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From Adam HammondQuantum business leader, IBM

Quantum computers bet on probabilities and could soon help the financial sector predict how market swings will affect future economies more precisely than ever before.

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

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 levels of accuracy and efficiency.

For example, to estimate future asset price fluctuations, you need to take into account past events, such as the state of the economy influenced by everything from natural disasters to inflation, government policies and technological changes, and extrapolate data into the future. A classical computer running a Monte Carlo simulation: the preferred technique for analyzing the impacts of risk and uncertainty financial models—create millions of possible outcomes and average them to arrive at the expected future value of the asset. The result of this simulation is an approximation. This simulation takes many hours to run and is subject to uncertainties, such as the impact of rapid changes occurring in the world.

Second The British Finance Report “Seizing Opportunities: Quantum Technology and Financial Services,” “Quantum computing has the potential to significantly accelerate Monte Carlo simulations, thereby enabling more agile risk calculations by considering and simulating a greater number of variables.”

A quantum computer could use far fewer samples to achieve the same, or better, accuracy faster, leaving far less chance that the results would be heavily influenced by market volatility. This is because quantum computers differ fundamentally from the classical computers we use today. They are based on quantum bits, or qubits, rather than the classical bits of today’s computers, and they work with probabilities rather than certainties. Digital bits must be 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 allow a quantum computer of the future to perform more complex calculations than a classical computer can.

Numerous financial institutions are already experimenting with this new technology and others are expected to follow suit. A recent Deloitte study have predicted that financial services industry spending on quantum computing will increase 233-fold, from $80 million in 2022 to $19 billion in 2032.

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

For example, the document “Quantum optimization: potential, challenges and path forward,” published in December 2023 by more than 30 organizations, including financial services organizations in the IBM Quantum Network, described how optimizing portfolio management and trading strategies could benefit from quantum. “The financial sector offers a broad spectrum of difficult optimization problems and requires the exploration of new solution approaches to address many of today’s trade-offs…. The main challenge remains to effectively combine both modeling and optimization 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 optimize their portfolios, better manage risks and improve their overall financial performance. Quantum computers can help with asset allocation, considering factors such as risk, return, liquidity and diversification. They could also assist in options pricing, macroeconomic modeling, algorithmic trading, lending and fraud detection. As for simulations to be modeled to predict financial market behaviors, quantum computers should help with more accurate and faster simulations, leading to better decision making and better risk management.

In an other recent document that my colleagues and I wrote with the UK banking and financial services trade association, UK Finance, “Seizing opportunities: quantum technology and financial services”, regarding the impacts of quantum technology on the financial sector and the its opportunities, we outlined several areas where quantum computing could help:

1. Risk analysis: Improved risk analysis capabilities by helping process complex data and running complex simulations at unprecedented speeds, leading to more informed business and investment decisions.
2. Compliance: Simplify compliance processes by identifying patterns and discrepancies in data sets, reducing the time and resources needed to ensure regulatory compliance.
3. Investments: Improve portfolio optimization and asset management by quickly processing complex calculations, identifying optimal investment strategies, and maximizing returns while minimizing risk.
4. Data privacy: Protects sensitive data through quantum cryptography and encryption techniques, ensuring customer and transaction information is protected.
5. Data management: Revolutionize data management in financial services by processing data quickly and efficiently, enabling better decision making, trend identification and overall operational efficiency.
6. Operations: Optimize operational processes, such as logistics, supply chain management and resource allocation, finding the most efficient solutions to complex problems.
7. Sales: Improving sales strategies through advanced data analytics and customer segmentation, identifying new market opportunities and personalizing product offerings.
8. Prices: Improve pricing models by quickly analyzing complex market data and identifying optimal pricing strategies, resulting in more accurate and competitive pricing.

Quantum computers are not yet capable of delivering industry benefits, including financial services applications, but they are getting closer. In 2023, a research article published in Nature, on which IBM scientists collaborated with the University of California, Berkeley, brought the world into the age of quantum utility. For the first time in history, quantum computers have demonstrated the ability to solve problems on a scale beyond classical brute-force simulation, where the only alternatives are carefully crafted problem-specific classical approximation methods. We are now at the point where quantum computers can serve as scientific tools to explore new classes of problems in chemistry, physics, materials, and the types of optimization problems found in finance.

This is the next important step on the path to quantum advantage, which we see as the moment when quantum computers will be able to offer a practical and significant advantage beyond brute force or approximate classical computation methods, by computing solutions in a way that is cheaper, faster or more effective. accurate of all known classical alternatives.

In an article by the Boston Consulting Group (BCG), cited in the IBM Institute for Business Value 2023 report “Make quantum readiness real” relationship, early adopters are ready to reap the benefits. BCG analysts have estimated that by 2035, quantum computing technology could potentially create between $450 billion and $850 billion in net income for all end users through cost savings and revenue generation. The problem is a critical note at this stage of the game: in most areas, a lot 90% of that value could go to early adopters.

Now is the time for financial institutions to prepare for quantum. Any leader of a financial services organization who is not actively exploring how quantum computing fits into their plans risks being left behind. As we wrote in the UK Finances Report:

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

“Many” for something countable, like the samples referenced. “A lot” for something uncountable.

ABOUT THE AUTHOR

Adam Hammond leads IBM Quantum’s enterprise business in EMEA and APAC, demonstrating to clients the potential of quantum computing to transform their businesses. He is an experienced technical architect helping to drive innovation and transformation, with a track record across multiple industries, including financial services and retail.

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