Ownership should sit across fraud, IAM, and platform teams because the abuse touches onboarding, verification, and telecom cost. If one team only sees user access while another only sees billing, the attack can scale unnoticed. Joint governance is the only practical way to close the loop.
Why This Matters for Security Teams
SMS fraud that drives identity abuse and telecom spend is not a single-control problem. It spans onboarding, verification, fraud monitoring, and platform cost management, which means gaps appear whenever those functions sit in separate reporting lines. If identity teams only tune access policy and fraud teams only tune transaction monitoring, the same attack can keep scaling through a blind spot in the middle. The operating model matters as much as the detection logic.
That is why this issue should be treated as shared control ownership, not a dispute over who “gets” the incident. Current guidance in NIST Cybersecurity Framework 2.0 supports cross-functional governance for risks that cut across business services, and NHIMG research on Ultimate Guide to NHIs shows how frequently identity failures remain invisible when ownership is fragmented. In practice, many security teams encounter spend abuse only after finance flags a bill anomaly, rather than through intentional joint detection design.
How It Works in Practice
The practical model is to assign one accountable owner for the risk domain, then define shared execution responsibilities across fraud, IAM, and platform engineering. The accountable owner should coordinate thresholds, review escalation paths, and decide when the issue is treated as an identity compromise, a fraud event, or a cost-control incident. Shared ownership does not mean shared confusion; it means each function owns a distinct slice of the kill chain.
A workable operating pattern usually includes:
- Fraud teams monitor abnormal verification, SIM swap signals, and account takeover patterns.
- IAM teams control step-up authentication, recovery flows, and policy for high-risk identity changes.
- Platform or telecom-cost owners watch spend spikes, SMS volume anomalies, and vendor billing drift.
- Security leadership ties those signals into one case workflow so the same event is not handled three different ways.
This is also where identity and non-human identity governance overlap. If automation is issuing verification messages, routing decisions, or retry logic, the underlying service accounts, API keys, and workflow permissions must be governed as tightly as user access. NHIMG’s Top 10 NHI Issues and the broader The 2024 ESG Report: Managing Non-Human Identities both point to the same operational lesson: identity controls fail fastest when no one owns the combined effect of access and abuse. These controls tend to break down when SMS providers, app teams, and fraud operations each run separate alert queues because attackers can shift from one signal type to another without triggering a single owner.
Common Variations and Edge Cases
Tighter ownership often increases coordination overhead, requiring organisations to balance faster escalation against clearer accountability. That tradeoff becomes visible in distributed environments where SMS is delivered through multiple carriers, regional app teams, or outsourced verification vendors. There is no universal standard for this yet, so best practice is evolving toward a named risk owner with a written RACI, not a committee that meets after the loss has already landed.
Two edge cases matter most. First, if SMS is used only as a fallback channel, teams may incorrectly treat fraud losses as low priority even when the channel is the easiest path to account takeover. Second, if spend exposure is managed by finance without telemetry from identity systems, the organisation may detect abuse too late to prevent repeated resends or recovery attempts. The right approach is to connect fraud, IAM, and platform metrics into one operational view, then review ownership whenever the verification journey, vendor stack, or billing model changes. Where organisations have high automation and frequent vendor handoffs, the control model can still fragment unless escalation thresholds and decision rights are documented and tested.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Non-Human Identity Top 10 address the attack and risk surface, while NIST CSF 2.0 and NIST AI RMF set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| NIST CSF 2.0 | GV.OV-01 | Cross-functional risk ownership fits CSF governance and oversight expectations. |
| OWASP Non-Human Identity Top 10 | NHI-01 | SMS abuse often exploits service workflows and credentials behind identity operations. |
| NIST AI RMF | Risk mapping and governance are needed where automated identity flows affect abuse and spend. |
Use AI RMF governance to define ownership, escalation, and monitoring across the SMS fraud lifecycle.
