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Quantum Reports

A Technical Review of Quantum Computing Use Cases for Finance and Economics

Manqoba Q. Hlatshwayo, Manav Babel, Dalila Islas-Sanchez, Κωνσταντίνος Γεωργόπουλος

Published Mar 17, 2026• 2 citations
Publisher

Abstract

Quantum computing has been rapidly evolving as a field, with innovations driven by industry, academia, and government institutions. The technology has the potential to accelerate computation for solving complex problems across multiple industrial sectors. Finance and economics, with many problems exhibiting computationally heavy requirements, comprise a high-profile sector where quantum computing could have a significant impact. Therefore, it is important to identify and understand to what extent the technology could find utility in the sector. This technical review is written for quantum applications researchers, quantitative analysts in finance and economics, and researchers in related mathematical sciences. It is divided into two parts: (i) a survey of quantum algorithms pertinent to problems in finance and economics, and (ii) mapping of several use cases in the sector to the potential quantum algorithms presented in part (i). We discuss some challenges on the pathway to achieving quantum advantage. Ultimately, this review aims to be a catalyst for interdisciplinary research that will accelerate the advent of the practical advantages of quantum technologies to solve complex problems in this sector.

DOI
10.3390/quantum8010026

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Quantum computing has been rapidly evolving as a field, with innovations driven by industry, academia, and government institutions. The technology has the potential to accelerate computation for solving complex problems across multiple industrial sectors. Finance and economics, with many problems exhibiting computationally heavy requirements, comprise a high-profile sector where quantum computing could have a significant impact. Therefore, it is important to identify and understand to what extent the technology could find utility in the sector. This technical review is written for quantum applications researchers, quantitative analysts in finance and economics, and researchers in related mathematical sciences. It is divided into two parts: (i) a survey of quantum algorithms pertinent to problems in finance and economics, and (ii) mapping of several use cases in the sector to the potential quantum algorithms presented in part (i). We discuss some challenges on the pathway to achieving quantum advantage. Ultimately, this review aims to be a catalyst for interdisciplinary research that will accelerate the advent of the practical advantages of quantum technologies to solve complex problems in this sector.
Quantum technology is evolving rapidly with a potential to influence financial services. While quantum computing offers strong prospects for improving predictive analytics, risk management, and portfolio optimisation, its integration into financial systems remains constrained by algorithmic redesign requirements and technological limitations. This study reviews and synthesises research at the intersection of quantum computing and finance to map prevailing trends, thematic concentrations, and future inquiry paths. A systematic search of Web of Science and Scopus (2000–2023) identified 75 relevant studies, which were analysed using VOSViewer and Biblioshiny. The analysis shows that scholarly interest in quantum applications to finance accelerates only after 2020, indicating a temporal lag relative to the broader quantum computing literature. Four thematic clusters emerge: quantum cryptography and security, financial data processing, quantum algorithms for finance, and quantum machine learning. These areas reflect differing levels of maturity but reveal a shared emphasis on high-complexity modelling, enhanced data processing, and secure transaction frameworks. The review underscores the need for deeper algorithmic refinement, robust validation of financial use cases, and interdisciplinary collaboration among physicists, computer scientists, and finance researchers. Advancing these fronts will be essential for translating quantum potential into practical, scalable financial innovations.
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Quantum computers can solve specific problems that are not feasible on "classical" hardware. Harvesting the speed-up provided by quantum computers therefore has the potential to change any industry which uses computation, including finance. First quantum applications for the financial industry involving optimization, simulation, and machine learning problems have already been proposed and applied to use cases such as portfolio management, risk management, and pricing derivatives. This survey reviews platforms, algorithms, methodologies, and use cases of quantum computing for various applications in finance in a structured way. It is aimed at people working in the financial industry and serves to gain an overview of the current development and capabilities and understand the potential of quantum computing in the financial industry.
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Quantum computation holds the promise of highly efficient algorithms, provides exponential speedups for specific technologically significant problems, plays the most promising role in quantum technological progress, and has transformative potential in numerous industry sectors. In quantum computing, finance is recognized as one of the most beneficial areas because of the potential for many financial cases that can be solved by quantum algorithms suitable for noisy-intermedia-scale quantum(NISQ) computers. The benefits of quantum computing are colossal time and computational memory reduction with which the computational tasks are performed, which leads to the accuracy of the computations. This paper presents a comprehensive summary of quantum computing for traditional and Blockchain financial applications.