An Emerging Business Case for Consumer Protection

December 2018

AN EMERGING BUSINESS CASE FOR CONSUMER PROTECTION Regional Assessment of 22 Smart Certified Financial Services Providers

ABOUT THE PARTNERSHIP FOR RESPONSIBLE FINANCIAL INCLUSION (PRFI) The Partnership for Responsible Financial Inclusion (PRFI), formerly the Microfinance CEO Working Group, is a collaborative effort by ten leading international organizations supporting the responsible delivery of financial services to low-income populations around the world. Harnessing the power of the CEOs and their senior managers, the PRFI commits to accelerating financial inclusion by leveraging their joint expertise in the advocacy and delivery of innovative, scalable, and responsible financial services for poor and low-income clients. Today, the members include Accion, Aga Khan Agency for Microfinance, BRAC, CARE, FINCA, Grameen Foundation, Opportunity International, Pro Mujer, VisionFund International, and Women’s World Banking. These organizations, through more than 260 local partners, offer a diverse set of products and services to accelerate excluded populations and underserved clients into the financial services ecosystem.

ABOUT THE ACCELERATING RESPONSIBLE MICROFINANCE PROJECT The IFC-PRFI Accelerating Responsible Microfinance Project is a three-year collaboration to accelerate responsible finance by supporting Smart Certification missions among the PRFI’s network: Accion, Aga Khan Agency for Microfinance (joined in 2017), BRAC, CARE, FINCA International, Grameen Foundation, Opportunity International, Pro Mujer, VisionFund International, and Women’s World Banking.

The collaboration is aimed at building a critical mass of certified entities to advance responsible microfinance globally. Participating FSPs are selected based on commitment, capacity, and client reach. By providing financial resources, the joint collaboration enables affiliated FSPs to prepare for and undergo certification to meet the Smart Campaign’s Client Protection Principles. Making such practices an industry standard is central in realizing a vision where all clients are not only included, but both clients and institutional stability are also protected.

ABOUT THE RESEARCH This report captures data from 22 financial service providers (FSPs) which were Smart Certified between 2013 and 2015. For each of these organizations, the research team reviewed key performance indicators (KPIs) from fiscal years (FY) 2011 to 2016 to determine if any trends were discernable. We broadly categorized FY 2011 to 2013 as before certification and FY 2014 to 2016 as after certification. FSPs were grouped by region within the analysis, allowing us to compare the Smart Certified cohort to their regional peers.

Most of the KPIs used were obtained from the MIX Market database. Where we were not able to use MIX data, we gathered information from the websites of FSPs and miscellaneous online sources.

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ACKNOWLEDGEMENTS

Project Director Sharlene Brown, Executive Director, PRFI Research Team Fatema Nahar, Bankers without Borders Volunteer Consultant An Nguyen, Bankers without Borders Volunteer Consultant We also want to acknowledge the contributions of the following colleagues who assisted us in gathering data for this analysis and/or provided a review of our research methodology as we tried to simplify the explanation of key business concepts.

AmĂŠlie Desrosiers, Partnership for Responsible Financial Inclusion Calum Scott, Opportunity International Australia Carmen Paraison, Smart Campaign Nicole Wong, Opportunity International Australia Robin Brazier, Smart Campaign Sarah Samuels, Smart Campaign

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TABLE OF CONTENTS EXECUTIVE SUMMARY

