The Challenge
Based in Spain, BBVA is one of the largest financial institutions in the world, with over €662 billion in assets and 83 million customers in more than 30 countries. Like most banks, BBVA relies on complex calculations to analyze risk and set the price of financial products.
Since the 2008 Financial Crisis, new regulations have required banks to assess credit risk and stress-test financial scenarios. Typically, this type of risk analysis is done using Monte Carlo simulations: an astronomically complex, costly and time-consuming calculation that must account for all possible credit default scenarios. Any performance improvements for this kind of simulation would directly impact daily operations costs, financial product pricing, and risk analysis.
Our Approach
BBVA teamed up with Zapata AI to design novel quantum circuits that provide a speedup over existing quantum algorithms for Monte Carlo simulations, which BBVA can use in credit valuation adjustment (CVA) and derivative pricing. This work reduced the resources required for a quantum computer to conduct Monte Carlo simulations by orders of magnitude, and significantly reduced the number of qubits required for a practical quantum advantage in quantitative finance. In other words, the research shaved years off the timeline for when financial institutions could expect to gain real value from quantum computers.
Moving forward, the team is exploring how it can expand on these results to address other computationally complex problems in finance, benchmarking novel quantum approaches with existing classical algorithms to detect potential advantages.