Download - Mobile money market sizing toolkit
CONFIDENTIAL
Mobile Money Market Sizing
Toolkit
1
Mobile Money Toolkit
• Objectives& Definitions
• Market analysis
–Sizing the market (direct & indirect)
–Estimating product mix
–Estimating unbanked access
–Stress-testing the numbers
• Macro tools
–Business plan framework
–Conducting Primary Market Research
• Best practice research guide
• Surveys and facilitator guides
–MMU database
–Market screening frameworks
• Appendix
–Philippines market documents
2
Overview of this document in the context of the toolkit
• This toolkit is designed to help a variety
of organisations conduct research and
analysis about the market for Mobile
Money. The toolkit contains analytical
frameworks, research tools as well as
data to help inform the analytical work
Objectives of the toolkit
Version history
• Version 1.0 was developed in March
2009
Key contacts:
• Mark Pickens
Note: This document is confidential
and should only be used outside
GSMA/CGAP with prior approval
Users of the toolkit
• GSMA/CGAP users looking at particular
markets
• Coffey International in assessing
applicants for funding
• Local market participants may elements
useful
CGAP
3
Key Definitions (1/2)
* Users of remittance services that do not require an account are considered “unbanked”. Note: World bank definition may include this category
Source:Team definitions
Key terms Definition
Emerging
markets
• For MMU purposes any market that has a GDP per capita of less than USD 15,000
Unbanked• Analysis; anyone who does not have formal access to financial services as per
World Bank composite measure in “Finance for all” (see next slide for detailed
definitions)
• Research; anyone who does not have an account of any kind (deposit, cheque,
savings, salary, credit, postbank etc)*
“Previously
” Unbanked
• Users of Mobile Money who had no other access to financial services (i.e. no bank
account of any kind) prior to becoming Mobile Money users
“Otherwise
Unbanked”
• Mobile Money users who have no other formal access to financial services (i.e. no
bank account of any kind)
Unbanked-
mobiled
• People who have no formal access to financial services (i.e. no bank account of any
kind) but who do have access to a mobile phone
Sub $2/day• Income segment of people who earn less than USD2/day per person (not ppp
adjusted)
• Any financial service delivered over a Mobile Phone. Includes Mobile wallet,
p2p,G2p and B2p transfers and remittances, payments (including airtime), savings,
credit, insurance, etc
Mobile
money
4
Key Definitions (2/2)
Source: Team definitions
Key terms Definition
• Segment of users who have some access to financial services (eg a bank account )
but who still rely on informal mechanisms for other financial services (eg borrows
from loan-sharks, save “under the mattress” or rely on informal money transfer
mechanisms)
Under-
banked
5
World bank definition of “Financial Access”
World Bank “Finance For All” – extract
Financial inclusion, or broad access to financial services, implies an absence of price
and non-price barriers in the use of financial services; it is difficult to define and measure
because access has many dimensions. Services need to be available when and where
desired, and
products need to be tailored to specific needs. Services need to be affordable, taking
into account the indirect costs incurred by the user, such as having to travel a long
distance to a bank branch (p.22)
Financial inclusion, or broad access to financial services, is defined here as an absence
of price or non-price barriers in the use of financial services. Of course this does not
mean that all households and firms should be able to borrow unlimited amounts at prime
lending rates or transmit funds across the world instantaneously for a fraction of 1
percent of the amount. Even if service providers are keenly competitive and employ the
best financial technology, prices and interest rates charged and the size of loans and
insurance coverage on offer in a market economy will necessarily depend on the
creditworthiness of the customer (p.27)
It is easier to measure the use of financial services since use can be observed, but use
is not always the same as access. Access essentially refers to the supply of services,
whereas use is determined by demand as well as supply (p.28)
Source: World Bank – “Finance for all”
6
Mobile Money Toolkit
• Objectives& Definitions
• Market analysis
–Sizing the market (direct & indirect)
–Estimating product mix
–Estimating unbanked access
–Stress-testing the numbers
• Macro tools
–Business plan framework
–Conducting Primary Market Research
• Best practice research guide
• Surveys and facilitator guides
–MMU database
–Market screening frameworks
• Appendix
7
There are 4 primary elements in sizing the market
Source: Team analysis
Description Objectives
Sizing the overall
market
• Sizing the direct market potential
– Estimate the number of potential
Mobile Money users
– Bottom-up modelling of overall
ARPU
– Total market revenue potential
• This is the primary methodology for sizing the
Mobile Money market in terms of users and
revenues
A
Estimating the
product mix
• Estimate size of financial service
flows by product category for each
market
• Estimate MM take-up rates & fees
• Calculate the overall revenue
potential and product mix
• This methodology can be used to estimate
relative potential for different mobile money
products and services based on revenue pools
• This approach can also be used as an
alternative method to help size the overall
market revenues by product category
C
Estimating un-
banked “access”
• Estimate how many incremental
people can be provided with
financial access by reducing cost to
serve through Mobile Money
• This approach would primarily be used to
illustrate the potential for extending financial
access to unbanked people
• The approach can also be used as an
alternative method to estimate the size of the
mobile Money revenues and subscribers
