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Table 6 Scorecard phase 2: computing the supervisory riskiness for regulatory capital

From: Measuring the model risk-adjusted performance of machine learning algorithms in credit default prediction

 

Lasso

CART

RF

XGBoost

MLP

Statistics

1

3

3

2

4

 Capital: 7.9%

     

 Credit: 6.41%

     

 Provisions: 6.38%

     

Technology

1

1

3

2

5

 Capital: 2.5%

     

 Credit: 3.09%

     

 Provisions: 2.36%

     

Market conduct

1

1

2

2

3

 Capital: 3.75%

     

 Credit: 5.13%

     

 Provisions: 3.9%

     

Supervisory model risk capital

14.15

29.95

38.7

28.3

55.35

Supervisory model risk credit

14.63

27.45

38.76

29.26

56.48

Supervisory model risk provisions

12.64

25.4

34.02

25.28

49,02