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

2021-06-25 · 91/93
ClassInterest computedInterest reportedPrincipal computedPrincipal reportedΔ
1-A113,895.0213,895.02343,369.02343,369.020.01
1-AX19,388.1819,388.20——0.02
2-A127,798.3227,798.321,014,558.721,014,558.720.01
2-AX27,432.8927,432.87——0.02
B-19,732.769,732.76170,589.74170,589.740.01
B-26,488.506,488.50113,726.49113,726.490.01
B-34,389.624,389.6276,938.5676,938.560.00
B-43,244.253,244.2556,863.2556,863.250.01
B-512,513.6012,513.590.000.000.01

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.