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

2015-05-26 · 18/93
ClassInterest computedInterest reportedPrincipal computedPrincipal reportedΔ
1-A198,213.6098,213.601,482,516.131,482,516.130.00
1-AX142,064.55142,064.65——0.10
2-A1209,637.75209,637.751,788,678.101,788,678.100.01
2-AX209,703.07209,703.20——0.13
B-128,685.5528,685.5627,808.0027,808.000.01
B-219,123.7019,123.7118,538.6718,538.670.01
B-312,937.6212,937.6212,541.8312,541.830.00
B-49,561.859,561.859,269.339,269.330.01
B-512,692.5212,692.520.000.010.01

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.