Looking closer at the credit side of M-Shwari, this is not the first telco-bank partnership to offer short term credit. Airtel teamed up with Faulu Microfinance in May to offer Kopa Chapaa, a 10 day loan up to 10,000 Kenya Shillings. And previously, there was of course M-Kesho from Safaricom and Equity Bank.

We wrote about airtime based credit scoring in March and had contributing posts from Experian MicroAnalytics and Cignifi who both work in this area. With the vast majority of mobile subscribers in emerging markets using pre-paid SIMs, there is incredibly rich data available on airtime purchase and usage behaviours. Couple that with the poor quality of information available at credit bureaus, and airtime based credit scoring is an attractive approach to targeting and risk profiling for credit products.

What does the launch of M-Shwari mean for mobile money? A few thoughts:

• The design of this product suggests telcos may be waking up to the value of their data. Telcos frequently monetise their own data for internal use to design smarter talk time promotions or offer better segmented VAS.  But M-Shwari shows how telco data can be leveraged as an asset to generate external sources of revenues.
• This credit and savings product is being offered through a telco- bank partnership rather than by the telco alone. Telcos don’t engage in direct lending or financial intermediation; rather they are focused on the high volume transaction-fee part of mobile financial services.
• Finally, it is encouraging to see mobile money customers can now earn interest; this benefit has been withheld for too long. Safaricom says 70,000 accounts were opened on the first day alone. But will this vanilla savings offering hold enough appeal to mobilise savings deposits?  One can envision mobile money savings products which better leverage the power of mobile i.e. programmed savings, innovative mobile savings reminders, progress trackers, rewards, etc.

What’s your take on M-Shwari?  What does the launch of this new product mean to you?  Is this a game changer for financial inclusion?  What do you expect the uptake to be of M-Shwari? Share your thoughts with the MMU readers.

FrontlineSMS

FrontlineSMS:Credit enables organizations that serve the base of the economic pyramid to bring the benefits of mobile money to the financially excluded by building and distributing free, open-source software for mobile money management.

FrontlineSMS:Credit’s PaymentView software is an extension of FrontlineSMS’s free, open-source technology that turns a laptop and a mobile phone or GSM modem into a central SMS communications hub. The tool enables users to send and receive text messages with large groups of people without the need for Internet access. With the PaymentView extension, users can also send, receive, and manage mobile money transactions. By expanding the uses of mobile money in developing markets, FrontlineSMS:Credit helps to fulfill the promise of mobile money to offer even the most underserved communities access to financial services and enable new business models that aid in development.

A lot has happened since we last talked to the FrontlineSMS: Credit team. In a previous blog post, we described their approach towards enabling organizations and businesses to easily use mobile money. Over the past few months, they’ve got the opportunity to test this approach through a project in partnership with a Kenyan financial services association (FSA) [1]. 

Challenge #1: Providing an easy and convenient way for groups to transfer money to the FSA…

This FSA is composed of 50 groups of around 20 people each. Like many others, it serves a large geographical area and some groups are more than 30km away from the FSA head office. This means that a representative of each group has to travel there every time the group wants to transfer money: which represents a day of travel for the representative of the group and a cost of around USD8 for the group on a monthly basis. The service implemented by FrontlineSMS: Credit allows representatives of groups to transfer money through M-Pesa directly to the FSA. FrontlineSMS estimates that there has been a reduction of up to 50% in the cost of repaying loans and a reduction of up to 85% in the time spent on repayments, depending on how far away a savings group meets from the FSA office. The groups saving the most are those who are far away from the FSA, as almost every group meets within a short walking distance of an M-Pesa agent.

Challenge #2: … without breaking group dynamics

The board of the FSA was initially worried that using mobile money would break down the group dynamics, which are very important to them. To face this challenge, FrontlineSMS: Credit has developed a process which allows FSAs to receive group payments through mobile money. A representative of the group collects money and transfers it to the FSA via mobile money.

The next step for the team is now to increase the number of FSAs using their service.

MMU: What are the main challenges faced by MFIS trying to use mobile money?

