Responsible Finance Forum

Factors Influencing Poverty Outreach Among Microfinance Institutions: Peru

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Hailed as the “Andean miracle,” Peru has been on of the fastest growing and most stable economies in Latin America.

 

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Background

Hailed as the “Andean miracle,” Peru has been one of the fastest growing and most stable economies in Latin America (‘IMF Survey: Peru: Latin America’s Economic Performer’ 2013). Over the period 2002–2012, the Peruvian economy almost doubled in size, real GDP grew at an average annual rate of 6.3%, and the average annual inflation rate fell to 2.8%, the lowest in Andean countries. The Peruvian economy relies heavily on its natural resources. It exports copper, gold, silver, zinc, lead, iron ore, fish, petroleum, natural gas, and lumber. During the 2008–2009 global financial crisis, Peru’s annual economic growth slowed to 0.9% but was one of the few in Latin America to maintain positive growth. The low and constant inflation rate has enabled the country to promote foreign investment and the development of a bustling financial sector. We will argue in this report that general financial sector development by non-MFIs has had a large impact on improving financial inclusion, even without explicit targeting of the poor.

Poverty incidences in rural areas of the country are high, at more than 60%. Peru’s economic future is promising given its recent economic growth and its low inflation rate. However, Peru has the challenge of coordinating economic policy with social issues: unequal income distribution, rural poverty, the environmental impact on rural communities by mining, a large informal sector, and a lack of social services in rural areas. The Peruvian government has implemented policies to promote a range of social programs, such as the cash-transfer program Juntos. Impact evaluations have demonstrated that these policies have been influential in reducing poverty incidences (Perova and Vakis, 2009).

Peru has held the top position in the Global Microscope, a microfinance industry report published by the Economist Intelligence Unit, for the past seven years. The report assesses the regulatory ecosystem for financial inclusion across 55 countries. The Superintendencia de Banca y Seguros (SBS) has been working to develop a regulatory framework to supervise and promote financial services to the poor since 1997. Nonetheless, financial inclusion is relatively low. According to the World Bank’s Global Financial Inclusion Index (Global Findex), only 20% of adults held an account at a formal financial institution in 2011 (World Bank, Financial Inclusion data, 2014).

In 2013, Peru became the first country in LAC to pass a law on electronic money, the intent of which is to promote financial inclusion amongst the unbanked in remote areas. However, over-indebtedness in the microfinance sector is a growing concern. In 2013, Standard & Poor’s issued a warning on the credit quality of loan portfolios due to growing delinquency and decreasing returns on assets and equity (Economist Intelligence Unit, 2014). The report uncovers that over-indebtedness has led most MFIs to incorporate internal policies to refuse service to individuals with three or more outstanding loans. Coupled with the high banking saturation in Peru, this has led MFIs who would have provided loans to the more affluent unbanked to broaden their outreach to poorer clients.

Peru is a country with a varied geographical landscape, defined by forest, highland, mountains, and a long coastline. This geospatial variation is a key factor in poverty outreach. The map in Figure 1 shows poverty incidence by region. Rural areas of Peru have much higher incidences of poverty than urban areas (38% versus 16%). The north of the country tends to see a higher incidence of poverty. Huanuco and Huancavelica experience the highest rural poverty incidences at 61.6% and 63.4%, respectively.

Conclusions

  • The consistently higher penetrations in urban areas supports our main hypothesis: poverty outreach is higher in areas with high banking sector competition and within MFIs with restrictions on outstanding debts of new clients.
  • MFIs consistently have relatively low concentrations in rural areas, in particular in areas with geographical challenges such as the forest of Loreto and San Martin or the highlands of La Libertad and Puno.
  • The regression analysis finds that women receive smaller loans than men; however, they also consistently receive larger numbers of loans. Less poor clients receive larger loans and are more likely to receive repeat loans. Given the concern for over-indebtedness in Peru, larger loans being disbursed to less poor clients appears to be an intuitive finding, particularly as less poor individuals are receiving more frequent loans, which may be more suited to the repayment abilities and needs of poorer individuals.
  • Other key findings include that the areas which receive on average larger loans reflect diversification of the portfolio.

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