Rate collection across lenders
Scrape mortgage, savings and loan rates from lender sites and comparison engines daily, keyed on product and term, so changes show up as diffs the morning after they happen rather than weeks later.
Industries
What we scrape in financial services
Public filings, rates, listings and disclosures from regulators, exchanges, banks and comparison sites, delivered as structured rows with source links.
Financial data on the public web is scattered across regulator portals, exchange notices, bank rate pages, fund fact sheets and comparison sites, much of it in PDFs or behind clunky search forms. We build scrapers that submit those forms, page through results, download the documents and parse them into tables with the publication date and source URL preserved. No account access and no market data that requires a licence: just the public record turned into something you can query.
Sources
Typical sources
Public pages and documents we have scraped in this vertical. Named sites are examples, not an exhaustive list.
- SEC EDGAR, Companies House and similar company registries
- Central bank and regulator notices, enforcement lists and bulletins
- Bank and lender rate pages for mortgages, deposits and loans
- Fund fact sheets, prospectuses and NAV pages
- Exchange announcement feeds and listing notices
- Loan and insurance comparison sites
- Fintech app store listings and public changelogs
- Public court and bankruptcy dockets
Schema
Fields
A common starting schema. You decide the final columns and names; we keep them stable across runs.
entity_nameregistry_iddocument_typefiled_atproductratetermfeesourcedocument_urlscraped_at
Output
What a row looks like
entity_name | registry_id | document_type | filed_at | product | rate | term | fee | source | document_url | scraped_at |
|---|---|---|---|---|---|---|---|---|---|---|
| Example Bank plc | 00000000 | Rate sheet | 2026-10-06 | Fixed-rate mortgage | 4.19% | 5 years | £999 | Bank website | https://example.com/rates | 2026-10-07 |
Values are illustrative placeholders to show shape and types, not records from any client or source.
Use cases
Jobs we are usually asked for
Filing and disclosure extraction
Download new filings from registries on a schedule and parse the fields you need from the PDF or HTML, such as officers, shareholdings or auditor changes, into a table with the filing date and document link.
Enforcement and sanctions list tracking
Pull regulator enforcement actions, warning lists and sanctions updates as they are published, normalised to one schema across jurisdictions, with the original notice URL and publication date kept on every row.
Questions
About financial services scraping
Do you scrape market or price data from exchanges?
Only public notices, listings and documents. Real-time or licensed market data is distributed under contracts we do not work around, and we point you to the vendor instead.
Can you parse PDFs?
Yes. Rate sheets, prospectuses and filings in PDF are parsed to tables with layout-aware extraction and validated against the document. Scanned documents go through OCR with a confidence flag on each field.
How do you handle registries with search forms and captchas?
We reproduce the form submission as the browser does it, page through results and solve or avoid captchas within the terms of the site. Volume is kept to what a research user would generate.
Is this suitable for compliance monitoring?
It is suitable as the collection layer: we make sure the public notices arrive complete and on time in your storage. The decisions and audit trail remain in your compliance tooling.
Need financial services data? Tell us the sites.
Send the sources and the fields you need. An engineer looks at them the same day and replies with a plan and a price.