1

INTRODUCTION 2 RESEARCH SCOPE AND METHODOLOGY

3

RESEARCH QUESTION

4

DATA LIMITATIONS AND DISCLOSURES

5

TREATMENT OF MONGOLIA

5

DATA ANALYSIS

6

OUTREACH 6 PORTFOLIO QUALITY

11

EFFICIENCY AND PRODUCTIVITY

15

FINANCIAL MANAGEMENT

19

PROFITABILITY 22 CONCLUSION 26 REFERENCES 28 APPENDIX A: SMART CLIENT PROTECTION PRINCIPLES

29

APPENDIX B: MIX DEFINITIONS OF KEY PERFORMANCE INDICATORS

31

APPENDIX C: COHORT OF CERTIFIED FSPS AND KEY CHARACTERISTICS BY REGION

34

APPENDIX D: MICRORATE TIER DEFINITIONS

35

APPENDIX E: EIU MICROSCOPE SCORING OF ENABLING ENVIRONMENT

36

APPENDIX F: EIU MICROSCOPE MATRIX AND RELEVANT SMART CLIENT PROTECTION

37

APPENDIX G: TIME OF RELEVANT MACROECONOMIC EVENTS

38

APPENDIX H: MISSING DATA POINTS

39

LIST OF ACRONYMS CAGR

Compounded Annual Growth Rate

D/E

Debt to Equity Ratio

EAP

East Asia & the Pacific

EECA

Eastern Europe & Central Asia

EIU

Economist Intelligence Unity

FSP

Financial Service Provider

GLP

Gross Loan Portfolio

GNI

Gross National Income

LATAM

Latin America & the Caribbean

MFI

Microfinance Institution

MIX

Microfinance Information Exchange

NBFI

Non-bank financial institution

NGO

Non-Governmental Organization

OER

Operating Expense Ratio

PAR 30>

Portfolio at Risk > 30 Days

PAR 90>

Portfolio at Risk > 30 Days

ROA

Return on Assets

ROE

Return on Equity

SA

South Asia

USD

U.S. Dollars

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EXECUTIVE SUMMARY More than 100 financial service providers (FSPs) have been Smart Certified since 2013. The decision to become Smart Certified is often driven by an institution’s social commitment rather than influenced by the potential to have stronger financial results as a consequence of improved policies and processes. This paper evaluates key performance indicators (KPIs) of 22 FSPs that obtained certification between 2013 and 2015, highlighting outreach, portfolio quality and internal efficiency indicators post-certification.

This paper analyzes the 22 Certified FSPs using a geographical lens. From our analysis, several observations emerged:

1. Certified FSPs gained internal efficiencies post-certification across regions and had comparable performance to regional benchmarks. While, on average, the representative entities in the certified cohort are more mature and regulated than the MIX regional cohort, they experienced a growth in Gross Loan Portfolio (GLP) and borrowers in the periods following certification, FY14 to FY16. The growth rate of the GLP for the certified cohort was higher than that of the regional cohort. In the EECA where the cohort experienced a decline in growth of GLP, the decline was significantly less than that of the regional benchmark indicating stability likely due to strong internal practices and management.

2. Certified FSPs tended to have lower PAR levels (below 7%)1 reflecting healthy management of loan portfolio risk. Additionally, these institutions had excellent risk management – risk coverage is generally over 100% which is highly desirable as many loans are non-collateralized.

3. Compared to regional peers, certified FSPs had higher debt to equity ratios and profitability denoting increased access to credit markets, and potentially an increased ability to churn out profits better than other players in their region. Fourteen of the FSPs in the certified cohort are organized as NGOs and NBFIs, which are typically unable to take savings from clients, making it necessary to access external loans to grow their loan portfolios to increase profits.

While not all results were positive, the financial results for the three years following certification show promising results. Longer-term studies should be conducted to support the emerging case that certification leads to positive outcomes in financial results. Such findings would encourage leadership of FSPs to undertake Smart certification.

1 MicroRate indicates that beyond 8% PAR 30, an organization has reasons to worry about their delinquency rate and going concern (2014).

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INTRODUCTION Through initiatives like the World Bank’s Universal Financial Access (UFA) and the United Nations Sustainable Development Goals, financial inclusion has emerged as a central focus of governments, development organizations, banks, fintechs, and other providers of financial services. With the growth of FSPs working to cater to the world’s low-income populations, concern for basic consumer protection practices has been on the rise. The Partnership for Responsible Financial Inclusion (PRFI, formerly the Microfinance CEO Working Group) encourages its local partners to undergo the Smart Campaign’s certification process, as a deliberate demonstration of our commitment to responsible financial inclusion. Certification is based on the Smart Campaign’s Client Protection Principles (Appendix A), which represents a set of best practices and policies FSPs should adopt to minimize harm.

Since the launch of the certification program in 2013, more than 100 FSPs have become Smart Certified.

