By Dave Weber, KF16 Cambodia
The microfinance industry has been slow to adopt information and communication technologies (ICTs) (Ivatury 2004, CGAP 2009). Everett Rogers, in his 1962 book Diffusion of Innovations, suggests that adoption of technology follows an s-shaped curve. In other words, adoption starts slowly and picks up pace before slowing down. He also suggested that adopters of technology (whether they be individuals, organizations, industries, or economies) can be segregated into one of 5 categories in a normal distribution as shown the chart below:
Let’s look at the example of mobile phones at the individual level of adoption. Zach Morris from Saved by the Bell was an innovator. He was in the first 2.5% of individuals to adopt a cell phone. He discovered intelligent uses for his brick-sized phone like making prank calls to Mr. Belding, asking Screech to help him cheat on a test, or confronting Slater on asking Lisa to the prom when they both knew that Zach and she were going steady. Here’s a photo I found on the Internet as proof:
My first mobile phone was acquired in 2002. It was smaller than Zach’s, had a black and white screen, and had an ‘app’ where you could manually type in notes and durations to create your own ringtones. I spent the good part of a semester coding in “Here Comes the Bride” as a surprise to my then fiancee, now wife. Her 20 seconds of enjoyment was more than worth my effort. Although that feature was innovative, I probably adopted my first mobile phone in the early or late majority.
Now moving on to my grandparents, who just acquired their first mobile phones in 2009. They were interested in groundbreaking features like large buttons and large-font screens. If we’re limiting the population to America, they would likely fit in the laggards category of individual cell phone adoption.
The microfinance industry as a whole could be grouped into the ‘late majority’ or ‘laggards’ category of technology adoption when compared with other banking industries. There are many reasons for this:
- MFIs operate in the developing world where there are greater barriers to technology adoption
- MFIs operate in economies where labor is relatively cheap and goods are relatively expensive
- Technology relies on electricity, which is unreliable in many parts of the developing world
- A robust and interconnected management information system (MIS) relies on Internet bandwidth, which is slower in many parts of the developing world
- Many MFI clients are not technologically savvy and are uncomfortable with technological interfaces to MFIs beyond mobile phones
Therefore, many MFIs are in a state of transition, many still on paper-based systems or simple spreadsheet-based systems. Information and communication technologies (ICTs) like mobile phones, relational databases, and client-server architectures are disruptive technologies that greatly impact the means by which MFIs operate.
We hope the change is for the better. We know that ICTs lower costs associated with transaction and coordination. As these costs decrease, MFIs should be able to lend to poorer borrowers while maintaining financial viability. Also, ICTs decrease the costs of communicating and processing transactions over a distance. Sending an e-mail one additional mile or making a phone call to someone one additional mile away is very low. This phenomenon has been called the Death of Distance.
A theoretical connection that I seek to make in part of my dissertation research is that the technological capabilities of an MFI enable them to lend to more geographically distant and poorer borrowers. With new technologies emerging in the microfinance industry such as mobile banking, borrowers do not need to make a trip into town to make a loan payment at their MFI branch and loan officers do not require as many trips to the field. Payments can be made electronically by borrowers using their mobile phones. It is estimated that only 25% of the world’s population have access to financial services, but 75% use a mobile phone. The infrastructure (cell towers and mobile phones) are already in place in most of the developed world. As MFIs adopt these technologies, they should be able to lend to borrowers that are increasingly rural and isolated while maintaining financial viability.
The term I use here to describe lending to poorer and more distant borrowers is ‘social performance.’ However, social performance is a much larger umbrella term that looks at the social impact that that MFIs have on families and communities in aggregate. It is a migration from the original MFI mantra of ‘do no harm’ to ‘do good.’ I applaud the industry’s recent emphasis on social performance alongside financial performance.
One would think that there is a tradeoff between social performance and financial performance, but research suggests this is not the case. While MFIs with outreach strategies do have greater operational costs, other benefits such as staff productivity and portfolio diversification outweigh these costs. Bedecarrats et al. (2009) state the reason for this is that MFIs with an outreach strategy have greater client participation and work in markets with lower levels of competition. MFIs with an outreach strategy also generate a greater social impact.
So what is Kiva’s role in all of this? Kiva Fellows like myself are playing an active role in Kiva’s data collection with respect to the MIS capabilities and social performance of their field partner MFIs. Kiva fellows enlist the help of MFI staff in various departments to collection information required on the MIS survey developed internally. Read here to learn more about Lorena Gil’s (KF12) experience in administering this survey to her host MFI in Chile. The social performance survey used by Kiva, CERISE, is a very comprehensive tool developed by a French organization. Read here to learn more about Casey Unrain’s (KF12) thoughts on MFI social performance and his experiences in administering the survey.
Please join me in helping families improve their livelihoods by making a $25 loan to an entrepreneur on Kiva.
Dave Weber is a 4th year PhD candidate in Information Systems at the W. P. Carey School of Business at Arizona State University. His dissertation topic is on the impact of information and communication technologies on the microfinance industry. He and his wife worked at Woodstock School in the Himalayan foothills of India and have volunteered with NightLight in Bangkok aimed at assisting the victims of sex trafficking. When he is not reading, writing, and researching, Dave enjoys playing basketball and tennis, music, traveling, wreaking havoc on his Harley, and rooting for the pathetic Cincinnati Bengals.