D
Sizing the
indirect benefits
• Sizing of the indirect benefits • This section provides a way to estimate the
indirect benefits of Mobile Money to an MNO–
these can be a significant driver of a business
case
B
8
Sizing the direct market potential
Source: Team analysis
• Market analysis to
estimate MM take-up
rates based on similar
markets
• Develop take-up
scenarios based on likely
market development
• Apply take-up rates to the
addressable market, as
well as to the “unbanked”
share of the market
• Validate through market
research if possible
Estimate potential mobile
money usersDerive MM ARPU
Estimate total market
revenues
Steps
End-
products
• Estimate of a range of
total mobile money
subscribers over time
• Top-down: Market
analysis to estimate MM
ARPU as % of total ARPU
based on similar markets
• Bottom-up: Estimate
actual usage per
subscriber of key services
at a given set of pricing
assumptions
• Estimate the total ARPU
per customer
• Validate through market
research if possible
• Estimate of MM ARPU per
subscriber
• Calculate the total market
revenues based on the
expected Mobile Money
users and the expected
ARPU
• Estimate what share of
these revenues each
player in the business
model will capture
(depends on business-
model & product mix –
see “financial service flow
sizing”)
• Break-down of total MM
revenues per player in the
ecosystem
1 2 3
A
9
Low end - Baseline scenario (to be developed locally)
2
7
35Best in class**
26Top segment
7.8Weighted Average
Middle segment
Lower segment
<1Bank models
• Choose an adoption rate
which best applies to
expected local market
conditions
• E.g., The weighted average
of all analysed cases
(7.8%) is applied to all
markets
High end – Aggressive scenario (to be developed locally)
8
26Leaders
Others
• Choose an
aggressive take-up
scenario which is
reasonable
• E.g., Average
adoption rate across
markets after
weighting for
“leadership”: 16.8%
Adoption rates, % Market share,%
MMU take-up rate ranges are derived based on existing
cases and potential market development
* Not included in calculation for average MM adoption rates; adoption rate for bank-led models based on total mobile subscribers in country
** Actual value for best in class MNO, not an average
Source: Press search; company websites; Gartner; Sida; CGAP; Merryll Lynch; McKinsey analysis; Interviews
Estimated take-up rates from case-data
Average adoption rates, %
5248
Asia
5050Africa
5446
Middle
East31
69Americas
4951
Eastern
Europe
Leaders
Others
ILLUSTRATIVE
2
7
35Best in class**
26Top segment
7.8Weighted Average
Middle segment
Lower segment
<1Bank models
A1
10
Adoption rates are applied to banked & unbanked mobile subscribers
to estimate the overall market potential
* Extrapolated based on CAGRs
Source: Informa World Cellular Information Service, Wireless Intelligence
Europe: Eastern
94Middle East
332Africa
260Americas
872Asia Pacific
143
Unbanked Mobile
subscribers 2012*, m
Unbanked Mobile Money
subscribers 2012*, m
Total Mobile subscribers
2012*, m
Mobile Money subscribers
2012*, m
33
49
75
88
15
23
35
41
362168
Africa
446Americas
2,155Asia Pacific
278Europe: Eastern
175Middle East
519
Estimate the total Unbanked Mobile Money subscriber potential by applying
the adoptions rates to total unbanked mobile subscribers per region
Estimate the total Mobile Money subscriber potential by applying each
adoption rate to total mobile subscribers per region
8
12
68
56
44
147
25
20
18
26
A1
16.8High end
7.8Low end
Adoption rates were
applied to the total # of
mobile subscribers
Adoption rates
%
High end
Low end
Estd Global MMU
subs, m
135Low end
290High end
11
* Ovum report shows distribution of transactions form 100-35,000 KSH, tightly bunched around 500-2500 with a long tail
** Safaricom website shows “User-to-User” 30 KSH, “Money-to-Non-User” 75-400 KSH, “Withdraw-cash-from-User” 25-170 KSH; average transaction
of ~500 KSH so assume lowest of flat fees; assume 80% of usage is user-to-user
Source: Ovum Report, Safaricom website, McKinsey Experts, Team Analysis
MM APRU is derived from cases and local market
experience
A2 ILLUSTRATIVE
“Top-down” Derive MM ARPU from reported market data1
1.5
20
5
~15
~0.5
~0.5
• Take total value of transactions (USDB/year)
• Divide by assumed avg transaction size (USD)
• Divide by # users (at time of reporting) (m)
• Output is average # transactions per user per year
• Divide by assumed avg fee per transaction (USD)
• Total users ARPU (USD/month)
“Bottom-up” Build MM ARPU using local market knowledge2
• Take average user’s frequency of usage for each MM
service (# uses/month)
• Weight each frequency by % of users using the service
• Apply average fee per MM service (USD)
• Active users ARPU (USD/month)
• Apply assumed non-active discount (% of total users)
• Total users ARPU (USD/month)
2-4
5-50%
0.1-0.8
1.9
~60%
~1.0
MMU ARPU,
USD/month
1.0High end
0.5Low end
12
This allows us to estimate the
total MMU market value
The MMU subscribers and ARPU for each scenario drives
a total market revenue estimate for a given market
Total MMU market size*
USDb/year
3.5High end
0.8Low end
High end estimate: Apply high-end ARPU to the
aggressive take-up rate MMU subscribers
Low end estimate: Apply low-end ARPU to the
baseline MMU subscribers
* NOTE: ARPU numbers are monthly, revenue numbers are annual
Source: Team analysis
A3 ILLUSTRATIVE
MMU ARPU,
USD/month
290High end
Estd Global
MMU subs, m
(Take-up: 16.8%)
High end 1.0
MMU ARPU,
USD/month
135High end
Estd Global
MMU subs, m
(Take-up: 7.8%)
0.5High end
X
X
13
There are 4 primary elements in sizing the market
Source: Team analysis
Description Objectives
Sizing the overall
market
• Sizing the direct market potential
– Estimate the number of potential
Mobile Money users
– Bottom-up modelling of overall
ARPU
– Total market revenue potential
• This is the primary methodology for sizing the
Mobile Money market in terms of users and
revenues
A
Estimating the
product mix
• Estimate size of financial service
