Enterprise mobile messaging is a well-established, safe, efficient and cost-effective way for enterprise to build trusted relationships and communicate with their customers. This is reflected in our research which shows that when communicating with companies, consumers trust SMS (short message services) above any other channel. However, if left unchecked, there is a risk that levels of trust amongst consumers and enterprise will fall, impacting the adoption of messaging amongst new enterprise sectors, stifling innovation and ultimately slowing the long-term growth of the industry.
In 2016, MEF published its A2P Messaging Fraud Framework Version 1.0. The framework set the foundation for the future work of the Programme to develop best practice guidelines for industry and buyers of messaging solutions, as well as providing the structure for an industry-wide certification programme.
This Version 2.0 of the Fraud Framework offers some further insight into the impact of fraud on all parties within the ecosystem, as well as categorisation of the means available to parties to detect and protect against fraud through the implementation of commercial solutions, technical solutions and through processes, compliance and legality.
A total of 13 fraud types have been identified, defined and mapped providing recognisable, real life examples of how fraud can occur, sharing how the different communities within the ecosystem can detect and protect themselves and their customers against fraud.
The framework was developed by a collaborative cross-ecosystem working group of participants of MEF’s Future of Messaging Programme, represented by senior executives from across Commercial, Operator Relations, Product and Technical teams.
13 Fraud Types
- SMS Originator Spoofing
- SMS Phishing
- Access Hacking
- SIM Swap Fraud
- SMS Roaming Intercept Fraud
- SMS Malware (SMS Hacking)
- MAP Global Title Faking
- SCCP Global Title Faking
- SMSC Compromise Fraud
- Grey Routes, Bypass, Non-Interworked Off-Net Routes
- SIM Farms
- Artificial Inflation of Traffic (AIT)