sha256:ad5e65c90d06ca772a56e65a332990b9fdec2d8966a2eec552aece2dadf7d3a1
ML-02 · Capital & Quantitative Risk · Credit Risk · IRB Pre-Validation

Credit Default Risk Scorer

Logistic regression credit default probability (PD) scoring on a synthetic loan portfolio. Computes AUC, KS statistic, and Gini coefficient as model performance metrics; produces a PD distribution; compares IRB (F-IRB and A-IRB) versus Standardised Approach (SA) capital requirements. Chains from ART-05 (EU AI Act Credit-Scoring Conformity) — the conformity check validates the model governance before scoring. Feeds SIM-03 (Basel RWA Scenario Modeler) with PD/LGD inputs for IRB capital computation. All computation client-side — no loan data transmitted.

score_credit_default_risk credit_assessment Basel III F-IRB / A-IRB EU AI Act Art. 11 BCBS d424 EBA GL/2017/16
Educational / Pre-validation only. Synthetic loan portfolio generated client-side using a seeded PRNG — no real borrower data processed. Logistic regression weights are illustrative, not calibrated to any real loan book. IRB capital figures are for scenario analysis ahead of Basel 3.1 (UK PRA PS1/26 January 2027). Chains from ART-05 to confirm EU AI Act model-governance compliance before scoring.
Preset 1
Retail Mortgage
500 loans · LTV-heavy · 2.5% default rate
Preset 2
SME Lending
300 loans · sector mix · 6% default rate
Preset 3
Corporate Book
200 loans · large exposures · 1.5% default rate
Chain Intake — paste AP2 JSON from ART-05 (EU AI Act Credit-Scoring Conformity)

Ask your agent

Copy this paragraph into Claude, OpenClaw, or any MCP-aware agent to run this exact tool, with this sample, and verify the artifact.

Run the AINumbers MCP tool `score_credit_default_risk`. Task: Score credit default probability using logistic regression with Basel III risk-weight mapping.
Call it with arguments: {"policy_parameters":{"n_loans":10,"asset_class":"retail_mortgage","target_default_rate":0.05,"lgd":0.45,"maturity_yrs":2.5,"pd_threshold":0.5,"seed":11}}
Verify before trusting: this node computes in your browser, so the MCP endpoint returns no execution_hash. Run the tool in the page, export the Policy Mandate artifact it produces, and call `verify_execution_hash` on mcp.ainumbers.co (https://mcp.ainumbers.co/mcp) with that artifact.
Return the ledger link https://ledger.ainumbers.co/ so a human can re-verify without contacting us.
PII rule: All inputs are processed locally in your browser. No data is transmitted. Do not enter real personal data — use synthetic or anonymised inputs only.
Open the tool with the sample prefilled: https://ainumbers.co/chaingraph/ml-02-credit-default-risk-scorer.html#p=v1.H4sIAAAAAAAA_wGEAHv_eyJuX2xvYW5zIjoxMCwiYXNzZXRfY2xhc3MiOiJyZXRhaWxfbW9ydGdhZ2UiLCJ0YXJnZXRfZGVmYXVsdF9yYXRlIjowLjA1LCJsZ2QiOjAuNDUsIm1hdHVyaXR5X3lycyI6Mi41LCJwZF90aHJlc2hvbGQiOjAuNSwic2VlZCI6MTF9W96Xf4QAAAA