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Evispot Articles: Case #1 – Detecting ​​Default ​​Payments ​​of ​​Credit ​​Card ​​Clients using Machine Learning

Hope you have had a great summer! While many have been lying on the beach and enjoyed vacation, Evispot has worked on interesting machine learning cases. 

During the upcoming weeks we will share our experiences in a serie of articles. The idea is to give you insights and a deeper understanding of machine learning in credit scoring. The articles follow Evispot´s development process going from raw data to actionable insights – and our hope is that you will share our view: 

Machine learning is the future in credit scoring

Case#1 –  Detecting ​​Default ​​Payments ​​of ​​Credit ​​Card ​​Clients using Machine Learning

The first article is about predicting default payments of credit card clients, using demographic data, credit data and history of payment bill statements of credit card clients. In this example, we use logistic regression to briefly demonstrate a classification problem, and how classification can be more useful than just predicting the outcome variable.

Follow the link to get to the article:
Case #1 – Detecting ​​Default ​​Payments ​​of ​​Credit ​​Card ​​Clients using Machine Learning 

If you have any questions or data you want to explore feel free to contact:

Sebastian.Larsson@evispot.ai, CEO & Co-founder Evispot

 

Tomas SelldenEvispot Articles: Case #1 – Detecting ​​Default ​​Payments ​​of ​​Credit ​​Card ​​Clients using Machine Learning
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