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Massachusetts Loan Default Risk

Project Type

EDA

Date

September 2025

Description

Click the images to see the insights

Keywords

EDA, Python, Financial Analytics

Financial institutions often struggle to assess borrowers with limited credit history and local economic context is rarely factored into lending decisions. This project analyzes LendingClub's 2019 loan dataset to uncover the drivers of credit default at a micro-market level, connecting individual borrower attributes (FICO score, income, loan grade, term length) with Massachusetts economic conditions. Starting with national trends and narrowing to a Massachusetts-focused lens, the analysis reveals that loan grade, term length, and income level are strongly predictive of default risk, while MA's portfolio skews toward higher-grade, lower-risk borrowers relative to the national average. Findings offer lenders a framework for more precise risk pricing while expanding responsible credit access.

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