A Network Based Fintech Inclusion Platform

This paper describes a multidimensional machine learning model and its implementation in a financial technology (fintech) application. The aim of the model is to learn from both micro economic financial data and macro economic trends the credit rating of companies that ask for credit. We show that the proposed model is able to reward the companies with better financial performance with better ratings and, therefore, a higher probability/lower cost of obtaining credit. At the same time, the model correctly takes into account the overall evolution of the economy, favoring financial inclusion for the more penalised economic sectors and, therefore, improving financial inclusion during crisis times. The model, its application to credit rating, and its evaluation, are illustrated with reference to more than 100,000 European companies before and during the COVID-19 pandemic crisis. The results shows that, while the impact of the financial variables does not change over time, and particularly during the pandemic, the impact of sectors changes considerably.