Live Demo

Document-Level Fraud Detection in Equipment Finance Applications

A fabricated vendor invoice looks exactly like a real one in a PDF viewer. So does an altered bank statement or a tax return with a re-typed net income line. No credit team catches that by eye at 40 applications a day.
In 30 minutes, watch a real broker-submitted equipment finance application get classified, extracted with source attached, and checked for metadata, font, layout, and cross-document inconsistencies, before a human opens the file.
Corey Ashline
Senior Account Executive
James Hallacy
Head - Solution Engineering
September 17th, 2026
12 PM CT
Location
Virtual Webinar

Fraud Controls, Inline at Intake

Intake

Every application arrives as a package, not a document. Watch the Intake Agent assemble a broker or vendor submission end to end — requesting what's missing, chasing it without a human, and organising the file so screening runs on a complete package instead of a partial one.
Requests, follows up, and organises documents automatically — no borrower or vendor chasing
Only asks for what's actually missing, using integrations and prior submissions
Built for equipment finance intake: vendor quotes and invoices, business tax returns, AR/AP aging, business credit reports, UCC filings, secretary of state records, Safer records
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Classification & Extraction

Fraud screening is only as good as the data underneath it. Watch 150+ financial document types classified with ranked alternatives and confidence, then extracted field by field — every value traceable back to the exact spot on the page it came from.
150+ production document types, each with its own schema, pipeline, and review screen
Signal confidence on every field: auto-accept, review, or human reviewClick any value and see exactly where it came from — bounding-box traceability across the file
Equipment-specific fields captured: equipment description, serial/VIN, equipment price, secured party and filing number, beneficiary bank and routing/ABA
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Verification & Fraud Controls

Document integrity checks run inline, not as a separate system your team has to remember to open. This is the part generic extraction tools skip — and the difference between structured data and data you can lend against.
Metadata inspection — creation and modification history, editing software traces, and timestamps that don't line up
Font and layout anomalies — mismatched fonts, misaligned values, and text sitting on top of the original
Cross-document consistency — the same figure on the bank statement, the tax return, and the application should agree
Flagged with evidence — suspected tampering routes to human review with the specific signals attached, never a silent pass
Configurable thresholds and escalation rules, set to your institution's risk appetiteEvery flag logged with rationale, examiner-ready
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What You'll See in 30 Minutes

A real equipment finance application parsed live on anonymised documents — vendor invoice, bank statements, business tax return, credit report
A tampered pay stub and an altered bank statement screened side by side against clean versions, with the signals that separated them shown on screen
Cross-document validation catching a net income figure that doesn't reconcile between the tax return and the statements
A flagged document routed into the human review queue with evidence attached — and a clean application moving straight through to a credit-ready file
Live Q&A on how fraud thresholds, escalation rules, and audit logging get configured to your credit policy

Built For

Equipment finance credit teams
Vendor and broker channel leaders
Risk & fraud operations
Chief Credit Officers
Chief Risk Officers
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Lending operations leaders
Independent lessors, bank-owned lessors & captives

Meet Your Speakers

Moderator
Corey Ashline
Senior Account Executive
Linked
Presenter
James Hallacy
Head - Solution Engineering
Linked
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