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Pricing and commissions Webinar English

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  • Welcome for those of you who don’t know me... [Paul; Camilo] ... I’m going to be hosting this webinar on behalf of GSMA. you’ll also be interacting with my colleague during this webinar [Neil; Yasmina] Today’s session is going to be divided into two segments: pricing and commissions. We’re planning to cover a lot of theory, but to really make this engaging, we’re also going to be working through an end-to-end exercise of creating our own tariff sheet and corresponding set of agent commissions in real time for an imaginary mobile money service. So our hope is that by the end of this session, you’ll have a clear understanding of the process that’s used to develop prices and commissions, as well as some useful tips and benchmarks. So this imaginary service we’ll be working on is going to be called MMU-PESA, and we’ll be looking at it from the perspective of a mobile operator who will be launching it. This exercise is going to start off with what may seem like some pretty basic stuff, but its going to be important to cover off as things will get increasingly complex as we progress. So do bear with us. Before we jump in, just one quick housekeeping note: Please type in your questions in the box on the right hand side of your screen. Neil/Yasmina will be responding to them as they’re posted, and we’ll pause after each section to come back to any unclear concepts. And of course remember that your identity will remain anonymous. So let’s get started then with our segment on pricing. And we’ve deliberately put pricing as the first section in this webinar, because its really the starting point in this process.
  • So there are many ways to price a service, and the one we’re going to use is the value pricing approach. And to use the value pricing approach, we’ll need to understand – and actually assign a dollar figure – to two variables: the customer’s perceived value of our service, and our cost of goods sold. Basically the customer’s perceived value is going to form the upper boundary for our price – if we set a price any higher than this, customer’s won’t have an incentive to buy. And our cost of goods sold is going to be the lower boundary for our price – if we set a price any lower than this, we’re not, as a mobile operator, going to have any incentive to offer the service. So really, we’ll know we’ve landed on an acceptable price when we’re somewhere higher than cost of goods sold, and lower than perceived value. By way of process, it makes sense to start on the left hand side of this equation – by creating a price based on customer’s perceived value, and then checking that price against our costs to ensure its higher. If we go in this order, we can make sure we’re pricing our service to capture maximum value, and not just working up from our costs. So let’s think about our imaginary service. To understand the value customers might see in MMU-PESA, we need to first understand the range of existing alternatives that they have to send money. Ultimately, its these formal – and informal – alternatives that they’re already be using that will dictate how much value they see in our service. If we were launching a service in a world where there were no formal or informal alternatives, we wouldn’t have to go through this exercise. But unfortunately there’s no market in the world where that’s the case.
  • In our imaginary market, there’s a whole host of alternatives for money transfer. But let’s assume we’ve done some analysis, and really to keep this exercise simple, there’s only two that we think are relevant: a formal service called Pesagram, and an informal method of sending money – using bus drivers. So let’s evaluate each by looking at the table at left. We can see that Pesagram offers customers wide distribution, and quick and reliable delivery, but this comes at a price: they charge 8% as a fee for any amount transferred. The graph that you see on the right illustrates this cost: along the ‘x’ axis, we have the value of money that is being sent, and along the ‘y’ axis we have the total fee for sending money. So the line in red plots the price a customer pays, in this case a rate of 8%, to send between $1 dollar and $100 dollars. Next we look at the bus driver option. We see that compared to Pesagram, they have extremely limited distribution, their pretty slow, and not surprisingly very unreliable. In line with this, bus drivers usually just take a bribe of $1.50 – regardless of the amount of money that’s being sent. So you can see this expressed as a cost on the graph at right as the flat blue line. So what does this mean for perceived value?...[SWITCH]
  • ... Well now we need to compare our service to these alternatives: We think eventually we’ll have better distribution than Pesagram, but this will take some time to materialize – and for a while, they’ll actually beat us on this dimension. And we can’t really beat them on speed or reliability. So for a customer to see value in our service, its going to have to be priced cheaper than Pesagram. So now we can start to create our window within which we might price our service, and so far it looks something like this. [SWITCH]
  • ... But surely the window shouldn’t go down to zero. Because if we compare our service with the bus driver alternative, we see that we’re faster and more reliable. So it’s reasonable to think we can be a bit more expensive than them and still have customers see value in our service. So we can raise the bottom of our pricing window to somewhere above the bus driver’s rate.
  • So it looks like a price at which customer’s will perceive value in our service is somewhere above the bus driver’s rate, and below Pesagram’s rate.
  • So this gives us an idea on how to value our service, but we still need to decide how we’ll structure our tariff. And we’ve already seen that in our market, there are a few different options to choose from. One of the models that we saw is the flat-rate model; this was used by the bus driver. With this approach, you simply charge the customer one fixed dollar amount regardless of how much they transfer. Another model that we saw is the percentage-based model; this was used by Pesagram. With this approach, you charge the customer the same fixed percentage regardless of how much they transfer. One model that we haven’t seen yet is something called the tiered model. This is one that we’ll be talking about in the slides to come.
