OpenChainGraph Suite · ART-426 · Banking · ASC 326 (CECL)

CECL Expected Credit Loss & Allowance Calculator

Computes a deterministic CECL (Current Expected Credit Loss, ASC 326) allowance from your declared PD/LGD/EAD curves, segment exposures, and forecast scenario weights — WARM, DCF, and loss-rate methods — and reconciles the result against the prior period's allowance balance.

ASC 326 WARM / DCF / Loss-Rate Allowance Reconciliation
🔒 All inputs are processed locally in your browser. No data is transmitted. Do not enter real personal data — use synthetic or anonymised inputs only.
⚠ BOUNDARY: PD/LGD/EAD curves and forecast scenario weights are YOUR policy inputs (human/model judgment) — this tool performs only the arithmetic combination into ECL and allowance reconciliation. It does not estimate, calibrate, back-test, or validate any PD/LGD/EAD model.
Distinct from IFRS9's 3-stage staging regime (see tools 196/198/204, a different accounting standard) — CECL recognizes lifetime expected credit losses from origination, with no staging transfer logic here.
Method & Rollforward Inputs

WARM/loss-rate scenarios use annual_loss_rate_pct (WARM, multiplied by remaining_life_years) or lifetime_loss_rate_pct (loss-rate, applied directly). DCF segments add lgd_pct + effective_interest_rate_pct, and each scenario supplies pd_curve (array of period PDs) + cash_flows (array of {period, contractual_payment_usd}); expected shortfall per period = contractual payment x PD x LGD, discounted at the EIR.

Per-Segment ECL
Allowance Rollforward Reconciliation
Execution Hash (SHA-256)

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 `calculate_cecl_ecl_allowance`. Task: Compute a deterministic CECL (Current Expected Credit Loss, ASC 326) allowance given caller-supplied PD/LGD/EAD curves, segment exposures, and forecast scenario weights, and reconciles the result against the prior period's allowance balance.
Synthetic sample input (policy_parameters): {"method":"warm","constants_version":"2026-07-23.cecl-warm-v1","prior_allowance_balance_usd":500000,"charge_offs_usd":20000,"recoveries_usd":5000,"forecast_weights":[{"scenario":"baseline","weight":0.6},{"scenario":"downside","weight":0.4}],"segments":[{"segment_id":"retail-auto","exposure_balance_usd":10000000,"remaining_life_years":3,"scenarios":[{"scenario":"baseline","annual_loss_rate_pct":0.012},{"scenario":"downside","annual_loss_rate_pct":0.025}]},{"segment_id":"retail-card","exposure_balance_usd":5000000,"remaining_life_years":2,"scenarios":[{"scenario":"baseline","annual_loss_rate_pct":0.03},{"scenario":"downside","annual_loss_rate_pct":0.06}]}]}
Verify before trusting: call `verify_execution_hash` on mcp.ainumbers.co (https://mcp.ainumbers.co/mcp) with the returned execution_hash.
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/art-426-cecl-ecl-calculator.html#p=v1.H4sIAAAAAAAA_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