Traditional methods of credit scoring used by financial institutions in emerging economies suffer deteriorated precision over time, resulting from the inability to timely respond to changes in the economic environment. GAILABO proposed an AI-based credit scoring that can handle rapid economic changes and consistently provide highly accurate credit scores.
Certain criteria exist in loan screenings that individuals must meet to be approved.
At many financial institutions, a scoring model is created based on accumulated past data, and screening decisions are made based on these scores.
However, accurately analyzing data items that are relevant to credit among an enormous volume of data to create highly precise scoring models involves difficulties. The continued use of scoring models with poor accuracy lowers screening precision and increases bad debt risks.
GAILABO proposed AI-based credit scoring as a solution to such issues.
AI-based credit scoring is a scoring model that leverages AI to study the massive amounts of data held by financial institutions, accurately analyzes data items that may lead to bad debt losses, and precisely predicts which customers have a higher risk of default. In the interest of full utilization of the AI-based credit scoring by the client, GAILABO worked side by side with the client from proposal through to operational support.
We succeeded in improving operational efficiency and screening precision by implementing AI-based credit scoring. With the effective use of this product, the client has reduced bad debt losses. At the same time, we helped the client to expand its customer base by approving loans for applicants who would otherwise be declined by traditional screening methods.
