Leonardo A.

Closer is a Portuguese company, operating in the main European countries. I am part of the Data Science Consultants team, currently helping one of the largest banks in the UK in developing methodologies and statistical analysis related to affordability risk for unsecured loans.

Sicoob is the largest Credit Union System in Brazil, having more than 6 million customers and over 20 billion dollars in credit portfolio. As a Risk Modeling Manager, I was responsible for managing the team's activities (18 data scientists), both from a technical and a business perspective. The team was in charge of developing and monitoring predictive models for Credit Risk (PD, LGD, EAD), Fraud Prevention and Anti-Money Laundering, as well as conducting statistical data analysis for the entire System. My duties also included reporting to the Executive Committee, in addition to negotiating and prioritizing demands with the IT teams and other business units. This paper shows how we used SAS to change Sicoob’s credit process as well as the main impacts (presented in Dallas-USA, at SAS Global Forum 2019): https://support.sas.com/resources/papers/proceedings19/3952-2019.pdf.