What is Quantum Computing’s Role In The Future Of Finance?

March 19, 2021

With its promise of extraordinary power, quantum computing (QC) is a game-changing possibility for the financial world. It’s a breakthrough that will decrease risk and increase profits margins by analysing market circumstances quicker and with infinitely more detail.

Satya Nadella, Microsoft’s Chief Executive Officer, calls QC: “One of three emerging technologies that will radically reshape the world, along with artificial intelligence and augmented reality.”

Bob Sutor, Vice President of IBM’s quantum computing program, explains: “[QC is] a completely different way of computing, a different beast entirely, and the most significant improvement in computation in the last century. It offers the opportunity to rethink so much of what we’ve achieved.”

A number of experts believe that the quantum tipping point has arrived and that within 10 years, quantum computers will make the fastest supercomputer of today resemble an abacus.

Jeremy O’Brien, Physicist and Professorial Research Fellow at the University of Bristol agrees: “In less than 10 years, quantum computers will begin to outperform everyday computers, leading to breakthroughs in AI. The very fast computing The power given by QC has the potential to disrupt traditional businesses.”

When you look at what the financial sector wants and combine that with quantum computing’s remarkable increase in the accessibility of processing capability for problematic algorithms, it’s a marriage made in heaven.

With Implications That Go Beyond Computing.

Advances in quantum communications and cryptography could create hypothetically unhackable systems. Quantum radar and sensing could expose the location of stealth aeroplanes and submerged submarines. What’s more, quantum navigation could give accurate geolocation capabilities without dependence on space-based GPS.

Whoever leads the way in harnessing quantum could achieve massive economic and national security advantages, particularly as QC can realistically supercharge AI applications.

China has given particular attention to investing in quantum science as a method of bypassing conventional technological advantages, as enjoyed by the likes of the United States and is said to be investing 11 billion USD to develop a laboratory for exploring quantum technology. Set to open in 2020, it will be one of the biggest laboratories for quantum development in the world.

In December 2018, President Trump signed the National Quantum Initiative Act into law. It has released more than 1.2 billion USD in spending to coordinate research and development in quantum computers.

The law came to fruition in an uncommon moment of bipartisanship. U.S. Representative Lamar Smith said in a speech at the time “Countries that harness the power of quantum technology will revolutionise computing systems.” He was a co-sponsor of the legislation in the House, where it passed with a 348-11 landslide.

The European Union has likewise released a 1.1 billion USD quantum research plan. To aid the research into high-performance computing as a component of the implementation of the European Cloud initiative.

Talking at the start of the London Tech Week in June, former British Prime Minister Theresa May announced a similar plan to invest 1 billion USD in the research of quantum computing in the U.K. In addition, this year the UK’s Cambridge Quantum Computing, an independent company, unveiled ‘Ironbridge’, the only commercially accessible quantum cryptographic device.

So it’s clear to see that quantum is definitely on the agenda of the main global countries and tech companies of all sizes. Who could fault them for pursuing the opportunity to unlock such a possibility? As Seth Lloyd, Professor of Mechanical Engineering and Physics at the Massachusetts Institute of Technology, said: “The history of the universe is, in effect, a huge ongoing quantum computation. The universe is a quantum computer.”

That’s too much power for the financial sector to ignore in any strategy for their future.

Quantum Applications In Financial Services.

Cash management enhancements in the ATM network is a key functional use case for quantum computing. Today, in banking, there is a genuine commercial advantage in operational proficiency and in managing short-term funds. For instance, by calculating the ideal amount of cash to be held in any individual ATM at a time and working out the most effective route for cash replenishment, machine by machine.

Simply at the level of operational productivity, cash replenishment costs represent somewhere in the range 35 and 60 percent of the overall cost of operating an ATM, which makes advancements a major factor in improving profitability. Streamlining where the cash is in the system at a given time can also result in profit from interest from the Bank of England that is paid on cash within a ‘bonded store’ (Secure locations from where cash is distributed to ATMs and banks). The mathematical dilemma is how to hold the right amount of cash in the ATMs and banks to provide the service customers demand while moving as little cash as possible in the system and keeping the majority of it in the bonded stores.