  • So which of these makes sense for us? Well, each has advantages and disadvantages. Flat Rate Model: The advantage of the flat rate model is that it’s clearly the simplest. Every customer can understand a service’s price when its just a single number. But there’s a serious drawback to mention: It’s difficult to set one price that’s competitive for low value transactions, and at the same time capture maximum value for high-value transactions. So think about the bus driver in our market: he charges $1.50 regardless of the amount transferred. You can imagine that this might actually be an expensive rate if I only wanted to send $5 or $10. On the other hand we know from Pesagram that customers are actually willing to pay a higher fee to send larger amounts of money. So really the bus driver is leaving value on the table by not charging more for higher value transactions. Percentage Based Model So next let’s look at the percentage based model. [SWITCH]
  • Clearly this model allows you to capture more value from high value transfers – so this addresses the drawback of the flat-rate model. Some people argue its other advantage is simplicity. Now whether consumers can actually do percentage calculations in their head is debatable, but either way, this model has two serious weak points:The first is for low value transactions. Operators who’ve used this model for mobile money find that it’s difficult to generate enough revenue from low-value transactions to adequately compensate agents for their time. In other words, an agent will be fine to earn, say, 1% for doing a $50 cash-in. But they may not be as happy to earn the same amount from a $5 cash-in. The second weak point occurs for high-value transactions. Here, the point is that the service is not likely to be competitive on price if you’re using one percentage price across all transaction values. In other words, its hard to put a stake in the ground and say 8% is our fee and be competitive at the very high end of transfers. [SWITCH]
  • So the third approach we’d like to introduce is something called the tiered model. With this approach, the MNO creates a series of pricing tiers that change according to value transferred. For instance, a customer might pay $0.50 for transactions between A and B, $1 between B and C, and $2 between C and D. The benefit here is that you can capture just about maximum value on high value transfers, and you can also generate enough income from low-value transactions to keep your agents happy.
  • And what we see in practice, really, is that most operators are choosing or evolving towards the tiered pricing model. If you take a look at the tariff guides for many leading deployments in Africa and Asia, you’ll see that they all use some form of tiered pricing.
  • So far we’ve covered off valuing the service and one structural decision. But the other structural decision we need to make is what transactions we’re going to charge for. Generally speaking, we see most deployments charge customers only for what we’ll call ‘value-creating’ transactions. So if we think about an end-to-end P2P transfer, we can look at each of the transactions and pick out the ones that are value creating as opposed to the ones that are simply technical. The first step in the process is cash-in. And really this is just a technical transaction. A customer has simply traded his physical cash for the same amount of electronic value – but really nothing else has happened yet. So typically operators avoid charging for cash-in if they can. But next, when the customer transfers that electronic value to his mother, that’s value creation. It’s a money transfer, and people pay for those all the time; so that’s something you can charge for. And then finally when his mother converts that e-money into cash, which is a currency that’s useful for buying things, that’s value creation again. So here again, you can justify a fee. In practice, we see that most mobile money deployments do not charge for cash-in, but do charge for P2P transfers, and for cash-out transactions as these are the ones that create value.
  • Okay so with all this in mind, we can probably sit down and create a tariff for MMU-PESA. And we can do so with a few guidelines in mind...
  • So here we have our tariff development worksheet. The table on the left hand side is our empty tariff sheet, and the graph you see on the right is the same one you saw earlier that plots our competitors. I’ve started things off by laying out the structure for our tariff. You can see that we’re going to use the tiered model, and that we’ve got three tiers – the first is from 0-35, the second from 36-70, and the third from 71 and above.
  • So let’s fill in some fees. We know we don’t want to charge customers a fee for cash-in, so let’s make that zero. Beyond that, we know our other constraint is that we need to be cheaper than Pesagram, but that we can be more expensive than the bus driver. So we fill in some prices...
  • ... And we end up with a tariff sheet that prices our service somewhere in our acceptable zone: less than Pesagram, but more expensive than the bus driver. And you can see that by using tiers, we’re capturing more value from high-value transactions than we would have by using a flat rate.
  • But our tariff sheet isn’t done yet. One other decision we need to make is whether we’ll allow MMU-PESA customers to send money to unregistered customers. And really, the choice is clear. Our market is fragmented, and for P2P transfer to be valuable, customers will need to be able to send money to anyone. In fact, we can look at this as an opportunity: we can build in a price premium for the opportunity to send money to an unregistered customer. And we can think of this price premium as our way of making sure that no matter how customers use our service, we always win. If they send to another registered customer, we capture value by having two subscribers less likely to churn. If they send to an unregistered customer, we capture value by charging a higher margin.
  • So let’s go back to the tariff we’ve been working on...
  • And let’s add in some new rows: these will be for the prices to send to an unregistered customer.
  • So now we just need to fill in some prices. And we know that we should make the price to send to an unregistered customer a bit higher to capture maximum value, so let’s do that. So here we are. You can now see our prices to send money to registered customers, and to unregistered customers.
  • The last step in our process is to inspect our tariff sheet for ways that customers might defraud us. And actually, there are two ways that we’re currently vulnerable. [SWITCH]
  • The first type of fraud we’re vulnerable to is a “direct deposit”. A direct deposit occurs when the customer initiating a P2P transfer hands an agent cash, but provides them with the mobile number of the recipient rather than their own in an effort to avoid paying a transfer fee. In our current set of tariffs, the P2P transfer fee itself accounts for as much as 85% of the end-to-end cost of making a transfer. So the customer is going to have a lot of incentive to try and avoid this fee – we’re going to need to change this. [SWITCH]
  • The second type of fraud we’re vulnerable to is a ‘split transaction’. A split transaction occurs when one transaction is divided into multiple smaller ones to minimize fees. In our current tariffs, we see that a registered customer could actually withdraw, say, $60, in two separate transactions at a cost of $.50 instead of all at once for a cost of $1.25.
  • Okay so let’s go back to our tariff sheet....
  • And erase all the work we’ve done so far... and let’s start from scratch.
