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

2019-09-25 · 70/93
ClassInterest computedInterest reportedPrincipal computedPrincipal reportedΔ
1-A128,764.8228,764.821,615,514.151,615,514.150.01
1-AX42,788.4842,788.51——0.03
2-A188,963.9088,963.90147,058.01147,058.010.00
2-AX86,735.1586,735.15——0.00
B-122,165.7322,165.74101,725.80101,725.800.01
B-214,777.1614,777.1667,817.2067,817.200.01
B-39,997.089,997.0845,879.8845,879.880.00
B-47,388.587,388.5833,908.6033,908.600.00
B-512,684.2712,684.220.000.000.05

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.