Article1963

The Development of Numerical Credit Evaluation Systems

141 citations0/0 files storedJournal of the American Statistical Association

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Financial Distress and Bankruptcy Prediction Statistical Methods and Applications Forecasting Techniques and Applications

Abstract

Several discriminant and multiple regression analyses were performed on retail credit application data to develop a numerical scoring system for predicting credit risk in a finance company. Results showed that equal weights for all significantly predictive items were as effective as weights from the more sophisticated techniques of discriminant analysis and “stepwise multiple regression.” However, a variation of the basic discriminant analysis produced a better separation of groups at the lower score levels, where more potential losses could be eliminated with a minimum cost of potentially good accounts.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 141 citations exist upstream.

Cited by

1982Credit Scoring Systems: A Critical Analysis 1970The Credit Granting Decision 1986The flat maximum effect and linear scoring models for prediction 1978Problems in applying discriminant analysis in credit scoring models 2018An artificial intelligence system for predicting customer default in e-commerce 2004Making a Market: The UK Retail Financial Services Industry and the Rise of the Complex Sub-Prime Credit Market 2016Financial innovation: Credit default hybrid model for SME lending 1986A scoring model for flexible manufacturing systems project selection

Imported from OpenAlex (CC0) — nothing here is generated.