About Dataset
Context
The consumer credit department of a bank wants to automate the decisionmaking process for approval of home equity lines of credit. To do this, they will follow the recommendations of the Equal Credit Opportunity Act to create an empirically derived and statistically sound credit scoring model. The model will be based on data collected from recent applicants granted credit through the current process of loan underwriting. The model will be built from predictive modeling tools, but the created model must be sufficiently interpretable to provide a reason for any adverse actions (rejections).
Content
The Home Equity dataset (HMEQ) contains baseline and loan performance information for 5,960 recent home equity loans. The target (BAD) is a binary variable indicating whether an applicant eventually defaulted or was seriously delinquent. This adverse outcome occurred in 1,189 cases (20%). For each applicant, 12 input variables were recorded.
BAD
1 = client defaulted on loan 0 = loan repaid
LOAN
Amount of the loan request
MORTDUE
Amount due on existing mortgage
VALUE
Value of current property
REASON
DebtCon = debt consolidation HomeImp = home improvement
JOB
Six occupational categories
YOJ
Years at present job
DEROG
Number of major derogatory reports
DELINQ
Number of delinquent credit lines
CLAGE
Age of oldest trade line in months
NINQ
Number of recent credit lines
CLNO
Number of credit lines
DEBTINC
Debt-to-income ratio