1. Home
  2. Finance and insurance data scraping
Finance data extraction

Rates, fees and premiums, delivered as clean data.

We collect rates and premiums, fees, terms and ratings from public bank, lender and insurer websites.

Built around your products and markets, delivered on your schedule.

Get a free sample from your own sources within 24 hours and see the data before you commit.

100% job success10+ years of experience20k+ course studentsWork directly with the founder
products.csvsample data
Illustrative sample of scraped finance and insurance products. Select a product to see its rate history.
productproviderratedays_listedstatus
Summit Bank4.60%75▼ 0.25
Northwind Credit11.90%52unchanged
Harbor Insurance$142/mo60▲ 2.9%
Pioneer Savings21.99%5new
Pioneer Savings4.85%39withdrawn
Illustrative data. Select a product to see its rate history.

Trusted by 500+ companies, startups and individuals.

Rock the Rankings
Iceland Travel
Blue Orange
myrunway
boxtribe
Kore Real Estate Group
42matters
Udemy
nextflat
Crunch
Swell Inc.
Sunday
Wildcat Capital Management
XCStats
Distribusion
catchhotels
QAPA
Product Folks
Client logo
Quotient
Saw.com
Markmi
Client logo
Tensile Capital Management
Car Geeks Collision
ParcelNinja
Packt
Pioneer Interests
Syndigo
Luxury Family Rentals
flowingbee
Moshbit
Velocity by design
Auditi
mxney
What you get

Every field you need from a financial product.

These are the usual building blocks. We add or drop fields to fit your project, and the free sample shows exactly what comes back.

Product

What is being offered.

  • product_name
  • product_type
  • provider
  • category
  • term
  • currency
  • promo_offer
  • description
  • product_url

Rates and fees

What it costs, or what it pays.

  • apr
  • apy
  • interest_rate
  • rate_type
  • monthly_premium
  • annual_fee
  • other_fees
  • minimum_deposit
  • rate_history

Coverage and terms

What is covered, and on what conditions.

  • coverage_limit
  • deductible
  • coverage_type
  • eligibility
  • credit_score_range
  • term_length
  • early_repayment
  • exclusions

Provider

Who is offering it. Public business details only.

  • provider_name
  • provider_type
  • headquarters
  • license_info
  • website
  • rating
  • review_count
  • branch_locations

Offer history

How each offer changes over time.

  • first_seen
  • last_seen
  • days_listed
  • listing_status
  • withdrawn_on
  • rate_changes
  • last_updated
  • duplicate_of

Source and comparison

Where the data was found, and how it compares.

  • source_urls
  • sources_count
  • market_rank
  • best_rate_flag
  • last_checked
  • product_id

On requestMortgage and savings rate tables, insurance quote pages, fee schedules, promotions and bonus offers, and provider ratings, where they are published.

Who uses it

How teams put finance data to work.

Comparison sites and fintech apps

Keep your rate tables current with offers from many providers, matched to one record per product, and remove products that have been withdrawn.

Typical refresh: daily

Banks, lenders and insurers

Watch competitor rates, fees and premiums by product and region, and see when others cut, raise or run promotions.

Typical refresh: daily to weekly

Brokers and advisers

Find the best current offer for each client profile, with fees and terms side by side and the history behind them.

Typical refresh: weekly

Analysts and researchers

Follow rates and fees across a market over time, from one consistent history instead of screenshots.

Typical refresh: weekly to monthly
Why it is hard

Why financial product data is harder than it looks.

Rates are easy to read and easy to get wrong. These are the five problems we plan for, and how we handle each.

The problem

Rates depend on conditions.

The same product shows different rates by loan amount, term, region, credit band or coverage level, so one scrape rarely matches what a customer sees.

How we handle it

We fix the conditions for every run, such as amount, term, region and profile, and store them with each row, so rates stay comparable across providers and over time.

The problem

Rate terms differ between sites.

Some sites show APR, others APY or a flat rate, quoted monthly, yearly or as an "up to" figure, with fees listed somewhere else.

How we handle it

We keep every rate exactly as published and add normalized columns, so APR, APY, monthly and annual figures can be compared like for like.

The problem

Offers change and expire.

Promotions end, rates move and products are withdrawn without notice, so a single snapshot goes stale quickly.

How we handle it

Scheduled re-checks store every change with a timestamp and mark products that disappear, so you get rate history, days listed and withdrawal dates.

The problem

The same product appears on many sites.

Providers, brokers and comparison sites list one product under different names, with slightly different terms.

How we handle it

We match products by provider, name and terms, then merge them into one record that keeps every source and rate.

The problem

Sites block and change.

Finance sites use bot protection and redesign their pages, and scrapers quietly return half the rows.

How we handle it

Every pipeline is monitored with row-count and field checks. When a site changes or blocks us, we fix it. Maintenance is part of the service.

How it works

From your list of products to a live data feed.

Tell us what you need

Share the providers or comparison sites, the products and regions, and the fields. A short call or a message is enough.

See a free sample

Within 24 hours of the call, depending on the sources, you get a sample from your own sources. You see the fields, the quality and the refresh rate before you commit.

Pick the schedule

Hourly, daily, weekly or monthly. We scope the price once you have seen the sample.

Receive and rely on it

Data arrives as CSV, JSON, Excel, Google Sheets, Airtable, in your database, through an API or in cloud storage. We monitor it and fix what breaks.

Common questions

Straight answers.

What teams ask before they start.

What finance and insurance data can you collect?

Savings, loan, mortgage, card and insurance listings with rates, fees, terms, coverage details and ratings, plus promotions and provider details. On request we also collect rate tables, fee schedules and public regulatory registers. Tell us the fields you need and the free sample shows what is possible.

Can you track rate changes and withdrawn products?

Yes. We re-check your sources on a schedule from hourly to monthly and store every change. You get rate history, days listed and withdrawal dates, not just a snapshot. A product that disappears is marked withdrawn. We cannot tell whether the provider ended it or only moved the page.

How do you compare products across providers?

We keep every rate as published, then add normalized fields such as APR, APY and monthly cost, so different providers can be compared like for like. We also store the conditions each rate applies to, such as amount, term and region.

Which sites and countries can you cover?

Comparison sites, bank and lender websites, insurer quote pages and public registers, in any country and language. If a source is not practical, for example because of heavy blocking, we tell you upfront, before you commit to anything.

Is scraping finance websites legal?

We collect publicly available data only, such as the rates, fees and terms any visitor can see. Rules differ by country and by site, a site's terms may restrict automated access, and financial products are regulated in many places. We flag risky sources and fields before we build. We are not lawyers, so for sensitive uses we recommend checking with your own counsel.

How do I receive the data?

CSV, JSON, Excel, Google Sheets, Airtable, your own database, an API or cloud storage, on a schedule you choose, ready to feed your comparison tables or dashboards.

How much does it cost, and how fast can we start?

Pricing depends on sources, volume and frequency. We scope it after a free discovery call and sample. Most samples are ready within 24 hours of the call, depending on the sources.

Your free finance data sample, built on your actual sources.

Tell us the providers, products, regions and fields you need. We reply with a plan and a sample.

Prefer to talk first? Book a call with the founder

Lazar Telebak, founder of REData Analytics

Lazar Telebak

Founder, REData Analytics

You work directly with the person who builds your data feed. In 10+ years he has worked with 500+ startups, agencies and companies, from one-time extractions to long-running systems processing tens of millions of records.

Founder profile on LinkedIn ↗