Table 5 Performance of the model. To evaluate the performance of the model, we use its predictive power for data outside the model. 54,000 records that were not used in training were entered into the model and their probability was calculated and compared with the values of the table. The degree of sensitivity and diagnosis of the model were 0.84.05% and 89.23%, respectively
From: A dynamic credit risk assessment model with data mining techniques: evidence from Iranian banks
Real estimate observation | Medium risk customers | High risk customers | Total |
|---|---|---|---|
P(Y) < =0.37 | 638 | 58 | 696 |
P(Y) > 0.37 | 77 | 307 | 384 |
Total | 715 | 365 | 1080 |
Correct | 638 | 307 | 945 |
Correct percent | 89.23% | 84.05% | 87.5% |
Incorrect percent | 10.76% | 84.1% | 12.5% |