Trade Confirmation Exception Identification — Dataset
AAL-D-001 is the dataset behind the trade-confirmation benchmark: 250 cases spanning equities, fixed income, listed futures, options, interest-rate swaps, FX forwards and NDFs, and credit. Each case carries a counterparty confirmation, an internal record, a constructed ground truth, and machine-readable scoring criteria with per-case numeric and exposure tolerances.
Coverage
Seven asset classes and sixteen exception categories — price, quantity, settlement date, standing settlement instructions, counterparty, currency, commission, duplicates, allocation, account, booking entity, and product, among others. 110 of the 250 cases are derivative products (IRS, FX forward/NDF, credit, options).
Scoring criteria
Every case specifies how it is graded: which dimensions count, the numeric tolerance for value matching, the exposure tolerance, and whether both exceptions must be identified. The deterministic scorer reads these criteria per-case rather than applying a single global rule.
Ground truth
Ground truth is constructed before evaluation and not adjusted afterward. The construction guide mandates an independent second reviewer, with a third reviewer adjudicating disagreements. Arithmetic in ground truth is independently verified.
Sample case preview
Case AAL-D-001-042 · Interest-Rate Swap · Dual Exception. This simplified, anonymized example shows the exception structure and deterministic scoring. Confirmed fixed rate: 1.245%; internal fixed rate: 1.250% (discrepancy 0.5 bps). Confirmed effective date: 2026-06-16; internal effective date: 2026-06-15 (discrepancy 1 day). Notional: 50,000,000 USD. Floating index: SOFR. Ground truth flags two exceptions: DIS-PRICE and DIS-SETTLE, with calculated exposure of 8,752.34 USD. Scoring criteria: both exception types must be identified; exposure must match within 100.00 USD; rate tolerance 0.1 bps; no false positives. A system fails if it misses one exception or invents a third (e.g., DIS-COUNTERPARTY).
How to cite
BibTeX: @dataset{aal_d_001_2026, title={AAL-D-001: Trade Confirmation Exception Identification Dataset}, author={{AI Alpha Labs}}, year={2026}, month={jun}, version={1.0}, publisher={AI Alpha Labs}, url={https://aialphalabs.ai/research/AAL-D-001}, note={250 cases across 7 asset classes with deterministic scoring criteria}}. APA style: AI Alpha Labs. (2026). AAL-D-001: Trade Confirmation Exception Identification Dataset (Version 1.0). Retrieved from https://aialphalabs.ai/research/AAL-D-001. MLA style: AI Alpha Labs. AAL-D-001: Trade Confirmation Exception Identification Dataset, version 1.0, June 2026, aialphalabs.ai/research/AAL-D-001.