flows by product category for each
market
• Estimate MM take-up rates & fees
• Calculate the overall revenue
potential and product mix
• This methodology can be used to estimate
relative potential for different mobile money
products and services based on revenue pools
• This approach can also be used as an
alternative method to help size the overall
market revenues by product category
C
Estimating un-
banked “access”
• Estimate how many incremental
people can be provided with
financial access by reducing cost to
serve through Mobile Money
• This approach would primarily be used to
illustrate the potential for extending financial
access to unbanked people
• The approach can also be used as an
alternative method to estimate the size of the
mobile Money revenues and subscribers
D
Sizing the
indirect benefits
• Sizing of the indirect benefits • This section provides a way to estimate the
indirect benefits of Mobile Money to an MNO–
these can be a significant driver of a business
case
B
14
Mobile Operators will benefit from significant indirect benefits when
deploying Mobile Money
Possible indi-
rect benefits Rationale
Churn
reduction
• People who use MM services are likely to be
more sticky since they get more utility out of
the SIM and have stored value on the SIM
• Churn of banking customers tends to be
lower than Mobile
• Lack interpretability can help reduce churn,
especially for market leaders (note to be
discussed
• MM churn rates can be more than
20% below non MM users
Range of impact (examples)
Reduced
channel costs*
• Cost savings as top-up sales can bypass
traditional channels
• Possible savings of 2–3% of channel
top-up sales margins when people
top-up from mobile-wallet instead of
channel
Market share
increase
• A compelling MM solution can help attract
subscribers by establishing a stronger value
proposition
• Some operators have increased
market by up to 8% since launching
MM
ARPU Increase• MM allows consumers to buy top-up in
smaller increments – driving up ARPU
• MM users are likely to use the MM SIM as
their primary SIM
• MM is a functionality which may attract
higher-end subscribers with more usage
• ARPU of mobile money users can be
more than 20% higher than non-users
* Not sized since this lever may not be relevant to all markets
Source:Interviews, company websites, Press clippings, Team analysis
B
15
A high level sizing of the indirect benefits gives an indication
of what MM is worth to an operator
Total benefit to MNO of
rolling out Mobile Money
$
Indirect
1
2
Example indirect benefit sizing methodology
Source: Team analysis
3
Value of reduced churn - example1
Reduced customer base churn revenue (of telco)*
• # Mobile Money users Nr subs
• Current churn of telco’s customer base (weighted avg) %/month
• Forecast reduction of churn in MM adopting segment %
• Value of churn reduction in # subs Nr subs
• Current telco’s customer base ARPU (weighted avg) $/month
Increased ARPU - example2
Higher phone usage revenue
• Current telco’s customer base ARPU (weighted avg) $/month
• Marginal increase in phone’s usage (voice/data) %
• Marginal ARPU $/month
• # Mobile Money users Nr subs
Added subscribers - example3
• ARPU
• New customers as % of total MM customers
• Incremental subscribers attracted through MM
• ARPU*incremental subscribers = total value
$/month
%Nr of subs
$
• ARPU * churn reduction = $ value $
B
$• Marginal ARPU*Mobile Money users = $ value
16
There are 4 primary elements in sizing the market
Source: Team analysis
Description Objectives
Sizing the overall
market
• Sizing the direct market potential
– Estimate the number of potential
Mobile Money users
– Bottom-up modelling of overall
ARPU
– Total market revenue potential
• This is the primary methodology for sizing the
Mobile Money market in terms of users and
revenues
A
Estimating the
product mix
• Estimate size of financial service
flows by product category for each
market
• Estimate MM take-up rates & fees
• Calculate the overall revenue
potential and product mix
• This methodology can be used to estimate
relative potential for different mobile money
products and services based on revenue pools
• This approach can also be used as an
alternative method to help size the overall
market revenues by product category
C
Estimating un-
banked “access”
• Estimate how many incremental
people can be provided with
financial access by reducing cost to
serve through Mobile Money
• This approach would primarily be used to
illustrate the potential for extending financial
access to unbanked people
• The approach can also be used as an
alternative method to estimate the size of the
mobile Money revenues and subscribers
D
Sizing the
indirect benefits
• Sizing of the indirect benefits • This section provides a way to estimate the
indirect benefits of Mobile Money to an MNO–
these can be a significant driver of a business
case
B
17
Estimating service revenues by product categoryC
Estimate the value of all retail financial service flows
Estimate take-up rates &
fees for Mobile Money
products
Calculate total market
revenues and product mix
• Mobile Money product mix
by service category (in
terms of total flow & fees
for each service category)
End-
products
• Breakdown of total financial
service flows by product
category (including
unbanked potential)
• Total Mobile Money
revenue estimate by
product category
• Estimate the value of all
retail financial service flows
• Estimate the “unbanked”
proportion of these flows by
scaling up the cash/informal
sectors to relevant products
• Estimate potential adoption
rate for MM from these
various service flows
• Estimate fees per service
accrued by different
players in the ecosystem
Top-down
Approach
• Estimate the overall
market opportunity
1 2 3
Mrkt
research
Approach
• Launch targeted survey in
your market to understand
current usage of informal
financial services in
unbanked mobile segment
• Evaluate per service:
– usage frequency
– average value
transacted/stored
– average fees
