Co-Hosted by GARP and CFA Society Spain
Credit models are the cornerstone of banks and the credit system. Institutions use them every day to make better decisions based on data. The digital revolution has enabled us to enhance these models by exploring new sources of information — both internal and external — and incorporating new modelling techniques featuring machine learning, making this sector one of the fastest growing and most profitable.
Join us to hear data scientist Marta Ortigosa illustrate a methodology for constructing robust credit models from scratch. Her presentation will cover:
• An introduction to scorings and ratings
• Model development, including data gathering, target definition, data analysis and variable generation, model estimation, and backtesting
• Monitoring and governance
This event will be held in Spanish.
Presentation with Q&A: 7:30-8:30pm
Networking Reception: 8:30-9:30pm
Calle del Pinar, 17
Credit Risk Manager Data Scientist, BBVA
Marta Ortigosa Tomás is Credit Risk Manager Data Scientist at BBVA, one of the largest financial institutions in the world. She started her career as a programmer at Telefonica and in 2013 she changed to the financial industry where she has been developing mathematical models to predict credit risk since then, first at Santander Bank and then at BBVA.
Marta holds a degree in Physics from the Universidad Complutense of Madrid. She completed her studies with a Master's in Physics and Mathematics (Specialization in mathematical methods and models for Science and Engineering) at Universidad de Castilla-La Mancha and a Master's in Quantitative Finance at AFI. She recently obtained the Sustainability and Climate Risk (SCR) Certificate at GARP.
Market Risk Analyst Global Market Risk Unit BBVA