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

2017-04-25 · 41/93
ClassInterest computedInterest reportedPrincipal computedPrincipal reportedΔ
1-A154,109.1854,109.18249,890.59249,890.590.01
1-AX79,062.6579,062.72——0.07
2-A1127,558.62127,558.62230,029.39230,029.390.00
2-AX126,007.70126,007.67——0.03
B-126,603.5026,603.5031,264.1631,264.160.00
B-217,735.6617,735.6720,842.7720,842.770.01
B-311,998.5811,998.5814,100.6114,100.610.00
B-48,867.838,867.8310,421.3910,421.390.01
B-512,679.0012,678.990.000.000.01

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.