The Quantum Computing Potential to Speed Up Monte Carlo Calculations for Credit Valuation Adjustments

The research proposes novel circuit designs that significantly reduce the resources needed to gain a quantum advantage in derivative pricing calculations

June 09, 2021 – today Zapata Computing announced the results of a research project conducted with the global bank BBVA. The project’s aim was to identify challenges and opportunities for quantum algorithms to speed up Monte Carlo simulations in finance. Monte Carlo simulations are commonly used for credit valuation adjustment (CVA) and derivative pricing. The research proposes novel circuit designs that significantly reduce the resources needed to gain a practical quantum advantage in derivative calculations, taking years off the projected timeline for the day when financial institutions can generate real value from quantum computers.

Fueled by regulatory pressure to minimize systemic financial risk since the global financial crisis of 2008, banks and other financial institutions have been increasingly focused on accounting for credit risk in derivative pricing. In the US, similar regulation exists to stress-test financial scenarios for Comprehensive Capital Analysis and Review (CCAR) and Dodd-Frank compliance. Monte Carlo simulation is the standard approach for this type of risk analysis, but the calculations required — which must account for all possible credit default scenarios — are immensely complex and prohibitively time-consuming for classical computers. Zapata and BBVA’s research reveals practical ways for quantum algorithms to speed up the Monte Carlo simulation process.

“Our innovative approach to quantum-accelerated Monte Carlo methods uses a novel form of amplitude estimation, combined with additional improvements that make the quantum circuit much shallower, in some cases hundreds of times shallower than the well-known alternatives in the literature,” said Yudong Cao, CTO and founder of Zapata Computing. “This approach reduces the time needed for a quantum computer to complete the CVA calculation by orders of magnitude, and also dramatically reduces the number of qubits needed to gain a quantum advantage over classical methods.” Zapata highlights that, in their enterprise customer collaborations, they perform in-depth studies of how much quantum computing resource will be required to obtain practical benefit for business operations. This type of in-depth research can directly inform the hardware specifications needed for quantum advantage in specific use cases.

“Improving the performance of these calculations in realistic settings will have a direct impact on the technological resources and costs required for financial risk management,” said Andrea Cadarso, BBVA Mexico’s Team Lead for Quantitative & Business Solutions. “The implications of this research are not limited to CVA calculations. We intend to extend our approach to other applications in quantitative finance, where Monte Carlo simulations are widely used for everything from policymaking and risk assessment to financial product pricing calculations.”

The BBVA-Zapata Computing joint publication is the result of one in a series of research initiatives that BBVA Research & Patents launched in 2019. These projects, conducted in partnership with leading institutions and companies including Spanish National Research Council, Multiverse, Fujitsu and Accenture, explore the potential advantages of applying quantum computing in the financial sector.

Escolástico Sánchez, leader of the Research & Patents discipline at BBVA, emphasized BBVA’s intention to continue exploring this cutting-edge technology: “BBVA is fully committed to its work in the quantum area. The bank has assembled a quantum team and is getting professionals from different areas involved in the development of a set of quantum solutions that meet the bank’s needs.”