R-codebase for a scientific research article, titled "Approaches for modelling the term-structure of default risk under IFRS 9: A tutorial using discrete-time survival analysis"
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Updated
Feb 18, 2026 - R
R-codebase for a scientific research article, titled "Approaches for modelling the term-structure of default risk under IFRS 9: A tutorial using discrete-time survival analysis"
Bank-style Credit Risk Scorecard using Logistic Regression, IFRS-9 Expected Credit Loss, and an Interactive Streamlit Risk Dashboard for loan default prediction.
This model estimates the 12-month Probability of Default (PD) for prime residential mortgage customers in the United Kingdom, aligned with the IFRS 9 impairment framework and calibrated to an adverse macroeconomic scenario. Version 1 (v1) is developed using gradient-boosted decision trees (GBDT)
Streamlit app that computes per-loan Expected Loss, Lifetime ECL, and Risk Rating from EAD/PD/LGD/WAL Excel portfolios
End-to-End IFRS 9 PD Model development by Cohort Model.
End-to-End IFRS 9 LGD Model development by Advance Workout Model.
Anonymised Power Query (M) and SQL logic used for Completeness & Accuracy testing in G-SIB financial audits.
IFRS 9 SICR model Mortgages
Commercial expected loss and decision-support engine combining PD, LGD, and EAD into facility-level and portfolio-level outputs for portfolio risk and lending use cases.
End-to-end PD/LGD/EAD credit risk platform reflecting industry-standard model development workflows across Canadian financial institutions and credit unions. Built to OSFI E-23 / IFRS 9 standards.
End-to-end credit risk and fraud risk modeling: PD, LGD, scorecards, IFRS 9 ECL, transaction fraud, and fraud ring detection.
Autonomous AI agent for IFRS 9 credit risk analysis using Google Gemini and BigQuery
International Intelligent Accounting Assistant
Automated IFRS 9 ECL calculation system with Python, BigQuery, and SQL analytics
End-to-end IFRS 9 Expected Credit Loss model on 1.18M LendingClub loans — PD/LGD/EAD, staging, forward-looking macro overlay, self-verifying dossier.
End-to-end credit risk pipeline for PD, LGD, EAD, expected loss, IFRS 9-style staging, and stress testing on LendingClub loan data.
End-to-end risk analytics platform for retail banking: PD model, IFRS 9 ECL staging, fraud detection (rules + ML), and customer analytics. Built with Python and scikit-learn.
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