Identifying realistic use cases, understanding governance and security implications, and assessing where quantum methods could eventually add measurable value
As artificial intelligence adoption accelerates across industries, financial institutions are running into a limitation that has become increasingly difficult to ignore. Many of the most critical challenges in finance, including intraday risk analysis, settlement timing, corporate actions processing, and long term security, are not constrained by data availability or modeling techniques, but by computation itself. Even with advanced AI systems, classical computing often struggles to keep pace with the scale, speed, and regulatory expectations of global financial markets.
This has raised an important question across the industry. If classical systems are reaching their limits, could quantum computing realistically help, or is it still too early for practical use in finance?
To explore this question, we spoke with Phaneendra Vayu Kumar Yerra, a senior financial technology leader and researcher who has led the design and delivery of large scale enterprise applications for top tier banks and financial institutions across the globe. His work spans global markets technology, risk platforms, and secure financial infrastructure, with a research focus on how emerging technologies such as quantum computing and blockchain could complement existing AI systems in regulated environments.
Rather than advocating immediate adoption, his research centers on evaluating readiness. That includes identifying realistic use cases, understanding governance and security implications, and assessing where quantum methods could eventually add measurable value. Industry observers note that while quantum computing has been discussed for years, practical financial applications remain limited by hardware maturity, algorithm development, and operational oversight. Research driven analysis is helping institutions understand whether, and when, quantum computing may become viable for financial risk management and security.
Mr. Yerra, Is quantum computing really ready for financial risk and security, or is it still too early?
Quantum computing is not ready to replace today’s financial systems, but it is starting to matter in practical ways. Its usefulness depends on steady progress in quantum hardware and algorithms, and that progress is happening faster than many people expected.
If these improvements continue, finance is likely to be one of the first areas to benefit. Risk and security calculations are complex, time sensitive, and expensive to run, which makes them a good fit for hybrid approaches that combine quantum and classical computing. Right now, researchers are focused on understanding where quantum methods could actually help, so financial systems are better prepared as the technology continues to evolve.
How is quantum computing different from the artificial intelligence and analytics systems already used in finance today?
Most AI systems used in finance today are built to recognize patterns and make predictions from historical data. They work well for tasks like fraud detection or forecasting, but they still rely on classical computing.
Quantum computing focuses on a different challenge. It targets the heavy mathematics behind complex calculations, such as evaluating many risk scenarios or optimizing decisions under constraints. Rather than replacing AI, quantum computing is more likely to support it. In a hybrid approach, classical AI continues to drive decisions, while quantum methods are used selectively to speed up the most demanding calculations.
Where do you see quantum computing making the biggest difference in financial risk management and security?
The biggest impact is likely in situations where financial risk and security need to be checked quickly and often. Intraday risk is a good example. As markets move faster and settlement timelines get shorter, banks need to understand their exposure during the day, not just after markets close.
On the security side, quantum computing can help researchers analyze how strong today’s security methods are over long periods of time and how financial communications can be protected in the future. While changes will not happen overnight, this kind of research helps institutions prepare early and avoid being caught off guard later. In both areas, the goal is faster insight and better preparedness.
Blockchain has been discussed in finance for years. Mr. Yerra, Where does it actually make sense alongside quantum computing and AI?
In finance, blockchain is most useful where accuracy, coordination, and trust matter more than speed alone. It provides a shared record that multiple parties can rely on, which is especially helpful in post trade processes like settlement, reconciliation, and corporate actions, where data mismatches are common.
When combined with advanced analytics, including quantum enhanced analysis, blockchain can help ensure that everyone is working from the same information while complex risk and security checks run in the background. Rather than replacing existing systems, it can act as a coordination layer that improves transparency and reduces operational friction.
Many people associate quantum computing with breaking encryption. How concerned should financial institutions really be?
It is a real concern, but it is often misunderstood. Quantum computers are not suddenly going to break today’s financial security systems overnight. What matters more is long term planning. Financial data is stored for many years, and security decisions made today need to hold up well into the future.
That is why researchers and institutions are studying post quantum security early. The goal is to understand which systems may eventually need to change and how to transition safely over time. This is less about panic and more about preparation, so security upgrades can happen gradually without disrupting financial operations.
Mr. Yerra, how should financial institutions start experimenting with quantum computing without taking on unnecessary risk?
The safest approach is to start small and stay controlled. Financial institutions do not need to overhaul their systems to begin learning. Instead, they can experiment with limited use cases where quantum methods are tested alongside existing systems.
This usually means using hybrid setups, where classical systems continue to run day to day operations, while quantum techniques are explored in research or pilot environments. That way, institutions can measure value, understand limitations, and build internal expertise without putting core systems or regulatory obligations at risk.
What role does communication security play as financial systems become more complex and distributed?
Communication security is foundational to how financial systems work. As systems become more distributed across regions, vendors, and platforms, the way data moves between them becomes just as important as how it is stored.
From a research perspective, this means looking at how messages, transactions, and sensitive information can remain secure over long periods of time, even as technology changes. Studying quantum resistant security methods and secure communication paths helps institutions plan ahead and protect financial data without disrupting existing workflows.
Mr. Yerra, does quantum computing introduce new transparency or governance challenges for financial institutions?
Any new technology brings governance questions, and quantum computing is no different. Financial institutions need to understand how decisions are made, how results are produced, and how systems can be explained to regulators and auditors.
That is why most research and early experimentation focuses on hybrid approaches. By keeping decision making, policies, and reporting in classical systems, institutions can maintain transparency while using quantum methods only to support complex calculations. This helps ensure that innovation does not come at the cost of trust or accountability.
What should financial institutions focus on today if they want to be prepared for quantum computing in the future?
The most important step is awareness and preparation, not immediate adoption. Financial institutions should start by understanding where their most computationally intensive and long term sensitive processes are, especially in risk, settlement, and security.
Mr. Yerra, when people look back a few years from now, what do you think will matter most about today’s quantum research in finance?
What will matter most is not who adopts quantum computing first, but who prepares for it responsibly. The research happening today helps financial institutions understand where quantum methods could realistically help and how they should be governed.
That early clarity leads to better designed, better governed, and more secure systems over time. Even if widespread adoption takes years, the work being done now helps ensure financial systems are resilient and able to adapt as technology evolves.