This paper aims to track key performance indicators (KPIs) of 22 FSPs that obtain certification between 2013 and 2015, highlighting the financial and operational post-certification outcomes, with consideration given for market context.

A key factor for management in undertaking the certification process is considering the costs and benefits of investment in both financial and human resources in the implementation of business processes.

To address this key hurdle, we examine the bottom-line with the working assumption that KPIs will show improvement over the 3-5 year period post-certification. Our research focuses on the quantitative analysis of operational and financial performance of a cohort of 22 FSPs for fiscal years 2011 to 2016.

It is our hope that the outcomes will encourage the leadership of uncertified FSPs to make the sound investment of getting Smart Certified and making client protection a non-negotiable gold standard in the delivery of financial services, especially for low-income and unserved populations.

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RESEARCH SCOPE AND METHODOLOGY The research team analyzed a cohort of 22 Smart Certified FSPs using a regional lens to benchmark KPIs. The scope of the financial, operational and outreach indicators used in this process incorporates widely accepted ratios tracked and used by investors and industry bodies to analyze the performance of microfinance institutions and other FSPs in the financial inclusion space. A list of the indicators is provided below: Category

Key Performance Indicators

Outreach

Gross Loan Portfolio

Key performance indicators (KPIs) are indicators that organizations continuously monitor because they have been identified as primary indicators of growth for their specific organization.

Number of Borrowers Poverty Outreach (Average Loan/GNI per capita) Portfolio Quality

Portfolio at Risk >30 days Portfolio at Risk> 90 days Risk Coverage

Efficiency & Productivity

Operating Expense Ratio Cost per Borrower Personnel Allocation Ratio

Financial Management

Debt-to-Equity Ratio Financial Revenue/ Assets Financial Expense/ Assets

Profitability

Return on Assets Return on Equity Yield on Gross Portfolio (nominal)

The 22 FSPs certified between the inception of the Smart certification program in 2013 and 2015 are geographically diverse. All regions with the exception of Sub-Saharan Africa and the Middle East North Africa are represented within the cohort covered in this case study. The 22 FSPs have the following geographical representation.

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Table 1: Regional Weighting of 22 Smart Certified Financial Service Providers Region

# of FSPs

% of FSPs

Eastern Europe and Central Asia (EECA)

6

27%

Eastern Asia and Pacific (EAP)

3

14%

Latin America

7

32%

South Asia

6

27%

Total

22

100%

The cohort is diversified with respect to their legal organization and tenure in the market. Eight of the FSPs are commercial banks, nine are non-bank financial institutions, and the remaining five are non-governmental organizations (NGOs). Fifteen of the institutions have been in the market for 15 years or more and seven have been in the market for less than 15 years—with the youngest institution having a tenure of nine years.

As of December 2018, most of the FSPs in the certified cohort are Tier 1 institutions with total assets in excess of $31 million USD. Three institutions are in Tier 2 assets ranging around from $25 million to $31 million USD (Appendix D). The institutions certified between 2013 and 2015 appear to be more mature institutions, defined as having at least nine years of experience in the market, have achieved financial sustainability with well-established systems and operational procedures.

RESEARCH QUESTION The researchers felt including broader national, regional, and global macro-factors that have an effect on performance of the FSPs allows depth in the analysis of KPIs, without which it may lead to misleading conclusions. To cancel background noise and normalize comparison of KPIs regionally, the Economist Intelligence Unit MicroScope (EIU Microscope) studies were referenced (see References). For instance, the financial results in the EECA region generally showed a downward trend in the FY14 to FY16 period. The EIU study captures the deterioration of market conditions in that region for those years, explaining this trend, which should not be confused as a negative correlation to certification.

Two types of comparisons are made to understand if Smart Certified entities tend to have better performance over the mid-term, defined as three years of financial performance. We compared each institution’s fiscal results for the three years before the certification program began, FY11 to FY13 and results for the three years following certification, FY14 to FY16. We also compare the certified cohort, by region, to a broader set of their peers based on the Global Benchmark report published by Mix Market data. Our goal was to see if we saw trends of improvements in key areas by evaluating the pre and post-certification periods, and to identify any difference in performance compared to regional players.

