Bank-style Credit Risk Scorecard using Logistic Regression, IFRS-9 Expected Credit Loss, and an Interactive Streamlit Risk Dashboard for loan default prediction.

Projeto da API do primeiro semestre de 2026

A Python library providing elegant, type-safe primitives for building the kinds credit models that typically force teams to reach for Excel.

Production-ready FastAPI service that converts Credit Reports (PDF format) into structured JSON data using CreditGraph AI patterns with automatic PII scrubbing for data privacy.

A dirty-work toolbox for data analyses about fixed income securities, developed by only me (not the institute) as an intern data analyst.

Coding assignments of the "Machine Learning in Finance & Insurance" course at ETH Zürich (Fall 2024).

Predict financial risk using behavioral and demographic data from the 2021 FinAccess Household Survey (KNBS). Built with Streamlit and XGBoost.

End-to-end AI Fraud Detection & Transaction Monitoring project using SQL, Python, ML models, SHAP explainability, and FastAPI integration.

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.

A predictive credit scoring system using alternative behavioral and demographic data from the 2021 FinAccess Survey to assess household loan default risk in Kenya.

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

Data preparation, predictive modeling and classification, conclusions and recommendations. Preparation and modeling preformed in Python. Work in progress.

This project potray's my capstone work. My work involved cleaning, manipulation and analyzing huge data sets and implementing ML models for predictive analysis. This analysis demonstrates that data-driven credit interventions can meaningfully reduce financial exposure while balancing customer retention.

A credit card expense tracker with NLP-powered quick entry, billing cycle intelligence, EMI tracking, and rich analytics. Built with Next.js, TypeScript, Tailwind CSS, and SQLite.

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

Implementa uma operação de crédito integralmente paga em dia, com sistema Price, sem inadimplência, sem renegociação e sem PDD.

Plim AI First

Unlimited credit works

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