This paper employs clustering and machine learning techniques to analyze validation reports. It provides insights into issues related to credit risk model development, implementation and maintenance.

The design of consistent classifiers to forecast credit-granting choices is critical for many financial ... flaw by proposing the simultaneous application of support vector machine and probabilistic ...

However, using ... credit risk assessment. With accuracies ranging from 0.249 to 0.819, implementation and assessment of classic machine learning models was performed first, such as Logistic ...

The Santander US Auto business uses FICO® Platform to enhance the use of machine learning capabilities to support credit risk analysis ... efficient systems that reduce development time.