The Fintech Lender needed a systematic approach to assess the creditworthiness of its loan applicants through a reliable and efficient credit scoring system.
Solution
An AI-powered solution was developed to analyze default patterns using correlation analysis, apply a unique technique to address data imbalances, and employ a gradient-boosted classification tree to continuously optimize predictions with each iteration.
Outcome
The deployed model simplified the risk assessment process for the lender and led to a reduction in payment defaults by over 20%.
A reliable and data-driven credit scoring Model for borrower assessment
The fintech lender needed a reliable way to assess the creditworthiness of borrowers. A credit scoring model was developed using data points such as form data, KYC IDs, demographic information, and app usage behavior. The solution analyzed default patterns using correlation analysis, applied the SMOTE technique for data balancing, and employed a gradient-boosted classification tree algorithm with hyperparameter tuning to optimize predictions.
The model simplified the lender's risk assessment process and reduced payment defaults by over 20%. As more data was processed, the model's accuracy improved, providing better credit scores and enabling more efficient decision-making. The solution allowed for faster, more reliable assessments while lowering the risk of defaults.
Smarter Scoring, Lowered Risk.
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Techvantage Analytics LLC.FZ, The Meydan Hotel,
Grandstand, 6th floor,
Meydan Road,
Nad Al Sheba, Dubai, U.A.E
We are passionate about building AI that is exceptional, cutting-edge, and transformative. We foster interdisciplinary synergy to drive breakthroughs that shape the future of AI.
Techvantage Analytics LLC.FZ, The Meydan Hotel,
Grandstand, 6th floor,
Meydan Road,
Nad Al Sheba, Dubai, U.A.E
We are passionate about building AI that is exceptional, cutting-edge, and transformative. We foster interdisciplinary synergy to drive breakthroughs that shape the future of AI.
