Barak Azar, Classiq’s quantum solutions architect, explores how financial firms use quantum computing to gain lucrative gains and bolster security in the quantum era.
As quantum computing edges closer to practical application, global finance giants like JPMorgan Chase, CITI, and HSBC are increasingly investing in this groundbreaking technology to revolutionize their operations and secure a competitive advantage.
Some may dismiss quantum computing as science fiction. But the technology is coming closer to reality, so much so that many of the world’s biggest banks, including Standard Chartered, JPMorgan Chase, and HSBC are all investing into quantum and investigating its potential. Citi Innovation Labs, for instance, is collaborating with quantum computing experts to use the Quantum Approximate Optimization Algorithm (QAOA) to enhance portfolio management, an effort that highlights the potential of quantum technologies to revolutionize financial analytics and risk assessment. Why are these financial giants exploring this scientific frontier, and how will it benefit them?
Quantum computing holds huge potential for the finance industry. Once fully realized, the technology could allow sophisticated calculations to be performed in a fraction of the time it currently takes or process financial models too complex for today’s technology. The finance industry is already exploring quantum’s potential for optimizing investment portfolios by finding arbitrage opportunities faster and calculating multiple variables simultaneously. Similarly, the technology could power machine learning models for credit scoring and risk analysis using ever larger datasets. But these are not the only opportunities.
Making Better Predictions
The finance industry has a substantial chance of being the first to extract business value from quantum computing and experience a positive financial impact in the shortest time. That’s because many quantum algorithms that would benefit financial institutions have already been written and are shown to work faster and better than their classical algorithms. It’s just a matter of time before quantum hardware is produced with enough qubits to run these algorithms.
For example, Monte Carlo simulations are commonly used in almost all financial analysis, especially to predict the price of complex derivatives and stock prices. The Monte Carlo method uses random numbers to simulate lots of scenarios, and these results are then used to estimate the likelihood of an outcome. The more scenarios you can run, the more accurate the outcome will be. The nature of quantum computing means that a quantum version of a Monte Carlo algorithm can run more simulations simultaneously, meaning financial analysts can converge on a more accurate answer in a shorter space of time.
Financial institutions are eager to explore use cases like this because of the potential benefits. Even if the result from a quantum Monte Carlo simulation is only a fraction of a percentage more accurate than a traditional simulation using classical computing, that increased accuracy could translate to billions—even trillions—of dollars of revenue from better returns and profits, given the large sums of money at stake. Making better investment or risk management decisions will also give these financial institutions a compelling competitive advantage.
In the future, quantum computing may even be able to help with the most complex tasks required by financial institutions, such as high-frequency trading, which requires fast, accurate, and highly demanding decisions to be made in quick succession.
See More: Why Companies Should Patent Their Quantum Technology Now
Security in the Quantum-era
The other reason the finance industry is exploring quantum technology is because of the risks it poses. It has long been established that quantum computing will be able to break the encryption protocolsOpens a new window used to secure digital assets, including the encryptions used to protect financial data and banking accounts. As such, quantum decryption has been recognized as a future security risk to financial systems.
However, quantum computing will also play a key role in securing these systems in the future. The technology could be used to detect if accounts have been broken into and spot fraudulent activity faster and more easily.
Similarly, current cryptographic protocols rely on random number generators (RNGs) to create security keys. But today’s RNGs are not truly random and are generally based on some form of algorithm—it is these algorithms that represent a vulnerability, as quantum computers will be able to solve them. The properties of quantum computers mean they will be able to generate truly random numbers, and so they could be used to improve encryption.
Organizations and government agencies are already exploring new security standards that will resist quantum decryption. In fact, the US National Institute for Standards and Technology (NIST) announced in 2022 the first quantum-resistant cryptographic algorithms that will become part of its new encryption standard.
To prepare for quantum decryption, banks and financial institutions must research these new methods and prepare to move their encryption to these quantum-resistant standards once they’re complete to ensure their data is protected. Institutions that make these changes quickly will enjoy a competitive advantage by virtue of being able to reassure clients and investors that quantum computers cannot break their encryptions.
In addition to researching quantum security, how else should financial organizations prepare for the quantum era?
Becoming Quantum-ready
Financial institutions need to explore how the advent of quantum computing will affect their core competencies and the areas of finance where they excel. Institutions must create new processes, algorithms, and computer codes incorporating quantum technology to protect those competencies and their competitive advantage. They can then patent these processes and build a fence around these competencies to protect their core business practices.
Banks will need to invest in their quantum capabilities to create quantum-ready patents. That might mean hiring quantum experts and scientists or teaching their financial analysts about quantum principles. Writing quantum computer code can be challenging as it is much different to classical programming. Still, modern quantum software providers are designing solutions that abstract some challenges and make it more accessible to those without quantum expertise. Also, as these quantum teams design quantum code for their institutions, they will need to investigate which quantum machines currently in development will work best with their code and produce the most accurate results with the fewest errors.
Becoming quantum-ready will take significant time and investment, but financial institutions must start considering it quickly. While fully working quantum computers may be several years away, banks need to be prepared to integrate this technology into their existing legacy systems, which they cannot do overnight. Changing the way these institutions make their calculations and financial decisions, such as by switching to a quantum Monte Carlo simulation, will not be a trivial task. However, the banks that make those switches first will be able to enjoy a considerable first-mover advantage over their slower competitors.
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