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

2018-05-25 · 54/93
ClassInterest computedInterest reportedPrincipal computedPrincipal reportedΔ
1-A137,364.5637,364.181,327,702.211,327,702.210.39
1-AX54,720.9754,720.35——0.62
2-A1108,939.92108,939.921,386,418.701,386,418.700.00
2-AX107,004.37107,004.31——0.06
B-125,131.3225,131.6397,915.6397,915.630.31
B-216,754.2116,754.4265,277.0965,277.090.21
B-311,334.6111,334.7444,161.4444,161.440.14
B-48,377.118,377.2132,638.5432,638.540.11
B-512,654.9112,655.200.000.000.29

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.