Waterfall Forensics.

Waterfall Forensics

We ran the contract forward for eight years. It matched to the penny.

Sequoia Mortgage Trust 2013-1: deconstructed from its prospectus into an executable encoding, then replayed against every monthly distribution the trustee ever reported — 93 periods, February 2013 through final termination.

$363M

of actual distributions reproduced

99.7%

of 2,139 comparisons within $1

$0.08

worst principal delta, ever

Every period, every class — computed from the contract vs. reported by the trustee

2014-05-27 · 6/93
ClassInterest computedInterest reportedPrincipal computedPrincipal reportedΔ
1-A1124,735.67124,735.67462,158.26462,158.260.01
1-AX184,473.82184,473.88——0.06
2-A1268,929.07268,929.07350,943.81350,943.810.01
2-AX271,347.12271,347.13——0.01
B-129,892.1229,892.1226,329.3126,329.310.00
B-219,928.0819,928.0817,552.8717,552.870.00
B-313,481.8013,481.8011,874.9211,874.920.00
B-49,964.049,964.048,776.448,776.440.00
B-512,789.3212,789.250.000.000.07

drag through 93 distribution dates — Δ is the summed absolute difference between the contract-computed and trustee-reported figures for the period

Or see all 93 periods at once: the tie-out heatmap ›

How

The governing documents are deconstructed into a provenance-linked encoding — every waterfall step, trigger, and floor provision cites the clause that defines it. A deterministic interpreter executes that encoding, period by period, against the collateral cashflows the trustee reported. State rolls forward on computed values only; an error anywhere would compound and surface. It doesn't.

The same engine then runs Monte Carlo counterfactuals — what should have happened under different prepayment, default, or servicing behavior — and exports the whole model as readable Python your own analysts run and defend. Every encoding is open to clause-by-clause verification, and every verification lands in an append-only ledger.