The first completed preregistered validation applied the Time Engine to historical FDIC banking data — with no banking equations, no banking training, and no domain tuning. It measures the temporal condition that precedes and shapes outcomes, and here those measurements carried meaningful forward-looking signal concerning later failures.
Evaluated on FDIC Call Report data — raw filings spanning 1999Q1–2012Q4, with a 2000Q1–2012Q4 evaluation window — across a full credit cycle, the 2007–2009 crisis, and the resolution period that followed.
The result is credible because of what happened before any score was computed. The validation protocol, the engine, the domain mapping, and the pass/fail criteria were all fixed and cryptographically hashed in advance. The engine had no access to the raw financial variables — only an abstract, pre-specified canonical representation. Nothing was adjusted after scoring began.
The engine and its logic were fixed and hashed before the banking data was ever scored.
The engine saw canonical temporal state — not banks, not balance sheets, not what any variable meant.
Success, non-inferiority, and kill criteria were defined before results existed.
The engine cleared its discrimination threshold decisively (AUROC 0.891, well above the 0.75 bar; no kill criterion triggered). It did not meet preregistered non-inferiority against a purpose-built banking model (CAMELS logistic, AUROC 0.964, ΔAUROC −0.073). Under the protocol, that records the outcome as Partial — and that honesty is the point: a domain-specific model tuned for banks still edges out a general engine that knew nothing about banking. That the general engine came this close, cold, is the signal.
This is the first completed formal validation of the Time Engine. It documents the platform's universal capability empirically in one domain; it does not define the platform's scope. Additional cross-domain validations are underway.
Two counts are easy to confuse: 574 is the number of failed institutions; 737 is the number of failure-labeled bank-quarters in the scored set. A failing bank contributes several failure-labeled quarters within the one-year horizon, so the two counts differ by design.