To create better models for credit card default prediction among current clients, without needing to utilize any additional features other than the ones already available.
We used deep learning models to encode temporal features that classic approaches could not facilitate during optimization.
We created a more accurate representation of customers who would been using the product for more than 6 months (50% of users), and reduced the effort required for feature engineering.
Tech Tools & Skills Applied:
We used a variety of skills and tech stack tools including: TensorFlow, Python, Deep Learning, RNNs, Forecasting, and Credit Scoring.