• Estimate the overall
market opportunity
18
Top-down Approach: Estimate the total “banked”
financial service revenue flows
Cash
Source: Team analysis, Interviews
Domestic
Transfers
International
Remittance
Deposits
Loans
Existing flow Definition Possible sources
Total economy FS flows
(illustrative)
• Value transacted on 5 e-
payment instruments &
scaling for cash component
• Total value of cash
transactions = M0 * GDP/M1
• Total value of domestic
payments & remittances
(p2p, g2p, b2p etc)
• Remittance volumes (inflows
and outflows)
• Total value of domestic
deposits
• Total value of outstanding
domestic loans and credit
• World Bank; Payment Systems
Group; outcomes of the 2008
global survey - appendix
• MGI Global Financial Stock
Database, IMF's International
Financial Statistics
• National Central banks
• World Bank; Outlook for
Remittance Flows 2008-2010
• National Central banks
• Worldbank
• Assume xx% of all flows
• National Central banks
• Worldbank
Non-cash
Payments
C1
ILLUSTRATIVE
19
Top-down Approach: Estimate the “Unbanked”
financial service flows as a proportion of the total
Cash
Source: Team analysis, Interviews
Domestic
transfers
International
Remittance
Deposits
Loans
Existing flow
Total economy FS flows
(illustrative)
Non-cash
Payments
Unbanked FS flow
(top-down indicative) Assumptions
Relevant to unbanked
• Pre-existing payment flows are all
“cash” for unbanked people (none in
electronic payments system)
• Unbanked segment is not accounted
for in formal e-payments flows
• Unbanked segment does account for
a share of total cash flow
• Unbanked share of income &
remittances can be derived by taking
the unbanked share of GDP (~2%)
and applying this to cash & transfer
flows
• Distribute total amount in relative
proportions as per “banked” (e.g,
28% and 72% in example)
• Unbanked share of Int remittance
flows (based on %GDP, ~2%)
• “Unbanked deposits are based on
residual value in MM accounts (calc
as 5% of total value transacted)
• Very small – could be sized from
Micro finance flows (if known)
C1
28%
72%
2%
Unbanked share of GDP
2%
Relative Cash/Transfers %
20
Mrkt research Approach: Build the “Unbanked” financial
service flows through primary analysis of current usage
Cash
Source: Team analysis, Interviews
Domestic
transfers
International
Remittance
Deposits
Loans
Existing flow
Total economy
FS flows
(illustrative)
Non-cash
Payments
Unbanked FS
flow (top down
indicative)
C1
Unbanked FS flow (mrkt
research – Country A),
USDM/year
0
8
0
68
224
161
MM services included
from survey results
• Cashless transactions in
restaurants, groceries,
supermarkets, malls
• Payment of bills
• Airtime purchase
• Transport access
• Receive salary/payment
• Money sent
• Money received (dom.)
• Airtime sent/received
• Money received (int.)
• Storing value
Relevant to unbanked
21
Estimate the Mobile Money fees
Source: Team analysis, Interviews
Existing flow
Loansn/a
Fees (indicative
ranges), %
Rationale (note must be adapted to local
markets)
Non-cash
Payments
1 • Same potential as cash replacement (below)
Cash1 • Based on average of reported fees for all
cash-replacing products
Domestic
Transfer
2-3 • ~1.5% cash-in, ~1-1.5% cash out (SMS excl.)
International
Remittance
0.5-
1.5
• ~0.5% as reported in market research• ~1.5% based on MMT work (total is 4-6% of
which MNO capture ~1/3
Deposits0.5-
1.5
• ~0.5% as reported in market research
• ~1.5% assumed potential interest spread
• TBD
C2
22
Estimate the Mobile Money product mix flows and revenues
Source: Team analysis, Interviews
Product
Cash
Domestic
Transfer
International
Remittance
Deposits
Loans
Non-cash
Payments
MM take-up
%
MM fee
%
Revenues
by product
USDm
Total flow
USDb
53,534
8,597 9,105
43,740
473 593
5,317 5,413
4,042
MM flows by
product
USDm
C3 ILLUSTRATIVE
23Source: Philippines Unbanked Consumer Insights Survey - Feb-Mar 2009, (n=400); Team analysis
MM fee,
%
MM revenue,
USDm/year
0.3%
0.8%
1.5%
1.1%
0.3%
0.7%
2.0%
0.9%
5
0
20
1
10
0
1
1
MM flows,
USDm/year
Receive
money (int)
Cashless POS
& remote payments
Send
money
Receive
money (dom)
1,932
Store money
Buy airtime
Receive salary
Send &
receive airtime
98
134
1,157
1,399
598
85
132
Cash
Domestic
Transfer
International
Remittance
Deposits
Product
Check estimate with targeted market research resultsC3
EXAMPLE
24
There are 4 primary elements in sizing the market
Source: Team analysis
Description Objectives
Sizing the overall
market
• Sizing the direct market potential
– Estimate the number of potential
Mobile Money users
– Bottom-up modelling of overall
ARPU
– Total market revenue potential
• This is the primary methodology for sizing the
Mobile Money market in terms of users and
revenues
A
Estimating the
product mix
• Estimate size of financial service
flows by product category for each
market
• Estimate MM take-up rates & fees
• Calculate the overall revenue
potential and product mix
• This methodology can be used to estimate
relative potential for different mobile money
products and services based on revenue pools
• This approach can also be used as an
alternative method to help size the overall
market revenues by product category
C
Estimating un-
banked “access”
• Estimate how many incremental
people can be provided with
financial access by reducing cost to
serve through Mobile Money
• This approach would primarily be used to
illustrate the potential for extending financial
access to unbanked people
• The approach can also be used as an
alternative method to estimate the size of the
mobile Money revenues and subscribers
D
Sizing the
indirect benefits
• Sizing of the indirect benefits • This section provides a way to estimate the
indirect benefits of Mobile Money to an MNO–
these can be a significant driver of a business
case
B
25
Estimating the incremental financial access provided by Mobile
Money
Source: Team analysis
Steps
Build "affluence
curves"
Apply "cost-to-
serve"
Estimate
addressable
group
Estimate the
incremental
access via MM
• Estimate the
