Nattawut Boonnoon's Workshop: Credit Risk Analysis and Fraud Detection with Dashboards.
End-to-end AI Fraud Detection & Transaction Monitoring project using SQL, Python, ML models, SHAP explainability, and FastAPI integration.
Coding assignments of the "Machine Learning in Finance & Insurance" course at ETH Zürich (Fall 2024).
The Credit Product Recommendation Engine
Simulação de concessão de crédito em uma instituição financeira. Analisa variáveis como renda, idade e histórico de inadimplência para entender padrões de aprovação e reprovação, gerando insights estratégicos para decisões baseadas em dados.
In diesem Projekt entwickle ich eine vereinfachte „Mini-Schufa“ mithilfe des Machine-Learning-Modells Random Forest. Ziel ist es, die Kreditwürdigkeit eines Nutzers anhand seiner Eingaben einzuschätzen
This project analyzes credit card customer & transaction data to uncover key business insights.
This project analyzes credit card transaction and customer data to uncover revenue trends, spending patterns, and customer demographics. Using SQL Server for data storage & transformation and Power BI for visualization, the dashboard delivers real-time insights into key performance metrics
📊 Analyze credit data to uncover insights that boost customer retention, revenue growth, and effective risk management for financial institutions.
Data preparation, predictive modeling and classification, conclusions and recommendations. Preparation and modeling preformed in Python. Work in progress.
A simple, interpretable credit approval model built on HMDA data using decision trees
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