Most of the data set analyzed was obtained from the MIX database. In instances when necessary data was incomplete, an effort was made to obtain audited financial reports of an FSP to complete the analysis. In

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some instances where we had the inputs for missing ratios, we calculated the ratios following the MIX formula. A summary of the missing data points by region is also included in Appendix H.

DATA LIMITATIONS AND DISCLOSURES Several important notes should be made regarding how institutions were grouped. a. Fiscal Year Results and The Pre and Post-Certification Periods For the purposes of this study, we define the term fiscal year-end as a 12-month period used for calculating annual financial statements. This means that our annualized calculations consider that the Smart Certified cohort is comprised of financial services providers with varying 12-month accounting periods. For example, some institutions may have December 31st as their end date for the fiscal year, while others may have July 31. Our results have not annualized all data sets for the calendar year-end: December 31st. Instead, the treatment of the fiscal year for the cohort and regional MIX benchmark report is similar in that varying FSP year-end dates are used.

In creating the periods defined as pre-certification (FY11 to FY13) and post-certification (FY14 to FY16), the research team recognized that a few of the institutions had been certified in 2013 but felt it was reasonable to expect that any resulting benefits of changes to institutional practice and policies would show up in the succeeding years. For institutions certified between 2014 and 2015, in the post-certification period, we take the position that certification does not happen in a vacuum, but many institutions begin with other social performance initiatives and audits which offer improved performance as well. In other words, the duration period for analysis has more effect on results than the exact date of certification within a year of getting certified.

While the treatment of the cohort may not be perfect, we believe it is sufficient to identify the trends of growth or decline that occur between the pre and post-certification periods. b. Treatment of Absolute Figures and Ratios/Percentages We used Cumulative Aggregated Growth Rates (CAGR) to analyze the growth of absolute figures such as gross loan portfolio and number of borrowers. Where we evaluated changes in key ratios such as debt to equity, we tended to take a simple average between our two key periods of analysis, FY11 to FY13 and FY14 to FY16.

TREATMENT OF MONGOLIA A final data disclosure is our treatment of one FSP in Mongolia. In this case study, we classified Mongolia in EAP for the regional benchmark although in the MIX benchmark report Mongolia is grouped under EECA. In our analysis, where we calculated sums, such as for number of borrowers, we corrected the sums for the two regions. However, where the MIX produced regional ratios in their Global Benchmarking reports, we did not amend those ratios. We have tested for the impact of the move on the ratios and found it to be negligible.

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DATA ANALYSIS For each set of indicators, we define the indicators in the margin and explain its significance to management; and if applicable, define its relationship with other indicators analyzed. In the main body of the paper below we explain the directional trends we would anticipate in a strong performing FSP and our observations as they relate to the Smart Certified cohort.

OUTREACH Outreach indicators such as number of borrowers and gross loan portfolio (GLP) are drivers of growth impacting most other performance ratios.

Generally, FSPs aim to grow GLP and the numbers of borrowers over time as both are important to attaining growth and setting internal performance targets. These key indicators can be used to gauge performance relative to market benchmarks and competitors. For financial service firms, GLP is often the largest asset.

For the financial inclusion industry, a proxy measure of poverty outreach such as average loan size compared to gross national income per capita is also important to gauge whether institutions are reaching low-income and unserved clients as they broaden access to financial services. a. Growth of Gross Loan Portfolio Gross Loan Portfolio Outreach

Number of borrowers Poverty Outreach (Average loan size/GNI per capita)

Growth in GLP is impacted by several factors: overall market penetration of the country and/or region an institution operates in; the maturity of the institution in operational years; and the ability to attract institutional borrowings to increase loan portfolio. Deposit-taking institutions may also see a better growth rate in GLP as they leverage low-cost savings for lending activity2.

