Maple AI Consultants

AI consulting case studies by Joel & Nanz Inc.

Financial Services • 14 Loan Officers

Case Study 22: Mortgage Brokerage

Marketing-optimized case study for Canadian SMBs.

$93,000
Annual Savings
455%
ROI
2.8 months
Payback
Financial Services • 14 Loan Officers
Industry Focus

Executive Summary

Document Collection: AI chatbot guides applicants through document requirements with visual examples. OCR extracts data from pay stubs, tax returns, bank statements. Validates completeness before loan officer review.

Challenge

Solution

  • Document Collection: AI chatbot guides applicants through document requirements with visual examples. OCR extracts data from pay stubs, tax returns, bank statements. Validates completeness before loan officer review.
  • Pre-qualification: Automated preliminary credit check, debt-to-income calculation, and loan program matching. Provides instant pre-qualification letters.
  • Application Processing: AI extracts and validates 1003 application data, identifies potential red flags, and generates compliance documentation.

Technical Stack

Key Metrics

18
Application to approval time reduced from 18 days to 7 days
81%
Document collection time reduced 81%
3.2
Loan officer capacity increased from 3.2 to 5.1 loans per month
68%
Processing errors reduced 68%
2
Eliminated 2 FTE processor roles ($78k savings)

Implementation Timeline

9 weeks including compliance review and loan officer training

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