Financial Inclusion of the Poor in Peru

Dr. Ana Marr, University of Greenwich, London, UK

Dr. Janina Leon, Universidad Catolica de PeruMg. Fatima Ponce, Universidad Catolica del Peru

LACEA 2012, Lima - PERU

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Content1. Background2. The importance of the study3. The Peruvian microfinance experience4. Poverty in Peru5. Hypothesis and Empirical model 6. Analysis of results7. Main lessons

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1. BackgroundReview of international academic literature on

microfinance. Particular interest in the debate about potential trade-off

between MF financial sustainability and poverty reduction. Cull et al (2007): 124 MFs in 49 countries. Evidence of

trade-off based on loan methodology (group vs individual), MFI size and age. Larger and older individual-based MFIs performed worse on outreach to clients.

Mersland and Strom (2008): 32 NGOs, 68 private MFIs, in 54 countries. They find little evidence of importance of ownership but regulation matters.

Karlan and Morduch (2010): Financial inclusion. From simplest form (micro-credit) to broader inclusion (savings, insurance, remittances, etc). Links with poverty.

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2. The importance of the studyOne of the first studies on financial inclusion –

taken as a specific subject of research. Applied to one of the most dynamic

microfinance markets in the world, i.e. Peru. Obtained exclusive information about financial

inclusion of all regulated MFIs in Peru. We employ the simplest concept of financial

inclusion, i.e. access to micro-credit. The determinants include: MFIs’

characteristics (i.e. size, age, branches); performance; strategic alliances

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3. The Peruvian Microfinance ExperienceHistorical facts

Financial requirements Importance of public policy

Current Financial System and Microfinance (Table 2, p.11)

Role of Prudential regulationMain formal and non-formal channels

Microfinance in Regulated Institutions Commercial banks “Non-bank” microfinance institutions

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4. Poverty in PeruMain features (Graph 1, p. 12)

Poverty and extreme poverty in the countryInequality of income –main trends

Financial Inclusion and Microfinance – main indicators (Graph 2, p.13)

Credits by Poverty LevelLoans by Poverty Level

Newly banked population (Graph 4, p.14; Graph 5, p.15)

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5. Hypothesis and Empirical modelResearch questions: How far has the Peruvian population

gained financial access to microfinance? Main hypothesis:

Financ.incl. = f(MFI charact; MFI profitab.; MFI social perf.; (+) (-) (+)

  MFI strateg connect, econ sectors, ). (+) (¿?)

Methodological issues:Main variablesData basesEmpirical model

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6. Main Correlations of Newly Banked Clients

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GRAPH 6: SCATTER PLOT BETWEEN: TOTPERS and PROFITABILITY, TOTPERS and NUMBER of BRANCHES, AND TOTPERS and ASSETS

Source: Own elaboration.

0

4,000

8,000

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ROE2008

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Positive correlation between newly-bankable clients (TOTPERS) and MFI profitability (ROE, rTOTPERS, ROE= 0.73), number of MFI branches (NSUC, rTOTPERS,NSUC= 0.92) and the MFI total asset value (ASSETS, rTOTPERS,ASSETS= 0.95).

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6. Multivariate Analysis of Results ^

TOTPERS = 1202.7 +7.07ASSETS + 64.2NSUC – 1364.4ANTIGUO + 1074 RBN9t-stat 1.43 6.5 2.3 -2.9 2.1

R2= 0.91 F=71.3All the slope coefficients with a significant level to 5%.

Positive relationship between the newly-banked clients and the value of total assets of MFI: For each million of New Soles increasing the MFI assets, around seven new clients will be banked, ceteris paribus.

Positive relationship between the newly-banked clients and the number of MFI branches: For each new MFI branch open, around 64 new clients will be banked, ceteris paribus.

Number of newly-banked clients closely associated to the MFI growth in Assets and # Branches; still estimated values are small.

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7. Main lessonsConclusions

Financial inclusion in the last decadeMicrofinance and poverty

Policy inferences

Further research

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TABLE 2: FINANCIAL INSTITUTION BY TYPE OF CREDITSType FI

Banks CMAC CRAC EDPYMES

Financial

Entities

Total

Commercial 56.1 9.1 6.6   3.0   11.0    

  97.5

1.3

  0.2   0.1   0.9 100.0

Mortgage 15.0 4.2 2.5   6.9   1.3    

  96.7

2.2   0.3   0.4   0.4 100.0

Microcredit 10.9 66.9

69.7   79.4   53.1    

  52.0

26.2

  5.7   3.6   12.5

100.0

Family consumption

18.0 19.9

21.2   10.6   34.7    

  82.6

7.5   1.7   0.5   7.8 100.0

Total 100.0

100.0

100.0

  100.0

  100.0

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GRAPH 1: PERUVIAN REGIONS BY INCIDENCE OF POVERTY, 2010

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GRAPH 2: LOANS BY TYPE OF FINANCIAL INSTITUTION AND REGION

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GRAPH 4: POVERTY INCIDENCE & NEWLY-BANKED BY REGIONS

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0.000.200.400.600.801.001.201.40

0.010.020.030.040.050.060.070.080.090.0

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Poverty Incidence (%) Newly-Banked pc (%)

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GRAPH 5: POVERTY INCIDENCE AND NEWLY BANKED – Scatterplot

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0.00

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Poverty Incidence

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GRACIAS!!

THANK YOU!!

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