Abstract
Mobile money systems, platforms built and managed by mobile network operators to allow money to be stored as digital currency, have burgeoned in the developing world as a mechanism to transfer money electronically. Mobile money agents exchange cash for electronic value and vice versa, forming the backbone of an emerging electronic currency ecosystem that has potential to connect millions of poor and “unbanked” people to the formal financial system. Unfortunately, low service levels due to agent inventory management are a major impediment to the further development of these ecosystems. This paper describes models for the agent’s inventory problem, unique in that sales of electronic value (cash) correspond to an equivalent increase in inventory of cash (electronic value). This paper presents a base inventory model and an analytical heuristic that are used to determine optimal stocking levels for cash and electronic value given an agent’s historical demand. When tested with a large sample of transaction-level data provided by an East African mobile operator, both the base model and the heuristic improved agent profitability by reducing inventory costs (defined here as the sum of stockout losses and cost of capital associated with holding inventory). The heuristic increased estimated agent profits by 15% relative to profits realized through agents actual decisions, while also offering substantial computational advantages relative to the base model.
Highlights
The rapid growth of cellular networks in the developing world in the past decade has laid the groundwork for a potential paradigm shift in financial services for the poor
Employing a large dataset of mobile money agent transactions provided by an East African mobile network operator, §4.2 presents a comparison of the models’ performance, showing that both the base model and the heuristic significantly increase agent profitability by reducing inventory costs, defined here as the sum of estimated stockout losses and the cost of capital associated with holding inventory
It is noteworthy that the heuristic’s stockout losses are higher than the base model (5.9% to 4.2%), while the capital costs are lower (12.3% to 14.8%). This observation is a direct result of the fact that the newsvendor heuristic is built upon the lower bound on underage cost – which leads to lower inventory recommendations than the base model
Summary
The rapid growth of cellular networks in the developing world in the past decade has laid the groundwork for a potential paradigm shift in financial services for the poor. The velocity of money has been limited by how fast cash can be physically transported, by foot or by bus in most circumstances (Batista and Vicente 2013) This limitation is a critical disadvantage to the poor when money is needed most, such as in the aftermath of a negative economic shock (e.g., sickness or job loss) or a rare opportunity to climb out of poverty through investment (e.g., fertilizer or improved seed purchases) (Helms 2006). At these decisive moments, friends and family willing and able to transfer money have traditionally. Mobile money has been shown to: enable quicker recovery from economic shocks such as job loss or illness to the primary wage-earner (Jack and Suri 2014); enable more efficient receipt of monetary transfers from non-governmental organizations (NGOs) after disasters (Aker et al 2011); and lay the foundation for access to formal savings, credit, and insurance opportunities for those who currently lack such access (Mas 2010)
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