  • So after we’ve re-thought our prices with this new information in mind, let’s fill in some new ones. This time, to make sure that customers can’t split transactions, we’re going to make sure that each progressive interval tier is double the last one, and we’re going to make sure that the fees for each progressive tier increase by less than double. So you can see our tiers go from 1-35, then double that 36-70, etc. And you can see our fees go up by a little bit less than double – from $1.75 to $3 to $5. And in this way, we are minimizing incentive to split transactions. We also make sure this time, that our P2P transfer fee (which you see here) is a relatively low value to discourage direct deposits. Before it counted for up to 85% of the total cost of our P2P transfer Now we’re going to keep it below 50% of the total end-to-end cost. And just to be safe, we’re also going to add some fine print into our tariff sheet reminding customers that they can only deposit funds into their own account, not somebody else’s. So after all this, we end up with a set of prices that we’re pretty happy with.
  • To conclude this segment, let’s take a look at our final tariff sheet. We see that it’s...
  • In this segment, we’ll start with the basics of mobile money agent commissions. We’ll then examine each of the variables that impacts agent profitability and provide some real world examples of how deployments have gone about maximising them. We’ll also, of course, be creating a set of commissions for MMU-PESA.
  • So some people wonder why we need to pay our agents at all. To answer this question, let’s think through everything customers rely on agents to deliver, and what each implies from an agent’s perspective. In many cases, agents are asked by mobile operators to register customers and educate them on how to use the service. And this takes a lot of time: one East African deployment estimates that it takes 30 minutes to teach a customer how to use their service. So if agents aren’t paid for an activity like this, they’re unlikely to offer up their staff’s time to fill out forms and educate customers. Agents are also asked to sell e-money to customers every time a customer wants to cash-in. But for agents to deliver this service, they need to tie up their valuable working capital in an e-money account. And there’s an opportunity cost here because that’s working capital the agent otherwise could have invested somewhere else. On the other hand agents are asked to buy e-money from customers every time a customer wants to cash-out. But to do this, agents need to carry an inventory of physical cash – and this is often easier said than done, or in some cases actually quite dangerous. And finally, agents are asked to create channel visibility for the service. Customers want to see clearly marked tariff posts on the walls, and they want to be able to easily spot an agent from the street. But in many cases, agent wall space is valuable – and if mobile money isn’t an important enough business, there’s usually someone else ready to pay them for their space. So as a general principle, we’re going to need to pay our agents in a way that’s commensurate with the time it takes them to do an activity, and the money they must invest in float. We’re also going to need to pay agents even for the activities we aren’t charging customers for. We’ll come back to these principals in a minute when we design commissions for MMU-PESA.
  • But first, there’s one other concept to cover off: and that is how the economics of being a mobile money agent differ from being an airtime retailer. In many cases, one of the first questions a mobile operator will be asked by agents when presenting a service is how the business is the same or different from selling airtime, which is something they’ll probably have done for years. So before designing a set of commissions it’s important to understand these differences, and there are three important ones: First, the cash flows are different for selling airtime and offering mobile money. When it comes to airtime, an agent simply buys a stock of cards at a discount, and as soon as he’s sold them all he’s earned back his principal as well as his profit margin. But for mobile money, agents often have to wait for some time to be paid their commissions. So there’s a delay here that some agents won’t be familiar with. The second difference is that, in some cases, the restocking frequency for mobile money is lower than for airtime. For airtime, once an agent has sold all of his scratch cards, he’s left with a pile of cash, but he can’t in turn sell that pile of cash as more airtime – he’s out of inventory. With mobile money, on the other hand, there are some instances where agents will both buy e-money from customers and sell e-money to customers in some with amount of balance. And the more balance there is between buying and selling, the less need an agent will have to restock inventory. And finally, the foot traffic benefits associated with offering mobile money are different from those of selling airtime. In most markets, airtime is a ubiquitous service – nearly every retailer offers it. Because mobile money will be less widely available for at least some time, its reasonable to think that agents will benefit in a unique way from foot traffic whereas they wouldn’t in most cases from selling airtime. Of course, please note that we assume in this exercise that the benefit of ‘foot traffic’ is not a compelling enough reason alone for agents to offer mobile money. We assume that an agent must be profitable on the basis of transaction revenues for him to offer a mobile money service.
  • So its clear that for agents, offering mobile money is incredibly different from selling airtime. It probably makes sense, then, to start with the basics and understand each of the factors that will impact an agent’s profitability: And I’ve been very careful to use the word “profit” here, and not simply “commission”. Because as we’ll see in just a minute, the commissions that we’ll lay out in our strategy for MMU-PESA are actually just one component of a broader equation that impacts whether agents earn a good return from providing mobile money, and in turn, are happy and engaged. Along the left, you can see that we’ve listed five different variables. Each of these variables impacts the profitability of an agent, and the way in which it does is laid out in the equations along the right. Broadly speaking, an agents profitability is a function of his profit margin times his asset turnover. Or, put another way, its equal to his commissions minus his restocking costs, divided by his investment, which for mobile money is his pool of float. For the purposes of the next couple slides we’ll use the formula at the bottom to run our scenario analysis. It’s important to note that this formula really just approximates reality. It’s not 100% real-world perfect, but will give us a good stylised way of seeing how these variables work. If you find any of these equations confusing, don’t worry: all you really need to understand are the variables that underpin them and what ‘good’ looks like for each one. The first variable is float: this is the amount of e-money and/or physical cash an agent must have on hand to be able to transact [what’s good] The second variable is restocking cost: this is the cost an agent incurs to restock his cash or e-money float balance. [what’s good] The third variable is volume of transactions: this is the volume of cash-in/cash-out transactions performed each day by an agent. [what’s good] The fourth variable is average commission value: this is the average commission earned for performing cash-in/cash-out transactions [what’s good] The fifth variable is average transaction value: this is the average value of cash-in/cash-out transactions performed by customers.
