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Credit Scoring in Digital Age: Benchmarking Telecom, Card Transactions and Credit History Data

Field of Science:Computer ScienceInformation SystemsEconomics and Econometrics
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ARTICLE ANNOTATION

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In this study, we compare the predictive power of models based on credit history, card transactions, and telecom data. We train machine learning models on online microloan data and benchmark their performance against models proposed by telecom operators. Our results indicate that the model based solely on credit history data outperforms those based on card transaction and telecom data. Based on this evidence, we recommend prioritizing credit history data when developing credit scoring models.

AUTHORS

I.Masuda

"Asakabank" aksiyadorlik jamiyati

Tags

# card history# credit history# scoring models# hyperparameter optimization# imbalanced data

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