Credit Scoring for Micro-Loans

Dubina, Nikolay, Kang, Dasom, Suh, Alex

arXiv.org Machine Learning 

Credit Scores are ubiquitous and instrumental for loan providers and regulators. In this paper we showcase how micro-loan credit system can be developed in real setting. We show what challenges arise and discuss solutions. Particularly, we are concerned about model interpretability and data quality. In the final section, we introduce semi-supervised algorithm that aids model development and evaluate its performance.

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