This blog was co-authored by Nuno Afonso, Senior Analyst, GSMAi.
For the past seven years, the GSMA Mobile Money programme has been collecting and analysing industry data via the Mobile Money Deployment Tracker and annual Global Adoption Survey. Our annual State of the Industry Report has been the main channel for disseminating the data and insights. In 2013, we started developing a statistical model to estimate mobile money indicators at global, regional and country levels which would allow us to fill gaps in participation in the annual Global Adoption Survey and generate aggregate numbers for the State of the Industry Report.
Since then, the digital payments landscape has changed significantly, with different forces such as fintech players introducing a new wave of disruption, and new mega markets such as India joining the ranks of markets with enabling regulatory frameworks. Mobile money is a rapidly transforming industry, and to better capture the diverse drivers of mobile money adoption and usage, we joined forces with GSMA Intelligence to review and adjust the methodology used for developing mobile money estimates. This partnership has enabled us to create a new proprietary modelling approach, which combines GSMA Intelligence’s analytical and telecoms expertise with our own industry knowledge. The results of this new model formed the basis of the 2017 State of the Industry Report, and will be displayed as part of our new interactive tool, Mobile Money Metrics, launching next week.
Explore Mobile Money Metrics
The new dataset covers 21 metrics across three main categories for all providers that offer or have offered mobile money services. The three main categories within the dataset are as follows: mobile money accounts (registered accounts, active 90 days, active 30 days), mobile money agents (registered agents, active agents), and mobile money transactions (volume and value of mobile money transactions processed via the following products: airtime top-ups, bill payments, bulk disbursements, cash-ins, cash-outs, international remittances, merchant payments and P2P transfers).
Our new methodology combines multiple approaches to market sizing, following these five main steps
1. Consolidation of industry data: This step involved creating a pool of industry data from publicly available data such as operator and regulator reports, to complement the data collected via our annual Global Adoption Survey. We created a comprehensive set of historical data reflecting the growth of the mobile money industry after reconciling this pool of data with our definitions.
2. Country-clustering: Countries were clustered based on fundamental conditions of mobile and banking adoption in each country, as well as criteria for mobile money success identified through a joint study with Harvard Business School. The clusters were further shaped by GSMA Mobile Money’s market knowledge.
Figure 1 – Country Clusters
3. Formation of guiding principles: We developed guiding principles to determine how any given metric is expected to evolve.
Figure 2 – An example set of guiding principles for growth patterns of a given metric
4. Modelling: The fourth step is about producing the country estimates, which are built using a ‘bottom-up’ approach, i.e. starting at the service level. Each country has a Microsoft Excel model prepared using compiled industry data (from step 1 of the methodology) for each service in the market (updated from the Mobile Money Deployment Tracker). Modelling assumptions to estimate missing historical data and to produce the forecast are informed by the guiding principles, the latest desk research and GSMA Mobile Money’s market knowledge.
5. Validation: Once the modelling is complete, we review the output at service, country and global levels. At this step, we identify any outliers and check for further explanation.
We hope that these new estimates, providing unique data on mobile money indicators, complement industry stakeholders’ existing research and analysis on future areas of focus or strategy.