Quality Measures for Predictive Scoring Models
| Authors | |
|---|---|
| Year of publication | 2011 |
| Type | Article in Proceedings |
| Conference | PROCEEDINGS ASMDA 2011 |
| MU Faculty or unit | |
| Citation | |
| Field | Applied statistics, operation research |
| Keywords | Credit scoring; Quality indexes; Gini index; Lift |
| Description | Credit scoring models are widely used to predict a probability of an event like client's default. To measure the quality of scoring models it is possible to use quantitative indexes such as Gini index, K-S statistics and Lift. They are used for comparison of several developed models at the moment of development as well as for monitoring of quality of those models after deployment into real business. The paper deals with mentioned quality indexes, their properties and relationships. Finally, a new approach to measure power of scoring models is discussed and a new quality index is proposed. A simulation study compares it with other quality indexes. |
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