incremental
population
theoretically
servable
through lower
"cost-to-serve"
mobile channel
(use range of
cost-t0-serve
reduction
scenarios)
• Calibrate this
theoretical
addressable
group to include
only those who
own a mobile
and then apply
a take-up
assumption to
this target
population
• Calculate
incremental
access to
financial services
through mobile
money
D
1 2 3 4
• Build income
distribution curve
to identify who
can reasonably be
served by current
banking system
(or use proxy
curves provided)
End-
products
• Estimate of
theoretical
access provided
by Mobile
Money
• Estimate of the
total potential
access provided
by Mobile
Money
• Estimate of
expected
incremental
access provided
by MM
• Income
distribution curve
for target region
26
0
5
10
15
20
25
30
35
40
0 10 20 30 40 50 60 70 80 90 100
Asia Pacific
Africa (limited
sample)*
Americas
Europe:
Eastern
Middle East
Populationpercent
Daily income/capita$
Affluence curves have been developed to establish
the income distribution for a range of markets
* Income distribution data for Africa sample is based on Nigeria data only (South Africa excluded, all other countries not available)
Source: Euromonitor, Team analysis
D1 PRELIMINARY
27
Key data for select markets can help determine which market proxy
is most relevant for a given market
Region
Population
2012,
Million people
Americas
Asia
Eastern
Europe
Middle East
Africa 1,004
597
3,581
357
247
GDP per
capita 2012,
USD/person
Mobile sub-
scribers* 2012,
%
Unbanked
share of GDP
2008, %
Financial
Service access
2008, %
1,898
6,889
3,150
13,517
7,730
52%
75%
60%
78%
71%
25%
22%
18%
21%
27%
23%
37%
41%
43%
38%
* Mobile subscribers is based on discounted count of total # SIMs per market. Number of SIMs discounted by Wireless Intelligence formula
Source: WMM, Global Insight; Wireless Intelligence; World Bank; Finance For All; Team analysis
D1
28
The income distribution can be linked to the “cost to serve” based
on assumptions about the share of GDP that goes to Financial Services
0 10 10020 30 40 50 60 70 80 90
Populationpercent
0.
0.01
0.010
0.011
0.012
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.09
Financial service revenue and cost to serve$
Source: Team analysis
0
1
2
3
4
5
6
7
8
9
10
11
12
0 10 10020 30 40 50 60 70 80 90
Populationpercent
Daily income per capita$
• Assume that Financial services account for X% of income (based on proxy market)
• The share of income determines the Financial services revenue for a given income band
• Assume that Financial services are offered to the point where Marginal Cost = Marginal Revenue
(ie the revenue curve = the cost curve at each point)
• A reduction in the cost to serve enables offering financial services to lower income bands (based
on same income share of GDP). Hence more people are accessible
D2 ILLUSTRATIVE
BA
A
B
C
MC = MR
C
C
29
By estimating the local cost to serve reduction it is possible
to determine the theoretical access made possible by mobile money
40 50 60 70 80 90
Populationpercent
0
0.01
0 10 10020 30
0.010
0.011
0.012
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.09
Traditional
cost-to-serveA
MM
cost-to-serve
• Current FS access
(%)
• Cost to serve
reduction (%)
– Current cost to
serve estimate ($)
– MM cost to serve
($)
• New theoretical
financial access (%)
• Increase in
Financial access
Source: Team analysis
Theoretical access
possible through
reduced cost to serve
D3 ILLUSTRATIVE
Inputs
Daily income per capita, $
A
B
B
DC
C
D
30
0 10 20 30 40 50 60 70 80 90 100
Populationpercent
0
0.01
0.010
0.011
0.012
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.09
Steps for estimating the increased financial access
Traditional
cost-to-serve
Source: Team analysis
1 Estimate current access to
financial services (eg 40%)
2 Use current access to plot
line to show where current
Cost to serve could lie
3 Estimate the cost to serve
reduction opportunity (e.g.,
50% reduction)
4 Estimate the number of
additional people who can
now access financial
services (eg 62%)
5 Map the total mobile
penetration (eg 52%)
Theoretical access possible
through reduced cost to
serve
1
0 Choose an income curve
D4
2
MM
cost-to-serve6
4
3
Total theoretical access
(62%) minus mobile
penetration (52%) = MM
potential access = 10%
6
Calculation
s
0 Daily income per capita, $
5
ILLUSTRATIVE
31
Mobile Money Toolkit
• Objectives& Definitions
• Market analysis
–Sizing the market (direct & indirect)
–Estimating product mix
–Estimating unbanked access
–Stress-testing the numbers
• Macro tools
–Business plan framework
–Conducting Primary Market Research
• Best practice research guide
• Surveys and facilitator guides
–MMU database
–Market screening frameworks
• Appendix
32
Subscribers
Revenues
Reality testing the numbers – test the key numbers against other variables
to see if they make sense
Source: Company reports, Literature search, Team analysis, World bank data
High end
of range
Low end
of rangeVariables
• Projected mobile money users as share of total
“unbanked” populationx% x% 5-8%
• Implied increase in “% banked” (ppts) x% x% 3-5%
• Share of total unbanked mobile segment x% x% 10-15%
Indicative
ranges
• Mobile Money ARPU as share of total ARPU x% x% 10-15%
• Total MM take up rate as % of total subscribers x% x% 5-25%
User input
Cost
• MM cost to serve per user (technical)
• MM marketing & agent costs as % of technical
costs x% x%
Indirect • MM churn and ARPU vs non-MM usersx% x% ~20%
x% x% ~$2-4
1x-4x
33
Mobile Money Toolkit
• Objectives& Definitions
• Market analysis
–Sizing the market (direct & indirect)
–Estimating product mix
–Estimating unbanked access
–Stress-testing the numbers
• Macro tools
–Business plan framework
–Conducting Primary Market Research
• Best practice research guide
• Surveys and facilitator guides
–MMU database
–Market screening frameworks
• Appendix
34
KEY QUESTIONS FOR A BUSINESS PLAN (1/2)
Source: McKinsey
Executive
summary
• What is the basic business idea, target customer segments, and value
proposition?
