The Dawn of Quantum Computing in Finance: Revolutionizing Data Analysis and Encryption, According to Investor Daniel Calugar
Currently, all at once, myriad emerging technologies are bringing about major changes in the world of finance. But, the one that has the most transformative potential, according to experienced investor Daniel Calugar, is quantum computing.
For years now, computers have been revolutionizing how we process information, making the entire process simpler, easier and quicker. Quantum computers, though, promise so much more.
Instead of being the next generation in computing, quantum computers are an entirely new approach. As such, they won’t replace computers as we know them today but will rather be used in specialized circumstances to solve extremely complex statistical problems that traditional computers simply can’t handle.
McKinsey & Company, one of the world’s most respected management consulting companies, identified quantum computing as “one of the next big trends in tech.” In fact, the company even estimated that, over the next 11 years, the tech could account for almost $1.3 trillion in value.
Quantum computing has the potential to completely transform industries, and finance is one of its main beneficiaries. It has the ability to significantly impact data analysis, risk management, encryption methods and so much more.
Below, Dan Calugar explores this transformative potential and examines the possible challenges and opportunities inherent in this emerging technology.
What is Quantum Computing?
For the most part, traditional computers operate in a relatively straightforward way. Even the most powerful computers work with the inputs given to them and then use algorithms to produce results.
Each of these individual processes is just that — individual. They don’t share any information about themselves with each other. This creates a siloed situation in which even the most complex processes that the computers complete don’t have any real value outside of themselves.
What this does is place limitations on the ultimate power of the computers to solve complicated problems because they can’t “think” beyond the narrow set of inputs they are given.
Daniel Calugar explains that this is where quantum computers differ.
Instead of using bits — the basic form of information on a traditional computer — quantum computers use qubits. They’re special because they have the ability to interact with other qubits on the computer, thereby allowing multiple calculations to occur at the same time.
This aspect of quantum computers is why they work exponentially faster than the traditional computers we use now.
And while speed is certainly good, it isn’t the only differentiating aspect of quantum computers. Unlike traditional computers, they deliver ranges of potential answers rather than just one definitive answer to a problem.
This isn’t to say that traditional computers are useless. In reality, they’re more than capable of handling a majority of use cases in the world.
However, sectors and industries that have extremely complex problems and questions with a wide range of potential answers can gain extraordinary results from quantum computing.
How Quantum Computing Works
By delving deeper into how quantum computing works, it’s easier to understand why it’s so powerful.
Classic computers use bits, which will be in either a state of 1 or 0. Qubits, by contrast, exist simultaneously in different states. This is possible through what are known as the phenomena of entanglement and superposition.
Entanglement is a phenomenon of quantum physics. In quantum computing, it refers to how a qubit’s state is related intrinsically to that of another qubit, regardless of how much distance separates the two.
By utilizing entanglement, multiple qubits can coordinate with each other at the same time. This is an essential aspect of solving complex algorithms.
Superposition, meanwhile, refers to the fact that qubits can exist in states of both 1 and 0 simultaneously. Because of this, one qubit is able to complete multiple calculations at the same time.
This isn’t possible for classic computers because their bits are clearly defined as one or the other.
These two quantum phenomena allow quantum computers to increase the speed and efficiency at which complex problems are solved, in addition to being able to solve some problems that classic computers simply can’t handle.
Why Doesn’t Everyone Use Quantum Computers?
With these immense potential benefits, the question is, why wouldn’t everyone use them? The fact is that you can’t just pick up a quantum computer from your local tech store.
Not only are they not readily available, but they are very expensive. That’s why, for now, only larger entities such as financial institutions and investment firms are likely to use them.
The McKinsey analysis discussed earlier estimated that only roughly 5,000 of these quantum computers would be fully operational by 2030. What’s more, the software and hardware needed to handle all the problems one might desire may not be available for five years or so after that.
Even before that time, though, many businesses will be able to get value from quantum computers. Even if they don’t own one themselves, they can get quantum services from cloud-based tech companies — many of whom are using these computers now for other services.
