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

2020-11-25 · 84/93
ClassInterest computedInterest reportedPrincipal computedPrincipal reportedΔ
1-A116,726.3416,726.341,182,488.921,182,488.920.01
1-AX23,784.8523,784.88——0.03
2-A151,087.2951,087.292,154,984.262,154,984.260.01
2-AX49,841.1449,841.14——0.00
B-115,011.6815,011.68268,213.96268,213.960.00
B-210,007.7910,007.79178,809.31178,809.310.01
B-36,770.506,770.50120,968.57120,968.570.01
B-45,003.895,003.8989,404.6589,404.650.01
B-512,723.6012,723.560.000.000.04

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.