Quantum Computing Explained - BUSN 4400 Blog

What Exactly is Quantum Computing? Before I started this blog, I hit a wall on deciding what I wanted to write about for this blog. I asked Google’s AI service Gemini to provide five emerging technology trends and examples of industries that could have an impact through AI. From this questi...

What Exactly is Quantum Computing? Before I started this blog, I hit a wall on deciding what I wanted to write about for this blog. I asked Google’s AI service Gemini to provide five emerging technology trends and examples of industries that could have an impact through AI. From this question, I stumbled onto quantum computing, a foreign phrase to me, from there I decided to dig deeper. This blog will be a basic explanation of quantum computing, the history of it, its uses in the financial services industry, and a fun quiz at the end. Quantum computing is a type of computing that uses similar mechanics to quantum mechanics and is based on its principles. It is an interesting field that is set to change the way complex problems are approached. To start off, quantum mechanics is a type of physics that deals with particles at the atomic and subatomic state. Unlike normal computers, which we will call “classical computers” throughout this blog, quantum computers use quantum bits (qubits) which can represent both 0 and 1 at the same time because of a phenomenon called superposition. Superposition allows these computers to process massive amounts of data at once and can solve complex problems way faster than classical computers. In addition to superposition, quantum computers work under a concept called entanglement, which is where quantum bits are linked in a way that the state of one qubit can influence the state of another qubit almost instantly. I like to think about entanglement compared to our brain’s neuronal communication, which is a highly interconnected and efficient system for problem-solving. With the use of qubits and special properties, quantum computing could completely shake up industries such as healthcare and drug discovery, finance, cryptography, materials science, chemistry, construction and supply chain. In finance, quantum computers can optimize portfolios and monitor KRIs (key risk indicators) faster (in real time) and be more accurate. In the rest of the blog, we will further explore the impact on the financial services industry. In healthcare, quantum computing can go through an enormous amount of genetic data to speed up drug discovery by providing faster and more authentic simulations of genetic interactions. Finally in cybersecurity, quantum computing allows cryptography new ways to protect our data in a more secure fashion that is not possible with our current classical computers. Quantum computing is still in its early ages much like AI, but its progress has been groundbreaking and its potential is clearly large. It is evident that quantum computing has the ability to reshape industries, but the question now is - how quickly can we use its capabilities, and when will it be practical? As it continues to grow and become more practical in implementation, quantum computing’s impact on technology, systems, and business will be transformative, as it will unlock solutions to problems we once thought we could never solve.  Key Milestones of Quantum Computing: Below are some major milestones to give a better sense of the history of quantum computing. 1982: Richard Reynmann introduced the theory of quantum computing and stated a computer can be used to accurately simulate quantum processes. 1985: David Deutsch created the first formal description and theoretical model. Deutsch proved that quantum computers can “in theory” simulate any physical process. 1994: Peter Shor developed an algorithm that could factor large numbers exponentially faster than classical computers. It was the first step showing quantum computers could help the cryptography industry. 1998: Physicists and computer scientists began building small quantum computers, by creating the first quantum bits (qubits) 2001: IBM created a version of Shor’s Algorithm on a 7 qubit quantum computer. It was not practical or sustainable, but was an improvement and showed the potential quantum computers have. 2012: The phrase “Quantum Supremacy” was created - It refers to the point where a quantum computer can solve a problem that a classical computer would take too long to solve (e.g: 10,000 years) 2019: Google created their quantum computer, Sycamore, that performed a calculation in 200 seconds that would take classical computers about 10,000 years to complete. Sycamore was considered the first example of Quantum Supremacy. 