compact

Create compact credit scorecard

Since R2019a

Syntax

csc = compact(sc)

Description

csc = compact(sc) converts an existing creditscorecard object to a compactCreditScorecard object (csc).

Note

To use this function, you must have a license for Risk Management Toolbox™.

Examples

Convert creditscorecard Object into compactCreditScorecard Object

Convert a creditscorecard object into a compactCreditScorecard object to use displaypoints (Risk Management Toolbox), score (Risk Management Toolbox), and probdefault (Risk Management Toolbox) from Risk Management Toolbox™ with the object.

First, create a creditscorecard object using the CreditCardData.mat file to load the data (using a dataset from Refaat 2011).

load CreditCardData.mat 
sc = creditscorecard(data)

sc = 
  creditscorecard with properties:

                GoodLabel: 0
              ResponseVar: 'status'
               WeightsVar: ''
                 VarNames: {'CustID'  'CustAge'  'TmAtAddress'  'ResStatus'  'EmpStatus'  'CustIncome'  'TmWBank'  'OtherCC'  'AMBalance'  'UtilRate'  'status'}
        NumericPredictors: {'CustID'  'CustAge'  'TmAtAddress'  'CustIncome'  'TmWBank'  'AMBalance'  'UtilRate'}
    CategoricalPredictors: {'ResStatus'  'EmpStatus'  'OtherCC'}
           BinMissingData: 0
                    IDVar: ''
            PredictorVars: {'CustID'  'CustAge'  'TmAtAddress'  'ResStatus'  'EmpStatus'  'CustIncome'  'TmWBank'  'OtherCC'  'AMBalance'  'UtilRate'}
                     Data: [1200x11 table]

Before creating a compactCreditScorecard object, you must use autobinning and fitmodel with the creditscorecard object.

sc = autobinning(sc);
sc = fitmodel(sc);

1. Adding CustIncome, Deviance = 1490.8527, Chi2Stat = 32.588614, PValue = 1.1387992e-08
2. Adding TmWBank, Deviance = 1467.1415, Chi2Stat = 23.711203, PValue = 1.1192909e-06
3. Adding AMBalance, Deviance = 1455.5715, Chi2Stat = 11.569967, PValue = 0.00067025601
4. Adding EmpStatus, Deviance = 1447.3451, Chi2Stat = 8.2264038, PValue = 0.0041285257
5. Adding CustAge, Deviance = 1441.994, Chi2Stat = 5.3511754, PValue = 0.020708306
6. Adding ResStatus, Deviance = 1437.8756, Chi2Stat = 4.118404, PValue = 0.042419078
7. Adding OtherCC, Deviance = 1433.707, Chi2Stat = 4.1686018, PValue = 0.041179769

Generalized linear regression model:
    logit(status) ~ 1 + CustAge + ResStatus + EmpStatus + CustIncome + TmWBank + OtherCC + AMBalance
    Distribution = Binomial

Estimated Coefficients:
                   Estimate       SE       tStat       pValue  
                   ________    ________    ______    __________

    (Intercept)    0.70239     0.064001    10.975    5.0538e-28
    CustAge        0.60833      0.24932      2.44      0.014687
    ResStatus        1.377      0.65272    2.1097      0.034888
    EmpStatus      0.88565        0.293    3.0227     0.0025055
    CustIncome     0.70164      0.21844    3.2121     0.0013179
    TmWBank         1.1074      0.23271    4.7589    1.9464e-06
    OtherCC         1.0883      0.52912    2.0569      0.039696
    AMBalance        1.045      0.32214    3.2439     0.0011792


1200 observations, 1192 error degrees of freedom
Dispersion: 1
Chi^2-statistic vs. constant model: 89.7, p-value = 1.4e-16

Convert the creditscorecard object into a compactCreditScorecard object by using the compact function. To use compact, you must have a Risk Management Toolbox™ license.

csc = compact(sc)

csc = 
  compactCreditScorecard with properties:

              Description: ''
                GoodLabel: 0
              ResponseVar: 'status'
               WeightsVar: ''
        NumericPredictors: {'CustAge'  'CustIncome'  'TmWBank'  'AMBalance'}
    CategoricalPredictors: {'ResStatus'  'EmpStatus'  'OtherCC'}
            PredictorVars: {'CustAge'  'ResStatus'  'EmpStatus'  'CustIncome'  'TmWBank'  'OtherCC'  'AMBalance'}

You can then use displaypoints (Risk Management Toolbox), score (Risk Management Toolbox), and probdefault (Risk Management Toolbox) from Risk Management Toolbox™ with the compactCreditScorecard object.

Input Arguments

sc — Credit scorecard model

creditscorecard object

Credit scorecard model, specified as a creditscorecard object.

Note

You must use a creditscorecard object (sc) for input that has been previously processed with autobinning and fitmodel, or fitConstrainedModel. Optionally, you can use formatpoints in addition to these functions.

Output Arguments

csc — Compact credit scorecard

compactCreditScorecard object

Compact credit scorecard, returned as a compactCreditScorecard (Risk Management Toolbox) object. You can then use displaypoints (Risk Management Toolbox), score (Risk Management Toolbox), and probdefault (Risk Management Toolbox) from the Risk Management Toolbox with this csc object.

References

[1] Anderson, R. The Credit Scoring Toolkit. Oxford University Press, 2007.

[2] Refaat, M. Credit Risk Scorecards: Development and Implementation Using SAS. lulu.com, 2011.

Version History

Introduced in R2019a