By Gayathri Ramani
(I will not be taking the second module)
Introduction
Recently, a Kenyan newspaper published an article about the
role of social media in promoting financial inclusion. The Chairman and CEO of
Equity Bank, one of Kenya’s largest banks Dr. James Mwangi said “Social
networks have the potential of empowering the youth economically by enhancing
their access to financial products and services.”[i]
By diversifying their marketing strategy onto social media platforms like
Facebook, Twitter, and Instagram, the bank is confident that they will be able
to enhance financial inclusion. However, despite the growing penetration of
internet services, reliable electricity continues to be a major challenge for
many parts of rural Kenya. This implies
that a large percentage of households in Kenya continue to have limited or no
access to Internet and cannot afford to own a smart-phone with readily
available data.
In contrast, mobile services have grown exponentially over
the last few years due to the introduction of Mobile Money called M-PESA. During
my work experience at Innovations for Poverty Action (IPA) in Kenya, I had the
opportunity to manage an evaluation study on the long-term impacts of Mobile
Money (M-PESA) around 2000 Kenyan households from different regions in Kenya.
According to a recent paper published by Tavneet Suri and William Jack, the
principal researchers behind this long-term study, M-PESA adoption rates grew
to 70% in just 4 years from its inception. Moreover, almost three quarters of
the households had at least one user (adoption in this case refers to either
being a registered user and those who had access to an M-PESA account). [ii]
Due to its success, the M-PESA Platform has expanded to
incorporate “Mobile Banking”. Products under this platform include M-shwari, a savings account linked to an
Equity Bank account through which you can also to take out micro-loans.
Additionally, other companies have also started using M-PESA as a payment
mechanism using services like M-Kopa
and Lipa na M-PESA. However, observational
data suggests that take-up of such products is relatively low compared to formal
savings instruments (e.g. Bank Accounts) and informal instruments (e.g. Merry
go round). In this context, understanding and analyzing the social networks
around M-PESA will provide crucial information for stakeholders in not only
creating a more successful and targeted social media campaign but will also
provide robust evidence for future marketing strategies to promote their range
of financial products.
Background
The topic of financial inclusion is increasingly becoming a
hotbed for development experts. The Center for Financial Inclusion (CFI)
defines it as the “access to quality financial services that are convenient,
affordable, suitable, and provided within a robust financial structure and
clear regulatory framework”. [iii]
Having access to cheaper and competitive credit will theoretically allow the
poor to be more economically self-sustainable and encourage a culture of
entrepreneurship that can potentially increase growth of the country. However, due
to lack of adequate infrastructure and other credit constraints, there is a
large proportion of Kenyan households that do not have access to such facilities.
In order to overcome these challenges, development practioners began implementing
innovative models such as the Grameen Bank in Bangladesh. This fed into a
digital revolution of the mobile phone technology and opened the gate to solving
development problems.
With mobile phones came “Mobile Money”. One of the most
successful model is M-PESA. In 2007, the leading cell phone company in Kenya,
Safaricom introduced M-PESA. It was a SMS based money transfer system where
individuals were allowed to deposit, send, and withdraw funds using their cell
phone. After its launch in 2007, M-PESA gained extraordinary momentum, reaching
nearly 70% of Kenya’s adult population in 2011. According to Jack and Suri, M-PESA’s
rapid uptake was in part due to the growth of network of agents. Agents are
small business outlets that provide the cash-in and cash-out services. The
agents exchange cash for so-called “e-money” from the individuals and then send
the electronic balances from one account to another via SMS. [iv]
M-PESA has dramatically transformed the social networks of Kenyan
communities. Apart from the business network, where entrepreneurs conduct
economic transactions, social networks have also burgeoned. According to a working
paper by Kusimba, Chagger et al, “Most users in Western Kenya use mobile
money as a social and economic tool through which they create relationships by
sending money and airtime gifts, assisting friends and relatives, organizing
savings groups, and contributing to ceremonies and rituals”.[v]
Understanding the dynamics of these networks will be crucial for Safaricom and
Equity Bank in promoting their financial products and forging ahead in the
realm of financial inclusion.