  • That’s the entire list of variables, but really most providers start the process by simply taking a crack at one of them: commissions. So let’s go back to our example and try to create some of our own. We won’t be too stringent with our guidelines: we’ll just say that the value of our commissions needs to be low enough that we, as a mobile operator, are earning an acceptable profit, and they must be high enough that the agent is also earning an acceptable profit. And by way of structure, we know that we’re going to have to pay our agents for every activity that they perform.
  • So if we create a new column beside our tariff sheet, we see that we’re going to need to pay agents for accepting deposits, and for processing withdrawals. There’s nothing for an agent to do in terms of a P2P transfer, so we don’t need to pay them for that. And you can note that for simplicity, we’re just assuming that an agent gets paid the same commission whether they’re serving a registered or unregistered customer – so we won’t fill in those blanks – we’ll just use the registered figures.
  • So we do some analysis, and as a first pass, we fill out some commissions. And the first thing we do is make sure that we’re going to be profitable, end-to-end, for a P2P transfers. And as you can see from the graph on the right, we are indeed: the line you see is our margin: it’s the sum of fees charged to send at each value, minus commissions paid at each value. You can see we’re always somewhere between 45% and 65%. This is generally in line with industry averages: we see most MNOs earning between 45% and 60% margins here.
  • So the next thing we check is whether our agents are making any money. But unfortunatelyit looks like they’re not – when we run the numbers using the variables at the bottom, it looks like our agents are earning a negative return on assets, and losing money each day by offering this service.
  • So what can we do? Well, let’s go back to our agent commissions table...
  • ... and let’s jack up the commissions – because we need to find a way for our agents to make money. So let’s fill in some new commissions, and let’s basically triple our old ones. So now agents are going to earn $.90 for accepting deposits, and between $1.80 and $7.20 for processing withdrawals.
  • ... and we look again at our agents and not surprisingly they’re making money... So that’s good. We see they’re earning a huge return on assets, 131%, and a daily profit of $3.60. So that’s not bad – we’re in the black.
  • but the bad news is, now we’re losing money. And you probably could have eyeballed this by just comparing our fees and commissions.
  • So it looks like we’ve got a problem. We can’t seem to find a rate where our agents are profitable and so are we. So what are our options? Well as a mobile operator, we have more control over some of the agent profitability variables than others. We’ve got complete control over the average commission value, but as we’ve just established, playing with that variable hasn’t been enough. There’s not much we can really do about customer’s average transaction values – we might be able to shape them by the prices we charge, but let’s focus on the low-hanging fruit for now. This leaves us with three variables then: float, restocking cost, and volume of transactions, all of which are at least somewhat in our control. So to inspire our thinking a bit about how we might augment our approach for MMU-PESA, let’s look at some real world examples of how deployments have influenced these three variables.
  • The first example we’ll look at comes from Asia. And in this scenario, we examine a mobile operator who has recently launched a mobile money service And their strategy has been basically to reduce the restocking cost and amount of float that its agents must hold, by tasking their own existing airtime sales representatives with visiting agents on a regular basis. Every time an airtime sales rep visits an agent, they rebalance that agent’s float – either by loading him up with physical cash, or loading him up with e-money. By implementing this model, what the MNO has done, is they’ve transferred the restocking cost away from each individual agent, and said ‘we’re going to take responsibility for this activity’ as the mobile operator. And you can understand why they might do this: the MNO already has a huge team in the field – and they’re in a position to rebalance float more efficiently than most agents would on an individual basis. Of course, the trade-off they might ask an agent to make in exchange, is to accept a lower commission than they otherwise might have given that they no longer bear this restocking cost.
  • So with this in mind, let’s come back to our example. Currently our agent’s restocking cost if $15. This includes the cost of a bus ride he takes into town to get cash at a bank branch, and it also includes the opportunity cost he’s incurred by closing his shop and missing out on sales...
  • ... So if we were able to all but eliminate restocking cost for him, and in turn pay the commissions we originally wanted to, we see that this agent would actually become profitable, and so would we. When we reduce restocking cost from $15 to $1, we see this agent earn a 40% return on assets, and earn a daily profit of $1.10.
  • Let’s look at another example. This example comes Celpay, which is a mobile money service operating in Zambia.Celpay has basically sought to reduce the amount of float that its agents need to hold by creating customized minimum liquidity requirements: $1500 for agents that operate in the main city of Lusaka, and $500 for agents that operate in the countryside. They customize their minimum liquidity thresholds because they know that some agents will see higher transaction volumes than others – and therefore will need more float. They also know that some urban agents will have an easier time tying up money in float than a rural one might.
  • ... So if we made a similar change for our imaginary agent, and reduced the float level from $1000 to $800...
  • We’d see that his daily profit stays pretty much the same, but his return on assets increases from 40% to 49%. So we’ve made this agent’s life better by offering him a better return on his assets.
  • So now with our float requirements and restocking cost in order, it’s time to do perhaps the most important thing of all: market the service to drive transaction volumes to the agent. There’s no secret here – one of the most important variables in this equation is the volume of transactions an agent sees: if there’s no volume, nothing else matters. So let’s assume that we invest a good amount of money into marketing now...
