BBVA Completes Its First Industrial Doctorates in Data Science in Partnership with the University of Navarra
BBVA and the University of Navarra have completed the first two industrial doctorates in data science under their joint program. This pioneering initiative enables working professionals to carry out advanced academic research into real challenges facing the financial sector. Both theses propose ways of developing AI models that can identify the causes behind financial decisions, not just the correlations.
Photo caption (from left to right): Paul G. Tobin, Global Head of Talent and Culture at BBVA; Paloma Grau, Vice President for Research and Sustainability at the University of Navarra; the newly awarded PhDs Paloma Marín and Jesús Renero; and Jesús López Fidalgo, Director of DATAI. / Source: University of Navarra
The program is jointly led by BBVA and the University of Navarra’s Institute of Data Science and Artificial Intelligence (DATAI). It demonstrates the value of professionals who combine scientific rigor and technical expertise with the ability to apply their knowledge to real-world challenges. This approach helps bring advances in research into the business world and, ultimately, deliver benefits for society.
The two theses address one of the biggest challenges currently facing artificial intelligence: developing systems that can identify the causes of specific outcomes, rather than simply detecting patterns and correlations in data. Paloma Marín, from BBVA CIB Global Markets, uses probabilistic models and causal reasoning to support better decision-making in complex financial markets such as bond trading, while incorporating key economic principles from the business. Jesús Renero, from Data, developed ReX, an explainable AI method that identifies cause-and-effect relationships in data and provides insight into how decisions are reached.
Both theses aim to make AI more transparent, robust and useful in decision-making. This could improve the explainability and reliability of important customer-facing financial processes, such as lending and risk management, while making it easier to explain how decisions are made.
“This program reflects the way we see data science at BBVA: not simply as a technical capability, but as a tool for making better financial decisions. By supporting industrial doctorates in partnership with the University of Navarra, we bring together talent, research and practical application to build more trustworthy artificial intelligence,” said Javier Marín, who oversees BBVA’s industrial doctorate partnership.
Jesús López Fidalgo, Director of DATAI at the University of Navarra, said: “This milestone embodies the university’s mission: to pursue truth through rigorous academic excellence and put that knowledge at the service of society. These doctorates are advancing data science and artificial intelligence, expanding the boundaries of knowledge while also delivering practical solutions that can improve people’s lives.”
The industrial doctorate program, jointly led by BBVA and the University of Navarra, currently has a further 10 doctoral candidates from Spain, Argentina and Peru, representing up to six different areas of the Group. This reflects the program’s international and cross-functional scope. The program has also opened applications for five additional places.
This initiative is further evidence of BBVA’s commitment to developing talent, working with academia and applying research to real business needs. It forms part of the partnership between BBVA and the University of Navarra, established in 2020 to train the bank’s employees in data science. Through this collaboration, employees can pursue an official Master’s Degree in Big Data Science, obtain data scientist certification and take part in applied research projects. These include Fair Learning, a project exploring the ethical, technical and regulatory challenges posed by AI. The partnership has also launched an Executive Program in Generative AI, which has already trained more than 150 BBVA leaders to use these technologies strategically.