Introduction

In this blog, I explored the credit default data using Microsoft Power BI.

The Microsoft BI dashboard for the “Credit Card Default” data has been made public on my Github here.

Data

The dataset used for the data analysis in Power bi is from UCI Machine Learning Repository. The dataset digs into the customer credit card default payments back in 2005. However, the last column used in the dataset is a made-up column.

Power BI Dashboard

Here is the dashboard I created.

Conclusions

  • Females defaulted more than males. To be specific single females faulted more than married women.
  • Undergraduate females defaulted the most, followed by Graduates. The lowest default rates were by high school males.
  • Females between the age groups of 20–35 defaulted the most. The male and female between the age group of 35+ had a similar default rate.
  • Idaho, Illinois, and Lousiana, and Florida had the highest default rates. Colorado and Okhlama had the least default rates,
  • About 22% of the customers defaulted. The average bill amount was approximately 51k.

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Engineer. Data Analyst. Machine Learning enthusiast