  • And what we’d see is our volume of transactions increase from 2 per day to 30 per day.
  • And of course our agent’s return on assets and daily profit are through the roof.
  • Conclusion
  • Transcript

    • 1. GSMA Webinar Mobile Money Pricing & Commissions
      “We are currently waiting for all participants to join and will begin the webinar shortly. If you have specific questions you’d like to answer via this webinar, feel free to send us a confidential message now.”
    • 2. Agenda
      Segments
      Our Task:
      1. Pricing a mobile money service
      9:00-9:45
      Task: design a tariff sheet and set of agent commissions.
      A. Valuing the service
      B. Structuring the tariff sheet
      C. Proofing against fraud
      Service: MMU-PESA, a new offering targeted at the unbanked
      Questions & Answers
      Features: Domestic P2P transfer
      Provider: Mobiphone, a GSM operator with 30% market share.
      9:45-10:30
      2. Setting mobile money commissions
      Country: Mobiland, a country with 20% bank penetration, and 4 competing mobile operators.
      A. Commissions 101
      B. Overview of agent profitability drivers
      C. Influencing agent profitability
      Questions & Answers
      *If you as a question, you will remain anonymous to the group*
    • 3. Valuing the service
      Value-pricing approach
      >
      >
      Price
      Customer’s Perceived Value
      Cost of Goods Sold
      What is the objective willingness to pay?
      What price must we charge to sustain our channel strategy?
      1
      3
      How cheap or expensive is the next best formal or informal alternative?
      What price must we charge to cover other variable costs?
      2
      4
    • 4. Valuing the service
      Cost of P2P transfer using existing alternatives
      P2P transfer alternatives in Mobiland
      Speed
      # Outlets
      Reliability
      Service
      Price
      Pesagram
      1,000
      Instant
      High
      8%
      Fee ($)
      Bus Driver
      80
      2-Day
      Low
      $1.50
      Value Transferred ($)
    • 5. Valuing the service
      Cost of P2P transfer using existing alternatives
      P2P transfer alternatives in Mobiland
      Speed
      # Outlets
      Reliability
      Service
      Price
      Pesagram
      1,000
      Instant
      High
      8%
      Fee ($)
      Bus Driver
      80
      2-Day
      Low
      $1.50
      500 ...
      ...10,000
      High
      ?
      MMU-PESA
      Instant
      Value Transferred ($)
    • 6. Valuing the service
      Cost of P2P transfer using existing alternatives
      P2P transfer alternatives in Mobiland
      Speed
      # Outlets
      Reliability
      Service
      Price
      Pesagram
      1,000
      Instant
      High
      8%
      Fee ($)
      Pricing
      Window
      Bus Driver
      80
      2-Day
      Low
      $1.50
      500 ...
      ...10,000
      High
      ?
      MMU-PESA
      Instant
      Value Transferred ($)
    • 7. Valuing the service
      Cost of P2P transfer using existing alternatives
      P2P transfer alternatives in Mobiland
      Speed
      # Outlets
      Reliability
      Service
      Price
      Pesagram
      1,000
      Instant
      High
      8%
      Fee ($)
      Pricing
      Window
      Bus Driver
      80
      2-Day
      Low
      $1.50
      500 ...
      ...10,000
      High
      ?
      MMU-PESA
      Instant
      Value Transferred ($)
    • 8. Structuring the tariff sheet
      Flat-Rate
      Tiered
      Percentage-Based
      1
      3
      2
      Model
      Transaction Fee
      Transaction Fee
      Transaction Fee
      Transaction Value
      Transaction Value
      Transaction Value
      In Mobiland...
      Bus Driver
      $1.50
      Pesagram
      8%
      Not in use
    • 9. Structuring the tariff sheet
      Flat-Rate
      Tiered
      Percentage-Based
      1
      3
      2
      Model
      Transaction Fee
      Transaction Fee
      Transaction Fee
      Transaction Value
      Transaction Value
      Transaction Value
      Advantages
      • Simpler
      Disadvantages
      • Difficult to remain competitive on price for low-value transactions
      • 10. Difficult to generate enough revenue from high value transactions to satisfy agents
    • Structuring the tariff sheet
      Flat-Rate
      Tiered
      Percentage-Based
      1
      3
      2
      Model
      Transaction Fee
      Transaction Fee
      Transaction Fee
      Transaction Value
      Transaction Value
      Transaction Value
      Advantages
      • Simpler
      • 11. Captures more value
      • 12. Simpler in some markets
      Disadvantages
      • Difficult to remain competitive on price for low-value transactions
      • 13. Difficult to generate enough revenue from high value transactions to satisfy agents
      • 14. Difficult to generate enough revenue from low value transactions to adequately compensate agents
      • 15. Difficult to remain competitive on price for high value transactions.
    • Structuring the tariff sheet
      Flat-Rate
      Tiered
      Percentage-Based
      1
      3
      2
      Model
      Transaction Fee
      Transaction Fee
      Transaction Fee
      Transaction Value
      Transaction Value
      Transaction Value
      Advantages
      • Captures more value
      • 16. Easier to satisfy agents
      • 17. Simpler
      • 18. Captures more value
      • 19. Simpler in some markets
      Disadvantages
      • Difficult to remain competitive on price for low-value transactions
      • 20. Difficult to generate enough revenue from high value transactions to satisfy agents
      • 21. Less simple
      • 22. Difficult to generate enough revenue from low value transactions to adequately compensate agents
      • 23. Difficult to remain competitive on price for high value transactions.
