Abstract
Purpose
– The purpose of this paper is to build a neural network system to predict corporate credit rating in Jordanian non-financial firms, using 19 different financial characteristics such as profitability, leverage ratios, liquidity, bankruptcy, and sales performance.
Design/methodology/approach
– The study adopts two neural network techniques namely, Kohonen network and Back Propagation Neural Network (BPNN). Our sample includes the manufacturing firms that have provided the required financial information for the period from 2000 to 2007.
Findings
– BPNN has successfully predicted firms with high performance gaining A rating and the bankrupted firms with D rating for the period from 2005 to 2007.
Originality/value
– This study is the first study to investigate credit rating in Jordan using Neural Network technique.
– The purpose of this paper is to build a neural network system to predict corporate credit rating in Jordanian non-financial firms, using 19 different financial characteristics such as profitability, leverage ratios, liquidity, bankruptcy, and sales performance.
Design/methodology/approach
– The study adopts two neural network techniques namely, Kohonen network and Back Propagation Neural Network (BPNN). Our sample includes the manufacturing firms that have provided the required financial information for the period from 2000 to 2007.
Findings
– BPNN has successfully predicted firms with high performance gaining A rating and the bankrupted firms with D rating for the period from 2005 to 2007.
Originality/value
– This study is the first study to investigate credit rating in Jordan using Neural Network technique.
| Original language | English |
|---|---|
| Pages (from-to) | 475-487 |
| Number of pages | 13 |
| Journal | Journal of Enterprise Information Management |
| Volume | 27 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 8 Jul 2014 |
| Externally published | Yes |