Standard Bank is embracing the digital transformation wave and intends to use new and exciting technologies to give their customers a complete set of services from the convenience of their mobile devices.
As Africa’s biggest lender by assets, the bank aims to improve the current process in which potential borrowers apply for a home loan. The current process involves loan officers having to manually process home loan applications. This process takes 2 to 3 days to process, upon which the applicant will receive communication on whether or not they have been granted the loan for the requested amount.
To improve the process, Standard Bank wants to make use of machine learning to assess the creditworthiness of an applicant by implementing a model that will predict if the potential borrower will default on his/her loan or not, and do this such that they receive a response immediately after completing their application.
This is an opportunity to step into the shoes of a Standard Bank team member and complete tasks that replicate the work that the Data Science team does every day. We'll learn how to understand the data science project lifecycle, course train a model, and present the process as it relates to business objectives.
- SQL for Data Scientists - A relationship with relational databases
- Data Science With Python - AutoML vs bespoke
- Preparing to Present - Back to understanding the business
- Putting It All Together - Presenting your insights to a non-technical audience