This is a private hackathon whose primary purpose is for the members of the DSN Ai+ Club Unilorin to apply what they have learnt. If you are part of Ai+ Club Unilorin contact the club leader for the secret code.

According to the Uganda FinScope 2018 survey findings, 46% (8.5 million) adults borrowed money during the 12-month period prior to the survey, with the majority borrowing to cover regular living expenses (such as education) during low-income periods. Further, the largest source of borrowing is from informal lenders i.e. savings groups, burial societies, community-based money lenders etc.

Xente is a Ugandan e-commerce startup that makes it easy for consumers to make payments, get loans, and shop using simply a mobile phone. Using the Xente app you can access personal loans of from UGX 500 – UGX 3,000,000.* The funds can be deposited into your Xente wallet, and then transferred into your Xente Visa card, mobile money wallet, or bank account. You can make transactions using the app using your mobile money or bank card.Alternatively, you can use the funds to buy any product or service in the Xente app. Xente also has a “Buy Now & Pay Later” option, for products such as airtime and data, bill payments, utilities, movies, and bus tickets.**

The objective of this challenge is to create a machine learning model to predict which individuals are most likely to default on their loans, based on their loan repayment behaviour and ecommerce transaction activity.

The resulting models and solutions will help Xente refine their credit decision processes, and enable them to more adequately assess the creditworthiness of new and existing clients. For Xente, this may result in improved profitability and financial sustainability; while for Xente’s cliente, increased creditworthiness would enhance their access to credit and contribute to an improved livelihood.

This challenge is hosted by Xente, in association with Standard Bank

About Xente (xente.co)

Xente is an e-payments, e-commerce, and financial services company in Uganda offering various products and services that can be paid for using Mobile Money (Airtel Money, MTN Mobile Money), Bank Card (Visa Card, Master Card,Amex), Xente wallet and on credit (Pay Later). Some of the products consumers can buy include airtime, data bundles, pay water and electricity bills, TV subscription services, buy event tickets, movie tickets, bus tickets, and more.

About DSN Ai+ Club Unilorin (twitter.com/AiUnilorin):

DSN Ai+ Club Unilorin (University of Ilorin, Nigeria) is a branch of Data Science Nigeria Community aimed at building and sustaining Ai talents at the university with the vision #1millionAiTalentsIn10Yrs.

This is a private hackathon whose primary purpose is for the members of the DSN Ai+ Club Unilorin to apply what they have learnt. If you are part of Ai+ Club Unilorin contact the club leader for the secret code.

Teams and collaboration

You may participate in this competition as an individual.

Multiple accounts per user are not permitted, and neither is collaboration or membership across multiple teams. Individuals and their submissions originating from multiple accounts will be disqualified.

Code must not be shared privately outside of a team. Any code that is shared, must be made available to all competition participants through the platform. (i.e. on the discussion boards).

Datasets and packages

The solution must use publicly-available, open-source packages only. Your models should not use any of the metadata provided.

You may use only the datasets provided for this competition. Automated machine learning tools such as automl are not permitted.

If the challenge is a computer vision challenge, image metadata (Image size, aspect ratio, pixel count, etc) may not be used in your submission.

If external data is allowed you may only use data that is freely available to everyone. You must send it to Zindi to confirm that it is allowed to be used and then it will appear on the data page under additional data.

You may use pretrained models as long as they are openly available to everyone.

The data used in this competition is the sole property of Zindi and the competition host. You may not transmit, duplicate, publish, redistribute or otherwise provide or make available any competition data to any party not participating in the Competition (this includes uploading the data to any public site such as Kaggle or GitHub). You may upload, store and work with the data on any cloud platform such as Google Colab, AWS or similar, as long as 1) the data remains private and 2) doing so does not contravene Zindi’s rules of use.

You must notify Zindi immediately upon learning of any unauthorised transmission of or unauthorised access to the competition data, and work with Zindi to rectify any unauthorised transmission or access.

Your solution must not infringe the rights of any third party.

Submissions and winning

You may make a maximum of 30 submissions per day.

Zindi maintains a public leaderboard and a private leaderboard for each competition. The Public Leaderboard includes approximately 50% of the test dataset. While the competition is open, the Public Leaderboard will rank the submitted solutions by the accuracy score they achieve. Upon close of the competition, the Private Leaderboard, which covers the other 50% of the test dataset, will be made public and will constitute the final ranking for the competition.

You acknowledge and agree that Zindi may, without any obligation to do so, remove or disqualify an individual, team, or account if Zindi believes that such individual, team, or account is in violation of these rules. Entry into this competition constitutes your acceptance of these official competition rules.

Please refer to the FAQs and Terms of Use for additional rules that may apply to this competition. We reserve the right to update these rules at any time.

The evaluation metric for this challenge is the Area Under the Curve (AUC).

Your submission file should look like:

TransactionId	        IsDefaulted
TransactionId_925	0
TransactionId_1080	1
TransactionId_2315	0
TransactionId_1466	0
TransactionId_337	1

Competition closes on 21 November 2020.

Final submissions must be received by 11am GMT.

The private leaderboard will be visible at 11am GMT 21 November 2020.

We reserve the right to update the contest timeline if necessary.