EXCLUSIVE: Big Banks Collaborate With IBM On Quantum Computing — Is Financial Services Industry Ready For Huge Opportunities?

The financial services industry is unprepared for the next revolution in fintech which promises both huge benefits and substantial risk.

Developments in quantum computing are happening at a fast pace and early adopters are few, according to research by Moody’s Analytics. In a survey of 200 innovation leaders at financial institutions in Europe and North America, Moody’s found that 87% lack the budget for quantum research, while 73% were yet to define any commercial advantage.

IBM IBM, which last year unveiled its powerful 430qubit Osprey quantum processor, has worked with several large banks over the past five years including Barclays BCLYF, Goldman Sachs GS and JPMorgan Chase JPM on potential commercial applications for quantum computing.

Meanwhile, D-Wave Quantum QBTS has named Spain’ s Caixa Bank as a collaborator.

Moody’s Analytics has defined eight key use cases: Risk analysis, stress testing, cybersecurity, synthetic data, detection of financial crimes, derivative pricing, predicting financial crashes and portfolio optimization.

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Presenting A Risk To Cybersecurity

Quantum computing poses both an opportunity and a risk to financial services companies’ cybersecurity. The Moody’s Analytics report theorizes that a powerful quantum computer could “break any lock.” And 86% of organizations admitted they are not ready for post-quantum cybersecurity, although 84% could foresee the need in the next two to five years.

“There are lots of advantages we can get from quantum computing but there are some potential risks,” said Raj Badhwar, Field CISO at Oracle. “That's why the best scenario is to get the advantages by doing stable implementations and we can mitigate the risks using postquantum cryptography.”

The report encourages financial institutions to focus on smaller, targeted projects with clear financial and strategic impacts, while remaining informed and adaptable to the evolving technology landscape.

Derivatives Pricing: Monte Carlo Or Bust

Among the more exciting applications is derivative pricing using so-called Monte Carlo simulations, named after the fabled attempts to “break the bank at Monte Carlo” casinos.

Calculating the cost of complex derivatives like stock options or oil futures using conventional computing methods can be quite costly.

“Derivatives are so common in finance that even a small improvement in pricing them, or in calculating related quantities, could be very valuable,” said William Zeng, head of quantum research at Goldman Sachs in a blog post.

But being an early adopter in this field doesn’t appear to be practical for the smaller and mid-sized banks. Costs are high, and the technology is still in its formative years.

“Everything has to have a return on investment,” Badhwar added. “So, if the quantum computing paradigm cannot deliver the financial benefits sought by businesses, then that may lead to the lack of funding or defunding some quantum computing initiatives.”

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