The Quantum Menace​​​​​

 
The opportunities presented by Quantum Computing to the Financial Sector

Quantum computing is a rapidly emerging technology that harnesses the laws of quantum mechanics to solve problems too complex for standard computers.  It differs from standard computing in terms of speed, data, and bits. According to Mckinsey,[1​] the global quantum computing market is projected to grow to US$93 billion by 2040 with an estimated US$6 billion invested to date. Further, several nations (e.g. China, Canada and Germany) are funding significant quantum computing projects aimed at making major quantum discoveries.[2]'[3​]The European Union (EU) has launched several initiatives, including the Quantum Flagship, a 10-year, EUR1 billion research and innovation program, and is developing the European Quantum Communication Infrastructure (EuroQCI), which aims to create a secure quantum communication infrastructure spanning all twenty-seven (27) EU Member States.[4]​

The financial services sector is well positioned to exploit the quantum advantage with global financial institutions increasingly engaging in quantum research to create higher value while ensuring unbreakable data security. For example, Mastercard has aligned with a strategic partner to develop quantum-hybrid applications for consumer loyalty and rewards, cross-border settlement, fraud management, and anti-money laundering[5]. Other financial institutions have started leveraging quantum computing for pricing and portfolio optimization, advancing net zero goals, and mitigating risks, including identifying and addressing fraudulent activity[6].   Examples of quantum-powered financial services applications include:

1. High-frequency trading: Quick execution of complex and quantitative buy-sell strategies which will improve a financial institution's ability to generate greater returns while controlling risk.

2. Fraud detection: Quick and accurate identification of fraud indicators to enable proactive fraud risk management.

3. Asset valuation: Efficient risk analysis by uncovering intelligence from large information sets and processing data at lightning speeds.

4. Transaction Optimization: Improved efficiency in clearing large batches of transactions that have varying credit, collateral, and liquidity constraints.

5. Clustering: Effective grouping of seemingly disparate sets of assets to enable the discovery of patterns in areas, such as asset performance, consumer sentiment, and risk aversion.

6. Quantum-proofing of cybersecurity systems: Next-generation cryptography to safeguard confidential customer data.

7. Simulation: Offer the potential to simulate larger complex processes and molecules that classical computers can't, enabling faster and more efficient solutions to certain class of problems. Basel standards require banks to perform stress tests and to hold an amount of capital that depends on their risk-weighted assets. However, pricing and estimating the risk of financial instruments is computationally intensive. Analytical models are often too simplistic to capture the complex dependencies between financial instruments or cannot consider some of their features such as path-dependency (Monte Carlo simulations vs quantum amplitude estimation).

8. Machine learning: Quantum versions of these subprograms (referred to as quantum BLAS[7]) offer exponential speedups compared to their classical counterparts, which in turn could dramatically speed up machine learning algorithms ranging from the relatively simple k-means[8] (used for clustering) to neural networks (used for many different systems such as recommendation systems).

 
The risks presented by quantum computing

Current aspects of information technology (IT) security rely on encryption and public key cryptography techniques, which underpins much of the current global internet security and privacy infrastructure. These techniques are based, in turn, on mathematical factorization algorithms that are very difficult to “break." However, quantum computers can solve these problems faster due to their ability to process vast amounts of data simultaneously and perform calculations at speeds unattainable by classical computers.

As a result, encryption that secures web interactions, personal data, financial information, and national security could be rendered useless against a quantum computer's capabilities. How this can potentially play out in the financial sector is summarised below:

1. Cybersecurity risk: Financial systems, especially web-based systems that rely on encryption for functions like login data or secure transmission of transactions could be compromised as quantum computers, should they reach sufficient size and power, may be able to break the encryption schemes widely used today to ensure secure financial transactions and data.

2. Data Privacy risk: Sensitive data transmitted could be and are potentially already being captured (including emails as an example), for later harvesting that could lead to risks like personal data breaches, espionage and embarrassment leading to the undermining of trust in corporates, financial markets and countries.[9]

3. Trust in the financial system: Quantum computing could potentially allow the 'breaking' of the hashes that are used in the security protocol layer that underpins blockchain technology. If that happens, it could render the entire blockchain mutable (meaning it could be changed without anyone realizing it), thereby potentially making all crypto assets and other blockchain based forms of value worthless and all related sensitive contracts immediately transparent.[10].

4. Black box risk: The nature of quantum computing and its programming makes it difficult to understand exactly how an output is determined. People cannot monitor quantum calculations without disrupting the quantum effects the computer relies on. This requires work with technical and ethics experts to evaluate whether quantum computing can limit bias by considering the ethical benefits that that can be derived from increased accuracy of computational outcomes.

