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Agents are critical to the customer experience of digital money services because they represent the first and most tangible service touch points for most end users. Agent networks are also probably the most operationally burdensome and costly element of the digital financial service value chain, typically costing anywhere between 40 and 80 percent of revenues generated from the business. Providers therefore need to approach agent network development and operation with a high degree of strategic clarity to drive a sufficiently tight operational focus.

The importance of agent networks is only rising. The MMU´s State of the Industry reports shows that since 2011 the amount of active agents providing digital finance services has grown by almost 800%, while the average number of agents per provider has increased by over 260%. Further, this has not just been happening in East Africa, but in regions around the world, like South Asia where bKash in Bangladesh and MobiCash in Pakistan have scaled much faster than any network in East Africa ever could have dreamed.

The successful design of an agent network must ensure that it is structured appropriately to deliver a specific value proposition to a chosen target market, while making business sense for the provider.  In a new paper, (Designing Successful Distribution Strategies for Digital Money), we document the variety of ways in which digital finance service providers (including banks, telecoms and third parties) have gone about assembling and then managing networks of third-party retail agents. We start our analysis with some strategic decisions involved with choosing stylized agent management models. However, based on seven case studies included in the report, and additional ones published on the Helix Institute website, we found that providers often evolved and especially hybridized their agent network strategies over time. We identified several core reasons behind the increasing diversity of models employed by the more mature providers.

Some providers who initially relied heavily on flat, centralized channel structures feel they need to embrace more scalable models to grow faster and avoid overly burdensome operations. For instance, Airtel Uganda evolved from a centralized build model to a master agent model to better manage growth, and UCB in Bangladesh opportunistically partnered with a third party specialist (MobiCash) that was building its own agent network.

Once they have successfully built a strong proprietary agent network, some providers have tended to feel safe in bringing in partners to complement their own agent network. For instance, both UCB in Bangladesh and Equity Bank in Kenya have been opening up to partnerships with retail chains.

But the trend is not always towards more outsourcing and partnering. Some providers who initially relied heavily on retail chain partners to roll-out their agent network may feel they need to regain some control over geographical coverage. For instance, BBVA Bancomer in Mexico and Eko in India added a centralized channel build to areas in their network with low coverage, while M-Sente in Uganda implemented master agents, to better extend their coverage into specific rural areas.

A related situation is where providers who were initially happy to work with non-exclusive channel partners or share retail agents with other providers in order to grow faster feel they need more control over the customer experience and bring back some differentiating elements. For instance, BBVA Bancomer in Mexico needed a direct, exclusive channel that could focus on customer acquisition (rather than merely cash in/cash out) and recruited agents directly that could do this to complement their retailor partnerships. Islami Bank (IBBL) in Bangladesh found that it had to provider better liquidity management services for agents, and brought in master agents for support. In the case of Easypaisa in Pakistan, an increasing level of competition in the market meant that more control was needed over at least part of the network, therefore increasing the strength of the direct relationships they have with the agents.

A change in the agent network model may also be required when a new service is added that puts pressure on the existing agent network, either because the new service requires a higher touch sale and service model or because it is targeted at a demographic that is not adequately served by the existing agents. This has been observed with banks that agree to distribute Government-to-Person (G2P) benefits and suddenly need to build a denser network in rural areas.

Sometimes the changes in agent network structure and operations happen organically over time, as the agent channel itself differentiates and it becomes clear to providers that certain agents are better at registering customers, or tend to have more float and do substantially more transactions. It becomes evident that not all agents are equal, and it does not make sense to treat them as such. In this case, providers usually implement systems to start segmenting their agent network and offering different levels of support based on performance or other salient criteria. These trends all seem to be natural progressions that channels make as they become larger and more sophisticated overtime, and are certainly a sign of a continually maturing industry.