PADGEA · MOAT A — FRAUD INTELLIGENCE

Fraud prevention — two layers, then a network

93.3% of multifamily operators reported fraud in the last twelve months, and 84.3% specifically saw falsified pay stubs (NMHC 2024 Pulse Survey). Pick an applicant below to see how Padgea screens one.

Genuine applicant

Everything reconciles. Should pass cleanly.

Altered pay stub

Real stub, edited income. The common case.

Fabricated identity

Generated documents, thin history.

Known to the network

Caught at another operator last month.

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Layer 1 — nine-signal rules engine

Layer 2 — GPT-4o document forensics

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Layer 3 — the cross-tenant network

SHA-256

one-way hash only

Verdict

returned, never raw data

Consent

checked on every call

raw records shared

How it stays legal under multi-tenancy. Operator A's raw applicant data never reaches Operator B. We store a one-way hash of the identifying signal, so a member can check a value they already hold but can never enumerate anyone else's applicants. The lookup returns a verdict — never who reported it.

What one prevented fraud is worth

Portfolio	Applications / yr	Est. fraudulent (1 in 8)	Avoidable exposure

Sources: NMHC 2024 Pulse Survey — 93.3% of operators experienced fraud; 84.3% saw falsified pay stubs; large operators write off an average of $4.2M in bad debt annually, roughly 24.5% of it fraud-attributable; 23.8% of eviction filings trace to fraudulent applications. Snappt's published analysis puts altered documents at roughly 1 in 8 applications and the average eviction at $7,685.

Padgea Inc. · Fraud intelligence demonstration. The rules engine and document forensics are live in production. The cross-tenant network layer is built and consent-gated; it populates as operators join. Credit bureau integration is built to the seam and pending API credentials.