What Is Quantum Financial System? [A Simple Overview]

Quantum finance is a branch of econophysics, a heterodox interdisciplinary research field that involves applying theories and techniques to solve complex problems in economics.

Implementing quantum technology to financial problems — especially those dealing with nonlinear dynamics, uncertainty, or stochastic processes — can be extremely beneficial for first movers. Faster reaction to market volatility, more accurate risk analysis, and employing behavioral data to improve customer engagement are some of the specific advantages quantum computing can deliver in the upcoming decades.

If you are wondering whether the quantum financial system could be a real thing, then the answer is yes. It may sound like science fiction to some people, but this is a very genuine technology.

In fact, the concept of implementing quantum money was introduced in 1970 by research physicist Stephen Wiesner. However, it remained unpublished until 1983, and a practical way of developing it (using methods from semidefinite programming) was invented in 2013.

Today, the primary objective of the Financial Quantum System is to facilitate consistent integrity of the funds’ movement, precisely estimate uncertainty in financial models, and eliminate the shortcoming of the central banking system.

Current Financial System

The financial world has evolved a lot in the past 50 years. Not so long ago, the most common way to pay while buying something was to use cash. Now we have plenty of options. Use a debit/credit card or pay with an app or cryptocurrency wallet on your smartphone. The choice is yours.

Today, the 30 largest banks in the world manage more than $55 trillion combined. According to the Securities Industry and Financial Market Association, the size of the bond market is over $119 trillion worldwide and $46 trillion for the US market.

In this complex market, a vast number of financial services activities (ranging from securities pricing to risk analysis) are performed every second. Each activity requires the ability to assess short-term and long-term outcomes.

To do this, financial institutions utilize advanced algorithms and machine learning models that measure statistical probabilities. However, these models are not completely accurate — we all saw what happened during the 2008 financial crisis.

The current technology still needs to mature in many ways to fulfill promises. Thus, several financial companies are testing new processors that leverage the laws of quantum physics to process massive volumes of data at unprecedented speed. The possibilities are endless.

How Can Quantum Computing Help?

Quantum machines can revolutionize industries that require enormous computing power, including discovering new medicines, empowering deep neural networks, modeling financial markets, and developing a secure way of communication (quantum internet). In this article, we have focused on how quantum computers can improve current financial systems.

Banking sectors, non-banking financial companies, hedge funds, and other financial institutions deal with very sensitive data like customer transactions and contracts. This data needs to be kept private and secure for a longer period of time.

Most of the banking activities like security pricing involve a high degree of computational complexity. In the case of option pricing, additional complexity arises due to the need to respond to rapidly changing markets.

Thus, financial institutions are always looking for ways to efficiently determine the price of stock options, while keeping the customers’ data secure. The research has shown that quantum computing has great potential to solve such critical financial problems.

When it comes to simulating quantum mechanics and other algorithms such as Grover’s algorithm for quantum search and Shor’s algorithm for factorization, Quantum computers can easily outperform classical computers.

Basics of Quantum Computing 

The working principle of quantum computers is based on quantum physics, which shows that certain properties of particles remain in two different states, or any combination of two states, at any given time. Unlike classical computers that work on dualistic processing systems (0s and 1s), quantum machines can simultaneously be 0 and 1, or a blend of 0 and 1.

Since the quantum system can exist in multiple states at the exact same time (this phenomenon is called superposition), it can perform far more complicated tasks that are beyond the scope of classical supercomputers. This opens the exploration of vast computational possibilities.

The outcomes of quantum computation are also different from their binary counterparts. They are probabilistic (instead of deterministic), which means outputs can differ even if the input remains the same. Thus, the same computation must be done several times to make sure its results converge toward a mean.

While classical computers work with bits, the basic unit of quantum information is called a qubit (or a quantum bit). It can be engineered as photons, electrons, or nuclei. Examples include the polarization of a photon in which the two states can be the ‘horizontal polarization’ and ‘vertical polarization’; or the spin of an electron in which two states can be ‘spin up’ and ‘spin down.’

