Kevin FRYATT kicked off this session by asking the panel and audience to consider the tension between the social and financial bottom line of microfinance institutions (MFIs). He wondered where we can help practitioners to make decisions based on frameworks which look at the complementary of social and financial performance instead of their divergence. Can we move beyond hunches to conclusively show that investing in social performance makes perfect business sense?
Aldo MOAURO presented a study by Microfinanza Rating (MFR) and the Centre for Responsible Banking and Finance at the University of St. Andrews into the relationship between social and financial performance of MFIs. The study was based on a sample of 115 MFIs using MFR's database of social and financial ratings. The sample represented MFIs from across the world and of different institutional types (e.g. NBFIs, NGOs, credit unions, banks). The results of the study showed that there is no linear relationship between financial and social performance (SP), but that the two are clearly correlated.
The relation between internal social performance and financial performance showed an inverse parabolic shape, meaning that initially investments in employee motivation pay off in better financial performance, until they reach a point where additional staff incentives do not lead to more motivation and even start affecting the financial bottom-line negatively (e.g. over-selling to meet targets). When looking at external social performance, e.g. measures such as client protection and social responsibility, the picture is reversed. Here, initial investments in client protection are costly and negatively affect financial performance until a minimal client protection level is reached to build client loyalty and investor trust. Once MFIs invest to move from this adequate to a high level of client protection, financial performance can improve strongly. According to Moauro, the study can contribute to MFIs social performance investment strategies and better balance such strategies with their mission towards social performance. It also serves by showing the business case of SP investments.
Michael RAUENHORST presented the Probability of Default Model for MFIs developed by Moody's Analytics. He explained that the Social Performance Group was specifically established to develop tools to analyse and measure social outcomes in microfinance and impact investing. He explained how the model was developed by carefully selecting and testing financial health indicators and social and financial factors which capture risks of default. The team analysed 46 single financial factors, out of which 21 were recommended for further exploration. These were combined in multi-factor analyses to come to the best model of financial performance. This model reached a predictive power of 73%. In a similar way, social factors were analysed with Moody's Social Performance Assessment, using information from the MIX. Eventually a combined model of two social (debt collection practices, range of products offered) and five financial factors was developed with a predictive power of 79%.
Although this was still a preliminary research effort and did not yet consider external factors, Rauenhorst indicated its outcomes did strongly support that a double bottom-line makes sense. It is a combination of social and financial performance which reduces risk for default and should be focused on by investors.
Fryatt congratulated the two research efforts for showing such promising outcomes, but also wondered about data availability and quality. He asked the panel how we can establish a more stable and comparable base of data points. Moauro explained how the industry is now aware of the need for social performance data collection. However, a more common framework for data collection is still needed to improve robustness and reliability of analyses. Rauenhorst added that data availability is improving and increasingly standardised. However, he also stressed the importance of diverse data inputs to improve quality, including outcomes of client surveys using automated systems based on automated voice response (AVR) or text messaging.
When questioned about the value of models which do not take into account external factors, Rauenhorst explained that this will be included in follow-up research. He added that such follow-up research should also uncover the effects of particular social performance standards on the double bottom line to validate and further improve on the tool-set available to practitioners, supporters and investors. Moauro added that data can be used and interpreted in different ways. For now, both research projects show that social performance matters for financial results. For future efforts, we need to ensure that research remains focused on improving impact by developing better products meeting client needs, and in better performance of MFIs to ensure system stability.
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