    • Structuring the tariff sheet
      Flat-Rate
      Tiered
      Percentage-Based
      1
      3
      2
      Model
      Transaction Fee
      Transaction Fee
      Transaction Fee
      Transaction Value
      Transaction Value
      Transaction Value
    • 24. Structuring the tariff sheet
      Cash-in
      P2P Transfer
      Cash-out
      Value-creating?
      Value-creating?
      Value-creating?
      Charge Fee?
      Charge Fee?
      Charge Fee?
      Best practice: charge only for ‘value-creating’ transactions
    • 25. Creating a tariff sheet for MMU-PESA
      Guidelines
      Structure
      Value
      Tiered pricing structure
      Only charging for value-creating transactions
      Cheaper than Pesagram
      More expensive than the bus driver
    • 26. MMU-PESA – Tariff Sheet
      Fee ($)
      Value Transferred ($)
    • 27. MMU-PESA – Tariff Sheet
      Fee ($)
      Value Transferred ($)
    • 28. MMU-PESA – Tariff Sheet
      Fee ($)
      Value Transferred ($)
    • 29. Structuring the tariff sheet
      Mobiland Mobile Market Share
      GPRfone
      X
      Mobiphone
      Cellfone
      24%
      17%
      50%
      9%
      “When a money transfer is between two registered customers, those are two customers who are less likely to churn.
      Registered Customer
      P2P Transfer
      “When a money transfer is sent to an unregistered customer, we earn a higher margin.
      P2P Transfer
      Unregistered Customer
    • 30. MMU-PESA – Tariff Sheet
      Fee ($)
      Value Transferred ($)
    • 31. MMU-PESA – Tariff Sheet
      Fee ($)
      Value Transferred ($)
    • 32. MMU-PESA – Tariff Sheet
      Fee ($)
      Value Transferred ($)
    • 33. Scanning for risks
    • 34. Scanning for risks
      Direct Deposit
      1
      “Occurs when the customer initiating a P2P transfer hands an agent cash, but provides them with the mobile number of the recipient rather than their own in an effort to avoid paying a transfer fee.”
    • 35. Scanning for risks
      Direct Deposit
      1
      “Occurs when the customer initiating a P2P transfer hands an agent cash, but provides them with the mobile number of the recipient rather than their own in an effort to avoid paying a transfer fee.”
      Split Transaction
      2
      “Occurs when a cash-in, cash-out or bill payment is split into multiple smaller ones to minimize fees.”
    • 36. MMU-PESA – Tariff Sheet
      Fee ($)
      Value Transferred ($)
    • 37. MMU-PESA – Tariff Sheet
      Fee ($)
      Value Transferred ($)
    • 38. MMU-PESA – Tariff Sheet
      Fee ($)
      All deposits must be made into a customer’s own account.
      Value Transferred ($)
    • 39. Pricing Summary
      Attributes
      MMU-PESA Tariff Sheet
      Priced according to perceived value
      1
      Structured using tiers
      2
      Option to send to unregistered recipients
      3
      Fees only applied to ‘value creating’ transactions
      4
      Minimal risk of direct deposits
      5
      Minimal risk of transaction splitting
      All deposits must be made into a customer’s own account.
      6
    • 40. Agenda
      Segments
      Our Task:
      1. Pricing a mobile money service
      9:00-9:45
      Task: design a tariff sheet and set of agent commissions.
      A. Valuing the service
      B. Structuring the tariff sheet
      C. Proofing against fraud
      Service: MMU-PESA, a new offering targeted at the unbanked
      Questions & Answers
      Features: Domestic P2P transfer
      Provider: Mobiphone, a GSM operator with 30% market share.
      9:45-10:30
      2. Setting mobile money commissions
      Country: Mobiland, a country with 20% bank penetration, and 4 competing mobile operators.
      A. Commissions 101
      B. Overview of agent profitability drivers
      C. Influencing agent profitability
      Questions & Answers
      *If you as a question, you will remain anonymous to the group*
    • 41. Commissions 101: do agents even need to be paid? what for?
      Help me register! And teach me!
      That takes up my staff’s time.
      Sell me e-money!
      That’s working capital I need to tie up in e-float.
      Buy my e-money!
      Holding cash is costly and risky.
      Show me a tariff poster!
      My wall space is very sought after.
      Principal: pay agents for every activity they perform, even if the MNO does not charge the customer a fee.
    • 42. Commissions 101: how are the economics different from airtime?
      Airtime
      Mobile Money
      “As soon as I sell all my scratch cards, I’ve earned back my principal and also my profit margin.”
      “When I sell my e-money, I’ve made my principal back, but don’t get paid commissions until end of month.”
      Cash Flows
      “Once my airtime is sold, it’s gone. I can’t make money by accepting someone else’s and reselling it.”
      “For every cash-in transaction I perform, I can do a cash-out in turn; this means restocking less often.”
      Restocking
      Frequency
      “Everyone on my street sells airtime – I get no major lift in sales from selling this product.”
      “Selling mobile money differentiates my business – it generates additional foot traffic.”
      Foot Traffic
    • 43. Overview of agent profitability drivers
      What are the variables that drive an agent profitability equation?
      What is the formula that determines agent profitability?
      Float
      1
      x
      the amount of e-money and/or physical cash an agent must have on hand to transact.
      Profit Margin
      Asset Turnover
      Restocking cost
      2
      or
      the cost an agent incurs to restock his cash or e-money float balance.
      -
      Commissions
      Restocking Costs
      Volume of transactions
      3
      Float
      the volume of cash-in/cash-out transactions performed each day by an agent.