5. Legal and reputation risk: Digitally signed or verified artifacts may be altered and signatures forged, thus changing the trustworthiness of underlying records resulting in major fraud, disputes, and compromised legal enforcement.[11]

 
Regulatory Implications

Given the risks highlighted above, regulators in major financial markets have encouraged pre-emptive moves to strengthen cryptographic security. This necessitates the transition to quantum-resistant cryptography from quantum vulnerable infrastructure long before large-scale quantum computers are operational. For example, the Bank for International Settlements (BIS) embarked on Project Leap to help secure the financial system against quantum computing vulnerabilities by assessing the feasibility of quantum-resistant cryptographic protocols. The initial phase demonstrated that applying new quantum-resistant schemes is possible.[12​].

Further, as at end-November 2023, the US National Institute of Standards and Technology closed its consultation for draft cryptographic standards designed to resist future attacks by quantum computers - a major milestone for moving post-quantum, or quantum-safe, cryptography (PQC) from the research stage to a global IT migration strategy. Closer to home, WITS University was given R54million in funding from the Department of Science and Innovation (DSI) in 2022 to start the South African Quantum Technologies Initiative (SA QuTI) to conduct research on quantum computing technologies and to grow the local quantum technology industry[13].

From the foregoing, it is apparent that the development of quantum technologies raises a series of questions for regulators and policy makers. For instance, how might quantum technologies stimulate wider market innovation and competition; how the transition to quantum-secure cryptography can be supported, and the role of the regulators in that process. Additional questions for consideration include the potential governance, societal and ethical implications from these technologies, how standards and ecosystem consensus can support quantum innovation while leveraging learnings from other emerging technologies to ensure that innovation in quantum and other technologies happens responsibly.

Concluding thoughts

Quantum computing could tackle problems that have simply been unsolvable before—and potentially introduces problems never encountered before in the financial sector. This will catalyse a paradigm shift and change the realm of possibilities. True commercial viability of quantum computers across the world is still a few years away, with 2030 often touted as the expected timeline, though some are anticipating sooner. It is thus worthwhile for regulators and policy makers to keep their fingers on the pulse on how this technology is evolving and start thinking about frameworks to build a cohesive ecosystem and prepare for a quantum-powered future.​​

[1] Quantum Technology Monitor (2023) available from: https://www.mckinsey.com/~/media/mckinsey/business%20functions/mckinsey%20digital/our%20insights/quantum%20technology%20sees%20record%20investments%20progress%20on%20talent%20gap/quantum-technology-monitor-april-2023.pdf

[2​]https://www.scientificamerican.com/article/china-is-pulling-ahead-in-global-quantum-race-new-studies-suggest/

[3​​]https://www.prnewswire.com/news-releases/government-of-canada-supports-xanadu-to-accelerate-quantum-computing-research-and-education-302068598.html

[4​​]https://digital-strategy.ec.europa.eu/en/policies/quantum-technologies-flagship 

[5​​] Banking on a Quantum Powered Future for Financial services available from: https://www.infosysbpm.com/blogs/digital-business-services/banking-on-a-quantum-powered-future-for-financial-services.html 

[6​​] HSBC working with IBM to Accelerate Quantum Readiness. Available from: https://newsroom.ibm.com/2022-03-29-HSBC-Working-with-IBM-to-Accelerate-Quantum-Computing-Readiness 

[7​​] Basic Linear Algebra Subroutines

[8​​] The k-means algorithm finds groups in data, with the number of groups represented by the variable 'k'. The algorithm works in an iterative manner to assign each data point to one of the k groups based on the features that are provided.

[9​​] Guarrera & Khan (2023). Preparing financial services cybersecurity for quantum computing. Available from https://www.ey.com/en_us/strategy/financial-services-cybersecurity-for-quantum-computing

[10​​] 15 Significant Ways Quantum Computing Could Soon Impact Society, Forbes Expert Council. Available from https://www.forbes.com/sites/forbestechcouncil/2023/04/18/15-significant-ways-quantum-computing-could-soon-impact-society/?sh=6caa3305648b

[11​​] Xu, Z., 2023. The Advance of Digital Signature with Quantum Computing. Highlights in Science, Engineering and Technology, 39: 1111-1121. Available from https://drpress.org/ojs/index.php/HSET/article/view/6716

[12] https://www.bis.org/about/bisih/topics/cyber_security/leap.htm

[13​​] IT Web (2022), “Wits gets R54m funding to put SA on quantum map", available here: https://www.itweb.co.za/article/wits-gets-r54m-funding-to-put-sa-on-quantum-map/JBwErvn33Zg76Db2#:~:text=R54%20million%20in%20funding%20from,Technologies%20Initiative%20(SA%20QuTI).

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