• To what extent will this service reach the “unbanked”
• What does the organizational business look like and who will lead the
business?
Market/competitor
analysis and own
positioning
• What is currently happening in the market?
• What are the key success factors for MM success?
• Who are current and future competitors?
• What is positioning compared with key competitors’?
Product and
customer value
proposition
• What services are offered at what prices?
• What take-up rates are expected for different services?
• What partnerships/cooperations are needed?
• Where does the value to the customer lie, especially to the unbanked?
• What evidence is there to suggest there is a consumer demand?
• How can advertising and promotions support the customer value?
Key questions (Examples)
Business-model
organization and
processes
• What business model will be deployed, have partnerships been agreed?
• What type of technology will be deployed?
• How will the service be distributed, how will the agent network be built,
what is value proposition for the agents?
• What organization and resources are needed?
• What are the core business processes?
ILLUSTRATIVE
35
KEY QUESTIONS FOR A BUSINESS PLAN (2/2)
Source: McKinsey
ILLUSTRATIVE
Management team
• Which people will manage the future business?
• How can the right people be attracted and retained? (Banking and mobile
experience is important)
Opportunities
and risks
• What is the position of the regulator with regards to this opportunity?
• What risks are involved with the market entry and how can they be
controlled?
Financial planning
and ROI analysis
• What are the expected financial results over the next five years?
• What are the costs of deploying MM? (technical, marketing, channel
costs etc)
Key questions (Examples)
Implementation
road map
• What are the key milestones in building the new business?
36
Mobile Money Toolkit
• Objectives& Definitions
• Market analysis
–Sizing the market (direct & indirect)
–Estimating product mix
–Estimating unbanked access
–Stress-testing the numbers
• Macro tools
–Business plan framework
–Conducting Primary Market Research
• Best practice research guide
• Surveys and facilitator guides
–MMU database
–Market screening frameworks
• Appendix
37
Consumer insight research will develop a better understanding
of current and potential users and inform market sizing-estimates
Source: GSMA RFP, Interviews
Research approach
Provide insights
regarding current and
potential MM users for
business planning
• Attitudes towards
traditional banks
• Usage of alternative
informal channels &
services
• Adoption barriers/funnel
Inform market sizing
estimates
• Unbanked share of MM
users, adoption rate,
churn and reload effect
• Provide understanding of
MM service-flows and
latent demand
• Focus groups
– Use a structured facilitator guide to manage flow of focus groups
while assisting agency in targeting answers on specific areas of
interest (see appendix)
– Can use a “survey-lite” of 30-40 close-ended questions for
respondents to complete pre-group (see appendix)
– Launch pre-design of quantitative survey to assist with customer
segmentation, language/local knowledge input and
hypothesis/options development
• Survey
– Use targeted sampling to address specific segments, but assess
incidence through random sampling to size population/opportunity
– Target ~200 respondents for each relevant customer segment to
ensure a 6-7% margin of error on each answer (n=100 is ~10%)
– Pre-draft core analysis/insights to help with planning option set
per question and ensure each questions relevance/impact
– Ensure flow of question leads with easy/non-intrusive questions
(e.g. daily mobile usage) pry into personal financial questions
once respondent is “warm”
Research Objectives
38
There are 6 key steps in conducting the primary market research
Design and run focus
groupsDevelop hypothesis
Refine close-ended
~30-40 minute surveyLaunch fieldwork
Ana-
lyse
data
Syn-
thesize
in-
sights
• 2 x focus groups with
unbanked MM users
and non-MM users
• Moderator notes to
focus 2 hours on
– Telco usage
– FS usage
– Mobile money
usage & perception
• Debrief with TNS team
& McKinsey Manila
team in attendance
• Attain observations of
group experiences
• Bolster understanding
of linguistic, emotive
nuances related to FS
and MM
• Develop storyline -
hypothesis using
indicative findings from
group
• Build well-phrased
questions with context
of language and
emotive reactions
• Define target segments
– MM users, no other
formal banking
access, urban/rural
– Non-MM users, no
formal banking
access, mobile
– <$2/day, mobile
• Ensure key q.s are
directly comparable w.
