Mobile Identity Verification: Why Raw Network Data Is Never Enough

In a recent interview with Liminal for their Friday Five series I sat down with Filip Verley to discuss the realities of mobile identity verification and the long-term value of behavioural data history.

While the mobile phone has become the central point for global transactions, relying solely on direct mobile network operator feeds presents clear operational challenges for fraud prevention teams.

The Gap Between Standardisation and Live Availability

The GSMA Open Gateway initiative represents positive movement, bringing operator groups together to standardise APIs for checks such as SIM swap verification. However, an agreed API specification does not automatically guarantee an operational, commercially available service across every target market.

Mobile network infrastructure was built to route calls and manage subscriber billing, not to provide instant verification for enterprise risk decisions. Local regulatory frameworks and varying operator technical capabilities mean raw data often arrives incomplete. Turning operator signals into actionable intelligence requires continuous data assembly and verification across global networks.

Data Freshness and Hidden Operational Risk

A common misconception when evaluating mobile identity tools is assuming network subscriber databases are constantly updated. A record created when an account opens may sit unchanged for years, despite subsequent changes in account ownership or porting status.

Relying on stale data fields introduces silent friction into core business processes. If a record fails to reflect recent changes, legitimate users face unnecessary hurdles during onboarding, while bad actors exploit outdated information. Effective risk management relies on dynamic attributes and real-time status signals rather than static database lookups.

Safeguarding Historical Data Assets

Over the next 12 to 18 months, protecting proprietary data assets will become a central priority for risk leaders.

The long-term value of mobile intelligence comes from accumulated behavioural history rather than a point-in-time query. As artificial intelligence tools become widespread, organisations risk exposing their historical data assets to public models without deliberate oversight. Defending this intelligence is now a board-level commercial consideration.

Watch the Full Episode

Catch the full discussion with Filip Verley on Liminal’s Friday Five series to learn more about mobile data quality and risk decisioning here: https://youtu.be/rov44vAsYZM