As per the quantum laws, a qubit can be in a coherent superposition of both states at the same time. For example, a two-qubit quantum computer could have ’00’ ’01’ ’10’ ’11’ states. A classical computer would require 4 bits to achieve this.

Similarly, 3 qubits can be the same amount as 8 binary bits, 4 qubits the same as 16 bits, 5 qubits the same as 32, 6 qubits the same as 64, and so on. To put this into perspective, a 300 qubit system can have more states than the total number of atoms in the universe. Even the most powerful classical supercomputer could never process that amount of data.

That is why financial institutions are showing a great interest in quantum computing. While no quantum machine is yet advanced enough to perform tasks that a classical computer can’t, great progress is underway.

Read: 22 Most Interesting Facts About Quantum Computers

Quantum Money System

In the standard model of banking, money is recognized in three different forms: commodity money, fiat money, and fiduciary money.

We have also seen the rise of cryptocurrencies in the past decade, but it is not yet widely recognizable. It’s a digital payment system that doesn’t have any central issuing or regulating authority. Instead, it is based on a distributed public ledger known as the blockchain, a record of all transactions held by currency holders.

Quantum money takes things to the next level. It applies quantum cryptographic protocol to generate and validate currencies. Since arbitrary quantum states cannot be perfectly copied, it is impossible to forge quantum money.

The idea looks great on paper, but it is not feasible to implement with current technology. This is because quantum money requires to store the arbitrary quantum states in quantum memory, a quantum-mechanical version of conventional computer memory.

Although years of research and experiments have enabled quantum memory to store qubits, it can do so only for a very short time. Many research institutes across the world are working on new materials to create memories that could hold the quantum information carried by light.

Benefits Of Quantum Financial System

While doubling the power of a conventional computer requires approximately twice the number of transistors working on a task, the power of a quantum computer can be doubled by adding only one qubit. Therefore, it could be significantly beneficial for first movers.

Quantum computing can enable financial institutions to solve very specific business problems and re-engineer some operational processes in the next decade.

Customer targeting and prediction modeling: Quantum computers are exceptionally good at finding hidden patterns from complex data structures, performing classifications, and accurate predictions. 

Fraud detection: Financial institutions lose $20-$45 billion in revenue every year due to fraud and poor service management practices. Existing fraud detection systems are not that reliable. They return 80% false positives, causing the banking sector to remain at risk most of the time.
Quantum computing may offer a definitive edge in the battle against payment fraud. The power of exponential speed, derived from quantum superposition and entanglement, can help re-evaluate various possible solutions to optimize fraud detection algorithms.

Client management: Quantum computing could perfectly streamline processes and help staff make the customer experience flawless.

Portfolio management: Quantum computing has the potential to speed up asset-pricing models and cultivate performance improvements. It can make a myriad of optimization calculations in a fraction of the time without the necessity to use approximations.

Its combinatorial optimization capabilities could help investors improve portfolio diversification, rebalance portfolio investments according to the market conditions and end goals, and efficiently streamline trading settlement processes.

Recent Developments In Quantum Finance

Progress made in the last 10 years towards quantum supremacy proves that quantum computers are more capable of solving some specific problems than any conventional computers.

In 2014, for example, a team of researchers from the Netherlands harnessed the capabilities of quantum mechanics to develop a fraud-proof technique for authenticating a credit/debit card that is virtually impossible to thwart.

In 2018, Canadian researchers published a quantum algorithm for the Monte Carlo pricing of financial derivatives, demonstrating a method to create relevant probability distributions in quantum superposition and a technique to extract the price of financial derivatives through quantum measurements.

In 2020, David Orrell proposed a binomial option pricing model based on a quantum walk that can be run directly on a quantum device. In the same year, D-Wave quantum computers were used to solve the Portfolio Optimisation problem. The results were very promising: the performance of the D-Wave hardware (though limited in size) is comparable to superfast classical computers.

In 2021, a group of researchers developed quantum algorithms for high-frequently statistical arbitrage trading by using variable time condition number estimation and quantum linear regression.

The Present and Future Of Quantum Finance

Quantum computing technology isn’t fully developed yet. In fact, most of its benefits and applications are still conceptual. Thus, the whole banking sector is left with two choices:

  • Either wait for the technology and react only when opportunities or threats are identified.
  • Or start connecting with the quantum world, identify use cases, and integrate quantum security solutions.

