Most economic development programs that aim to reach the poorest households have not been designed using a sustainable business approach. Instead, these programs have been developed as grants and charity-driven projects. While there is a role for grant-driven programs, organizations can also make sustainable business decisions to extend outreach to poorer populations in the medium to long term.
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Grameen Foundation’s holistic approach to microsavings provides the framework and tools to develop and offer convenient, accessible, and secure poverty-focused savings programs while building sound financial, organizational, and operational practices that help transform microfinance institutions (MFIs) from credit-led to demand-driven institutions.
Since 2008, Fonkoze has been using PPI and food security data to monitor and evaluate the progress of clients participating in its targeted programs for hurricane relief. Fonkoze is now also using it for earthquake recovery efforts.
The capability of their staff is perhaps the single most important resource microfinance institutions (MFIs) have for meeting the challenges of reaching more people, while navigating financial, regulatory, political, competition and other issues.
Effective data analytics is essential for meeting the bottom line, and is even more critical when you are trying to meet a double bottom line. This case study examines how PT Ruma – a social enterprise based in Indonesia – is using social and business data to change its business practices.
This case study shows how PT Ruma, the first technology-for-development initiative to use the PPI, applied its findings to guide twin goals to reach more poor women with its mobile phone business microfranchises and to affirm its social accountability to shareholders.
For over 30 years, microfinance institutions (MFIs) have been successfully serving some of the poor and poorest people around the world, primarily with credit products. Generally however, MFIs grapple to successfully add savings services to their portfolio of financial products.
Targeting and selecting groups for social development programs based on poverty levels can be a powerful first step in achieving greater impact. However, the complex nature of poverty often leads to processes that are accurate, but extremely customized, making it difficult to make comparisons across projects and geographies. This paper presents a methodology that aims to address both these issues.
The case study explores how Grameen Koota, a leading socially-focused microfinance institution in India, is using the PPI to measure and track its clients’ movement out of poverty.
This case study illustrates how PRISMA Microfinance, an MFI in Peru, has collected three years of PPI data to reach and serve its target clientele. It also discusses the challenges and opportunities that the institution is facing and how it plans to address them.