── ── Industry
Mortgage — Loan Program Matching
The parent decision-tree maps branching choices to outcomes. Program selection is a decision tree over borrower attributes (credit, DTI, LTV, down payment, property type, VA eligibility) → eligible programs → net cost/fit.
Run Mortgage — Loan Program Matching on a real problem
Bring something you're actually deciding — free, in the browser.
How it works
Branch on gating attributes and roll back to best fit: - Credit + DTI + LTV + reserves → which agencies qualify. - Down payment / MI: FHA (MIP) vs Conventional (PMI removable) vs VA (0% + funding fee). - Property/occupancy and loan size (conforming vs jumbo). - Compare total cost + approval probability, not just rate.
When to use it
- matching a borrower to Conventional/FHA/VA/USDA/Jumbo/Non-QM
- deciding fixed vs ARM
- 'which program fits this borrower?'
- borderline DTI/LTV/credit
When not to use it
borrower is pre-committed to one specific product with no alternative.
Worked example
Mortgage — Loan Program Matching
The parent decision-tree maps branching choices to outcomes. Program selection is a decision tree over borrower attributes (credit, DTI, LTV, down payment, property type, VA eligibility) → eligible programs → net cost/fit.
Install this skill (free, MIT)
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Related mental models
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The parent checklist converts "are we covered?" into a verifiable gate.
The parent loss-aversion-prospect-theory shows losses loom ~2× gains and that framing drives choices.