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

2019-03-25 · 64/93
ClassInterest computedInterest reportedPrincipal computedPrincipal reportedΔ
1-A131,069.3431,069.34233,059.20233,059.200.00
1-AX46,114.3446,114.31——0.03
2-A194,793.2194,793.211,169,966.311,169,966.310.00
2-AX92,725.4992,725.45——0.04
B-123,243.5823,243.5872,646.7872,646.780.01
B-215,495.7215,495.7248,431.1948,431.190.00
B-310,483.2110,483.2132,764.8032,764.800.00
B-47,747.867,747.8624,215.5924,215.590.01
B-512,690.2912,690.380.000.000.09

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.