scikit-learn compatible tools for building credit risk acceptance models
machine-learning scikit-learn logistic-regression scorecard credit-risk creditrisk scorecard-model scorecards
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- Python
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creditrisk
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This project mainly implements the Monotonic Optimal Binning(MOB) algorithm in SAS 9.4. We extend the application of this algorithm which can be applied to numerical and categorical data. In order to avoid the problem of creating too many bins, we optimize the p-value iteratively and provide bins size first binning, monotonicity first binning, a…
sas monotone mob credit risk-management creditrisk data-discretization creditrisk-analysis monotonic-optimal-binning
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- SAS
A Collection of Python Functions for Vasicek Distribution
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- Python
Projeto Hackathon 2025: Implementação de Data Lakehouse no Databricks Free para criação de book de variáveis e modelos de previsão de inadimplência.
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A Collection of R Functions for Vasicek Distribution
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- R
Credit card credit dataset analyzed using multiple machine learning models to determine which model best fits the data, reduces bias and predicts credit risk. Undersampling and oversampling done using various python libraries (imbalanced-learn and scikit-learn).
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In this project, we wanna create Credit Risk Management by using Machine Learning, so we dig into the data. what we do for the next steps are Data Preparation, EDA(Exploratory Data Analysis), Data Visualization, Data Preprocessing (Handling Outliers, Missing Value, Feature Encoding, Standardization, and Normalization), Creating Machine Learning …
machine-learning risk-analysis machine-learning-algorithms regression logistic-regression regression-models decision-tree credit risk-management creditrisk creditrisk-analysis decission-tree-classifier
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My practice notebooks from tasks on Kaggle
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Credit risk EDA + logistic regression (class imbalance handling)
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Credit card customer segmentation, churn prediction, and revenue analytics with Power BI dashboard
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- Python
Credit risk analysis with different econometric and statistic tools.
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- Jupyter Notebook
Lendora is an intelligent credit scoring platform that combines machine learning, behavioral analysis, OCR, and generative AI to assess an individual's creditworthiness. It is designed for lenders, fintechs, and microfinance institutions to streamline credit evaluation and minimize risk in real time.
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Submitted Solution to Kaggle's Home Credit Competition
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Dissecting Argentina’s sovereign risk, default probabilities, and the sovereign–bank doom loop.
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Full toolkit for credit risk monitoring/validation
irb validation pd credit monitoring-tool credit-risk creditrisk credit-risk-modelling irb-compliance irb-calibration-testing pd-testing
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- Python
This repo has an IBM's Narrative of MLOps. It uses all the services in IBM's Cloud Pak for Data stack to actualise what an MLOps flow looks like.
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- Jupyter Notebook
End-to-end credit risk analysis project using SQL, covering customer risk segmentation, credit exposure evaluation, repayment behavior analysis, and default rate insights.
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