The potential permutations of cash and routes over an ATM network of this scale, however, are overwhelming. Regardless of whether the total number of ATMs has reached its peak, there are still a staggering 65,379 in the UK alone according to the Bank of England. Each quarter, UK ATMs dispense around 44 billion GBP spread over 628 million transactions, with an average withdrawal amount of £702. Calculating the ideal answer to this puzzle, even for a single bank-owned network (The largest UK network accounts for around 10 percent of the total ATMs), has been impossible to do in a timeframe short enough to be able to react to the day to day requirements of the network. Until now, recalculating continuously and altering plans for a new advanced distribution network to take into account any anomalies in random spikes in demand for cash in a particular city, town, district, or bank and then repeating these activities every time there is a small change in conditions has defied us, or rather, has defied current computing capabilities.

Risk management is another significant cause for the use of Digital Annealer. In credit risk evaluation for banks and insurance businesses, for instants, the goal is to reduce credit risk by improving the credit rating accuracy of people or businesses. This is accomplished by assessing the numerous factors provided by credit rating agencies while keeping the accuracy of the removed credit assessment information.

Right now, credit risk evaluations are made at a point-in-time and then carried on from that point onwards. In a perfect world, they would be done in real-time and continually refreshed. One huge barrier, however, is that as the credit data used for assessment increases, so does the volume of combinations increase exponentially.

Digital annealing can overcome these obstacles, with the outcome that bank credit risk is decreased by increasing the capacity to correlate credit assessment data, making it simpler to keep credit rating accuracy.

Another risk management example comes in derivatives transactions, where interest rate swap streamlining can hypothetically be accomplished through transaction netting interest rate swap arrangements to decrease clearinghouse risk exposure in fixed and variable interest rate swap transactions between businesses. However, because of an enormous number of interest rate swap combinations for transaction netting, it is incredibly hard to locate an ideal combination that limits interest rate costs. Derivative transactions will regularly include interest rate swaps across 20-30 currencies and continuously calculate which is accurately the ideal trade, in real-time, which currently is not viable.

By streamlining the necessary interest rate swaps, digital annealing diminishes the clearinghouse’s risk exposure, including the total amount of interest rate exchanged.

Looking at asset management, digital annealing has a key role to carry out in portfolio streamlining, where the definitive objective is a solid portfolio that is impervious to market changes and delivers consistent profits.

Rebalancing a portfolio just intermittently brings about significant periods of diminished income, missed market opportunities and exposure to increased instability and risk in the in-between reassessments. Digital Annealer gives the ability to do consistent and continuous rebalancing, as the calculations are instantaneous and can be carried out as often as required, and market changes and risk can be overseen more effectively. Ultimately, this can potentially disrupt whole business processes, enabling lower risk and greater portfolio management returns.

As far as long-term streamlining, a generally utilised strategy is to build a Constrained Minimum Variance portfolio. Correlations between assets are found through clustering, and a tree is made to show a streamlined portfolio with low asset correlation and diversified risk. However, making portfolios that are not overly impacted by market changes has been difficult. Clustering enables higher accuracy and greater scale than traditional methods, however, in the case of just the S&P 500 stocks, the quantity of potential combinations is 1.63×10150. Hierarchical Risk Parity (HRP) is another method used in standard computing systems. But, including more price and volume factors for calculation requires extremely high performance and hence HRP on standard computers doesn’t create an ideal diversified portfolio providing maximum profit with minimal risk.

The scope for potential applications for digital annealing in the financial sector will, without doubt, increase with time and experience. A further example of this is in business improvement, where scheduling management includes such complex factors that are currently impractical to produce enhanced plans that react to real-time changes in conditions.

Other limitations could also be incorporated, for instance, the accessibility of suitably configured RPA (Robotic Process Automation) robots to handle specific tasks. As increasingly more programmed robots are deployed to automate simple, repetitive tasks, these can conceivably be controlled in real-time by the Digital Annealer, guaranteeing that the robots are completing work as effectively as possible. Given the potential for solving such advancement challenges continuously, running a scheduled enhancement every hour or minute instead of once a month because of time constraints and what may be the overall business impact be?

This is where the disruption begins.

The financial services sector has been one of the forerunners to look at quantum computing as a potential answer to the multifaceted nature and size of its combinatorial improvement challenges. While genuine quantum computing answers to these questions remain at a test level, a new quantum-propelled method of digital annealing has opened up and is currently delivering radical streamlining rewards to early adopters.

