创建信用评分卡

信用评分卡建模、分 bin、模型拟合、获取点数和分数、模型验证、违约概率、创建紧凑型评分卡

有关开发信用评分卡的工作流的信息，请参阅Credit Scorecard Modeling Workflow。Risk Management Toolbox™ 中提供了用于信用评分卡的其他工具。有关详细信息，请参阅 Consumer Credit Risk (Risk Management Toolbox)。

对象

creditscorecard Create creditscorecard object to build credit scorecard model

函数

`autobinning`	Perform automatic binning of given predictors
`bininfo`	Return predictor’s bin information
`predictorinfo`	Summary of credit scorecard predictor properties
`fillmissing`	Replace missing values for credit scorecard predictors (自 R2020a 起)
`modifybins`	Modify predictor’s bins
`modifypredictor`	Set properties of credit scorecard predictors
`bindata`	Binned predictor variables
`plotbins`	Plot histogram counts for predictor variables
`fitmodel`	Fit logistic regression model to Weight of Evidence (WOE) data
`fitConstrainedModel`	Fit logistic regression model to Weight of Evidence (WOE) data subject to constraints on model coefficients
`setmodel`	Set model predictors and coefficients
`displaypoints`	Return points per predictor per bin
`formatpoints`	Format scorecard points and scaling
`score`	Compute credit scores for given data
`probdefault`	Likelihood of default for given data set
`validatemodel`	Validate quality of credit scorecard model
`screenpredictors`	Screen credit scorecard predictors for predictive value
`compact`	Create compact credit scorecard

实时编辑器任务

筛选预测变量的阈值

Select thresholds for predictor risk metrics in the Live Editor (自 R2021b 起)

主题

Feature Screening with screenpredictors (Risk Management Toolbox)
This example shows how to perform predictor screening using screenpredictors and then set predictor thresholds using the Threshold Predictors live task.
Case Study for Credit Scorecard Analysis
This example shows how to create a creditscorecard object, bin data, display, and plot binned data information.
Bin Data to Create Credit Scorecards Using Binning Explorer (Risk Management Toolbox)
Create a credit scorecard using the Binning Explorer app.
具有约束逻辑回归系数的信用评分卡
计算 creditscorecard 对象的分数时，如果逻辑回归模型系数要应用等式约束、不等式约束或边界约束，需要使用 fitConstrainedModel。与 fitmodel 不同，fitConstrainedModel 可以求解无约束问题和有约束问题。当前用于最小化 fitConstrainedModel 的目标函数的求解器是 fmincon，来自 Optimization Toolbox™。
Credit Scorecard Modeling with Missing Values
This example shows alternative workflows to handle missing values when working with creditscorecard objects.
Credit Scoring Using Logistic Regression and Decision Trees (Risk Management Toolbox)
Create and compare two credit scoring models, one based on logistic regression and the other based on decision trees.
Use Reject Inference Techniques with Credit Scorecards (Risk Management Toolbox)
This example demonstrates the hard-cutoff and fuzzy augmentation approaches to reject inference.
Credit Rating by Bagging Decision Trees
This example shows how to build an automated credit rating tool.
Credit Rating by Ordinal Multinomial Regression (Risk Management Toolbox)
This example shows how to use ordinal multinomial logistic regression to build a credit rating model that you can use in an automated credit rating process.
compactCreditScorecard Object Workflow (Risk Management Toolbox)
This example shows a workflow for creating a compactCreditScorecard object from a creditscorecard object.
Impute Missing Data in the Credit Scorecard Workflow Using the k-Nearest Neighbors Algorithm
This example shows how to perform imputation of missing data in the credit scorecard workflow using the k-nearest neighbors (kNN) algorithm.
Impute Missing Data in the Credit Scorecard Workflow Using the Random Forest Algorithm
This example shows how to perform imputation of missing data in the credit scorecard workflow using the random forest algorithm.
Treat Missing Data in a Credit Scorecard Workflow Using MATLAB fillmissing
This example shows a workflow to gather missing data, manually treat the training data, develop a new creditscorecard, and treat new data before scoring using the MATLAB® fillmissing.
Explore Fairness Metrics for Credit Scoring Model (Risk Management Toolbox)
Calculate and use data and model metrics to investigate the biases that exist in a model.
Bias Mitigation in Credit Scoring by Reweighting (Risk Management Toolbox)
Use bias mitigation with a credit scorecard model to make it more fair.
Bias Mitigation in Credit Scoring by Disparate Impact Removal (Risk Management Toolbox)
Use disparate impact removal as a pre-processing technique in bias mitigation to a credit scorecard model to reduce bias in the model.
Interpretability and Explainability for Credit Scoring (Risk Management Toolbox)
This example shows different techniques for interpreting and explaining the logic behind credit scoring predictions.
Credit Scorecard Modeling Workflow
Use the credit scorecard workflow to create, model, and analyze credit scorecards.
About Credit Scorecards
The goal of credit scoring is ranking borrowers by their credit worthiness.
Credit Scorecard Modeling Using Observation Weights
Use observation weights with the credit scorecard workflow to create, model, and analyze credit scorecards.

疑难解答

Troubleshooting Credit Scorecard Results

Troubleshoot results when using a creditscorecard model.

创建信用评分卡

对象

函数

实时编辑器任务

主题

疑难解答

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