How Quantum Computers Can Give Fintech a Major Boost

6

By Adam Hammond, Quantum Business Leader, IBM

Quantum computers bank on probabilities and may soon help the financial sector predict how market wobbles will impact future economies more precisely than ever before.

Typically, financial institutions use complex algorithms to forecast, for example, the movements of financial assets such as shares and commodities. However, predicting when and how an asset’s price will change is difficult, as the future price relies on a probability distribution calculated from time-series data. Traditionally, investors have used time-consuming and expensive simulations to determine the probabilities of future payoffs while assessing potential risks.

The quantum computers of the future could take financial forecasting to a whole new level, helping to predict the impacts of future market fluctuations with much higher degrees of accuracy and efficiency.

For instance, to estimate assets’ future price fluctuations, it is necessary to account for past events, such as the state of the economy impacted by anything from natural disasters, inflation, government policy and technological changes, and extrapolate the data into the future. A classical computer running a Monte Carlo simulation—the preferred technique to analyse the impacts of risk and uncertainty in financial models—creates millions of possible outcomes and computes their average to reach the asset’s forecasted future value. The result of such a simulation is an approximation. This simulation takes many hours to run and is subject to uncertainties, such as the impacts of fast-paced changes occurring in the world.

According to UK Finance’s report “Seizing the opportunities: quantum technology and financial services”, “Quantum computing has the potential to significantly accelerate Monte Carlo simulations, therefore allowing more agile risk calculations considering and simulating a larger number of variables.”

A quantum computer could use many fewer samples to achieve the same—or better—accuracy faster, leaving much less chance for the results to be strongly affected by market volatility. That’s because quantum computers fundamentally differ from the classical computers we use today. They rely on quantum bits, or qubits, instead of today’s computers’ classical bits, and they work with probabilities instead of certainties. Digital bits must be either 1 or 0, but qubits can be in a “superposition” of both states. And when qubits are linked together, or “entangled”, these and other quantum mechanical properties will enable a quantum computer of the future to run more complex calculations than a classical computer can.

Several financial institutions are already experimenting with this new technology, and more should follow suit. A recent Deloitte study forecasted the financial-services industry’s spending on quantum computing to surge 233 times from US$80 million in 2022 to US$19 billion in 2032.

Other benefits go beyond assessing potential credit risks. In the future, quantum computers are expected to excel in optimisation.

For example, the paper “Quantum Optimization: Potential, Challenges, and the Path Forward”, published in December 2023 by more than 30 organisations, including financial-services organisations in the IBM Quantum Network, described how the optimisation of portfolio management and trading strategies could benefit from quantum. “The financial industry offers a broad spectrum of hard optimization problems and demands the exploration of new solution approaches to tackle many of today’s trade-offs….The main challenge remains to effectively combine both the modeling and optimization of problems to achieve practically relevant results for industry use cases.”

Quantum computers could potentially find the best solutions to these problems faster than classical ones, helping financial institutions optimise their portfolios, better manage risks and improve their overall financial performances. Quantum computers may help with asset allocation, considering factors such as risk, return, liquidity and diversification. They could also assist with option pricing, macroeconomic modelling, algorithmic trading, lending and fraud detection. As for simulations to model to predict the behaviours of financial markets, quantum computers should help with more accurate and faster simulations—leading to better decision-making and risk management.

In another recent paper that my colleagues and I wrote with the trade association for the UK banking and financial-services sector, UK Finance, “Seizing the opportunities: quantum technology and financial services,”  regarding the impacts of quantum technology on the financial sector and its opportunities, we outlined several areas in which quantum computing could help:

1. Risk analysis: Enhancing risk-analysis capabilities by helping to process complex data and running complex simulations at unprecedented speeds, leading to better-informed investment and business decisions.
2. Compliance: Streamlining compliance processes by identifying patterns and discrepancies in datasets, reducing the time and resources required to ensure regulatory adherence.
3. Investments: Improving portfolio optimisation and asset management by processing complex calculations rapidly, identifying optimal investment strategies and maximising returns while minimising risks.
4. Data privacy: Securing sensitive data through quantum cryptography and encryption techniques, ensuring the protection of customer and transactional information.
5. Data management: Revolutionising data management in financial services by processing data quickly and efficiently, enabling better decision-making, trend identification and overall operational efficiency.
6. Operations: Optimising operational processes, such as logistics, supply-chain management and resource allocation, by finding the most efficient solutions to complex problems.
7. Sales: Enhancing sales strategies through advanced data analytics and customer segmentation, identifying new market opportunities and personalising product offerings.
8. Pricing: Improving pricing models by quickly analysing complex market data and identifying optimal pricing strategies, resulting in more accurate and competitive pricing.

Quantum computers are not yet capable of delivering advantages for the industry, including financial-services applications, but they are getting close. In 2023, a research paper published in Nature, on which IBM scientists collaborated with the University of California, Berkeley, moved the world into the era of quantum utility. For the first time in history, quantum computers demonstrated the ability to solve problems at a scale beyond the brute-force classical simulation—in which the only alternatives are carefully crafted, problem-specific classical approximation methods. Now, we’re at the point at which quantum computers can serve as scientific tools to explore new classes of problems in chemistry, physics, materials and the kinds of optimisation problems found in finance.

This is the next major step on the path towards quantum advantage, which we consider the moment when quantum computers can deliver a significant, practical benefit beyond either brute force or approximate classical computing methods—calculating solutions in a way that is cheaper, faster or more accurate than all known classical alternatives.

In an article by the Boston Consulting Group (BCG), cited in the IBM Institute for Business Value’s 2023 “Make quantum readiness real” report, early adopters are poised to reap the rewards. BCG’s analysts estimated that by 2035, quantum-computing technology could potentially create $450 billion to $850 billion in net income for all end users via cost savings and revenue generation. The catch and a critical note at this stage of the game: In most industries, as much as 90 percent of that value could go to early adopters.

Now is the moment for financial institutions to get quantum-ready. Any leader of a financial-services organisation who isn’t actively exploring how quantum computing fits into its plans risks being left behind. As we wrote in the UK Finance report:

“Quantum computing has the potential to revolutionise optimisation, portfolio management, and investment strategies in the financial services industry. By harnessing the power of this cutting-edge technology, financial institutions can optimise their investment portfolios, reduce risk, and maximise returns by efficiently solving complex mathematical models, considering a vast number of variables and constraints, and leveraging quantum and machine learning algorithms.”

“Many” for something countable, like the samples referenced. “Much” for something non-countable.