Data Science Nigeria Challenge #1: Loan Default Prediction
Knowledge
11 October 2018–11 October 2019 23:59
A learning competition designed for DSN Bootcamp 2018

This challenge was designed by Data Science Nigeria specifically for the DSN Bootcamp 2018, which takes place 11-14 October. Welcome to the DSN participants!

After the Bootcamp, this competition will remain open for another year to allow others in the Zindi community to learn and test their skills.

Description of the challenge:

SuperLender is a local digital lending company, which prides itself in its effective use of credit risk models to deliver profitable and high-impact loan alternative. Its assessment approach is based on two main risk drivers of loan default prediction:. 1) willingness to pay and 2) ability to pay. Since not all customers pay back, the company invests in experienced data scientist to build robust models to effectively predict the odds of repayment.

These two fundamental drivers need to be determined at the point of each application to allow the credit grantor to make a calculated decision based on repayment odds, which in turn determines if an applicant should get a loan, and if so - what the size, price and tenure of the offer will be.

There are two types of risk models in general: New business risk, which would be used to assess the risk of application(s) associated with the first loan that he/she applies. The second is a repeat or behaviour risk model, in which case the customer has been a client and applies for a repeat loan. In the latter case - we will have additional performance on how he/she repaid their prior loans, which we can incorporate into our risk model.

It is your job to predict if a loan was good or bad, i.e. accurately predict binary outcome variable, where Good is 1 and Bad is 0.

About Data Science Nigeria (www.datasciencenigeria.org):

Data Science Nigeria is a non-profit run and managed by the Data Scientists Network Foundation. Our vision is to accelerate Nigeria’s development through a solution-oriented application of machine learning in solving social/business problems and to galvanize data science knowledge revolution, which can position Nigeria to become the outsourcing hub for international Data Science/Advanced Analytics/Big Data projects, with opportunity to access at least 1% share of the global big data and analytics market, valued at $150b in 2017 ($203b in 2020).

We adopt a practitioner-led model where experienced and hands-on data scientists in Nigeria and in the Diaspora train and mentor young Nigerians through face-to-face, virtual coaching classes, project-based support and holiday boot camps funded by individuals and corporate organizations.