Table 2 below provides a summary of GLP growth rates of Smart Certified FSPs aggregated by region. In all regions, a significant decline in growth rate is noted when comparing the period FY11 to FY13 (pre-certification) and FY14 to FY16 (post-certification), with the exception of South Asia. Although EIU Microscope study shows a general strengthening of enabling factors over 2011 through 2016, global economic macro factors would have had an 2

Gross Loan Portfolio (GLP): All outstanding principals due for all outstanding client loans. This includes current, delinquent, and renegotiated loans, but not loans that have been written off. It does not include interest receivable.

Source: MIX Market

This dimension has not been explored in this paper.

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impact on the difference in growth rates. Towards the beginning of 2011, financial markets were enjoying tailwinds after the global recession (see the timeline in Appendix F). There’s also a trend in investing in microfinance during the financial crisis as it is considered to be unaffected by the traditional banking sector. Therefore, although the post period shows better growth rates than the benchmark cohort, it is not as robust as the pre-period.

Table 2: Growth of GLP Growth by Region for Pre and PostCertification Periods with MIX Benchmark FY11-13 AVG Smart Cohort

FY14-16 AVG Smart Cohort

FY14-16 Regional AVG

Eastern Asia and Pacific

37%

19%

15%

Eastern Europe and Central Asia

26%

How does it impact other ratios?

Most ratios have GLP in either the denominators or numerator.

The rate of growth in GLP is important to discussion of internal performance of FSPs. Rapid growth in GLP also affects other ratios such as PAR and generally necessitates risk mitigation initiatives.

Why is this an important metric?

Rapid growth would require

-2%

-27%

adjustment in business practices to meet demand in a responsible way. During periods of high

Latin America

21%

7%

1%

growth, it is important to monitor the components of GLP and have a

South Asia

35%

31%

32%

good balance between borrowings, deposits and internally generated equity.

It is notable that despite being relatively mature , the research cohort still performed better than their peers in each region during FY14 to FY16. In EECA, which was affected by the European financial crisis, Smart Certified entities experienced less of a loss in GLP compared to regional peers. This is a positive outcome that may indicate sound operational practices and policies, such as those required by the Client Protection Principles, allow institutions to weather bad storms.

3

Figure 1 below shows annual GLP data for the Smart Certified entities by region. Between 2011 and 2016, GLP grew in all regions with the exception of EECA. It is also notable that although LATAM and SA started off in comparable positions in 2011, SA’s cohort of certified entities outgrew LATAM significantly with sustained growth rates.

3

Mature institutions have more than 9 years of tenure in the market.

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Figure 1: Total GLP (in USD) for Smart Certified Cohort by Region for 2011-2016

BILLIONS

$3

$2

$1

$0 EAP

2011

EECA

2012

2013

LATAM

2014

2015

SA

2016

b. Growth in the Number of Borrowers To grow their business, FSPs need to grow GLP and the number of borrowers served. Growth in number of borrowers leads to a: increase market share (a mix of both urban and rural clients); increased economies of scale (generally diminishes after the 5 million USD mark in assets) (MicroRate, 2014); and contributes to the growth of interest income from loans disbursed. Generally, there is a positive correlation between the growth of GLP and the number of borrowers.

Both EAP and SA had a higher growth rate of borrowers post-certification.

This indicates that the base of clients served increased during the post-certification period. By contrast, EECA and LATAM saw a decline in growth rates of borrowers in the post-certification period mirroring the decline in GLP for these regions discussed above. The economic downturn, oil crisis, and national events (see the timeline in Appendix F) are contributors to the negative performance in borrower growth rates.

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Number of Borrowers: The number of individuals or entities who currently have an outstanding loan balance with the MFI or are primarily responsible for repaying any portion of the Loan Portfolio, Gross. Individuals who have multiple loans with an MFI should be counted as a single borrower.

Source: MIX Market How does it impact other ratios?

Number of borrowers is either the denominators or numerator in some KPIs. The rate of growth of borrowers is relevant to the discussion of internal performance of an FSP.

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Table 3: Growth of Number of Borrowers by Region for Pre and Post-Certification Periods with MIX benchmark FY11-13 AVG Cohort

FY14-16 AVG Cohort

FY14-16 Regional AVG

Eastern Asia and Pacific

14%

22%

8%

Eastern Europe & Central Asia

3%

-3%

-15%

Latin America

16%

3%

2%

South Asia

6%

9%

0%

Why is this an important metric?

