In the last few years we have seen a notably bleaker narrative around our efforts to end global poverty. Severe impacts of climate change, lingering effects of an unprecedented pandemic, and a looming food insecurity crisis: all suggest that the challenges we face in achieving the UN Sustainable Development Goals (SDGs) set in 2015 are more daunting than ever.
Global economic and political challenges mean that resources to support poverty relief programs are finite. It’s clear that – as we pass the half-way point to 2030 – if we are to reach the SDGs we need to allocate those resources as efficiently and effectively as possible.
Now more than ever, there is a pressing need to understand which solutions are most effective in helping the vulnerable, in order to channel funding where it will have the greatest impact on poverty and inequality. However, one of the longest standing problems in international development is the difficulty of comparing outcomes across different programs.
As one of the largest and fastest growing sectors in development, microfinance is a good example of this problem. Over the past five decades, microfinance institutions (MFIs) have sprung up across the Global South to provide financial services to previously unserved low-income, remote and rural households. The sector now serves over 140 million households, and access to finance can be transformative, allowing microfinance clients to start or grow small businesses, cover medical costs or pay children’s school fees. However, research also shows that client outcomes are highly dependent on many different ‘performance’ factors for providers, for example how carefully clients are selected, how well staff are trained, and how effectively the institution trains clients.
As with any other area of development work, we could get more bang for our development buck if we could identify the highest performing institutions and redirect our finite funding to those providers. But such efforts have until now been stifled by a lack of good quality, comparable and complete data.
A new initiative is aiming to change this. The 60 Decibels Microfinance Index was launched earlier this year to provide comparable outcomes data across the microfinance sector.
60 Decibels uses a lean-data approach to data collection. Expert enumerators survey a sample of clients by telephone to understand their experience with the MFI, for example, to what extent have they seen an increase in income and savings, an improvement in quality of life, or increased their spending on education, essential healthcare costs or home improvements.
Using this approach, 60 Decibels surveyed a total of 18,000 microfinance clients across 72 MFIs in 41 countries in the first three months of 2022, completing analysis of the data and publishing results from their Microfinance Index in June. Each of the 72 participating MFIs received a report detailing results for their sample of 200–250 clients across 18 key indicators, and how each of these results compared with regional and global benchmarks for all 72 MFIs. Institutions can identify where they perform well, and where they perform below average, leading to action to address specific challenges and shortfalls.
International development networks participating in the initiative are using these benchmarks to better direct investment. One of those networks is Opportunity International, a global non-profit that has funded microfinance in developing countries for over 40 years. Nine of Opportunity’s microfinance partners participated in the first year of the Microfinance Index, and results were positive.
It was found that Opportunity’s partners do a good job of reaching households who did not previously have access to finance; a majority of clients reported an improvement in quality of life thanks to the microfinance services received; microfinance services improved client resilience, increasing savings balances and improving the ability of clients to meet unforeseen expenses; and clients generally reported few problems in making loan repayments.
Perhaps more importantly, the results also showed a broad range of performance across Opportunity’s partners. For example, a much larger percentage of clients increased savings in the best case, compared to the lowest performing partner. These variations allow Opportunity to reward high performers with additional funding, and work with the remaining partners to address challenges and help them improve performance.
Based on the success of the Microfinance Index in its first year, 60 Decibels hopes to double the size of the survey in year two, covering 150 MFIs who collectively serve 50 million clients, or around a third of the microfinance sector, and providing national outcome benchmarks for the first time. 60 Decibels plans to take the same approach with the energy sector next, allowing institutions that are connecting remote and rural communities to the grid, or providing solar-powered lighting or clean cooking stoves, to compare themselves with their peers.
This innovation in data collection, analysis and benchmarking should lead to more effective allocation of development funding across all parts of the development sector. We might also expect an increase in overall funding for international development thanks to greater confidence about outcomes and the ability to ensure value for money in development spending.
As the challenges of meeting the SDGs seem tougher than ever, this data-driven approach to understanding performance and allocating resources will be an important spur to more effective and impactful international development programs.
This article appeared first on Devpolicy Blog (devpolicy.org), from the Development Policy Centre at The Australian National University. Calum Scott is Global Impact Director for Opportunity International. He leads Opportunity’s program to promote best practices in client-focused financial inclusion, and impact measurement and reporting, across Opportunity’s global network of microfinance and development partners.
Disclosure: Opportunity International part-funded the 60 Decibels Microfinance Index.