- Case Study 02
- Mortgage & Foreclosure
- United States
AI Web Scraping for Foreclosure Lead Discovery
A US mortgage services company spent 4–6 hours every day manually checking government websites for foreclosure listings. We brought that down to 5 minutes.
Headline results
- Less manual work
- 98%
- Data accuracy
- 99%
- Daily processing time
- 5 min
The situation
The Problem
Foreclosure notices are published daily across dozens of US government websites in unstructured formats. The client's team was spending half their day manually reading, filtering, and copying this data into spreadsheets — a process that was slow, error-prone, and impossible to scale.
WHAT WAS BREAKING
- 4–6 hours of manual data collection every single day
- 3–5 team members tied up on repetitive data entry
- ~85% data accuracy — opportunities missed due to errors
- Slower than competitors who were getting to listings first
What we built
What We Built
A custom AI-powered scraping platform that monitors all relevant government websites in real time, identifies valid foreclosure notices, and delivers clean structured data — automatically, every day.
THE SYSTEM
- Continuous automated monitoring of multiple government websites
- AI filtering to identify only valid foreclosure and auction notices
- NLP-powered extraction — auction date, lender, property address, notice details
- Clean CSV and JSON output, ready for CRM or analytics integration
- Compliant scraping — rate limits, session management, CAPTCHA handling
- Runs on standard Mac or Windows — no infrastructure investment needed
Afterwards
Results
| Metric | Before | After |
|---|---|---|
| Daily processing time | 4–6 hours | ~5 minutes |
| Team members required | 3–5 people | 1 person |
| Data accuracy | ~85% | 99% |
| Missed leads | Occasional | Zero |
| Infrastructure cost | Significant | None |
Built in 4 Weeks
From kick-off to deployment in four weeks. Two optimisation cycles using real foreclosure notice samples improved keyword recognition, filtering accuracy, and field-level extraction. The client was processing live data in their first week of operation.