How laurien03/corporate-credit-risk-assessment-engine works
This desktop credit-risk application collects corporate financial indicators, validates them, then trains a Logistic Regression model on the bankruptcy dataset and assesses the submitted applicant. Its runtime orchestrator also screens and evaluates the training data, classifies bankruptcy probability, generates a lending recommendation, and saves a report. The README documents these capabilities; the graph’s implementation links are based on the shown excerpts, so it omits unverified UI details beyond those excerpts.
Main entry points: main.py Assessment Orchestrator · app.py Questionnaire UI · risk_assessor.py Risk Assessor · report_generator.py Report Generator
Components 9
Desktop Interface
- Questionnaire UI
app.py
Data Preparation
- Bankruptcy Dataset
bankruptcy_dataset.csv - Dataset Loader
data_loader.py - Dataset Screener
data_loader.py
Modeling
- Logistic Regression
model_trainer.py
Risk Decision
- Assessment Orchestrator
main.py - Risk Assessor
risk_assessor.py - Report Generator
report_generator.py
Other components
- Loan Applicant
Connections 12
- Loan Applicant → Questionnaire UI: enters finances
README.md - Questionnaire UI → Dataset Loader: loads feature names
app.py - Bankruptcy Dataset → Dataset Loader: reads dataset
data_loader.py - Questionnaire UI → Assessment Orchestrator: submits validated inputs
app.py - Assessment Orchestrator → Dataset Loader: loads and splits data
main.py - Assessment Orchestrator → Dataset Screener: screens dataset
main.py - Assessment Orchestrator → Logistic Regression: trains and evaluates
main.py - Assessment Orchestrator → Risk Assessor: assesses applicant
main.py - Assessment Orchestrator → Report Generator: generates report
main.py - Assessment Orchestrator → Risk Assessor: passes trained model
main.py - Risk Assessor → Report Generator: passes risk results
main.py - Report Generator → Loan Applicant: exports assessment
README.md