FrontlineSMS: Credit: We’ve noticed that software is a big problem. The ability of an MFI to find a software tool that enables them to easily process mobile payments is very limited, even in Kenya, where the use of mobile money for P2P transfers is very high. This software issue is a major reason why many businesses in Kenya have not adopted mobile money and have instead continued to use other forms of payment.

In addition to this, a transition to a new mode of payment combined with the new business process required at an MFI’s office to process these payments is not a small change. Within an MFI, there needs to be someone who is pushing the project forward and buy-in from the staff is essential, especially loan officer, who will be training clients on how to use the new, mobile money-enabled system. The technology is quite simple, but the human part can be a bit slower as clients adjust to repaying loans in a new way and MFI staff members adjust to a new process.

Finally, increased use of mobile money, especially larger transactions, can put strain on the agent networks in rural areas, who are not accustomed to processing larger amounts. For an individual to make a repayment, this may not apply, but if repayment is done at the group level, sometimes the nearest agent does not have sufficient float to make the transaction. However, increased cooperation between mobile money agents and MFIs or savings groups can alleviate this strain. Because groups meet and repay on the same day each month, a small amount of advance planning enables agents to retain sufficient float for group transactions.

MMU: What advice would you give other MFIs integrating mobile money to their systems?

FrontlineSMS: Credit: We would advise MFIs to plan carefully and make sure to walk through each part of the new, mobile money-enabled process, both from the perspective of an MFI staff member and a client. This enables an MFI to plan appropriately and mitigate any risks that they see in light of the new system. It also enables MFIs to design a system that fits well with their local context and customer base. Because our software, PaymentView, is free, we lower the barriers to technology adoption by MFIs and enable them to easily experiment with new processes.

We would also advise MFIs or any organization or business adopting mobile money to start with a small pilot first to work out the best system for your organization before scaling up. This means try starting out with just loan repayments and with a few savings groups. This way, an MFI can test their new system and get feedback to improve it before scaling up to include all groups and before adding other mobile money-enabled services. During the pilot, carefully measure the impact of using mobile money on your operations. This can range from increase efficiency in payments processing to time and cost savings from clients to other kinds of intended or unintended effects. Be in touch with your clients and staff members frequently to get feedback and make changes to your system as needed.

Detailed planning and iterative pilot testing can help to ensure success of a new system and process by helping with staff buy-in and improving customer satisfaction.

A lot has been written on the opportunity of using mobile money to provide microcredit and on why Micro Finance Institutions (MFIs) should be using mobile money. Indeed, mobile money is a cheap and convenient channel that can be used for loan disbursement and repayment. It also reduces the risk of fraud as MFI officers often travel with cash from the place they collect it to the MFI branch office.

However, the number of MFIs substantially using mobile money is actually quite limited, and for good reason: typical mobile money services have not been designed with the vision of serving MFIs, but rather individuals, and using mobile money to supplement their operations presents a number of challenges for MFIs. In this blog post, we present how two organizations are trying to find solutions to these challenges in Kenya.

Musoni

Musoni (‘M’ for Mobile and ‘Usoni’ for future) is a young but very promising MFI in Kenya. Established at the end of 2009, Musoni believes the next generation of microfinance is mobile. Musoni’s vision is to substantially improve the quality and availability of financial services to low income, unbanked and underbanked individuals in the developing world through the establishment and support of best-practice MFIs with an emphasis on efficiency, transparency and client focus.

Musoni is the first MFI in the world to go 100% mobile, using mobile money transfer services for all loan repayments and disbursements. Musoni has successfully integrated its back office with the leading Kenyan mobile network operator, thus enabling seamless processing of all transactions. Musoni’s success in taking advantage of the Kenyan M-PESA service, with its 45,000 agents and 18m clients, has enabled it to offer a flexible and convenient alternative to the traditional time-consuming and manual microfinance processes.

Musoni has cash-lite operations, but not branchless. The branches are places for clients to visit to meet Staff and discuss issues on hand but not for Cash transactions which are done at Money Transfer Agents and Shops. After a little over two years, Musoni has set up five branches spread out in three cities, two of which are in and around the capital city of Nairobi.