How Quantum Computing Will Change the Game of Finance
As Dan Calugar mentioned, many different industries can benefit from the power of quantum computing. Yet, the prospects might be most favorable in the world of finance — at least in the near term.
Below are some areas where quantum computing could have the biggest impact on financial services.
The basics of quantum computing’s immense power come in the realm of data analytics. Since quantum computing processes data so much differently than traditional computers, it is literally changing how data is analyzed.
Parallel computing, powered by superposition, allows qubits to explore more than one solution simultaneously. This is particularly valuable in financial realms, where the “best” outcome isn’t always the one that you might think of at first — or one that you may have thought of at all.
Daniel Calugar points out that people’s assumptions can sometimes cloud traditional data analysis. Remember, algorithms in traditional computers spit out answers to questions based solely on the data they receive and the parameters that are set.
Therefore, if those who are inputting the data and setting the parameters have overlooked something — or have skewed them due to an inherent bias — the results of the analysis may not be the best possible or could even be incorrect.
Quantum computing, by contrast, allows you to perform every potential solution to a problem possible — all in one calculation.
This allows financial institutions to optimize their processes significantly faster and more efficiently than traditional computers. It’s even possible that data analytics through quantum computing could produce a solution that no one has thought of before.
While traditional computers can analyze data in real time, quantum computers can take this one step further. They can handle extremely large datasets simultaneously so that nothing is overlooked.
Risk management is a major subset of data analytics that financial firms can improve using quantum computing. So much of data analytics today revolves around managing risk, and the same will likely be true for years to come.
The transformative potential of quantum computing as it relates to data analytics alone can help to improve risk management. The fact that so much more data can be analyzed simultaneously — with great efficiency and effectiveness — can help banks make better lending decisions and investment firms create more optimized portfolios.
Financial forecasting and risk modeling can be inherently improved with this, as organizations will be able to identify their risks and then mitigate them in ways that just aren’t possible with traditional computers.
“Real-time” in data analytics doesn’t just refer to models that seek to analyze the performance of investment funds or other financial products. It can also be used to monitor risk as things develop.
In this way, quantum computing can enable companies to respond to the many potential threats as they’re happening. Today, risk factors often change rapidly, necessitating a response that can be just as rapid.
Risk can be defined in many different ways in finance, depending on the specific sector. For instance, the above mainly refers to risk related to banks and credit card companies.
But, investment companies can also greatly benefit from using quantum computing in risk management, Dan Calugar says.
These powerful computers can conduct simulations and scenario analyses at speeds unheard of before, with a complexity level that isn’t possible through other means. This could help organizations understand what risks they might face before they face them and the potential outcome of each of those risks.
Further, investment companies can better optimize asset allocation in portfolios. By reducing the amount of time it takes to conduct balancing — and by doing so at highly accurate levels — you can lessen the impact of downturns in the market.
With so much data available and being used nowadays, there are natural concerns about security. If the data isn’t safely secured, it can easily be accessed by bad actors who can use it for negative purposes.
Businesses everywhere have an obligation to protect their users’ data, and this is perhaps of greatest significance in the financial realm. Personally identifiable information such as Social Security numbers, account numbers, usernames and passwords are just the tip of the iceberg when it comes to data security.
Traditional methods of data encryption are sufficient for protecting against a majority of attacks as long as they’re designed, installed, managed, maintained and executed properly. At the same time, they have the same limitations that traditional computers have.
Daniel Calugar points out that it’s possible for hackers to use quantum computing systems to take advantage of vulnerabilities in data that’s encrypted using classic technologies. Luckily, quantum computers can be used to protect against this.
Businesses can create data encryption codes that are virtually unbreakable by using quantum cryptography — a process that uses quantum mechanics.
There are two main use cases for this.
The first is in cloud security. As more and more data is being stored and analyzed in the cloud, the need for another security level has never been more necessary. Quantum encryption has the ability to provide this to both computing providers and end-users alike.
