Mortgage Rate Scraper

Scrape current mortgage rate data from leading financial comparison sites including Bankrate, NerdWallet, and Forbes Advisor. This actor extracts lender names, interest rates, APR, points, loan types, and monthly payment estimates for comprehensive mortgage rate comparison.

Features

• Scrapes multiple mortgage rate comparison websites for comprehensive data
• Supports all major loan types: 30-year fixed, 15-year fixed, ARM variants, FHA, VA, and jumbo
• Extracts lender names, rates, APR, points, and monthly payment estimates
• Location-specific rates using ZIP code filtering
• Deduplicates results across sources for clean output
• Works with empty input using sensible defaults

Input Parameters

Parameter	Type	Default	Description
loanType	string	30-year-fixed	Mortgage loan type (30-year-fixed, 15-year-fixed, 5-1-arm, etc.)
zipCode	string	75024	ZIP code for location-based rates
loanAmount	integer	400000	Desired loan amount in USD
maxResults	integer	50	Maximum number of results to return

Output Fields

Each result in the dataset contains:

• lender - Mortgage lender name
• rate - Interest rate percentage
• apr - Annual Percentage Rate
• points - Discount points
• loanType - Type of mortgage loan
• loanAmount - Loan amount queried
• monthlyPayment - Estimated monthly payment
• zipCode - Location ZIP code
• url - Source page URL
• source - Website the data was scraped from
• scrapedAt - ISO timestamp of data collection

Use Cases

Mortgage rate data is essential for real estate professionals, mortgage brokers, fintech applications, homebuyer research tools, and market analysis platforms. Financial advisors use this data to track rate trends and help clients find the best mortgage terms. Real estate investors monitor rates to optimize financing decisions across different loan types.

Pricing

This actor uses pay-per-event pricing at $1.50 per 1,000 results. You are only charged for actual data delivered to your dataset.

Legal and Compliance

This actor scrapes publicly available mortgage rate information. Users should review target website terms of service before large-scale data collection. Rate data is for informational purposes and should not be considered as financial advice.