Musoni has identified Uganda as its second country of operations and plans are underway to set up the first office in Kampala, Uganda. In Kenya, Musoni works with Safaricom’s M-Pesa, but plans to use multiple mobile money services in Uganda.

Challenge #1: Reducing the cost of setting up MFI branches…

Setting up brick-and-mortar branches is quite expensive for an MFI, and Musoni made the bet that this cost could be substantially reduced if transactions were not in cash. For example, a strong room is an obvious requirement if cash is to be held at a branch. In addition, tellers are required in the branches to process the cash repayments. In many MFIs, a number of the costs associated with brick-and-mortar operations are eventually passed on the consumer. And it’s not just about cost; it’s also about convenience, speed of transaction processing and fraud related risks.

This is why Musoni decided to operate cashless. This way, using the same resources as other MFIs, particularly staff, Musoni has been able to establish more branches and serve a much larger number of customers. Going forward, Musoni has a better capability of setting up branches in more remote areas than a traditional MFI would due to its cashless nature.

Challenge #2: … while improving quality of service

Loans are disbursed and repaid via mobile money enabling Musoni to disburse loans much faster than traditional cash and cheque based models. Musoni guarantees its customers loan money within 72 hours of application. The MFI enjoys lower risks, less paper work, better customer service, easier and more accurate transaction tracking.

The first loan was given in May 2010 and since then over 18,000 loans have been disbursed, totalling over KSh.500M (approx USD 6M). Musoni currently serves over 8,000 clients.

At the moment Musoni does not take deposits or savings, but is now moving in that direction, planning to offer a variety of products around savings. A lot of work is being done to define the nature of savings products to offer, particularly to the base of the pyramid, but one thing will be unifying – they will all be mobile.

MMU: What are the main challenges faced by MFIS trying to use mobile money?

Musoni: Creating the automated bridge between mobile money and the back end systems has been the greatest challenge. Customers not only pay for themselves, they pay for others within the group and beyond. Non customers also pay for our customers. There are individuals who make wrong entries even after rigorous training, including paying for the wrong person. So the technology must be “intelligent” enough to learn and accommodate these issues with the support of customer service personnel. There being no such software in the market, we’ve had to create it and refine it continuously. Our model is cash less and minimum paper work, which means we depend heavily on the technology. It’s got to work all the time, otherwise we are in chaos.

MMU: What advice would you give other MFIs integrating mobile money to their systems?

Musoni: We’ve learned a number of lessons over the past 3 years which could be beneficial to other MFIs willing to use mobile money:

• Rather than start with brick and mortar, why not leverage mobile? Setting up systems may be challenging, but the rewards are worth the trouble.
• It’s critical to establish trust, particularly through face to face interactions. Cashless can never mean doing away with loan officers/relationship officers!
• Mobile money is a game changer; it streamlines the process and all other processes need to be adjusted accordingly.
• You must conduct market research to ensure that you are meeting customers’ needs by offering loans through mobile money.
• Customers value reliability and convenience. As you establish your back end systems, you got to aim at 100% uptime.
• Customers want to know what you will charge for any transaction. Be transparent about any fees.
• Customers will take advantage of the flexibility to pay after working hours so you better be ready for that.
• A well trained customer makes things easier for the MFI, more so if you introduce technology

In addition, Musoni is now looking to license its innovative IT platform to non-Musoni MFIs, thus greatly increasing its potential outreach and social impact.

According to a recent McKinsey Publication, “new alternative data models have cut credit losses in experimental forays into lower-income segments by 20 to 50% and doubled their application approval rates.”[1] Experian MicroAnalytics has experience implementing such initiatives.

Is there a demand for mobile loans?

We have worked with a bank and an MNO launching a set of loan and savings products as an enhancement of mobile money in South East Asia. We have done a lot of experimentation with different loan and savings products. The most successful loan product proved to be a revolving credit line, with clients choosing via their phone the amount to be credited in their wallet and offering a flexible reimbursement schedule. The most successful savings product proved to be a “purpose” product, where clients define an amount to save and a target date and the system defines the weekly deposit needed to achieve such a target. The response to the pilot was overwhelming, with over 50% response rate for the combined loans and savings offering, driven especially by the loan product. Activity rate to the MNO for their mobile money customers was also very high as the loan product was structured with weekly installments, generating at least 4 transactions per month.

