AI Playbook for Mortgage Fraud — Straw Buyer Network

A mortgage lender's quality control team has identified 12 residential loans closed in 4 months where the appraised values are 22–38% above comparable sales, the buyers have no prior real estate ownership, and 9 of the 12 used the same real estate attorney.

When to use this playbook

• Use this playbook when the decision looks like the situation above: A mortgage lender's quality control team has identified 12 residential loans closed in 4 months where the appraised values are 22–38% above comparable sales, the buyers have no prior real estate ownership, and 9 of the 12 used the same real estate attorney.
• It is a fit when you have source files in hand and need a structured, reviewable analysis — not a generic chat answer about "Mortgage Fraud — Straw Buyer Network".
• Do not use it as a substitute for licensed, legal, clinical, or authorized official judgment in the domain.

What you'll need

• 12 loan files (application, appraisal, title, closing docs)
• Comparable sales data from MLS for each property address
• Borrower credit and employment verification records
• Title chain for each property (prior 5 years)
• Real estate attorney's transaction history with this lender

Attachments: Documents (Documents)

You are a mortgage fraud investigator reviewing a suspected straw buyer ring. I am attaching:

Work only from the attached source files. If a conclusion is not supported, say so.

Produce:
1. Calculate the appraisal variance for each property: appraised value vs. median comparable sale, and flag any appraiser who appears in more than one file.
2. Identify whether any seller in the 12 transactions has a prior ownership connection to the buyer (nominee/straw buyer indicator).
3. Map the real estate attorney's total transaction volume with this lender and assess whether the concentration is anomalous.
4. Determine whether the down payments were sourced from the seller (a flip fraud indicator) by tracing fund flows in the closing statements.
5. Tell me which loans should be referred to HUD-OIG, what the lender's potential SAR obligation is, and whether early payment default clauses apply.

Call out where independent models are likely to disagree, and list follow-up documents a reviewer should request.

What to expect

• Appraisal variance report with appraiser flags
• Seller-buyer relationship map
• Attorney concentration analysis
• Down payment source tracing
• HUD-OIG referral and SAR checklist

Review before you act

• Validate this output against source files before relying on it: Calculate the appraisal variance for each property: appraised value vs. median comparable sale, and flag any appraiser who appears in more than one file.
• Validate this output against source files before relying on it: Identify whether any seller in the 12 transactions has a prior ownership connection to the buyer (nominee/straw buyer indicator).
• Validate this output against source files before relying on it: Map the real estate attorney's total transaction volume with this lender and assess whether the concentration is anomalous.
• Validate this output against source files before relying on it: Determine whether the down payments were sourced from the seller (a flip fraud indicator) by tracing fund flows in the closing statements.
• Confirm every cited figure, date, counterparty, or requirement against the attached originals — models compress and can drop a qualifier.
• Treat disagreement between models as a review item, especially on classification, materiality, and recommended next action.
• Do not authorize an operational, clinical, legal, credit, or enforcement action solely because the models agree.