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

data_engg
  • 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 icon

Airflow

Python

Python

PowerBI

Power BI

postgresql

PostgrSQL

pytest

PyTest

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