How do you manage credit risk on mobile loans?

You need four distinct components to make mobile branchless loans work. These are:

1. An origination credit scoring system that utilizes the information available on the borrower at the time of application to predict credit risk. The key predictors of risk are: Airtime top-up patterns (for example, do you top-up large amounts once a month or small amounts every other day?); Voice and SMS usage; Information gathered directly from the borrower (for example income, marital status, etc.);
   Information available externally (for example, where available, from a credit bureau);
   When combining this data it is possible to develop scorecards that discriminate well credit risk.
2. An automated customer management system to send alerts to borrowers to remind them of a due payment, to increase or decrease dynamically exposure to good / bad borrowers, to streamline the management of overdue payments.
3. A credit risk agent management system todynamically rank agents by the quality of the clients they have introduced to the bank and to calculate and disburse risk adjusted commissions. In addition the system alerts agents when some of their introduced clients are late to allow early collections actions.
4. An enhanced mobile interface for the end clients that allows them to manage their credit product and review for example when the installment is due, make anticipated payments, request additional credit lines, etc., all managed in an automated and real time fashion.

Experian MicroAnalytics offers such functionality, integrating the mobile money system of the MNO and the core banking system of the bank to enable mobile loans. For more information visit www.e-microanalytics.com

The following is a guest post by Jonathan Hakim, President & CEO of Cignifi, as part of the series on airtime based credit scoring. Also read part 1 and part 3 of the series.

The Cignifi behavior-based scoring platform leverages behavioral analytics and data from mobile phone users to understand the response and risk levels of prospects and customers. For financial service providers, Cignifi scores enable profitable customer targeting, acquisition, and retention. For mobile network operators, sales of credit products linked to the mobile phone can serve to further deepen relationships with their customers.

How it works

An individual’s mobile phone use is not random. On the contrary, it is highly predictive of behavior. The Cignifi analytics platform uses leading-edge mathematical behavior models to develop consumer scores based on large volumes of mobile usage data. Anonymized call records and text messaging patterns are combined into behavioral and time-dependent attributes, which are in turn used to generate scores. Cignifi scores do not use any content from voice calls or texts. They are optimized to protect the privacy of end-mobile phone users while giving underwriters enough information to make decisions.

Traditional credit scores typically require payment history over twelve months or longer to forecast credit behavior. By contrast, Cignifi scores can be calculated with as little as one month’s calling history. Because the underlying raw data is constantly evolving, the scores are dynamic and able to leverage the resulting behavior patterns on a monthly basis. The Cignifi scores are highly effective decision keys for pre-paid customers. Pre-pay accounts for over 80% of mobile subscribers in emerging markets and they are typically new entrants to the formal financial system.

Oi Telecom pilot

In 2011 Cignifi partnered with Oi Telecom in Brazil on a pre-commercial pilot of Cignifi’s credit scoring platform. Oi is the mobile telephone subsidiary of Tele Norte Leste (TNE), Brazil’s largest telecommunications company.

The Pilot was conducted with data from pre-pay mobile customers located in 21 cities in the north-east of Brazil,, one of the poorest regions of the country with very low levels of financial penetration.

The Cignifi scoring models were built from detailed mobile phone records for 2.7m pre-pay customers. They were then tested against loan and payment data from a portfolio of 40,000 virtual credit cards issued to a set of those same mobile customers by Oi Paggo, the financial products subsidiary of Oi.

Key results:

• Cignifi Risk Score is a significant discriminator of default risk.
• Cignifi Response Score is a significant indicator of customer response.
• The scores offer lenders a substantial opportunity to improve portfolio returns through a combination of lower defaults and reduced customer acquisition costs.
• Mobile customers using the Oi Paggo credit were significantly more loyal telecom customers and spent more on their phone service than their peers.