Research Questions
In order to make recommendations pertaining to the marketing
strategies of key stakeholders (i.e. Safaricom and Equity Bank), one must
formulate and answer the following research questions:
Question 1: What does the Mobile Money (MM) market
look like?
In order to answer this question, we will need to answer the
following sub-questions:
- Key players - Who are the key players of the M-PESA Network? We can identify these by looking at several centrality measures (distance, betweeness, high in and out-degrees)
- Density of the Network – Is the network really dense or are there several distinct and sparse components? Are there any isolates in the network?
- Strength of ties - Have the ties gotten stronger? Do we have more reciprocal ties within members of the network?
- Is there any evidence of homophilly – Are there any distinct networks based on gender or other attributes?
Depending on some of these measures, we will be able to
identify potential roles that these key players will have in marketing or
information campaigns. For example, players that have high out-degrees can be
information sources.
Question 2: By narrowing in on the Ego Networks for
these key players, what are their characteristics/attributes of all members of
this network?
We can filter the data to look at the following
characteristics (dichotomized for frequent and very frequent ties:
- Urban/Rural demographic
- Gender
- Occupation
- Social Media Presence
- Do they have Facebook/Twitter/Instagram?
- How many followers do they have?
- Do they have access to these sites on their phone?
- 5. Function of the money being transacted
By analyzing the characteristics of the Ego Networks, we can
segment the target population and identify the M-PESA Users that could have the
greatest impact of a targeted marketing model. For example, if we have a rural network
that has a “leader” who has a strong social media presence, providing them with
information about different products and offers through Facebook or Twitter could
eventually trickle down to the rest of the network that might not necessarily
be plugged into social media.
Data
There have been only a few studies using social networks
analysis in understanding mobile money adoption. In particular, The Consultative Group to
Assist the Poor (CGAP) in collaboration with Real Impact Analytics conducted a
study in 2013 on the use of data analytics in understanding take-up of mobile
money. They collected and compared data across 3 different countries (including
Kenya) on variables such as mobile money transfers, frequency of transfers, and
the networks that surround these potential key drivers of adoption.
For purposes of this research design, we can use this data
and assume a high level of synonymy between drivers of adoption of Mobile Money
or “Technology Leaders” (as defined in their working paper) and drivers of
adoption of new financial products within the M-PESA platform.
Given that the data set is large and difficult to interpret
through social network analysis, it would be useful for us to take a smaller
random sampling of the original sample and conduct a follow-up study on these
sampling units (taking into account attrition of the sample). Questions
regarding social media usage can be added into the survey.
More information
about this study can be found here:
http://www.cgap.org/sites/default/files/social_networks.pdf
[i] http://www.standardmedia.co.ke/?articleID=2000180681&story_title=equity-bank-chief-says-social-media-key-in-expanding-financial-inclusion&pageNo=1
[ii] Jack,
William and Tavneet Suri (2011): “Mobile Money: The Economics of M-PESA”
[iii] http://www.centerforfinancialinclusion.org/about/who-we-are/our-definition-of-financial-inclusion
[iv] Jack,
William and Tavneet Suri (2011): “Mobile Money: The Economics of M-PESA”
[v] Sibel
Kusimba, Harpieth Chaggar, Elizabeth Gross, & Gabriel Kunyu “Social
Networks of Mobile Money in Kenya”, 2013, Working Paper for The Institute for
Money, Technology, and Financial Inclusion.
2 comments:
This is an excellent layout and description for an M-Pesa case study. However, you don't make a strong case for using an SNA approach. Let's look at your research Qs. Your first one--what does the MM market look like--is not really a network Q, because you don't tell us what the connections are (unlike the SNA study you cite, which talks about funds flows within and between families and villages.) And Q2 is off to a good start when you talk about ego nets, but again, the actual network needs to be defined, as in previous Q. And just listing
All this can be developed into a meaningful SNA given a bit more work. Maybe someday you'll do it. Hope so.
(Cut off from previous comment) And just listing or mentioning some SNA measures without telling us why you're using them doesn't give us insight into what the study would mean.
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