Coreunda

The problem

Most risk tools give you a score. Not a reason.

A single blended ECL number is easy to report and impossible to defend. When a regulator asks why a segment's provisioning moved, or a declined customer asks why, "the model said so" is not an answer — and increasingly, it's not a legal one either.

Fair-lending obligations and the EU AI Act's explainability requirements are pushing credit decisioning toward the same standard good engineering already wants: show the work, not just the answer.

Reg B / ECOA, US

Adverse action notices require specific, accurate reasons — not a generic score.

EU AI Act, Art. 86

Credit scoring is named high-risk; affected individuals get a right to explanation.

IFRS 9 / CECL

Provisioning has to be auditable back to the scenario assumptions that produced it.

The approach

One calculation. One record. Every view drawn from it.

Coreunda never recomputes a number for a different audience. A single decision record — versioned, content-hashable, reproducible — feeds the internal dashboard, the regulatory report, and the explainability export alike.

01 — Portfolio & macro data

What you already have

Your loan-level portfolio, plus macro history from open sources — unemployment, GDP, inflation, and more where relevant. Governance decides which variables drive the model.

02 — Scenario engine

Five named futures, not one guess

A vector autoregression fit to your macro history, simulated forward by resampling real historical shocks — not an assumed bell curve. Worse, Bad, Base, Good, Better, each a full monthly path.

03 — Decision record

Every dollar traced to its scenario

PD × EAD × LGD, computed monthly, per contract, per scenario, then blended by governance-approved weights. The full breakdown is retained — not just the blended total.

Transparency in practice

Every contract's loss curve, in the open.

Pick any contract, any month, any scenario, and see exactly what fed the number — the same view your team, your auditor, and eventually your customer's notice would draw from. No separate "explainability layer" bolted on after the fact.

Worse Base Better

Illustrative — the real thing is one chart among the full monthly, per-scenario breakdown Coreunda produces for every contract.

Built for

Two verticals underserved by generic ECL software.

Both run on the same transparent engine — what differs is the loss mechanics each product actually needs.

In development — first

Unsecured lending & BNPL

Fixed-installment and revolving credit lines with no collateral. Loss given default modeled as a recovery-rate blend sensitive to the same macro scenarios driving PD.

SME & trade finance

Adds a collateral-based LGD waterfall — cure, restructure, repossession — plus trade-specific macro drivers like FX volatility and trade volume.

Where the line sits

Coreunda supplies the evidence. You supply the judgment.

Complete, reproducible decision records for every contract — factors, weights, and the exact reason codes behind a scenario shift.
Jurisdiction-aware export templates for adverse-action and explainability requirements.
No claim to being your compliance department: your legal and compliance teams make the final regulatory call, the same way they already do with bureau data today.

Why this split works

A transparent parametric model — not an approximated black-box explanation — means exact factor decomposition is possible in the first place. Coreunda's job is to make sure nothing is hidden. Your compliance team's job is deciding what a given regulator needs to see.

Coreunda is in active development.

The scenario engine and calculation core are built and tested. We're looking for a first design partner in unsecured lending or BNPL to build the rest around.

Request early access