Quantum computing in finance: Key use cases

Quantum computers versus traditional computers for finance

The United Nations General Assembly declared 2025 the "International Year of Quantum Science and Technology." There's good reason for such a bold designation. Quantum -- more specifically, quantum computing -- promises to be transformative.

Part of quantum computing's power and how it differs from classical computing stems from the nature of its calculations. In quantum computing, calculations are probabilistic, allowing for multiple possible outputs from the same input. Classical computing, in comparison, performs deterministic calculations that give the same output for the same input time and again.

Another key difference is how data is processed. Classical computing processes data in a binary matter, using bits with code written with 1s and 0s for "on" or "off."

But quantum computing uses quantum bits, or qubits, which can be expressed as a value of 1 or 0 -- or both at the same time. This ability to exist in multiple states at once is known as superposition, and it's what enables more complex computations.

Quantum computing's ability to solve complex problems with multiple parameters is one of its biggest appeals, both for financial firms and others, said Marc Lijour, an entrepreneur, researcher educator and member of the professional association IEEE.

"Quantum computing is actually about solving more difficult problems -- problems that we can't solve today efficiently with the computers we have," he said, explaining that quantum computers will be able to solve in minutes what would take thousands of years -- or more -- for classical computers to solve.

Key use cases for quantum computers in finance

Quantum computing is not yet commercially operational, but organizations are experimenting with quantum computing use cases and running quantum-inspired algorithms and computational approaches on classical computers.

The financial services industry is among the sectors exploring how quantum could enhance its services, products and operations.

"Financial institutions are actively experimenting, developing proofs of concept and running pilot programs to explore quantum computing's potential," Dave said. "While fully operational applications remain in development, leading banks are testing quantum algorithms for portfolio optimization, fraud detection and risk analysis."

She noted that JPMorgan Chase and HSBC have dedicated quantum research teams, while Citi Innovation Labs, Mizuho Bank and Truist "have also joined the quantum revolution, focusing on enhanced trading strategies, cybersecurity and advanced financial simulations." She added that quantum computing is poised to reshape the financial sector as adoption expands.

According to Dave, Lijour and Jeff Zych, a partner and insurance practice leader at global advisory firm Guidehouse, the most likely finance use cases for quantum computing include the following:

1. Investment strategy and portfolio management

Determining optimal investment strategies and managing portfolios involves numerous dimensions, and while computations that run on classical computers support these activities, Zych explained that quantum computing's ability to consider all the myriad dimensions and parameters involved in investment strategies and portfolio management will yield much more precise insights.

2. Research

Similarly, financial services firms can use quantum computing to get more refined and detailed research results, whether they're researching market conditions or trying to predict consumer trends. Zych said quantum computing really shines here for its ability to compute potential scenarios in lightning-fast time.

3. Fraud detection

Although the financial sector has used classical computing methods for fraud detection, it struggles to keep pace with the volume and speed of transactions as well as the sophistication of attacks. Quantum computing, however, can bring additional speed and precision to the task by replacing traditional, rule-based fraud detection methods (which must be defined and continuously updated to detect evolving fraud techniques) with quantum algorithms and complex financial models more suited to analyzing every available data point. This will enable firms to identify fraud more accurately, as fast as possible.

4. Customer experience

Quantum computers could help financial firms deliver a superior customer experience through improved services, such as more precise investment strategies and portfolio management as well as better fraud detection capabilities. Financial firms might also be able to use quantum computing for more targeted, personalized and proactive marketing and outreach, thanks to enhanced know-your-customer capabilities.

5. Underwriting

Quantum computing is expected to transform underwriting through its quantum algorithms and supercharged analytics capabilities. This will mean better actuarial models, more accurate risk profiles and assessments, and more precise and personalized pricing. Zych said such capabilities could help insurers better predict the impact of natural disasters and accidents as well as analyze and process claims, which could result in more accurate payments delivered faster and with less friction, along with fewer fraudulent claims.

Potential drawbacks and challenges of using quantum computers in finance

While quantum computing is often heralded for its potential, it comes with potential drawbacks and challenges. They include the following:

• Cybersecurity risks. Quantum computers will be able to quickly break the public-key encryption methods used today, doing in hours what classical computers would need millions of years to do, Lijour said.
• New security measures. Consequently, there is a need for widespread implementation of so-called post-quantum cryptography before quantum computers become fully operational, Lijour said. Work on this front is already underway. For example, in 2024, NIST finalized three post-quantum encryption standards.
• Preparations for quantum. Organizations of all kinds, including in the financial sector, must be able to have on hand the data needed for their quantum computing applications. They must also develop the workflows, processes and business cases for quantum computing use, Zych said; otherwise, the technology won't deliver the expected ROI.
• Unequal access. The resource-intensive needs and high cost of quantum computing mean smaller organizations won't be able to afford it and take advantage of its potential -- at least early on, Zych said.

Dave named these additional challenges:

• Technical barriers, including hardware limitations, qubit instability and high error rates.
• High investment costs that cut into short-term ROI.
• Difficulty integrating quantum systems into legacy IT infrastructures.
• A shortage of quantum talent.
• Geopolitical risks of quantum supremacy.
• Ethical concerns about potential market manipulation.
• Regulatory uncertainty.
• Data privacy concerns.

Best practices for finance's adoption of quantum computers

To be ready for quantum computing, these experts recommend that organizations do the following:

1. Develop strategies today to get ready for the future. Lijour noted that organizations can adopt quantum-inspired algorithms and computational approaches that run on classical computers to start understanding the potential of quantum and develop use cases for their organization. "You can learn, build and develop capacity in your teams now," he added.
2. Ready your defenses, too. "You have to start working with providers to upgrade your cybersecurity, and especially your cryptography. It will take a few years to get there, so you have to get started now," Lijour said.
3. Plan for a human in the loop. Quantum computing won't replace the need for humans, Zych stressed. "It's not ready to make decisions on its own. It will need to be checked."
4. Hold onto classical computing. Quantum won't be the right tool for every task, and even when it matures, it won't fully replace classical computing. "You'll need both classic and quantum computers because they're good at different things," Lijour said.

Mary K. Pratt is an award-winning freelance journalist with a focus on covering enterprise IT and cybersecurity management.