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Improved Assessment of Credit Health Using Trended Credit Data

This 2020 report represents the third annual model performance assessment ofVantageScore 4.0 (which was launched in April 2017). The model is the first and only tri-bureau credit scoring model to incorporate for superior performance both trended credit data and leverage machine learning.

Trended data supplements the static borrowing and payment activity which has been historically recorded in consumer credit files and used to develop risk models. Trended data captures the trajectory of borrower behaviors overtime, thereby allowing additional insights into consumers’ credit risk profile.

As part of the annual assessment, VantageScore 4.0 performance results are compared to the performance results of credit scoring models that were developed earlier and contain only static credit attributes. VantageScore 4.0 also scores approximately 40 million consumers who cannot obtain credit scores when conventional scoring models are used. Machine learning techniques were utilized in the development of scorecards for this “Newly Scored” segment. During the annual assessment, performance of the model in this segment is compared with that of the earlier VantageScore 3.0 model.

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