The chance has opened up for banks and insurance businesses to build a bridge to the quantum future, figuring out how that new world will look and work while delivering real-world enhanced calculations that can revolutionize tasks and create disruptive leadership in their business sector.

So let’s look at a working example.

Case Study – NatWest

Quantum computing is helping NatWest bank comprehend a number of its most complex, challenging and time-consuming financial investment issues by improving its diversity of high-quality liquid assets (HQLAs) including bonds, cash, and government securities.

Utilising quantum-inspired Digital Annealer, NatWest Bank has achieved a highly complex calculation that is required to be completed on a routine basis by the bank, at 300 times the speed of a standard computer, whilst giving a greater degree of accuracy.

It enabled the NatWest portfolio managers to enhance the makeup of the bank’s £120bn HQLAs portfolio. HQLAs are assets such as cash and bonds that all UK banks must hold as a cushion in case it runs into financial difficulty.

In addition to performance upgrades, the utilisation of quantum computing has also decreased the risk of human error. NatWest can finish a comprehensive risk assessment for its portfolio a lot quicker, as well as accessing a far larger spectrum of results and permutations, therefore helping to ensure an optimized spread and decreased risk.

Financial companies like NatWest face a nonstop challenge of making and maintaining an ideally balanced portfolio of assets, chosen from a huge number of choices. Preferably, these include a selection of liquid assets that deliver the greatest possible profit while helping manage risk to an acceptable level. While liquidity is of extreme importance to financial companies, the procedure undertaken to calculate the best mix of assets is generally only completed infrequently. Customarily, this is a very costly and time-consuming manual task. Quantum computers can process this sort of complex operation and can provide results of magnitude far quicker than standard computers of today.

Given this early success, it is currently believed that quantum computing could dramatically change the way in which a number of processes are undertaken at NatWest and the bank is currently looking at which other portfolios can be enhanced using the technology. For example, portfolio managers might be able to modify the allocation of assets following an unexpected change in the market, in a much shorter time scale than normal.

So How Does Qfinity Labs Fit Into The Picture?

Qfinity researchers were among the first in the world to respond to the realisation that the phenomena in quantum computers could be copied within digital architectures and make what it calls the Digital Annealer. It has a fully-connected architecture enabling the free exchange of signals between any two bits and can, therefore, solve large-scale, highly complex combinatorial enhancement solutions at great speed.

An easy way to understand what a Digital Annealers are is to think of it as a special accelerator to speed up combinatorial enhancements.

The power of the Digital Annealer start to finish process lies in QFinity’s quantum-inspired digital architecture that uses advancements in ultra-high-density circuit integration and high-performance processing. The Digital Annealer gives up to 10,000 times quicker execution speed compared to the industry standard computer systems running with commercial servers and it currently supports an 8,192-bit, fully-connected architecture with a promising future set to support a 100,000-bit scale solution. This state of the art offering is inspired by the key characteristics of quantum computing: superposition, quantum tunnelling and entanglement, enabling Digital Annealer to assess numerous possible options simultaneously and to deliver super-fast results.

To stay ahead of the game Qfinity has also created the Digital Annealer’s core algorithm for the new architecture, which is completely compatible with those being developed for the prototype true quantum computers, therefore the current Digital Annealer offering will be compatible with future quantum computers when they finally appear.

Qfinity’s Digital Annealer has been described by independent experts as an exceptional opportunity to pre-empt quantum computing and accomplish the first stage rewards of enhancement today, working within a conventional data centre environment. They speak about building a ‘bridge’ to the quantum future, getting the rewards of combinatorial enhancements today while also figuring out how true quantum computing can possibly be applied to operations moving forward.

And the most forward-thinking financial services companies are already crossing this bridge, including NatWest Bank and others which are watching these advances closely, including BBVA, which discussed Digital Annealer’s potential in a recent article.

While investment transactions on superconductivity quantum computers are still some way off, there is currently an opportunity to not just form understanding and skill about quantum computers but to solve real-world combinatorial enhancement issues using the Qfinity Digital Annealer bridge to quantum and to gain enhanced knowledge and leadership.

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