Management is concerned with the growth of new clients and in retaining existing clients. In a saturated market, especially in urban centers, growth may require an institution to reach more “down market� populations in remote rural areas. Reaching rural clients tends to be more costly.

Post-certification results for all regions outpaced that of the regional benchmark. EAP sharply outpaced the regional benchmark whereas EECA sustained a much lower decline rate compared to the regional -15%. Again, these results suggest that the Smart cohort may be benefitting from the effectiveness of good internal practices and better client retention strategies and policies.

Figure 2 below shows annual data of borrowers for the Smart Certified entities by region. Between 2011 and 2016, all regions for the certified cohort experienced a growth in total number of borrowers, with the exception of EECA.

Figure 2: Growth of Total Number of Borrowers of Smart Certified Cohort by Region for 2011-2016 14

MILLIONS

12 10 8 6 4 2 0 EAP

2011

EECA

2012

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LATAM

2014

2015

SA

2016

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c. Average loan size/GNI per capita (Poverty outreach) FSPs operating in the financial inclusion space are challenged to expand and deliver services to unserved clients, typically those with lower incomes.

Average loan/GNI per capita is a proxy for reaching further “down market” clients who are often located in rural geographies requiring costly outreach.

For example, if GNI per capita is 20 USD and average loan size for an FSP is 100 USD, then the ratio would be 500%, indicating the institution is lending at a level significantly above what the average person would be able to borrow. By contrast, if GNI per capita is 100 USD and the average loan size was 50 USD, then the FSP is lending at 50% of the average person’s income.

From a business perspective, as urban centers reach saturation in most regions, rural markets are next in line for penetration. Presumably due to lower income of these prospective clients, smaller loans would be disbursed and thus this ratio would get smaller.

Table 4: Poverty Outreach by Region for Pre and PostCertification Periods

FY11-13 AVG

FY14-16 AVG†

Eastern Asia and Pacific

14%

150%

Eastern Europe & Central Asia

87%

65%

Latin America

42%

39%

South Asia

18%

27%

Poverty Outreach: Average loan divided by GNI per capita (formerly GNP per capita). GNI per capita is the gross national income, converted to U.S. dollars using the World Bank Atlas method, divided by the mid-year population. GNI is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output , plus net receipts of primary income (compensation of employees and property income) from abroad.

If average loan size is smaller compared to GNI per capita, the ratio indicates the FSP is reaching clients further down the economic ladder.

Source: MIX Market

† No regional benchmark data available for this key performance indicator.

How does it impact other ratios?

This indicator is not an input for other performance ratios. Its purpose is to give an indication of whether FSPs are reaching lowerincome clients within the market in which they operate.

Post-certification numbers show that EECA and LATAM experienced a downward shift in the ratios, indicating the institutions are reaching clients further “down-market”. Data suggest that FSPs in LATAM are increasingly reaching more rural clients and EECA is a market where institutions predominantly service individual loans, and some specialize in agricultural loans (Microrate, 2014). In SA, where village-banking was already more prevalent compared to other regions, there was an increase in this ratio. This suggests that the SA cohort has now expanded to serve clients further up the

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economic ladder through diversified product offerings. The EAP cohort has larger banks and NBFIs that service businesses in addition to individuals leading to the large size of the loans, explaining why this group has the highest ratios of the Smart Certified entities.

PORTFOLIO QUALITY Portfolio quality

Portfolio at Risk>30 days Portfolio at Risk >90 days Risk Coverage

For any lending institution, the quality of its loan portfolio significantly impacts its ability to be profitable. If an institution takes too much risk, lending to risky borrowers and does not manage the portfolio of risk associated with its loan products, it may likely encounter high levels of unpaid loans.