existing surveys if
relevant
• Target ~1000 responses
with proportionate urban-
to-rural representation:
– MM users = 400
– Non-MM users = 400
– <$2 day = ~200
• Process involves door-to-
door screening followed by
30-40 minute interview
• ~30 interviewers (4 teams)
trained to use prompt
cards, record answers &
drive flow of conversation
•
* Dialects for fieldwork: Tagalog, Ilocano, Ilonggo, Cebuano, and Bicolano
Field-team briefing, Manila, 27 Feb
• Validation of
market sizing
assumptions
• Testing and
validation of key
hypothesis
• Consumer
insights to help
inform the “go to
market” strategyFocus Group moderator guide Close-ended 30-40 min survey
39
The research should be designed to test a specific set of hypothesis
about the market
Segment sizing
Usage
Trial
Access
Awareness &
understanding
Latent Demand
Examples of MMU Consumer narrative
Screening section• The Unbanked mobiled are a significant group: As many as X % of low-
income groups are unbanked but do own a mobile phone.
• The sub$2/day makes up approximately X% of this group
Sect C• Unbanked consumers have a strong underlying demand for financial
services, but most currently rely on informal alternatives
Sect E• Unbanked consumers are generally aware of MM services and tend to
know the MNO brands better than the banks
• Many unbanked consumers do not fully understand the MM service
Sect E
• People are often reluctant to try MM because they find it difficult or they
don’t see the services as something “for people like me”
Sect C,D,E,F
• People need to have access to the agent network if they are going to
sign up for the service, agents are much more ubiquitous than banks, but
they are still far from the levels of air-time vendors
• Those who do use MM start with simple services at first but do have
needs for more advances services if they can be made relevant to them
Sect D
Sect D,E• People who have good experience with MM tend to become loyal users,
but the slightest service disruption can lead to abandonment of the service.
Loyalty
Survey section
Implications for
accelerating MM to
the unbanked
See consumer Survey in
appendix
40
Primary market research tools
Description
• Facilitators
guide for focus
groups with
unbanked MM
users and non-
MM users
• Moderator notes
to focus 2 hours
on
– Telco usage
– FS usage
– Mobile money
usage &
perception
Focus Group
moderator guide
Close-ended 30-
40 min survey
Focus group facilitators guide Consumer adoption survey
Description
• Defines target
segments
– MM users, no
other formal
banking access,
urban/rural
– Non-MM users,
no formal
banking access,
mobile
– <$2/day, mobile
• Standard
questions to
ensure
consistency
These documents are
provided separately
41
Mobile Money Toolkit
• Objectives& Definitions
• Market analysis
–Sizing the market (direct & indirect)
–Estimating product mix
–Estimating unbanked access
–Stress-testing the numbers
• Macro tools
–Business plan framework
–Conducting Primary Market Research
• Best practice research guide
• Surveys and facilitator guides
–MMU database
–Market screening frameworks
• Appendix
42
The MMU database contains key data for 147 markets
• Key data for 147 markets e.g.;
– Macro data
• Population
• Economy
• Income
• Demographics
– Mobile Penetration
– Financial access
• Access to financial services
• Unbanked population
– MMU Population Data
– Financial flows
Source: Ranges of sources detailed in database appendix
This spreadsheet is
provided separately
43
Mobile Money Toolkit
• Objectives& Definitions
• Market analysis
–Sizing the market (direct & indirect)
–Estimating product mix
–Estimating unbanked access
–Stress-testing the numbers
• Macro tools
–Business plan framework
–Conducting Primary Market Research
• Best practice research guide
• Surveys and facilitator guides
–MMU database
–Market screening frameworks
• Appendix
44
Markets with high mobile penetration relative to financial access
penetration may by “ripe” for Mobile Money
* Mobile penetration can include double counting due to multiple SIM-cards, this is not adjusted
Source: Wireless Intelligence, World Bank, WMM
0
10
20
30
40
50
60
70
80
90
100
110
120
130
0 10 20 30 40 50 60 70 80 90 100
Turkey
Germany
Vietnam
Philippines
Mexico
Pakistan
Saudi Arabia
Indonesia
United States
India
China
Malaysia
Peru
Poland
Argentina
Colombia
SpainUkraine
Access to financial services%
Mobile penetration*%
United Kingdom
France
Thailand
Brazil
• Mobile
penetration
exceeds the
access to
financial services
in most markets
>1 bn
<0.1 bn
0.1 bn – 1 bn
Size = population
45
0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
5.5
6.0
Poland
Kenya
AlgeriaMorocco
Uganda
Iraq
Nepal
0 10
China
110 120 130 140 150 16020 30 40 50 60 600 610 620 63070 760 770 780
India
IndonesiaBrazil
Pakistan
Bangladesh
Nigeria
MexicoPhilippines
Vietnam
Turkey
Ethiopia
Thailand
Myanmar
100
South
Africa
Ukraine
Colombia
Argentina
Tanzania***
Sudan
80 90
Unbanked Population**
mn
Mobile vs. Banking Reach*
Mobile / banking penetration and size appear to be important criteria in
determining readiness for Mobile Money
B A
C
B Quick Risers
• High to very high mobile
vs.. banking reach
A Major Potential
• Large unbanked
populations
• High mobile vs. banking
reach
C Giants
• Relatively low mobile vs..
