Hi, guys. My goal is to get a new scorecard better than the old one. But on test month it has higher bad rate and lower approval... What am I doing wrong? I try to build a scorecard model in Enterprise Miner: diagram I keep the only non-correlating predictors: variable correlation It seems my variables are pretty valuable: from scorecard results before reject inference from interactive grouping before reject inference And I meet several problems: 1) very few target events: def_6_30 - overdue 30+ on 6 months to overcome this limitaion I involved frequency variable, but I suspect model to bias: 2) cannot get stable model before reject inference 3) train / validation gini varies drastically: before reject inference, data partition 50/50 stratified, train gini=0.52, validation gini=0.49 before reject inference And some questions: 1) How to estimate bad rate and approval of scorecard model? All I need - is to improove old scorecard model, to archive this I tried to exclude predictors (start from the lowest information value) and add new ones (with high IV) . Honestly speaking have no other ides of doing that. P.s. I used Naim Siddiqui's book and "developing credit scorecards using credit scoring for sas"
... View more
