the quantum era. By acting now, they can establish a competitive edge, mitigate future risks, and realize near-term value. Here’s how banks can position themselves effectively for quantum computing:
1. Develop a quantum action plan aligned with business goals
Banks need a plan to guide their quantum efforts. Ideally, it would cover the next two to three years, encompassing immediate opportunities and long-term transformation.
- Define priorities. Identify areas where quantum computing could have the greatest impact. Common areas include portfolio optimization, fraud detection, and risk modeling. Prioritize use cases that align with the bank’s strategic objectives and offer measurable benefits.
- Set realistic timelines. Recognize that quantum computing will evolve in phases. Focus on near-term opportunities with hybrid quantum–classical methods while planning for the eventual arrival of fault-tolerant quantum systems.
- Secure leadership buy-in. Ensure that senior executives understand the potential of quantum computing and are committed to supporting investments in this emerging technology.
2. Collaborate with the quantum community
Banks don’t need to navigate the quantum journey alone. By partnering with key quantum computing players, they can accelerate their learning curve and gain access to cutting-edge technologies.
- Partner with technology providers. Collaborate with quantum companies to gain early access to tools and expertise. These partnerships can help banks test quantum solutions and stay ahead of competitors.
- Join industry consortiums. Participate in quantum-focused consortiums and working groups to share knowledge, influence standards, and stay informed about industry developments.
3. Build quantum awareness across the organization
Quantum computing is a complex and rapidly evolving field. To prepare for its adoption, banks must invest in education and skill development.
- Educate leadership and decision-makers. Provide training for executives and managers to help them understand the strategic implications of quantum computing and its potential impact on the business.
- Upskill technical teams. Offer specialized training for IT, data science, and risk management teams to familiarize them with quantum principles, algorithms, and tools. This will enable them to identify opportunities and collaborate effectively with quantum experts.
4. Prepare for post-quantum security
One of the most immediate challenges posed by quantum computing is its potential to break current cryptographic systems. Banks must act now to safeguard their data and systems against future quantum threats.
- Assess vulnerabilities. Conduct a comprehensive review of cryptographic systems to identify areas at risk of quantum attacks. Prioritize critical systems for upgrades to PQC. Start planning for adopting PQC standards, currently under development by bodies such as the National Institute of Standards and Technology in the United States and the European Union Agency for Cybersecurity in Europe. Early preparation ensures a smooth transition before quantum computers can threaten existing protections.
5. Start small and scale strategically
Quantum computing is still in its early stages, and banks should approach it with a focus on experimentation and learning.
- Run pilot projects. Test quantum-inspired solutions on specific problems such as optimizing trading strategies or improving fraud detection. Use these pilots to evaluate the technology’s potential and refine your approach.
- Scale successful solutions. Once pilot projects demonstrate value, expand their scope and integrate them into broader operations. This phased approach will help banks manage risks and maximize returns on their quantum investments.
- Invest in long-term R&D. Allocate resources to explore advanced quantum applications and stay ahead of the curve. This will position the bank as a leader in the quantum era.
Quantum computing represents a paradigm shift for the financial industry, offering transformative potential in areas such as risk management, operational efficiency, and cybersecurity. While the technology is still maturing, the time to act is now. By developing a clear strategy, collaborating with the quantum ecosystem, building internal expertise, preparing for post-quantum security, and starting small to scale strategically, banks can position themselves to thrive in the quantum era. Those that take proactive steps today will be best equipped to lead the next wave of financial innovation.
