An institutional-grade Expected Credit Loss modelling platform — PD calibration, LGD analysis, forward-looking macroeconomic overlays, and full audit-trail provisioning in a single enterprise SaaS.
The PD Engine constructs Probability of Default curves from historical migration data, applies logistic regression calibration, and projects Point-In-Time PDs under multiple macroeconomic scenarios using validated MEV relationships.
Compute and validate Loss Given Default across your full loan portfolio. The LGD module segments by secured vs. unsecured exposure, analyses collateral coverage, and produces stage-stratified LGD outputs ready for the ECL calculation engine.
Combine calibrated PD, LGD, and EAD inputs to compute Expected Credit Loss across Stage 1, 2, and 3 — with probability-weighted macroeconomic scenario overlays, management adjustment capability, and period-to-period movement reconciliation.
Built on peer-reviewed quantitative methodology — not black-box calculations. Every model output is fully traceable, explainable, and audit-ready.
Exhaustive C(n,k) variable combination search with ANOVA F-test filtering. Identifies the optimal macroeconomic variables — typically GDP, Unemployment, Exchange Rate, or sector-specific drivers — with full regression output for audit review.
Logistic regression maps TTC-PD to PIT-PD via macroeconomic factor. Full OLS output: coefficients, standard errors, t-statistics, p-values, and goodness-of-fit metrics for audit sign-off.
Year-over-year transition probabilities across rating grades built from your historical data. Cohort-level detail, vintage segmentation, and trend analysis — forming the foundation of the PD calibration engine.
The IFRS 9 ECL Suite is architected for the governance, security, and auditability requirements of banks, finance companies, and asset managers operating under regulatory scrutiny.
Every model run, data upload, and parameter change logged with timestamp, user ID, and IP address — tamper-proof.
Programmatic access for batch portfolio uploads, model runs, and result retrieval — integrates with core banking systems.
Granular permissions for modellers, reviewers, and approvers — with segregation of duties controls enforced at the platform level.
Full model documentation auto-generated: methodology narrative, assumption log, validation results, and sensitivity analysis.
Load your loan or receivables portfolio via template upload or REST API. The platform validates data integrity and flags missing attributes before processing begins.
Configure PD migration inputs, LGD parameters, MEV variable selections, and scenario probability weights. Execute the full PD → LGD → ECL chain with a single click — every step logged.
Generate provision journals, IFRS 7 disclosure notes, movement reconciliations, and sensitivity analyses — packaged audit-ready with complete model workings attached.
Designed for accountants and credit risk professionals — not quants. The platform guides users through the IFRS 9 methodology with clear inputs and explainable outputs.
Full statistical modelling pipeline — migration matrix, logit calibration, MEV regression. Every number is traceable to its source data, assumptions, and methodology documentation.
Complete methodology documentation, model validation reports, and sensitivity outputs are generated automatically — reducing ECL audit cycles and eliminating spreadsheet risk.
Request a personalised demo and let our team walk you through the platform using your own portfolio data.