Zapata and BBVA explore financial services

Introduction

The partnership between Zapata Computing and BBVA emerged as part of BBVA’s broader digital transformation strategy and commitment to exploring cutting-edge technologies. As one of Spain’s largest financial institutions with a global presence, BBVA recognized the potential of quantum computing to revolutionize various aspects of banking operations, from complex financial modeling to risk management. Zapata Computing, founded by Harvard quantum computing researchers, brought to the partnership its Orquestra platform and expertise in developing quantum algorithms for enterprise applications. This collaboration aimed to identify and develop quantum computing use cases that could provide BBVA with competitive advantages in areas where classical computing faces limitations. The partnership focused on exploring near-term quantum applications using both quantum simulators and actual quantum hardware from various providers, with the goal of preparing BBVA for the quantum advantage era while building internal quantum literacy and capabilities.

Challenge

The financial services industry faces increasingly complex computational challenges that strain the capabilities of classical computers. BBVA, like other major banks, deals with massive portfolios requiring optimization across thousands of assets and variables, complex derivative pricing models that demand extensive Monte Carlo simulations, and risk analysis scenarios that grow exponentially with market complexity. Traditional computing methods, while powerful, face fundamental limitations when dealing with certain types of optimization problems and probabilistic calculations that are central to modern finance. Additionally, as markets become more interconnected and volatile, the need for real-time or near-real-time analysis of vast amounts of data becomes critical for maintaining competitive advantage. BBVA recognized that quantum computing could potentially offer exponential speedups for specific financial calculations, particularly in areas involving optimization, simulation, and machine learning. The challenge was not just technical but also organizational - how to build quantum expertise within a traditional financial institution, identify the most promising use cases, and develop a roadmap for quantum adoption that aligns with business objectives while managing the uncertainty inherent in emerging technology.

Solution

Zapata Computing and BBVA developed a comprehensive approach centered around Zapata’s Orquestra platform, which provides a hardware-agnostic quantum computing workflow management system. The solution focused on three primary areas: portfolio optimization using quantum algorithms like QAOA (Quantum Approximate Optimization Algorithm) and VQE (Variational Quantum Eigensolver), Monte Carlo simulations for derivative pricing leveraging quantum amplitude estimation, and credit risk analysis using quantum machine learning techniques. The teams worked together to translate BBVA’s financial models into quantum-ready formulations, developing hybrid classical-quantum algorithms that could run on near-term quantum devices despite their limitations. Zapata’s approach involved creating a library of quantum algorithms specifically tailored for financial applications, along with benchmarking tools to compare quantum performance against classical methods. The solution also included an educational component, with Zapata providing training and workshops to BBVA’s technology and quantitative teams to build internal quantum computing capabilities. This comprehensive solution allowed BBVA to experiment with quantum algorithms across multiple hardware platforms while maintaining a unified development and deployment environment through Orquestra.

Implementation

The implementation began with a proof-of-concept phase where Zapata and BBVA identified specific use cases with the highest potential for quantum advantage. The teams started with portfolio optimization problems, implementing quantum algorithms on simulators before moving to actual quantum hardware from IBM, Rigetti, and other providers. The Orquestra platform served as the central hub, allowing BBVA’s teams to write quantum workflows that could be executed across different backends without modifying the core algorithm logic. Implementation involved several key phases: data preparation and classical preprocessing to reduce problem sizes to fit on current quantum hardware, development of variational quantum algorithms that could work within the constraints of noisy intermediate-scale quantum (NISQ) devices, and creation of benchmarking frameworks to measure quantum performance against classical baselines. BBVA established a dedicated quantum computing team that worked closely with Zapata’s scientists, creating a collaborative environment for knowledge transfer. The implementation also included integration points with BBVA’s existing IT infrastructure, ensuring that quantum computing capabilities could eventually be incorporated into production systems. Regular workshops and training sessions ensured that BBVA’s teams could independently develop and test quantum algorithms using the Orquestra platform.

Results and Business Impact

The partnership yielded several significant outcomes for BBVA’s quantum computing journey. In portfolio optimization, the teams successfully demonstrated quantum algorithms running on actual quantum hardware for simplified portfolio models, showing promising results that could scale to provide advantage as quantum hardware improves. While current quantum devices did not yet outperform classical methods for production-scale problems, the work established clear benchmarks and identified the hardware improvements needed to achieve quantum advantage. The collaboration resulted in BBVA building one of the first quantum computing teams within a European bank, with staff capable of developing and evaluating quantum algorithms independently. From a business perspective, BBVA positioned itself as a leader in quantum computing adoption within the financial sector, enhancing its reputation for innovation and attracting top talent interested in cutting-edge technology. The partnership also produced several research papers and presentations at quantum computing conferences, contributing to the broader understanding of quantum applications in finance. Perhaps most importantly, BBVA developed a clear roadmap for quantum adoption, identifying specific milestones and metrics for transitioning from experimental to production use of quantum computing as the technology matures.

Future Directions

Looking ahead, BBVA and Zapata Computing planned to expand their collaboration to explore additional use cases, including quantum machine learning for fraud detection and customer behavior analysis, and quantum algorithms for regulatory compliance and stress testing. The partnership aims to develop more sophisticated hybrid algorithms that can extract value from near-term quantum devices while preparing for fault-tolerant quantum computers. BBVA intends to continue building its internal quantum capabilities, potentially establishing a quantum computing center of excellence that can serve the entire organization. As quantum hardware improves, the focus will shift from proof-of-concept demonstrations to pilot programs that can deliver actual business value. The collaboration also looks to contribute to quantum computing standards and best practices for the financial industry, potentially working with regulators and industry bodies to establish frameworks for quantum computing adoption in regulated environments. Both organizations recognize that the path to quantum advantage in finance is still evolving, but their continued partnership positions them to capitalize on breakthroughs as they emerge.