BBVA believes the knowledge derived from financial data can transform the banking industry and its role in the world. Therefore the Advanced Analytics area performs research in the application of AI to the banking industry. It that takes into account aspects such as bias mitigation, fairness and the ethical and secure usage of information. The privacy and protection of personal data is one of the top priorities, surpassing the legal requirements of the countries BBVA operates.
Fernández Tebar, Juan José
Lines of research:
- Dynamic pricing
- Clustering / Segmentation
- Recommendation systems
Garcia Montiel, Conrado
"Multi-product dynamic pricing strategies with unlimited inventories".
Ariza Mayo, Victor
Risk & Opportunities of the transition to a low carbon economy
Díaz Lanchas, Adrián
Detecting illicit activity to minimise the spread of fraud in dynamic networks
García Muñoz, Luis Manuel
Application of Machine Learning Techniques in Quantitative Finance
Guerrero San Martín, Ainhoa
Conversational Recommender Systems and their application in the financial field
Gómez Tejerina, Pedro
Searching for a Universal Predictor for Economic Time Series Using Language Models
Mahari, Thandiwe Irina
Machine Learning Solutions for Complex Market Risk Models
Marin Martínez, Paloma
Profitability and adverse flow forecasting in financial markets and multi-contributor platforms
Ojeda Trejo, Christian
Algorithmic market-making strategies with stochastic optimization techniques and reinforcement learning
Renero Quintero, Jesús Salvador
Adding Causal Inference to Reinforcement Learning methods
Rodriguez, Eddy
Performance metrics for use of a machine learning model in revenue estimators
Tasar, Emre
Enhancing Fairness in AI Systems: A Study on Uncertainty Quantification for Banking Applications.
Stivala, Ignacio José
model Bayesian approach for estimating optimal prices in banking products with few observations in Argentina
Zaballa, Miguel
Algorithmic trading strategies for pricing and hedging using covariance matrices with uncertainty