What are Spam Detection Databases?
Spam detection databases are essentially collections of phone numbers flagged as potentially spam, scam, telemarketing, or robocalls. These databases are maintained by:
- Mobile carriers (e.g., Verizon, AT&T)
- Third-party apps (e.g., Hiya, Truecaller)
- Global or regional organizations dedicated to call fraud prevention.
Why Regional Difference Exist
Data Contribution Variability: Different regions (countries, states, even cities) may have more active contributors or regulatory bodies feeding data into these databases.
Legal Frameworks: Spam definitions and regulatory frameworks vary by region. For example, the US's FCC and TCPA regulations may enforce stricter reporting compared to some other countries.
Call Volume Patterns: High-volume calling numbers in one region may be flagged as spam there, but not in others where that number isn't as active.
Carrier-Level Agreements: Carriers in certain areas may partner with spam detection providers that have region-specific data. For example, a carrier in California might use a database more attuned to West Coast patterns than a national or international one.
Language and Cultural Factors: Some regions may flag calls in certain languages or from specific area codes more aggressively due to localized fraud patterns.
Impact on NumberVerifier Results
If NumberVerifier's results come devices with standard, unmodified consumer settings, the results reflect what a device in a particular region will display - without access to more comprehensive or localized spam lists that a carrier or third-party app might use. For example, a number might appear “clean” in one region but be labeled “Robo Caller” in another due to the specific spam reports fed into regional databases.
Why It Matters
When a customer sees a discrepancy between what NumberVerifier shows and what another device (with carrier or third-party filters) shows, it is likely because of these regional differences - combined with additional filtering apps that might use more localized or robust databases.