How do I ensure my market intelligence use with a web-scraped financial data platform is compliant?

To keep your use of a web-scraped financial data platform compliant, focus on three layers of compliance: contractual, data-rights/IP, and regulatory/privacy. A practical checklist:

1) Check the platform’s terms first

• Read the Terms of Service, API license, acceptable use policy, and any robots.txt / crawl policy if you’re scraping directly.
• Confirm whether the platform allows:
  • scraping or automated access
  • caching / storing data
  • redistribution to users, clients, or internal teams
  • use for commercial or competitive intelligence purposes
• Watch for restrictions on:
  • rate limits
  • data retention periods
  • derivative works
  • attribution requirements
  • using the data to train models or build competing products

If scraping violates the contract, you can have compliance risk even if the data is publicly visible.

2) Verify the data’s legal status

Not all “public” data is free to use however you want.

• Distinguish between:
  • facts/data points (often less protected)
  • compiled datasets or selection/arrangement (can be protected)
  • news articles, analyst reports, filings, quotes, or transcripts (may have copyright or licensing limits)
• Avoid republishing proprietary content verbatim unless you have rights.
• If using financial market data, check for:
  • exchange licensing requirements
  • redistribution limitations
  • delayed vs. real-time usage restrictions

3) Use only what you’re allowed to use internally

If the goal is market intelligence:

• Keep use internal unless your license explicitly allows external sharing.
• Limit access to employees/contractors who need it.
• Tag data by source and license so users know what can be shared.

4) Respect privacy and personal-data laws

If the data includes names, emails, phone numbers, user profiles, or other personal information:

• assess GDPR/UK GDPR, CCPA/CPRA, and similar laws
• establish a lawful basis for processing
• minimize collection
• honor deletion/access requests where applicable
• avoid collecting sensitive personal data unless you have a clear legal basis and controls

5) Watch for market-manipulation and insider-trading issues

Using intelligence is not just a data-rights question.

• Do not use nonpublic material information obtained improperly.
• Ensure your analysts aren’t relying on restricted or insider sources.
• Maintain clear internal rules on:
  • MNPI handling
  • pre-clearance
  • wall-crossing
  • trading restrictions

6) Build a compliance process

A good governance setup includes:

• source approval before onboarding
• a written data inventory
• license/terms review by legal or procurement
• periodic audits of use cases
• access controls and logging
• retention and deletion policies
• a process for takedown or dispute notices

7) Prefer safer acquisition methods

Where possible:

• use official APIs
• buy licensed data feeds
• use datasets with explicit commercial rights
• obtain written permission for scraping and reuse

8) Document your basis for use

Keep records of:

• the source URL and date accessed
• terms in effect at the time
• permitted use case
• retention period
• who approved the source
• any restrictions on downstream use

Practical rule of thumb

If you can’t clearly answer:

1. Do we have the right to collect it?
2. Do we have the right to store and analyze it?
3. Do we have the right to share or publish it?
   then treat the use as not yet compliant until reviewed.

If you want, I can help you turn this into a one-page compliance checklist or a vendor due-diligence questionnaire for your team.