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Exploring the Game-Changing Potential of Quantum Computing in Finance and Beyond

  • Vrinda Mathur
  • Jul 23, 2024
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Many scientists believe that a full-scale fault-tolerant quantum computer could be operational by 2035. However, important technological breakthroughs are already underway. 

 

This means that financial services organizations can gain significant value long before fault-tolerant quantum computers are accessible by learning, developing business capabilities, and aligning business processes to speed up integration when fault-tolerant quantum computers become available. Machines can be used to price derivatives and generate inputs for portfolio optimisation.

 

Brief about Quantum Computing

 

A quantum computer uses some of quantum mechanics' almost-mystical phenomena to achieve massive increases in computing power. Quantum machines have the potential to outperform even the most proficient supercomputers of the present and future.

 

However, they will not eliminate conventional computers. Using a classical machine will still be the easiest and most economical solution for tackling most problems. But quantum computers promise to power exciting advances in various fields, from materials science to pharmaceuticals research. Companies are already experimenting with them to develop things like lighter and more powerful batteries for electric cars, and to help create novel drugs.

 

Today's computers use bits, which are a sequence of electrical or optical pulses that represent 1s or 0s. Everything from your tweets and e-mails to your iTunes albums and YouTube videos is essentially a long string of binary bits.

 

In contrast, quantum computers rely on qubits, which are typically subatomic particles like electrons or photons. Generating and managing qubits presents a scientific and engineering challenge. Some organizations, including IBM, Google, and Rigetti Computing, use superconducting circuits cooled to temperatures colder than deep space.

 

What future missions could quantum computing help achieve?

 

One of the most potential applications of quantum computers is to simulate the behavior of matter at the molecular level. Quantum computers are being used by automakers such as Volkswagen and Daimler to simulate the chemical composition of electric vehicle batteries in order to discover novel ways to improve their efficiency. Pharmaceutical companies use them to analyze and compare chemicals that may lead to the development of new medications.

 

As technology advances, the challenges we face become increasingly complex. Quantum computing provides a solution for complicated challenges such as protein modeling. The recent global problem caused by COVID-19 demonstrates that scientists require a novel approach to predict and deactivate a single protein. Another example of an exponential increase in difficult problems is energy usage.

 

As the human population and consumption rate grow rapidly, more difficult challenges arise, such as source optimization. Quantum computers can employ quantum mechanics to overcome the limits of difficult tasks.

 

Classical computing is an effective technique for executing sequential operations and storing data. Chaotic situations, on the other hand, are difficult to solve because they are modeled using linear mathematics.

 

Quantum computing appears to be a promising contender for solving nonlinear problems due to its natural nonlinear features. That stated, quantum computers are not appropriate for all types of computation.

 

Also Read | Everything you need to know about Quantum Artificial Intelligence

 

How can Quantum Computing be used in Finance?

 

Potential use cases in finance go beyond the well-known ones, such as portfolio optimisation, and include a few that could be revolutionary.

 

  1. Corporate Banking

 

Corporate banking is the most important application of quantum computing due to the large monetary value at risk and the various complex use cases in sectors such as trade finance.

 

Consider collateral optimisation in use cases like securities lending, which requires cross-optimizing numerous sets of variables. Optimisation issues with a large number of variables and constraints get more complex. Certain aspects of the optimization can be delegated to a quantum computer, solved with greater precision, and then returned to the entire calculation.2 This approach can similarly be used to estimate the probability of default, which consists of many optimization variables, before making a lending decision.

 

  1. Risk and Cybersecurity

 

Risk is one of the most difficult business units in banks, as it entails recognising, mitigating, and reporting risks across many units. Quantum computing is expected to cause a huge shift in regulatory risk reporting.

 

A full-scale fault-tolerant quantum computer would be capable of decrypting existing encryption algorithms. Even now safe data can be captured by malicious actors for later decryption when quantum technologies enable it.

 

Post-quantum cryptography (PQC) and quantum key distribution (QKD) are the leading approaches to making data quantum-safe. PQC algorithms are classical, quantum-resistant algorithms that solve cryptography issues that are computationally complex. Quantum key distribution (QKD) establishes a secure communication channel between two parties. Any attempt to eavesdrop or intercept the exchange of encryption keys would be detected, causing the secret keys to be discarded.

 

  1. Payments

 

When compared to the blockchain, quantum states would provide greater security and payment speed. Specifically, quantum payments would eliminate the current problem of money laundering on the blockchain.

 

Quantum states are really non-falsifiable money since they cannot be duplicated. The hardware required for QKD is a major enabler of quantum payments that we anticipate will be available soon.

 

  1. Wealth Management

 

The applications and problems of quantum computing in wealth management are comparable to those in investment banking. The key distinction is that a wealth manager may have a poorer understanding of the assets under management than asset managers at investment banks.

 

In the future, quantum technology may make it easier to manage nonphysical assets by encoding contracts in quantum states. This is faster, more secure, and more sustainable than current blockchain alternatives, which rely on a mining process.

 

  1. Investment Banking

 

The most common applications of quantum computing in investment banking are portfolio optimisation and derivatives pricing.

 

Quantum computing allows investment banking teams to generate comprehensive digital twins of a bank's positions, which they may then use to mimic various macroconditions and paths. Teams might also run granular simulations to understand how different scenarios would affect each asset in a bank and build quantum models of markets. The result could be optimal capital allocation in terms of collateral and assets.

 

Summing Up

 

With only 100 qubits as the current state of the art, quantum computers can accomplish very little. Qubits will need to be counted in the thousands, if not millions, before they can do useful calculations.

 

"While there is a tremendous lot of potential and enthusiasm about what quantum computers will achieve in the future, I believe what they can do now is very unimpressive," adds Buchholz.

 

Increasing the qubit count in gate-model processors, however, is incredibly challenging. This is because it is difficult to retain the particles that make up qubits in their quantum state - similar to trying to keep a coin spinning without falling to one side or the other, but considerably harder. 

 

In recent years, billions of dollars have been invested in quantum computing due to its ability to tackle large-scale combinatorics problems more quickly and cheaply. The greatest opportunity may be to discover new applications that benefit from the answers supplied by quantum. As professor and entrepreneur Alan Aspuru-Guzik stated, there is "a role for imagination, intuition, and adventure." Perhaps it isn't how many qubits we have, but how many hackers we have.


Also Read | Impact of Superconductors on Data Science: Explained

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