The second is quantum keys, which can be used in all non-cloud processes. They use quantum entanglement to create data encryption keys that can’t be intercepted. That’s because when an attempt is made to measure a system’s qubits, the system automatically changes the qubits’ states and simultaneously alerts the affected parties.
It’s essential for financial institutions to explore how they can encrypt their data in ways that are resistant to efforts by bad actors to use quantum computers against them. And that’s exactly what many are doing now so that all transactions and communications can be secure for the future.
Quantum Computing’s Immense Opportunities
Quantum computing provides innumerable opportunities in the financial realm. Customers today demand products that are highly personalized and that anticipate the needs they have, even as those needs change rapidly.
The challenge for financial firms is how to create highly personalized products that can meet the needs of a diverse client base. With traditional computing, that’s tough, if not impossible.
With quantum computing, the possibilities are endless.
Analytical models can pore through behavioral data accurately and quickly so that customers can receive the products that they need on a real-time basis. Instead of waiting for customers to come to them with what they need, financial firms can get ahead of the game and suggest the optimal products and features that would serve their customers best.
For investment firms, quantum computing can provide a level of trading optimization never seen before. Instead of only suggesting trades based on market factors, this level of computing can help firms integrate real-life scenarios, such as major life changes for their clients, into the decision-making process.
In this way, investment managers could simulate a huge pool of scenarios and options, helping them to create advisements that perform at top levels.
There is also a litany of ways quantum computing can save financial firms billions of dollars. A recent IBM study found that financial institutions lose anywhere from $10 billion to $40 billion in annual revenue because of poor practices for data management and fraud.
Part of the reason for this is that the systems used to detect fraud today are just plain inaccurate, with as many as 80 percent of all flagged fraud possibilities being false positives.
Quantum computing can dramatically improve this vital process for financial institutions, helping them mitigate losses and become less risk-averse.
Challenges Associated with Quantum Computing
Of course, there are challenges associated with quantum computing that don’t make it an instant “slam dunk” for everyone.
Dan Calugar points out the obvious to start — that quantum computers are not readily available, obtainable or affordable for many organizations at this point. While they will likely become more available in the future, how far off that might be is anyone’s guess at this point.
And while quantum computing services are available through computing providers now, there are limits to what you can do. As with any new development, accessibility will be a major factor in how widely the masses embrace and use it.
There are also cybersecurity threats posed by quantum computing. While there are many ways in which it can help improve life in financial services, the technology can also be used with bad intent.
In fact, many people are concerned that cybersecurity, in general, will lag behind quantum computers in terms of development. In other words, criminals may be able to take advantage of many cybersecurity systems before they are able to update to a more modern version.
Daniel Calugar notes that it will be important to create algorithms that can withstand the potential malicious use of quantum computers. Developing quantum-resistant algorithms is a significant challenge that will require attention.
There’s also likely to be a steep learning curve for those who will manage and use quantum computing systems. Since the technology is so new and evolving by the day, there aren’t many people who are well-versed in how it works.
This means that, even though the technology provides many potential benefits, these likely won’t be realized until enough people “skill up” to put it into practice. This is a major roadblock to the widespread adoption of quantum computers, and it will need significant investment to help close skill gaps.
Along those lines, the new quantum computing systems will have to be integrated with other existing systems, and that could cause major headaches. Financial institutions will have to ensure that their legacy systems can communicate properly with quantum computing services and that their technological backbone is up to snuff.
Still, despite these challenges and others, the transformative potential of quantum computing makes it essential for the financial sector to do all it can to learn and adopt it quickly.
About Daniel Calugar
Daniel Calugar is a versatile and experienced investor with a background in computer science, business, and law. While working as a pension lawyer, he developed a passion for investing and leveraged his technical capabilities to write computer programs that helped him identify more profitable investment strategies. When Dan Calugar is not working, he enjoys working out, being with friends and family, and volunteering with Angel Flight.
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