      *
      or
      Average commission value
      4
      )
      (
      )
      (
      the average commission earned for performing cash-in/cash-out transactions.
      -
      avg. trans value x # of transactions
      -
      avg. commission value
      restocking cost
      x
      float
      avg. trans value
      float
      Average transaction value
      5
      the average value of cash-in/cash-out transactions performed by customers.
      *
      Assumptions:
      • The agent performs only one type of transaction (cash in or cash out), not a mix
      • 44. The agent incurs no labour costs
      • 45. Every transaction is the same average value, and the agent depletes her stock of float completely before restocking
    • Creating agent commissions for MMU-PESA
      Guidelines
      Structure
      Value
      Agents need to be paid for every activity
      Low enough such that MNO earns acceptable margin
      High enough such that agent earns acceptable profit/ROA
    • 46. MMU-PESA – Agent Commissions
      All deposits must be made into a customer’s own account.
    • 47. MMU-PESA – Agent Commissions
      MNO Profitability
      All deposits must be made into a customer’s own account.
    • 48. MMU-PESA – Agent Commissions
      Agent Profitability
      Return on assets
      Daily profit
      (11%)
      (.30)
      Variables
      Float
      Restocking cost
      Volume of transactions per day
      Average commission value
      Average transaction value
      $1,000
      $15
      2
      $60
      $50
      All deposits must be made into a customer’s own account.
    • 49. MMU-PESA – Agent Commissions
      All deposits must be made into a customer’s own account.
    • 50. MMU-PESA – Agent Commissions
      All deposits must be made into a customer’s own account.
    • 51. MMU-PESA – Agent Commissions
      Agent Profitability
      Return on assets
      Daily profit
      131%
      $3.60
      Variables
      Float
      Restocking cost
      Volume of transactions per day
      Average commission value
      Average transaction value
      $1,000
      $15
      2
      $0.60
      $50
      All deposits must be made into a customer’s own account.
    • 52. MMU-PESA – Agent Commissions
      All deposits must be made into a customer’s own account.
    • 53. Overview of agent profitability drivers
      What are the variables that drive an agent profitability equation?
      MNO Influence
      Agent Perspective
      Float
      “the less float I need to hold, the less amount I have tied up in working capital”
      1
      the amount of e-money and/or physical cash an agent must have on hand to transact.
      Restocking cost
      “the less time and money I spent balancing float, the better”
      2
      the cost an agent incurs to restock his cash or e-money float balance.
      Volume of transactions
      “the more transactions I process, the more I earn”
      3
      the volume of cash-in/cash-out transactions performed each day by an agent.
      Average commission value
      “the higher commissions I earn for each transaction, the better”
      4
      the average commission earned for performing cash-in/cash-out transactions.
      Average transaction value
      “the more transactions of a profitable value, the better”
      5
      the average value of cash-in/cash-out transactions performed by customers.
    • 54. Influencing agent profitability drivers
      What are the variables that drive an agent profitability equation?
      Tactic #1: Leverage airtime distribution network to rebalance liquidity for agents on a regular basis.
      Float
      1
      the amount of e-money and/or physical cash an agent must have on hand to transact.
      VISIT SCHEDULE
      Restocking cost
      2
      the cost an agent incurs to restock his cash or e-money float balance.
      Volume of transactions
      3
      the volume of cash-in/cash-out transactions performed each day by an agent.
      Average commission value
      4
      the average commission earned for performing cash-in/cash-out transactions.
      Average transaction value
      5
      the average value of cash-in/cash-out transactions performed by customers.
    • 55. MMU-PESA – Agent Commissions
      Agent Profitability
      Return on assets
      Daily profit
      (11%)
      (.30)
      Variables
      Float
      Restocking cost
      Volume of transactions per day
      Average commission value
      Average transaction value
      $1,000
      $15
      2
      $0.60
      $50
      All deposits must be made into a customer’s own account.
    • 56. MMU-PESA – Agent Commissions
      Agent Profitability
      Return on assets
      Daily profit
      40%
      $1.10
      Variables
      Float
      Restocking cost
      Volume of transactions per day
      Average commission value
      Average transaction value
      $1,000
      $1
      2
      $0.60
      $50
      All deposits must be made into a customer’s own account.
    • 57. Influencing agent profitability drivers
      What are the variables that drive an agent profitability equation?
      Tactic #4: Create different sets of liquidity requirements according to likely volume.
      Float
      1
      the amount of e-money and/or physical cash an agent must have on hand to transact.
      Restocking cost
      2
      the cost an agent incurs to restock his cash or e-money float balance.
      Volume of transactions
      3
      the volume of cash-in/cash-out transactions performed each day by an agent.
      Capital City
      Countryside
      Region
      Average commission value
      4
      the average commission earned for performing cash-in/cash-out transactions.
      Liquidity
      Requirement
      $1,500
      $500
      Average transaction value
      5
      the average value of cash-in/cash-out transactions performed by customers.
    • 58. MMU-PESA – Agent Commissions
      Agent Profitability
      Return on assets
      Daily profit
      40%
      $1.10
      Variables
      Float
      Restocking cost
      Volume of transactions per day
      Average commission value
      Average transaction value
      $1,000
      $1
      2
      $0.60
      $50
      All deposits must be made into a customer’s own account.
    • 59. MMU-PESA – Agent Commissions
      Agent Profitability
      Return on assets
      Daily profit
      49%
      $1.10
      Variables
      Float
      Restocking cost
      Volume of transactions per day
      Average commission value
      Average transaction value
      $800
      $1
      2
      $0.60
      $50
      All deposits must be made into a customer’s own account.
