Mobile industry body the GSMA has announced that a private telecoms industry blockchain network designed to simplify wholesale roaming is ready for commercial use.
The industry body has been working alongside half a dozen major international telecoms operators to research the use of blockchain in roaming for the best part of four years, coming up with an open-source blockchain solution that automates the operations of the wholesale roaming settlement process. That solution “informs” the new GSMA eBusiness Network and a suite of wholesale roaming service applications, the GSMA said, but added that the services were developed independently of the aforementioned operator initiative.
It’s all quite carefully worded, but it seems that the GSMA’s blockchain network is based on the operator group research, but the industry body is keen to retain ownership of it, and the services it will facilitate.
To rewind just a little, Deutsche Telekom Global Carrier, CK Hutchison, Orange, Telefónica, Verizon, and Vodafone were the founding members of the Blockchain for Wholesale Roaming (BWR) initiative, which came into being under the auspices of the GSMA a few years ago. The parties carried out numerous proof of concept trials – Vodafone, Deutsche Telekom and Telefonica announced they had carried out various successful trials in late 2019, for example – and wrapped these all together to create a a minimum viable product (MVP); that’s an early version of a product with basic features. This led to the delivery of an open-source blockchain solution that automates the operations of the wholesale roaming settlement process, the GSMA said.
The GSMA explained that its new roaming services are aligned with BWR’s open-source principles and specifications to end up with a multi-party, multi-vendor, and ledger-agnostic environment on the GSMA eBusiness Network.
It might not sound simple, and indeed, a lot of work has gone into this blockchain roaming initiative from all sides, but the idea of using blockchain for roaming is actually pretty straightforward.
As it stands, the world’s many hundreds of mobile operators have to keep records of roaming transactions and settle the bills between them. They’re not actually doing this with a pen and paper or anything, but even with back-end systems and roaming hubs doing the heavy lifting, there’s a lot of time and effort involved in figuring out who owes what.
The trustless nature of blockchain technology makes it the ideal candidate for roaming, removing much of the complexity along the way. Any process involving counterparty risk requires a middleman, be it the likes of Visa and Swift in the financial space, or specialist players in the telecoms space, a number of whom are doubtless at the GSMA’s Mobile World Congress event – in person or virtually – at present. Blockchain makes everything easier, quicker and cheaper, and that is good news for the telcos.
“The combination of increasing international data flows and momentum around 5G and IoT create a natural impetus to overhaul existing wholesale roaming practices,” said Alex Sinclair, CTO of the GSMA, in a statement. “Harnessing the potential of blockchain to automate processes and mitigate inefficiencies is a crucial step towards strengthening the global mobile ecosystem and enhancing inter-operator connectivity,” he added.
Just to get a little bit techie, the GSMA eBusiness Network is built on Hyperledger Fabric, a permissioned blockchain network, which effectively means it’s available to a closed user group. Hyperledger was launched by the Linux Foundation and its decentralised ledger technology (DLT) platform was designed by IBM for industrial enterprise use.
The GSMA eBusiness Network is commercially ready, the GSMA said, but it’s not clear when we’re likely to see operators actually using the new roaming services it will facilitate. Nonetheless, the industry body is looking ahead to other industry use cases that it will support in future, throwing around buzz words like cloud computing, edge computing, quantum computing, artificial intelligence and machine learning.