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Maintaining a Critical Link To Last-Mile Customers: Challenges and Opportunities Facing Financial Service Agents During COVID-19

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Maintaining a Critical Link To Last-Mile Customers: Challenges and Opportunities Facing Financial Service Agents During COVID-19

Posted | Updated by Insights team:

Publication | Update:

Sep 2020
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Editor’s note: This article is part of NextBillion’s series “Enterprise in the Time of Coronavirus,” which explores how the business and development sectors are responding to the pandemic. For news updates and analysis, virtual events, and links to useful resources related to the COVID-19 crisis, check out our coronavirus resource page.

 

Agents are a critical last-mile link to financial services for lower-income households and micro- and small enterprises, registering new customers and providing cash-in and cash-out services (i.e.: loading value into the mobile money system, and then converting it back to cash again). Depending on local regulations and the broader digital financial services ecosystem, agents may provide other services, too. While agents are not normally direct employees of financial service providers (FSPs), they are often the primary access point for customers. They can help build customer trust in the FSP’s products, and bridge the gap between the cash and digital worlds.

As the COVID-19 crisis has spread globally, limiting people’s mobility, it has had a profound effect on how agents and FSPs operate. On one hand, in many countries, agents are not considered an essential service provider – so the lockdown restricted their working hours, which limits their ability to serve customers. On the other hand, because agents are now sometimes the only interface between customers and their money, they are now taking on extra responsibilities beyond cash-in and cash-out. Below we’ll explore the Savings Learning Lab’s recent report, “Leveraging High Performance Agent Networks to Deliver Customer Value,” outlining challenges faced by agents, discussing how they have responded, and highlighting opportunities going forward. We’ll also share how Savings Learning Lab partners are responding to the COVID-19 crisis.

 

Challenges for Agents and Financial Service Providers

Agents and financial service providers are facing a number of challenges, including:

Reduced transaction volumes and commissions: To take just one example, in March 2020, the government of Kenya issued a directive to waive transaction fees on bank to mobile wallet transfers, cutting the commission paid to agents. While these directives were put in place for public health reasons, it meant that agent transactions and commissions were reduced to half or less. In other countries in East Africa, agents saw fewer transactions – often of larger value – as people were trying to limit their number of visits to an agent to reduce exposure to the COVID-19 virus. These larger transactions in turn created liquidity challenges (see below).

Float management and regulation challenges: Several governments in Africa have announced government-to-person transfers to support their citizens during this pandemic. As a result, the increased use of digital channels caused by these payments has created pressure for agents to rebalance their float more frequently – several times a day in many cases. (Float refers to the balance of e-money, physical cash or money in a bank account that an agent can immediately access to meet customer demands to cash in or cash out electronic money.)

Agents are at a greater risk of exposure to the coronavirus: As the COVID-19 pandemic spread, the World Health Organization warned governments to limit cash transactions, given their potential to transmit the virus. However, agents have been forced to ​physically handle banknotes, with little or no guidance on appropriate precautions, or access to personal protective equipment (PPE).

 

Responses by Agents and Financial Service Providers

There are a number of ways agents and providers are addressing these challenges, including:

Revisiting fees and commissions: FSPs are revisiting their agent commission and fee structures. In the Savings Learning Lab’s research, we‘ve seen at least one case where the FSP has started paying its agents a salary plus an additional financial incentive based on their previous commission history, to encourage them to stay on as agents instead of seeking safer or more lucrative work. Using the data and transaction history of agents can help FSPs create a pandemic-specific financial plan, and allow them to develop a short-term coping strategy. In addition, in response to float management challenges, some FSPs have increased the float balance of super agents (who often manage a group of agents in a specific geography) by up to five times, to support the frequent float rebalancing requests coming from field-based agents.

Providing Personal Protective Equipment: The pandemic has increased the cost of doing business for many agents, as they now need to have masks, hand sanitizer and other PPE to ensure they provide a safe transaction space to their customers. Given the decline in commissions, this is not always a viable option for agents. We found several examples of FSPs that are now providing their agents with PPE, along with guidance on how to safely conduct transactions.

Adapting service models: FSPs are being forced to adapt their service models and expand the role of their agents. Two recent examples include:

  • Increasing visibility and providing PPE training: Many agents who collect daily savings from customers have increased their visibility and level of interaction with savers, to maintain confidence that their business was still up and running. On the FSP side, many now empower agents to play the role of community trainer – e.g.: to guide the customers about the proper use of masks, sanitizers and hygiene measures, alongside their routine savings collection.
  • Use of technology to circumvent gathering rules: Another example of service adaptation comes from Zambia, where the government limited the number of people gathering in a place to 20. In response, one of the financial service providers working with local savings groups (which usually have 20+ members) informed the group members that they could either pay digitally before the group meeting time into the agent’s account, or they could pass their weekly savings to another group member – thus reducing the number of people who would need to be present for the group meeting.
  • Remote agent management: Some FSPs are calling their agents more frequently, and using communication channels such as WhatsApp to monitor their liquidity needs and address any other business challenges in a timely manner.

 

Opportunities going forward

As outlined in our recent report, the increased use of technology offers considerable opportunity for managing and supporting agent networks, especially as providers adapt to respond to the challenges of the COVID-19 pandemic. Some specific opportunities include:

Remote training and performance management to support agents: Even before the pandemic, FSPs were increasingly turning to technology-based solutions for agent management, such as e-learning apps for training, WhatsApp for agent communication and monitoring, and real-time data dashboards for liquidity and performance management. These solutions have proven to be essential in the current context, where FSPs’ staff travel and contact with agents has become limited, but the need for agents to cash in and cash out has grown. They also offer a unique opportunity for FSPs to adopt a data-driven approach to managing and growing their agent networks and delivering value to customers.

