Rabobank - Python Training
On Monday February 11, Rabobank will organize a Python training for all econometrics students interested in learning how to work with this software! It will start at 17.00 hours and the training will take place in Cube Z213 at Tilburg University. The training will end at approximately 19.00 hours.
Rabobank is among the world’s largest banks in the world. To remain in the top, an important task for the Rabobank is predicting clients’ probability of making their contractual payments, and recover cash flows in the event that a customer defaults. Quantification of credit risk fundamental to many internal applications. Which clients should we allow to take out a loan? What rate should we charge these clients? When do we take action on a client, when a business is overdue on a contractual payment?
The Python training will focus on one of the keystones of these questions: What is the likelihood that a client will not be able to fulfil his loan payments? In this training we will create a Probability of Default (PD) model, to assess the quality of potential clients. Using a large dataset with more than a hundred variables and information on their empirical outcome, we will identify ways to maximize out of sample prediction power. Machine learning techniques can be used, among many other statistical analyses. The student is encouraged to find his/her own superior modelling techniques and get the highest score.
You can register for the Python Training by clicking the ‘Register’ button and filling in the form below. You can register until February 6.
All econometrics students who are interested can register! However, please note that third-year bachelor and master students will be given priority. There will be 20 spots available.
Please note that you need to be a member of Asset in order to register for this event. Are you not a member of Asset yet? Read more about all the benefits of becoming a member here.
- Took place on February 11, 17.00h
- Registration Deadline
- February 07, 00:00h
- Tilburg University, Cube Z213
- Participating companies