The second option seems better. Many investment banks and financial services holding companies, including JPMorgan Chase, HSBC, and Wells Fargo, have already started pouring millions of dollars into quantum research and innovation programs.

A large body of research and engineering work has been dedicated to the realization of quantum algorithms with substantial polynomial speedups in data-loading and data data-processing subroutines.

So far, no practical application of quantum computing with exponential speedup over its classical counterpart has been invented, but numerous promising models have been proposed.

IBM, for example, has been managed to pack 127 qubits in its proprietary quantum-computing chip. The processor uses multiple layers to host signal-carrying wires, which allow precise readouts of the qubits. Although the technique is common in classical chips, it’s a huge achievement in the world of quantum computing.

It is expected that quantum computers will surpass the capabilities of classical computers by the end of 2030. Tech giants, including IBM and Google, are working on quantum machines that can hold hundreds of quantum bits. IBM has made its aspirations more concrete by releasing a blueprint for the development of quantum computers, which includes the aim of developing a 1000-qubit computer.

This will have a disruptive impact on numerous industries, particularly finance. In fact, finance is estimated to be the first sector to benefit from quantum computing in the short and long terms.

However, the future advancements of quantum computing within banking and financial institutions are not without challenges. Identifying what problems can be efficiently solved by quantum machines, improving the interface for better accessibility, upgrading the infrastructure to suit this technology, and extending the interest in such quantum machines beyond an elite group of physicians and mathematicians — these are some of the challenges in this field that have to be dealt with in the near future.

Overall, adopting quantum-based solutions is not a short-term process. It’s not like upgrading your software systems where you click a button and be done with everything. It’s a long-term journey, and it depends not only on the banking sector’s capability to define problems and adjust the infrastructure but also on its ability to include staff and customers in this process as well.

Frequently Asked Questions

What are the most popular quantum algorithms?

A quantum algorithm is a step-by-step instruction, where each step can be performed on a quantum computer. The term ‘quantum’ is used for those algorithms that utilize some basic features of quantum computations, such as quantum entanglement or quantum superposition.

These algorithms can be applied in various fields, including search and optimization, cryptography, solving large systems linear equations, and simulation of quantum systems. The five most popular quantum algorithms are —

  1. Shor’s algorithm: factors integers in polynomial time
  2. Grover’s algorithm: can quickly solve the unstructured search problems
  3. Simon’s algorithm: solves a specific problem exponentially faster and with fewer queries than the best deterministic classical algorithm.
  4. Bernstein–Vazirani algorithm: was developed to prove an oracle separation between complexity classes BPP and BQP.
  5. Deutsch–Jozsa algorithm: was the first to show that using a quantum computer as a computational tool for a particular problem can be advantageous.
When will the quantum financial system start?

The era of the quantum financial system is about to begin. Within the next decade, quantum computing will most probably become one of the mainstream solutions in the finance sector.

According to the MarketsandMarkets Research report, the quantum computing market size is expected to reach $1.76 billion by 2026 from $472 million in 2021, growing at a CAGR of 30.1% during the forecast period. The early adoption of quantum-based technologies in the finance sector is expected to fuel the growth of the market worldwide.

Which banks are investing in quantum computing?

J.P. Morgan, Goldman Sachs, Citigroup, Mitsubishi Financial Group, Barclays, Wells Fargo, BNP Paribas, HSBC, and Japan Post Bank — they all are pouring millions of dollars into this technology; some have started experimenting with quantum computing applications.

Can you invest in quantum computing?

Yes, there are a lot of opportunities available for investors who want to bet on quantum computing technology. A number of companies working in this area are listed on New York Stock Exchange. A quantum computing ETF (defiance quantum ETF) is also available to get more general exposure to this industry.

Written by
Varun Kumar

Varun Kumar is a professional science and technology journalist and a big fan of AI, machines, and space exploration. He received a Master's degree in computer science from GGSIPU University. To find out about his latest projects, feel free to directly email him at [email protected] 

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