AI and Quantum Technology: On the Verge of Transforming Finance
The convergence of AI and Quantum is every financial engineer's dream.
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While the AI revolution in finance is underway, quantum technology remains in cryogenic sleep, and combining quantum and AI remains an enticing dream.
Author’s note: This report’s coverage of AI is worth reading, but for my write-up, I will focus on the sections on quantum computing and the goal of combining quantum and AI.
Quantum computing, with its chips bathed in liquid nitrogen to deal with their inherent instability, is always just around the corner.
Don’t get me wrong, progress is being made, but so far the lightning-fast computers promised haven’t been delivered, and only the largest banks have been able to conduct meaningful proof-of-concepts. So, for now, our quantum future remains frustratingly out of reach.
Still, using quantum’s unfathomably large computing capability to solve whole-ecosystem calculations is a worthy goal that will come to fruition. Imagine calculating risk or return on all of a bank’s assets at once, something that is impossible today.
Despite the delays in quantum computing, this doesn’t mean we can sit on our hands and do nothing as we wait for quantum to develop.
Key financial infrastructure built today with a predicted lifespan of over a decade will need to use post-quantum encryption to ensure security.
The fear of quantum breaking existing cryptographic security is real and once quantum becomes available, all of our data, including blockchain and Bitcoin, will be at risk.
If this doesn’t drive more financial services firms to research quantum computing and post-quantum cryptography, nothing will.
The combination of AI and quantum is tantalizing but still theoretical. The basic idea is that quantum computing will vastly accelerate machine learning, making massive AI analysis practically immediate.
This is why the use cases center on speeding up existing machine learning uses such as fraud detection, credit scoring, and risk modeling.
Quantum and AI convergence is still more theoretical, but the potential of combining the two is every financial engineer’s dream.
The paper's advice, however, is spot on: “follow the value of AI and quantum, not the hype.”
Quantum and AI can wait for now, but we can’t wait for post-quantum encryption because the risks are too great.
See my article on HSBC’s use of post-quantum encryption in tokenized gold. The paper is not overly technical and does a great job of explaining the technology: HERE
👉Post quantum cryptography is now, quantum + AI is a work in progress:
🔹 Practical implementations of quantum computing have yet to materialize due to technical limitations in algorithms and hardware.
🔹 The financial services sector is still evaluating the value that quantum technology can bring and investing in identifying use cases.
🔹 Most experiments by institutions are currently in the algorithm exploration phase, with a limited number of POCs. Quantum use cases of interest to institutions include portfolio optimization, risk management, derivative pricing, and transaction settlements.
🔹 The quantum industry is making progress in addressing the hardware limitations preventing the practical implementation of quantum algorithms.
🔹 Quantum-resistant cryptography is now.
🔹 Dowson Tong, Executive VP of Tencent, talked about Tencent’s collaborations on post-quantum security, to ensure existing data cannot be decrypted.
🔹 Colin Bell, CEO of HSBC, elaborated on HSBC’s efforts in applying NIST post-quantum algorithms on tokenized gold trading, with new [NIST post-quantum] algorithms to the product.
🔹 HSBC is the first bank to successfully test QKD to safeguard a €30 million foreign exchange trading scenario against quantum attacks.
🔹 Chase the value of AI and quantum technology, not the hype: Focus on initiatives that deliver tangible business value, leveraging pilot projects to validate outcomes and guide investment
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