For more information visit www.cignifi.com

Airtime based credit scoring in a nutshell

Most emerging markets have little to no infrastructure that adequately collects customers’ credit history: Credit bureaus either don’t exist, or exist on a limited number of individuals and with very thin financial data. For individuals without credit history, the result is stringent borrowing terms such as high collateral coverage, months of demonstrated savings, and/or individual or group guarantors.

The idea behind airtime based credit scoring is to use an individual’s history of airtime top up as a proxy indicator of what amount they can afford to borrow and their credit-worthiness.  The precise calculations and algorithms employed to do this is the “secret sauce” of Experian MicroAnalytics and Cignifi, two companies working in this space.

What does it take for this to work and what is the upside for those involved?

Models for Collaboration & Benefits

• MNOs are the owners of the customer data, so for starters, they have to allow analytics firms access to build the predictive models.  (It is of course possible that in some countries, airtime top up aggregators have enough customer data for this business, or that an MNO chooses to build their own predictive models, but both of these seem less likely.) The MNOs presumably would only do so if they believed they could gain the following:
  • Increased customer loyalty – Depending on the exact terms of the loan, credit is typically a fairly attractive product offering and one with the potential to keep customers loyal.
  • Drive mobile money usage –Disbursing loans and collecting weekly loan repayments, can drive increased usage of mobile money platforms, leading to increased revenue.
  • Topline revenues – MNO data is typically used for internal analytics, but monetising the data for credit scoring produces topline revenue by leveraging an existing asset.
• Financial institutions – The risk of the credit will always need to be underwritten by a financial institution i.e. bank or credit card company.  While there is certainly effort and risk involved to getting the model right, they have three things to gain if it works:  1) ability to reach a customer segment not previously accessible 2) improved ability to target the right product at the target customer i.e. loan size appropriate to the clients ability to repay and 3) revenues from loans
• Data analytics company / credit agencies – The models take time to develop before they are truly good predictors of credit worthiness, but if these firms get it right, they earn money on the valuable models they have built and hold a key position sitting between MNOs and financial institutions, who otherwise may not want to share data.
• Customer – It is the customer and the customer alone who applies for a loan and gives the ok for a company to use their airtime patterns in the approval process.  The client benefits from access to “instant decision” low value loans, which can be used to smooth monthly cash flows.

What do you think? Will MNOs use this technique to develop and offer innovative mobile money micro-loans? Will stakeholders work together to offer this service?  Is there demand from the unbanked?

Also check guest posts from Experian MicroAnalytics and Cignifi on their work to date in this area.

Additionally, in light of market saturation, MNOs face the task of growing average revenue per user (ARPU) and market share in rural areas. Agricultural Value Added Services (Agri VAS) present a considerable business opportunity due to the enormous potential user base in LDCs. The farming sector in these countries often suffers from chronically low productivity. Lack of information acts upon productivity and income levels like a glass ceiling.  However, with increasing teledensity in the developing world – Africa is being tipped to pass one billion mobile subscriptions and become the world’s second largest mobile market by 2016, mobiles are uniquely positioned to address the information and financial needs of farmers – an intervention that can help increase their incomes, yields and economic wellbeing.  Vodafone’s research indicates potential $138 billion addition to developing world farmers’ incomes by 2020

The financial and information opportunities at the base of the pyramid (BOP) in themselves hold significant untapped value for the private sector.  The BOP has both intricate financial and information needs, which have the potential to be met through mobile money and information-based mobile services.   Mobile Money can reduce the financial gap for farmers by giving them access to savings and insurance, which in itself reduces the impact of extreme weather and allows for greater investment in improving production.[1] Meanwhile, m-information services have the potential to open up significant markets opportunities, by relaying sales prices, GIS-based commodity demand information, as well as more basic yet essential information on agricultural best practices and reliable weather forecasts.

While there are existing agricultural information services provided via traditional channels such as radio and television, government extension services as they are usually referred to can be made much more efficient by leveraging the mobile channel. This can help improve their quality and trust amongst user communities increasing their potential for scale.  In addition, by linking to them to mobile financial services, farmers will not only improve their productivity but will also be empowered to make better investment and risk management decisions (e.g. request credit for new fertilizers or other inputs they need to grow more and better crops). These benefits are also likely to extend to the wider community as increased agricultural income helps rural families afford education, healthcare and other services.

