Building Credit Scorecards Using Credit Scoring for SAS® Enterprise MinerTM

Building Credit Scorecards Using Credit Scoring for SAS Enterprise Miner

Building Credit Scorecards Using Credit Scoring for SAS(R) Enterprise Miner(TM)

Reject Inference Techniques Implemented in Credit Scoring for SAS® Enterprise MinerTM

Many business elements are used to develop credit scorecards. Reject inference, related to the issue of sample bias, is one of the key processes required to build relevant application scorecards and is vital in creating successful scorecards. Reject inference is used to assign a target class (that is, a good or bad designation) to applications that were rejected by the financial institution and...

Improving Credit Risk Scorecards with Memory-Based Reasoning to Reject Inference with SAS Enterprise Miner

Many business elements are used to develop credit scorecards. Reject inference, related to the issue of sample bias, is one of the key processes required to build relevant application scorecards and is vital in creating successful scorecards. Reject inference is used to assign a target class (that is, a good or bad designation) to applications that were rejected by the financial institution and...

153-2008: SAS/OR®: Rigorous Constrained Optimized Binning for Credit Scoring

Credit scoring can be defined as a statistical modeling technique used to assign risk to credit applicants or to existing credit accounts. We present a new process that enhances the formulation and solution approach in the SAS® system during the so-called “binning” phase by exploiting SAS/OR optimization capabilities to approach the problem from a mathematically rigorous perspective. Usually, a...