Multivariable data imputation for the analysis of incomplete credit data.

•A novel iterative imputation method for incomplete credit data is proposed.•The method combines an iterative mechanism and a Bayesian network classifier.•Our method is less dependent on the hypothesis for probability distribution than other methods.•The proposed method suits for both single variable and multivariable missing data.•The proposed method is more accuracy and more applicable than other baseline methods.