The GSMA mAgri Programme

The Mobile for Development’s mAgri Programme was set up in 2009 to accelerate the development, provision and adoption of mobile solutions to benefit the agriculture sector in emerging markets. In June 2011, the programme announced the second phase of their mobile agricultural programme, the introduction of the mFarmer Initiative, a partnership between GSMA, USAID and the Bill and Melinda Gates Foundation.  The scope of the mFarmer Initiative is to support mobile phone operators and agricultural partners in launching commercially viable mobile information services that bridge the information gap and increase the productivity and income of rural small-holders.  It aims to attract 2 million of the worlds’ poorest farmers to become users of mFarmer Services by 2013. This compliments their previous work on mobile agricultural services in India and Kenya.

The team has recently launched the Agri VAS  Market Entry Toolkit which explores the opportunities for Agricultural VAS  and covers emerging best practice on marketing, service design and business modelling.  It is primarily addressed to Mobile Network Operators (MNOs), other service providers, and agricultural organisations that are looking to partner and launch Agri VAS.

Just as the successful provision of mobile financial services for the BOP requires innovative partnership models; Agri VAS will require similar efforts from the part of its stakeholders.  While MNOs have a leading role to play, they will need the collective support and partnerships from key stakeholders in the agricultural supply chain in order to fully unlock the benefits for farmers in LDCs.

[1] For more information on agricultural m-insurance, visit the MMU Insurance Topic Page

Launched in 2010, FrontlineSMS:Credit is a social enterprise that produces software tools to enable organizations and businesses to easily use mobile money. Realizing that there was a gap in the market for an efficient way of managing organizational data, FrontlineSMS seized this opportunity and linked FrontlineSMS’ existing platform to mobile money.

FrontlineSMS:Credit derives its name from its original target market: MFIs. In the early days of mobile money, MFIs wanted to connect to mobile money services in order improve their processes and reduce their transaction costs, especially in rural areas. However, since MFIs are complex entities in terms of financial needs, FrontlineSMS:Credit has decided to broaden  its scope and target a wider group of  organizations that also trade directly with the BOP and which could also benefit from mobile money such as NGOs and SMEs.  Nathan envisions the role of FrontlineSMS:Credit as that of an interface; a partner for MNOs which helps SMEs, NGOs and MFIs leverage the potential of mobile money.

FrontlineSMS:Credit appears well-positioned to overcome some of the main obstacles that have impeded SMEs and MFIs from adopting mobile money. According to ACCION International, one of the biggest challenges for MFIs is the weakness of their technology infrastructure[1]. For example, ACCION International highlights the difficulty MFIs have in connecting to an MNO’s mobile money platform. FrontlineSMS:Credit works as an interface with operators by providing this service.  In addition, a weak country infrastructure (including difficulties to access the internet) often prevents MFIs from using alternative channels. FrontlineSMS:Credit does not require internet access and not only does it provide free turn-key software to organizations, but also serves as an interface, in addition to providing consultancy services to help organizations implement its software when there is no in-house capacity.

FrontlineSMS:Credit is currently running a series of pilots in Kenya with a wide-range of organizations such as a member-owned community-level rural MFI, a microinsurance provider that plans to expand a life insurance and savings product from group to individual distribution through mobile payments, and a final pilot involving local NGOs in Western and Central Kenya which distribute ToughStuff solar products through networks of micro-franchisers.

The software, primarily designed for the Kenyan market, will be publicly released at the end of the year. There are plans to expand to other countries where mobile money services already exist at a large scale, and where there are operators willing to link up their platforms to SMEs and MFIs.  We look forward to hearing more about the developments of FrontlineSMS:Credit in the coming months.

[1] In December 2009, ACCION International published a report on the 10 obstacles for MFIs launching alternative channels, including mobile money channels. In particular, the following elements are listed among challenges: “Technological infrastructure remains weak”, “Dedicated and specialized human expertise for channel projects are lacking”, and “MFIs are unsure about how to engage third parties”.