banking reach
• Very large unbanked
population in absolute
terms
* Mobile Penetration (net of multi-sim proxy) vs.. % banked, average ratio of mobile penetration to banked share across markets shown is ~2
** Average of unbanked population across markets shown is ~90 mn
*** Tanzania potential does not seem to be observed in the market.
Source: Wireless Intelligence, World Bank, WMM, Global Insight
PRELIMINARY
D Unclear potential
• Low mobile & banking
penetration
D
46
There are a lot of markets in the “B & D” segments
* Mobile Penetration (net of multi-sim proxy) vs. % banked, average ratio of mobile penetration to banked share across markets shown is ~2
** Average of unbanked population across markets shown is ~30 mn
Source: Wireless Intelligence, World Bank, WMM, Global Insight
0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
5.5
6.0
6.5
7.0
7.5
8.0
8.5
9.0
9.5
10 100 110 120 130 140 150
Myanmar
20 30 40 50 60 600
Tanzania
Nicaragua
Armenia
160
Kenya
Pakistan
Ethiopia
Nigeria
Georgia
Belarus
Iraq
610 620 63070 760 770 78080 90
Romania
Ukraine
MexicoPhilippinesArgentina
South Africa
Unbanked Population**mn
VietnamAlgeria
Bangladesh
IndonesiaChina
Brazil
India
Mobile vs. Banking Reach*
0
B A
C
Question marks:
Sudan
Thailand
Colombia
South Africa
Uganda
Iraq
Algeria
Morocco
Uzbekistan
Nepal
Peru
Poland
Malaysia
Guatemala
Niger
Senegal
Zimbabwe
Sri Lanka
Rwanda
Bolivia
Chile
Cuba
Tunisia
Honduras
Sierra Leone
El Salvador
Paraguay
Jordan
Bulgaria
D
47
Macro factors per archetype/segment are fairly inconclusive
A
B
C
Quick Risers
• 14 countries including
Philippines, Kenya,
Tanzania, Argentina
Major potential
• 2 countries
• Pakistan, Nigeria
Giants
• 5 countries
• China, India,
Indonesia, Brazil,
Bangladesh
D Unclear potential
• 85 countries (see
page 2)
308
543
3,105
987
Total
Population,
mn
Average
Mobile
Penetration,
%
47
61
46
48
43
60
45
48
Urban
Population
Share, %
Access to
Financial
Services,
%
18
32
14
41
Gini Co-
efficient
39
45
37
42
Direct Credits
% of total
Non-Cash
Payments*
39
55
55
57
Total cash
payments as
% of GDP*
22
45
43
35
* Initial team estimates
Source:World Bank, Wireless Intelligence, WMM, Global Insight, CIA World Fact Book
PRELIMINARY
48
Data on select markets
0
1
7
14
28
28
30
30
30
46
46
48
53
54
54
58
65
66
71
75
76
78
83
89
92
93
98
Russia
123Ukraine
115Poland
112Argentina
Thailand
South Africa
Algeria
Turkey
Colombia
Brazil
Philippines
Morocco
Mexico
132
Iran
Indonesia
Egypt
Iraq
Pakistan
Kenya
China
Nigeria
Bangladesh
Tanzania
India
Sudan
Uganda
Congo, DRC
Nepal
Ethiopia
Myanmar
Vietnam
Mobile
penetration
GDP/capita
$
934
5,340
2,192
2,058
4,022
953
868
3,166
1,689
475
427
1,050
1,463
437
179
340
187
423
12,258
4,199
13,943
7,914
4,355
5,828
4,843
9,933
4,351
7,958
1,787
2,656
9,605
11,530
n/a
17,210
7,790
5,410
8,720
n/a
11,350
5,470
7,560
2,690
n/a
17,010
1,070
n/a
2,200
n/a
n/a
2,280
n/a
4,350
n/a
n/a
n/a
3,590
n/a
n/a
n/a
n/a
n/a
n/a 19
14
20
20
15
48
5
32
15
42
10
12
17
40
29
25
28
26
43
41
49
31
46
59
28
66
24
n/a
n/a
n/a
n/a
"Median
Household
Income ($)"
% With Access
to financial
services
Prepaid share
Q3 2008, % ARPU, USD
88
99
94
99
99
99
83
99
97
99
70
99
98
99
96
97
48
98
85
97
97
80
85
83
97
86
90
73
56
93
91
7
3
13
10
3
14
10
5
17
11
5
15
10
14
8
17
7
12
19
7
12
Source: Wireless Intelligence, World Bank, WMM, Global Insights, EIU, Euromonitor
PRELIMINARY
49
Additional ideas for data to explore (1/2)
Additional ideas
• Market gaps: (eg market share of
independent privately owned banks or
telcos)
• Saving propensity: savings rates,
consumer consumption as % of income
• Access to credit: Prepaid as % of total
mobile market
• Telco & Banking competitiveness:
Herfindahl-Hirschman Index
• Environmental risks: Crime statistics,
inflation rates
• Size: Unbanked population
• Demographics: Age distribution, family
size
• Banking reach: Geographic bank/ATM
penetration, Rural population %
Rational
• Will the private sector fill the gap (if there is one)?
• Are there indicators of propensity to save vs the
consumption patterns?
• What share of population lacks access to credit?
(Prepaid can be an indicator)
• How competitive are the banking and telco industries?
• Are there environmental factors which may indicate
people need safe savings options?
• How many unbanked people are there?
• What is share of young vs old people? Does size of
family indicate the need for saving?
• Does the banking system reach people who need it?
PRELIMINARY
50
Additional ideas for data to explore
Additional ideas Rational
PRELIMINARY
Domestic remittances
Domestic migration
flows
ATM infrastructure
Regulatory environment
Alternative channels
• What is value of domestic remittance flows?
• Are there large domestic migration flows?
• What is ATM penetration?
• Does regulatory environment allow Mobile
Money?
• What are alternative channels?