Quantum computing in finance – what is the potential of the technology?

• Quantum computing in finance will change the game.
• But companies need to be aware of quantum security as well.
• The IBM Quantum Network has helped partners develop and test use cases for quantum computing.

Although quantum computing is still in its infancy when it comes to global use cases, many industries are already planning how they can use it not only to improve their products and services, but also to protect their operations.

Quantum computing use cases can be applied to most industries today. However, since the technology is still a costly affair for many, most of these use cases are still in the testing phases. Still, this doesn’t stop industries from planning how to use the technology when it’s more affordable and available.

Quantum computing in finance continues to be tested in a variety of use cases. In fact, according to a study by Deloitte, financial industry spending on quantum computing capabilities is expected to grow 233x from just $80 million in 2022 to $19 billion in 2032, growing at a 10-year CAGR of 72%. Companies working to develop quantum-related capabilities now could enjoy a competitive advantage as those capabilities mature.

Quantum computing in financial investments. (Image by Deloitte).

Quantum computing in finance

According to a report by IBM, quantum computing in finance will be a game changer. Not only is the technology capable of dealing with issues of uncertainty and limited optimization, but it can also ensure greater compliance, use behavioral data to increase customer engagement and react more quickly to market volatility.

The report also stated that quantum computing can allow financial services organizations to re-engineer operational processes, such as:

• Front office and back office customer management decisions for “know your customer”, credit granting and onboarding.
• Treasury management, trading and asset management.
• Business optimization, including risk management and compliance.

Looking at the bigger picture, potential applications for quantum computing in finance include:

• Portfolio optimization: Quantum computing can help investors find the optimal allocation of assets in their portfolios, taking into account various factors such as risk, return, liquidity and diversification.
• Risk management: Quantum computing can help financial institutions assess and manage different types of risks, such as market, credit, operational and liquidity risks.
• Fraud tracking: Quantum computing can help detect and prevent fraudulent activities, such as money laundering, identity theft and cyber attacks.
• Encryption: Quantum computing could also pose a threat to the security and integrity of financial data, as quantum computers could potentially break encryption schemes currently used to protect online transactions and communications.

Quantum computing has almost unlimited applications, especially in economics. (Image generated by AI)

Develop quantum computers for finance and other industries

John Duigenan, IBM’s global leader in the financial industry.

To understand more about quantum computing in finance, Tech Wire Asia spoke with John Duigenan, IBM’s global leader in finance. Duigenan is an industry veteran who has held technical and business roles spanning the entire product, sales and implementation lifecycle, with extensive development, service, sales and technology leadership.

When it comes to quantum computing in finance, Duigenan naturally believes that IBM is at the forefront of developing the technology. During a recent visit to its quantum computing research center in New York, Duigenan said there was a lot of excitement about the innovations being developed in the field.

“We are close to having a quantum advantage. This means that we are on the way to having algorithms that will make conventional decisions better or more efficiently on a quantum computer than on a traditional or classical computer. It is very exciting. If we think in the areas where quantum computing will make a difference in economics, it will be in how we generate quotes when assessing risk, how we optimize a portfolio of investments, and even how we price securities for anything where there is a large modulus, or large simulations, says Duigenan.

While Duigenan acknowledged that the world is still years away from quantum computers being widely available, IBM is already working on developing and testing more use cases with partners around the world.

“At IBM, we are working with innovative financial services companies and innovative companies from all industries on the Quantum Network. The Quantum Network allows innovative companies to use quantum computing today by connecting to the IBM cloud. They are using quantum computing right now,” he added.

IBM’s quantum network.

Quantum Network

The Quantum Network consists of over 200 Fortune 500 companies, universities, laboratories and startups all pulling together towards the quantum future. Members of the network include financial institutions such as Goldman Sachs, EY, University of Tokyo, Capgemini, Chicago Quantum Exchange, Samsung and others.

In May 2023, IBM announced plans to open its first Europe-based quantum data center to facilitate access to cutting-edge quantum computing for businesses, research institutions and government agencies. The data center is expected to be operational by 2024, with multiple IBM quantum computing systems, each with utility-scale quantum processors, i.e. those of more than 100 qubits.

In June 2023, France’s Crédit Mutuel Alliance Fédérale and its technology subsidiary Euro-Information announced plans to continue their investments with IBM in quantum computing. After a successful initial phase, the organizations have identified specific use cases, among many areas of interest in financial services, for the next scaling phase of the collaboration. This includes research into customer experience, fraud management and risk management. This phase also intends to explore opportunities for how quantum computing can lead to future improvements in Crédit Mutuel Alliance Fédérale’s customer and employee experience.

Duigenan also acknowledged that while these partnerships allow the most innovative companies to get in front of the technology and reap their own benefits as quantum computers become widely available, there will be a race for talent. And Duigenan believes the race for talent will be intense. This means that the companies that invest now will have the edge in quantum computing.

Cybercriminals will most likely use quantum computers in the future as well. (Image generated by AI)

With great technology comes a greater threat

As the use cases for quantum computers grow, Duigenan pointed out that there needs to be a focus on quantum security as well.

“Quantum security is an idea based on the premise that as soon as quantum computers exist, bad actors will use them for bad purposes. The primary bad aim, of course, is to break conventional encryption. This is a huge threat to any industry where encrypted data is a standard, because we all have to work on the basis that everything we encrypt today could be decrypted in the future,” he explained.

In the US, the National Institute of Standards and Technology (NIST) has championed the importance of quantum security. This year, the agency began the process of standardizing algorithms as the final step before making them available so that organizations around the world can integrate them into their encryption infrastructure.

“There is a massive research effort on and beyond research standards adopted in the US around quantum-safe algorithms. IBM is at the forefront of quantum-safe algorithms, both in terms of research and having these standards adopted by NIST. Quantum security is an area where many customers ask us how we are going to prepare and what they should do,” Duigenan added.

Considering the capabilities of quantum computers and the possible threats in the future, Duigenan believes that the biggest advantage of a quantum computer is its ability to support AI. That includes providing the computing power needed to run AI models, especially with the demand for greater computing by organizations today.