A coworker recently asked me to explain how one goes about building a credit risk model. It’s something my company does a lot of, but apparently it’s not taught during new hire on-boarding. Also, it made me think, how would I actually explain the process end-to-end to someone interested in our industry but not a practitioner? Curious, I searched Google in case anyone had already done so, and of course someone else had! So, here’s a quite impressive deep-dive into credit risk modelling thanks to Natasha Mashanovich, Senior Data Scientist at World Programming: Credit Scoring: The Development Process from End to End
This is a ten-part series of blog posts describing the entire process. Her company seems to be some sort of SAS competitor, and I am not endorsing her product or company in any way. That said, her write up is pretty tool-agnostic and pretty general, so it is worth a read if you are interested.
Personally, I would create a modelling pipeline in python / pyspark (since we deal with large data sets) in a cloud environment (like AWS) instead of SAS, but not everyone in the financial services industry has moved to the cloud yet. I hope you find the link to be helpful…
David Mantilla 