ML applied to Credit Risk: building explainable models
The iDanae Chair (where iDanae stands for intelligence, data, analysis and strategy in Spanish) for Big Data and Analytics, created within the framework of a collaboration between the Polytechnic University of Madrid (UPM) and Management Solutions, has published its 3Q22 quarterly newsletter on Machine Learning (ML) applied to Credit Risk
The iDanae Chair for Big Data and Analytics, created within the framework of a collaboration between UPM and Management Solutions, aims to promote the generation and dissemination of knowledge, the transfer of technology, and the furthering of R&D in the Analytics field. In this context, one of the lines of work developed by the iDanae Chair is the analysis of meta-trends in the field of Analytics.
ML applied to Credit Risk: building explainable models
The "ML applied to Credit Risk: building explainable models" paper, corresponding to 3Q22, analyzes the implications of this challenge for financial institutions, as well as different approaches on how to address it, through the use of so-called interpretable models, or non-interpretable models that are complemented with an explainability tool.
The publication is now available for download on the Chair's website in both in spanish and english.