Project from TATA job simulation program from Forage "Exploratory Data Analysis (EDA) and risk factor identification for Geldium's credit delinquency prediction model."

This repository contains my submission for Task 2 of the Tata Data Analytics Virtual Internship 2025, focused on predictive modeling using the Geldium dataset. This task builds on insights from Task 1 (EDA) and applies GenAI-powered methods to design a responsible and explainable credit risk model.

This report provides an exploratory data analysis (EDA) of Geldium’s dataset to assess data quality, identify key insights, and highlight factors that influence credit delinquency risk. The goal of this analysis is to ensure data readiness for predictive modeling and risk assessment.

Exploratory Data Analysis (EDA) and logistic regression modeling to predict customer delinquency risk using financial and behavioral data from Geldium. This project focuses on identifying early risk indicators like credit utilization, missed payments, and debt-to-income ratio to support predictive modeling and financial decision-making.