Financial Services data mining example: Identifying risky borrowers
To introduce you to data mining with the CART decision tree software we are going to walk through a real world example drawn from the Financial Services industry. The database is an extract from a group of customers who selected a financial loan product, some of whom went "BAD". The information we will make use of comes from standard credit reports provided by all the major credit bureaus, including variables such as:
- Number of credit reports requested for this person in last 6 months
- Number of credit cards with balances greater than 80% of available credit
- Number of new credit accounts opened in last 12 months
- How long ago was oldest account opened?
- How long ago was newest account opened?
Our goal is to see if we can predict who goes BAD (stops making payments) using standard credit bureau information. We'll use this example to display the look and feel of CART and to show you how much you can learn quickly from a CART analysis.