Data Engineering & Scorecard Development
for a Fintech Client
Requirement
1) Business & Operational MIS Automation
2) Risk & Marketing Scorecard Development
Solution Delivered
- Analytical Ready Data Mart for Credit Risk and Marketing Campaigns
- Borrower Single View to get a 360-degree view of borrowers
- Dashboards to track business growth
- Automated Scheduled Reports in MS Excel format emailed to Operational Users
- Focused Target Lists for Marketing Campaigns
- Credit & Collection Scorecard for Risk Management
- Bureau Reports Automation & Adhoc Analysis
Solution Framework
- Airflow was used to orchestrate the reporting workflow and scheduling purpose
- Data Engineering (ETL) code were all written in Python
- Power BI Dashboards were built for portfolio growth insights and analysis
- MySQL Database was used for data storage, data mart, and ARDM
- Credit Risk scorecards for automated decisioning were built using the Logistic Regression technique
- Collection Scorecard and Marketing Scorecards were developed using the XGBoost algorithm
- Customer Segmentation analysis was done using the K Means algorithm
Tech Stack
Airflow
Python
Power BI
PostgrSQL
PyTest
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