Case Study 2: Finance Technology


The Challenge:

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.

The Solution:

We used deep learning models to encode temporal features that classic approaches could not facilitate during optimization. 

The Outcome:

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.