A machine learning and NLP‑based credit scoring system was developed to help an African SMB that provides small loans to underbanked populations streamline real‑time loan approvals. The client needed a more reliable and flexible alternative to traditional credit bureau data to reduce default risk and processing delays. The solution introduced a unified data source combined with machine learning models and natural language processing to automate credit score generation. By analyzing structured and unstructured data, the system enabled faster, data‑driven lending decisions with minimal manual intervention, improving approval efficiency while maintaining low default rates for both the SMB and partnering financial institutions.

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