2020 & Future: Companies like IBM, Google, Microsoft, Intel, and D-Wave Systems are leading the charge in quantum computing. Right now, it’s a race to build quantum computers that are scalable, practical, and useful for real-world applications. One of the biggest challenges they're all working on is quantum error correction. Quantum Computing in the Finance Industry Quantum computing has the potential to transform various sectors, such as healthcare, cryptography, materials science, and more, but in this blog, I’ll dive into how it specifically impacts the finance industry. According to Mckinsey, Quantum Computing could create $625B in the finance industry by 2035  According to Deloitte, the financial services industry’s spending on quantum computing is expected to grow from $80 million to around $19 billion 2032 Quantum computing is on track to change the game for risk management in financial services. Because quantum computing has gigantic processing power, it will be able handle complex calculations and process data faster than classical computers. It will help financial institutions with their portfolio optimization, real-time monitoring, predictive models, and Monte Carlo simulations. By using quantum computing, predictive models will be able to be created using more variables than classical computer models are able to offer. According to Linkedin’s article, quantum computing will allow banks and investment banks to solve Value at Risk (VAR), Expected Shortfall (ES), and Expected Loss (EL) which are used to measure risk, faster and more efficiently. When the market becomes volatile, these faster systems can help forecast potential future states and speed up the institution's reaction to the market changes decreasing their potential loss. Touching on Monte Carlo Simulations, quantum computing will allow simulations to run quicker and give a more precise answer. This increased accuracy in forecasting, even if it's a tiny percentage, could translate to billions of dollars in improved returns and profits. This is due to quantum computers' processing power able to run more simulations of the Monte Carlo, creating a better understood bell curve. As for some specific areas within the financial industry, quantum computing is expected to improve option pricing, credit score analysis, macroeconomic modeling, and loan and portfolio calculations. In addition, quantum computing will improve fraud detection and security principles. Quantum computing will have increased accuracy and detection of fraud and can also protect from future quantum-type attacks. As hackers get more familiar with quantum systems, it’s crucial for financial institutions to keep up in order to avoid big losses. In terms of real time analysis, quantum computing can reduce risk exposure and response to emerging threats in real time. Because of the qubits, the qubits can have many forms and therefore can track multiple KRIs at one time. Instead of tracking 3 or 4 variables, the improved processing power can track 20/30 KRIs at one point. The improved accuracy in risk assessments will lead to better regulatory compliance and enhanced overall stability within the financial system. By having access to more data, quicker, and more precise, financial institutions will be able to make better decisions on investments, reduce and respond to risk more effectively. How did I incorporate AI? After reading last week's blog, I read Aiden Kane’s Blog, Search-vival of the Fittest, which discussed how AI could replace the role of search engines and his experience with that. From it, I learned about a new AI tool called Perplexity, a free AI search engine, that I used to research and write this entire blog. I enjoyed using a new tool and will be using it moving forward as I was able to get immediate answers plus great articles tailored to my questions. Before testing Perplexity, I saw how an AI search engine would be beneficial, but during my research, it showed its benefit. In addition to perplexity, I used ChatGPT for the usual grammar check and adjusting the structure of my sentences when finished. I also tried out a new AI tool called QuizGecko, which takes a PDF or text and turns it into quiz questions. Although it is a fun, silly use of AI, my main goal was to explore new AI tools I could use in the future. Sources: - https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/tech-forward/quant um-technology-use-cases-as-fuel-for-value-in-finance - https://thequantuminsider.com/2020/05/26/history-of-quantum-computing/ - https://www2.deloitte.com/us/en/insights/industry/financial-services/financial-services-in dustry-predictions/2023/quantum-computing-in-finance.html - https://kpmg.com/au/en/home/insights/2024/04/cyber-security-risk-from-quantum-compu ting.html - https://www.ibm.com/topics/quantum-cryptography - https://www.linkedin.com/pulse/how-quantum-computing-revolutionize-financial-risk-jo nathan-t-/ - https://www.ey.com/en_us/insights/strategy/financial-services-cybersecurity-for-quantum -computing#:~:text=A%20particularly%20urgent%20concern%20is,vulnerable%20can% 20be%20immediately%20deployed.