Information sharing and quick adaptation to support clients: In many cases, government regulations around both social interactions and payments are changing rapidly. FSPs have an opportunity to proactively communicate with agents, to make them aware of these changes and help them provide the right support to customers. Some FSPs are leveraging existing agent communication platforms such as WhatsApp or SMS to provide information on new regulations, revised fees and COVID-19 prevention tactics. 

The pandemic has accelerated the shift to mobile money across sub-Saharan Africa, but it threatens to leave behind the most vulnerable customers and communities. Agents have proven to be an essential link to serving these customers – they are embedded in the communities and have a close relationship with them. Investing in developing and maintaining a robust agent network could be key to building a digital financial ecosystem that is not only resilient, but truly inclusive.

 

Want to know more?

The Mastercard Foundation’s Savings Learning Lab publication “Leveraging High-Performing Agents to Deliver Customer Value” provides an overview of how agents are an essential component of delivering value to informal savers and other excluded populations. Drawing on the experiences of FSPs in sub-Saharan Africa, the paper offers guidance on key strategies for building and managing high-performing agent networks – including selecting and recruiting agents, training and monitoring them, and designing incentives to motivate them.

Additionally, if you want to learn more about solutions for managing agent liquidity, our partner Savings at the Frontier recently produced this excellent “How To Note” on liquidity management, with an informative blog on the specific difficulties presented by COVID-19. In addition, for practical examples on agent banking pricing strategies and technology solutions for agency banking, we invite you to read these case studies from our partner Scale2Save.

 

Nisha Singh is an Independent Contractor and James Robinson is a Principal Consultant at Itad.

 

Photo courtesy of World Bank.

 


 

 

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The future outlook “forecast” is based on a set of statistical methods such as regression analysis, industry specific drivers as well as analyst evaluations, as well as analysis of the trends that influence economic outcomes and business decision making.
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Forecasts, Data modelling and indicator normalisation

Review of independent forecasts for the main macroeconomic variables by the following organizations provide a holistic overview of the range of alternative opinions:

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As a result, the reported forecasts derive from different forecasters and may not represent the view of any one forecaster over the whole of the forecast period. These projections provide an indication of what is, in our view most likely to happen, not what it will definitely happen.

Short- and medium-term forecasts are based on a “demand-side” forecasting framework, under the assumption that supply adjusts to meet demand either directly through changes in output or through the depletion of inventories.
Long-term projections rely on a supply-side framework, in which output is determined by the availability of labour and capital equipment and the growth in productivity.
Long-term growth prospects, are impacted by factors including the workforce capabilities, the openness of the economy to trade, the legal framework, fiscal policy, the degree of government regulation.

Direct contribution to GDP
The method for calculating the direct contribution of an industry to GDP, is to measure its ‘gross value added’ (GVA); that is, to calculate the difference between the industry’s total pre­tax revenue and its total bought­in costs (costs excluding wages and salaries).

Forecasts of GDP growth: GDP = CN+IN+GS+NEX

GDP growth estimates take into account:

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All relevant markets are quantified utilizing revenue figures for the forecast period. The Compound Annual Growth Rate (CAGR) within each segment is used to measure growth and to extrapolate data when figures are not publicly available.

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Our market segments reflect major categories and subcategories of the global market, followed by an analysis of statistical data covering national spending and international trade relations and patterns. Market values reflect revenues paid by the final customer / end user to vendors and service providers either directly or through distribution channels, excluding VAT. Local currencies are converted to USD using the yearly average exchange rates of local currencies to the USD for the respective year as provided by the IMF World Economic Outlook Database.

Industry Life Cycle Market Phase

Market phase is determined using factors in the Industry Life Cycle model. The adapted market phase definitions are as follows:

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The Global Economic Model
The Global Economic Model brings together macroeconomic and sectoral forecasts for quantifying the key relationships.

The model is a hybrid statistical model that uses macroeconomic variables and inter-industry linkages to forecast sectoral output. The model is used to forecast not just output, but prices, wages, employment and investment. The principal variables driving the industry model are the components of final demand, which directly or indirectly determine the demand facing each industry. However, other macroeconomic assumptions — in particular exchange rates, as well as world commodity prices — also enter into the equation, as well as other industry specific factors that have been or are expected to impact.

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The principal explanatory variable in each industry’s output equation is the Total Demand variable, encompassing exogenous macroeconomic assumptions, consumer spending and investment, and intermediate demand for goods and services by sectors of the economy for use as inputs in the production of their own goods and services.

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The individual characteristics of a good or service will have an impact, but there are also a number of general factors that will typically affect the sensitivity of demand, such as the availability of substitutes, whereby the elasticity is typically higher the greater the number of available substitutes, as consumers can easily switch between different products.
The degree of necessity. Luxury products and habit forming ones, typically have a higher elasticity.
Proportion of the budget consumed by the item. Products that consume a large portion of the consumer’s budget tend to have greater elasticity.
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Prices are also forecast using an input-output framework. Input costs have two components; labour costs are driven by wages, while intermediate costs are computed as an input-output weighted aggregate of input sectors’ prices. Employment is a function of output and real sectoral wages, that are forecast as a function of whole economy growth in wages. Investment is forecast as a function of output and aggregate level business investment.

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