ACCION International, “Accelerating Financial inclusion through Innovative channels. 10 Obstacles for MFIs Launching Alternative Channels – and What Can Be Done About Them”, 2009

MMU:   What advice do you have for mobile operators and others who are trying to develop financial services for the poor?

ED: Keep your eyes open, evaluate the impact of what you are doing, be willing to adapt and change, don’t over promise, and measure what you deliver.

MMU:  You touch upon the notion of risk and how agricultural profitability could be 30% higher if there were no weather risks.  In a time of climate change, what role do you see for agricultural mobile insurance products such as Kilimo Salama in Kenya?)

ED: The problem many current weather insurance product is that the demand for them tend to be quite low. The reason is that the products that the market can sustain are not considered to be very attractive by the farmers: these products are generally very simple (for example a weather insurance product will pay you if the rainfall level falls below a specified levels), which make them easy to administer, but also implies that they don’t cover many of the relevant risk: for example it may be very dry in your field but the rainfall at the weather station is above the threshold.  There is a need to continue to develop better products and products that can be administered as cheaply as possible (so that they are worthwhile for farmers). But in the book, we argue that there may also be a need for governments or international organizations to subsidize insurance, at least for a while, while the market gets established.

MMU: The development community believed microfinance could increase the poor’s earnings partly through business growth, partly though new business creation and partly through greater investment in human capital. Yet, in practice microcredit was used not just for business investment but also for consumption, repaying other loans, etc.  Was the non-business use of microcredit its downfall?

ED: No, I don’t think so.  First I think that the problems that microcredit is experiencing today have nothing to do with its intrinsic value; they are mostly of a political nature. Second, it is  a great use of microcredit to repay an old debt: if you have a debt on which you pay 70% interest or more (actually up to 5% per DAY for the fruit vendor), and a microcredit loan comes along, and you only have to pay 25% or 30% in interest, then it really help freeing up money. The rate of returns of doing that is likely greater than what you could do in your business. In a sense I would say that was surprising in our evaluation of a microcredit program in Hyderabad is that few people used their loan to repay an old loans. This was perhaps because they want to maintain a relationship the money lender in case they need money quickly.

I think the problem with microcredit was less what it is doing, which I think is quite respectable and important, than what it promised to do, which was a bit inflated. If the hopes had been reasonable, people would not be so disappointed today. I hope that microcredit will be able to continue and not be a victim of a fad in reverse.

MMU: Increasingly the development sector is turning to RCTs as the new standard for measuring impact?  Every methodology has its drawbacks – how can development practitioners strengthen their understanding of impact?  Are there methodologies complementary to RCTs than need to be maintained?

ED: Obviously I think RCT is a great methodology, and to be honest, I don’t see many drawbacks to it, but then of course I am biased. But there are other useful methods as well. For example, Tavneet Suri is evaluating the impact of M-PESA in Kenya using the progressing introduction of the program across Kenya: essentially she compares places over two periods, and some of them got the M-PESA program in the meantime, while other did not. One needs to be careful in exploiting the data, but this can be done and is very helpful. That said, a program like mobile money lends (or programs that can be layered on it) lend themselves wonderfully to RCT, so there should be a lot of exciting opportunities there.

MMU: Thank you very much

Esther Duflo is Abdul Latif Jameel Professor of Poverty Alleviation and Development Economics in the Department of Economics at MIT.. She has received numerous honors and prizes including a John Bates Clark Medal for the best American economist under 40 in 2010, a MacArthur “genius” Fellowship in 2009. She was recognized as one of the best eight young economists by the Economist Magazine, one of the 100 most influential thinkers by Foreign Policy since the list exists, and one of the “forty under forty” most influential business leaders under forty by Fortune magazine in 2010. Together with Abhijit Banerjee and Sendhil Mullainathan of Harvard University, she founded the Abdul Latif Jameel Poverty Action Lab in 2003

For more than fifteen years Abhijit V. Banerjee and Esther Duflo have worked with the poor in dozens of countries spanning five continents, trying to understand the specific problems that come with poverty and to find proven solutions. Their new book is radical in its rethinking of the economics of poverty, but also entirely practical in the suggestions it offers.  It argues that so much of anti-poverty policy has failed over the years because of an inadequate understanding of poverty.  Through a careful analysis of a very rich body of evidence, including the hundreds of randomized control trials that Banerjee and Duflo’s lab at MIT has pioneered, they show why the poor, despite having the same desires and abilities as anyone else, end up with entirely different lives.

