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Credit RiskLoan DefaultFeature EngineeringMulti-table

Credit Risk Analysis

Loan Default Analysis — Home Credit Dataset

End-to-end data analytics project on the Home Credit loan dataset. 11-notebook pipeline covering multi-table data cleaning across 8 source files, feature engineering (DTI, credit utilization, payment on-time rate), master dataset construction, EDA, and SQL-based KPI queries — producing a Power BI-ready final dataset.

Type
Analytics / BI
Category
Analytics & BI
Year
2025
Stack
Python · SQL
Credit Risk Analysis
At a Glance
8
Source tables merged
11
Notebooks
5
Engineered features
100K+
Loan records
What's Built

Key features & capabilities.

01

8-table merge: application, bureau, bureau_balance, previous_application, installments, credit_card, POS_CASH

02

Debt-to-Income ratio, credit utilization, on-time payment rate, bureau avg days overdue

03

Previous application approval rate as a predictive feature

04

11-notebook sequential pipeline with clean data outputs at each stage

05

DuckDB for fast in-process SQL queries on the merged master dataset

06

Power BI-ready final export with all engineered features

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