This Power BI dashboard provides an interactive analysis of the German Credit dataset, originally compiled by Prof. Hans Hofmann. The dataset includes 1,000 loan applicants with 20 attributes related to financial behavior, employment, personal details, and credit history.
The dashboard explores patterns between credit risk (good/bad classification) and key variables such as credit history, checking accounts, employment status, savings, loan purpose, and age. Visualizations highlight distributions, risk patterns, and correlations to support decision-making in credit scoring and financial risk assessment.
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