MMU: Dr. Duflo, Congratulations on the book launch.   How do you measure impact for financial inclusion?  Widely believed to be an important factor to lift individuals out of poverty, do we actually have evidence that the existence of financial services leads to increased income?

ED: There is some evidence. There is a paper by Robin Burgess and Rohini Pande that looked at the “social banking” regulation in India: for several decades, banks were forced to open bank branches in rural areas. Burgess and Pande found that poverty reduced and poor household were able to diversify their activity when rural bank branches were opened. At the same time, there were many problems with the scheme (not least that a lot of the loans the banks made were never repaid, and ended up being used for political giveaways), so the Indian government eventually shut down the scheme.

There is also a recent study by Pascaline Dupas and Jonathan Robinson, where they measure the impact of access to a savings account by randomly offering to pay the opening fees for a number of depositors. They find that not all people who have access to the free account use it: most men did not, and among them, about half of them did. But even though, a large effect was evident: small business owners were able to save and buy in bulk at better prices, so their income increased. They were able to deal better with health shocks, such as a bout of malaria. We need much more evidence on the effect of access to financial services.  The problem is that the cost of opening this savings account is very large (more than 5 dollars by account). Finding a way to reduce this will be essential to make financial inclusion possible.

MMU: A household that wants to invest in a new business uses savings as a way to accumulate collateral and increase the amount they can borrow. Yet many poor households have a hard time finding a place to save.  How can mobile money help address this situation?

ED: There are many reasons why it is hard for poor people to find a safe place to save, but one reason is that banks do not want to deal with very small accounts, due to the fact that the paperwork needed to accept savings is demanding. That means that only bank employees are allowed to handle money that belongs to a depositor. And there is not a bank branch in every town.

With mobile money, if the account is linked to a bank, people will be able to wire money in and out of their savings accounts using local correspondent, without having to trek all the way to the bank. A number of countries have passed new laws permitting this kind of deposit taking (in India, for example, this is called the Banking Correspondent Act), and this may be greatly help by mobile money. This might eventually revolutionize the whole business of savings.

MMU: In the book you make an argument that exercising self-control with regards to savings decisions tends to be more difficult for the poor? How can this problem be addressed?

ED: It is difficult for everyone, but the poor suffer the additional handicap that the goods they really aspire to may be relatively harder to reach.  So even when they have a savings account, or other savings opportunity (like investing in their own business), they don’t always take advantage of it. Innovative financial products that have a “commitment feature” to them. For example, some accounts could be earmarked for a specific goals, ‘school fees’ or ‘fertilizer’, and could not only be released for this goal. Or the money could be locked for a certain period or until some specific goal has been met. A study by Nava Ashraf, Dean Karlan, and Wes Yin showed that these types of account can help those who take them up to save more. One could design even more creative program targeted exactly around the needs of the specific person. For example, coffee farmers could decide IN ADVANCE, to dedicate part of the big lump sum they get at the end of the season towards a specific goal. We are hoping to pilot soon such a program in Kenya or Tanzania.

Tomorrow we will be posting the second part of this interview with Dr. Duflo.

Esther Duflo is Abdul Latif Jameel Professor of Poverty Alleviation and Development Economics in the Department of Economics at MIT.. She has received numerous honors and prizes including a John Bates Clark Medal for the best American economist under 40 in 2010, a MacArthur “genius” Fellowship in 2009. She was recognized as one of the best eight young economists by the Economist Magazine, one of the 100 most influential thinkers by Foreign Policy since the list exists, and one of the “forty under forty” most influential business leaders under forty by Fortune magazine in 2010. Together with Abhijit Banerjee and Sendhil Mullainathan of Harvard University, she founded the Abdul Latif Jameel Poverty Action Lab in 2003.