Statlog (German Credit - SCHUFA)

Several categorial and numerical attributes of 1,000 credit applicants in Germany, including the result of their credit score. Read full description here.

Data Types: Multivariate

Default Task: Classification

Attribute Types: Categorical, Integer

Format: csv

Number of Entries: 1000

Number of Attributes: 20

Year: 1994

Source: UCI Machine Learning Repository - extracted from the German Credit Rating Agency SCHUFA

Attributes

• Status of existing checking account
• Duration in month
• Credit history
• Credit Purpose
• Credit amount
• Savings account/bonds
• Present employment since
• Personal status and sex
• Other debtors / guarantors
• Present residence since
• Property
• Age in years
• Other installment plans
• Housing
• Number of existing credits at this bank
• Job
• Number of people being liable to provide maintenance for
• foreign worker

Download link

Download Warning: benchmarking used not on raw data set

Reference

Lichman, M. (2013). UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science.

 {
 @misc{Lichman:2013 ,
 author = "M. Lichman",
 year = "2013",
 title = "{UCI} Machine Learning Repository",
 url = "http://archive.ics.uci.edu/ml",
 institution = "University of California, Irvine, School of Information and Computer Sciences" }
 }

Please refer to the Machine Learning Repository for further citation requirements.