    • 60. Influencing agent profitability drivers
      What are the variables that drive an agent profitability equation?
      Tactic #6: Market the service to drive up transaction volumes.
      Float
      1
      the amount of e-money and/or physical cash an agent must have on hand to transact.
      Restocking cost
      2
      the cost an agent incurs to restock his cash or e-money float balance.
      Volume of transactions
      3
      the volume of cash-in/cash-out transactions performed each day by an agent.
      Average commission value
      4
      the average commission earned for performing cash-in/cash-out transactions.
      Average transaction value
      5
      the average value of cash-in/cash-out transactions performed by customers.
    • 61. MMU-PESA – Agent Commissions
      Agent Profitability
      Return on assets
      Daily profit
      49%
      $1.10
      Variables
      Float
      Restocking cost
      Volume of transactions per day
      Average commission value
      Average transaction value
      $800
      $1
      2
      $0.60
      $50
      All deposits must be made into a customer’s own account.
    • 62. MMU-PESA – Agent Commissions
      Agent Profitability
      Return on assets
      Daily profit
      736%
      $16.13
      Variables
      Float
      Restocking cost
      Volume of transactions per day
      Average commission value
      Average transaction value
      $800
      $1
      30
      $0.60
      $50
      All deposits must be made into a customer’s own account.
    • 63. Agenda
      Segments
      Our Task:
      1. Pricing a mobile money service
      9:00-9:45
      Task: design a tariff sheet and set of agent commissions.
      A. Valuing the service
      B. Structuring the tariff sheet
      C. Proofing against fraud
      Service: MMU-PESA, a new offering targeted at the unbanked
      Questions & Answers
      Features: Domestic P2P transfer
      Provider: Mobiphone, a GSM operator with 30% market share.
      9:45-10:30
      2. Setting mobile money commissions
      Country: Mobiland, a country with 20% bank penetration, and 4 competing mobile operators.
      A. Commissions 101
      B. Overview of agent profitability drivers
      C. Influencing agent profitability
      Questions & Answers
      *If you as a question, you will remain anonymous to the group*
    • 64. Appendices
    • 65. Influencing agent profitability drivers
      What are the variables that drive an agent profitability equation?
      Tactic #5: Help agents anticipate and prepare for events that will be strains on liquidity.
      Float
      1
      the amount of e-money and/or physical cash an agent must have on hand to transact.
      Restocking cost
      2
      SALARY PAYMENTS
      the cost an agent incurs to restock his cash or e-money float balance.
      Volume of transactions
      3
      the volume of cash-in/cash-out transactions performed each day by an agent.
      Average commission value
      4
      the average commission earned for performing cash-in/cash-out transactions.
      Average transaction value
      5
      the average value of cash-in/cash-out transactions performed by customers.
    • 66. Influencing agent profitability drivers
      What are the variables that drive an agent profitability equation?
      Tactic #2: Create a layer in the distribution system above frontline agents, whose responsibility it is to manage liquidity in exchange for a fee...
      Float
      1
      the amount of e-money and/or physical cash an agent must have on hand to transact.
      Share of
      commission
      Cost of liquidity management
      Restocking cost
      2
      80%
      the cost an agent incurs to restock his cash or e-money float balance.
      Masteragent
      Volume of transactions
      3
      the volume of cash-in/cash-out transactions performed each day by an agent.
      Average commission value
      4
      Agent
      Agent
      100%
      High
      the average commission earned for performing cash-in/cash-out transactions.
      Average transaction value
      Agent
      Agent
      5
      the average value of cash-in/cash-out transactions performed by customers.
    • 67. Influencing agent profitability drivers
      What are the variables that drive an agent profitability equation?
      Tactic #3: Link agent e-wallet accounts with business bank accounts to create rapid, low-cost mechanism for loading e-money.
      Float
      1
      the amount of e-money and/or physical cash an agent must have on hand to transact.
      “Transfer $100 from my bank account to my True Money e-wallet”
      Option-1
      Option-2
      Restocking cost
      2
      the cost an agent incurs to restock his cash or e-money float balance.
      Volume of transactions
      3
      the volume of cash-in/cash-out transactions performed each day by an agent.
      +
      Average commission value
      4
      the average commission earned for performing cash-in/cash-out transactions.
      Average transaction value
      5
      the average value of cash-in/cash-out transactions performed by customers.
    • 68. Benchmarks: fee as a percent of value transferred
      Fee as a % of Value Transferred
      Value Transferred
      Sample includes deployments from East Africa, West Africa, and Asia
    • 69. Benchmarks: premium to send money to unregistered customers
      Premium
      Value Transferred
      Sample includes deployments from East Africa, West Africa, and Asia
    • 70. Benchmarks: transfer fee as a % of end-to-end cost for P2P money transfer
      Transfer Fee as a % of Total
      Value Transferred
      Africa: Ghana, Kenya, Tanzania, Uganda
      Asia: Fiji, Afghanistan
    • 71. Benchmarks: MNO gross margin on P2P transfer to registered customer (sum of fees minus commissions)
      MNO gross margin
      Value Transferred
      Africa: Ghana, Kenya, Tanzania, Uganda
      Asia: Fiji, Afghanistan
    • 72. Benchmarks: Cash-out commission as a % of total commission
      Cash-out commission as % of total
      Value Transferred
      Africa: Ghana, Kenya, Tanzania, Uganda
      Asia: Fiji, Afghanistan