Mortgage processing. 240 applications annually. Manual qualification consuming 180 hours. Built n8n workflow. Zero manual calculations. Systematic validation. THE MORTGAGE PROBLEM: Every application manual. Loan officer reading documents. Calculating housing payments. Computing DTI ratios. Checking credit. Verifying employment. 45 minutes per application. 240 annually = 180 hours. Audit revealed errors - 34 incorrect DTI calculations. 67 missing credit verifications. 89 inconsistent qualification decisions. 14.2% error rate. Manual process breaking down. Same borrower calculated differently by same loan officer week to week. Different officers applying different standards. No systematic criteria application. THE n8n AUTOMATION: 6-node workflow with 5-path credit routing: Node 1 - Gmail Trigger: Monitors applications Node 2 - Get Email: Downloads with attachment Node 3 - Prepare Binary: Formats document Node 4 - Extract Data: Pulls borrower/income/assets/liabilities/property/loan Node 5 - Calculate & Validate: Computes DTI/LTV/reserves, validates criteria Node 6 - Log Database: Updates tracking Node 7 - Credit Router: Routes by tier (Excellent/Good/Fair/Poor/None) EXTRACTION: Borrower - name, email, employment, income Assets - checking, savings, retirement, investments Liabilities - debts with monthly payments Property - address, type, purchase price Loan - amount, down payment, term, rate CALCULATIONS: ```javascript // Housing payment const payment = (loan * rate) / (1 - Math.pow(1 + rate, -months)); const tax = (price * 0.012) / 12; const insurance = (price * 0.006) / 12; const housing = payment + tax + insurance; // DTI ratios const frontDTI = (housing / income) * 100; const backDTI = ((housing + debt) / income) * 100; // Other metrics const ltv = (loan / value) * 100; const reserves = assets / housing; ``` VALIDATION CRITERIA: Back-end DTI > 43% = Needs Review Front-end DTI > 28% = Conditional Credit < 620 = Needs Review Employment < 2 years = Conditional

Not every AI initiative should continue.Knowing when to stop is part of good consulting. You should pause or stop an AI transformation when: - Decision ownership keeps shifting - Success metrics change every review - AI is used to avoid fixing core process issues - Leadership asks for speed but resists accountability Continuing in these conditions doesn’t reduce risk. It multiplies it. Stopping is not failure. It is preventing the organization from scaling confusion. An AI Transformation Partner is judged not by how many projects they launch,but by how many bad ones they prevent.