This translates into loss in income and could have material implications for its going concern (i.e. dissolution of entity). Consequently, FSPs need to pay attention to the inputs that lead to a healthy loan portfolio, including good underwriting practices, diversifying its client base through various product lines, and by seeking a mix of sources of funds (i.e. subsidies vs. institutional debts). FSPs manage portfolio quality risk by monitoring: •

Portfolio at Risk > 30 days

•

Portfolio at Risk > 90 days

•

Risk Coverage

a. Portfolio at Risk > 30 days Portfolio at risk greater than 30 days (PAR>30) is the first measure of the health of an FSP’s loan portfolio. It represents the portion of the portfolio that is “contaminated” by arrears (the amount of late or missing payments) and therefore at risk of not being repaid. The longer a client goes without repayment, the less likely it is that the loan will get repaid. An institution’s PAR level is affected by: quality of credit worthiness of clients selected; the type of lending methodology employed; macroeconomic factors that create household-level shocks; and the loosening and tightening of credit underwriting policies.

In general, lending institutions strive to keep PAR>30 below 7%4. A measure of PAR>30 at 7% or below is a good indicator of risk mitigation methodologies within an FSP. It suggests that solid practices are in place: clients are

Why is this an important metric?

A concern among FSPs working for a more inclusive society is that profits sometimes become a focus instead of serving lowincome clients. GNP per capita is a widely used metric that quantifies outreach towards ‘down market’ clients. A lower figure on this metric coupled with client protection is a good indicator of outreach and a strong client-orientation in the business approach of an FSP.

PAR>30: GLP is the largest asset for an FSP and therefore represents the largest source of risk. PAR>30 is calculated by dividing the outstanding balance of all loans with arrears over 30 days, plus restructured loans, by the outstanding gross loan portfolio.

Source: MIX Market

4 According to MicroRate, PAR>30 and PAR>90 that is greater than 8% should be a reason for worry. In markets dominated by individual loans, higher PAR ratios are expected. In regions where group lending is predominant, PAR ratios can be less than 1% on average.

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contacted immediately after a non-payment; client selection is effective, and the client’s ability to repay loans has been well-evaluated. The latter are practices embodied in the Client Protection Principles.

Post-certification results in Table 5 for PAR>30 days shows a nominal increase or flatness for all regions except SA. According to EIU Microscope data, SA has experienced substantial improvements in terms of the enabling factors to sustain financial inclusion. Although other regions have shown improvement, it’s not as sharp. Potentially, SA is benefitting from an enhanced regulatory environment enabling informed client selection and credit policies. Despite experiencing a sharp increase in GLP (Figure 1) and the number of borrowers (Figure 2), PAR>30 declined in the post-certification period indicating prudent client selection.

The EAP Smart Certified cohort primarily offers microenterprise loans.

These institutions tend to be larger and serve businesses. Consequently, a higher PAR>30 would be expected compared to institutions predominantly offering village-banking loans which is likely the case for the benchmark cohort.

Table 5: Average of PAR>30 by Region for Pre and PostCertification Periods with MIX Benchmark FY11-13 AVG

FY14-16 AVG

FY14-16 Regional AVG

Eastern Asia and Pacific

1%

3%

3%

Eastern Europe & Central Asia

5%

5%

10%

Latin America

4%

5%

5%

South Asia

4%

1%

5%

How does it impact other ratios?

This indicator is not a direct input for other performance ratios.

Why is this an important metric?

One of the primary indicators of going concern for an FSP – meaning if there’s a high level of delinquency the FSP may be out of business. High-level of delinquency also disintegrates reputation and trust within the client sector who are included within the financial services sector for the first time.

Regulators also use this as a primary indicator and government funding is dependent on maintaining threshold levels of PAR.

A comparison of results for the Smart Certified cohort to regional results shows the same or better for all regions. Notably, in EECA the Smart entities was able to maintain an average PAR>30 of 5% compared to the regional benchmark of 10%. This suggests that even in deteriorating economic conditions, good credit policies should pay off in terms of maintaining a relatively healthier portfolio.

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b. Portfolio at Risk > 90 days Portfolio at risk greater than 90 days (PAR>90) is a secondary measure of an FSP’s loan portfolio. The longer loans remain delinquent, the lower the probability they will be repaid. FSPs work hard to minimize the number of outstanding loans that fall this far behind. PAR>90 should be lower than PAR> 30. If this is the case, it would indicate that the FSP has an effective collection policy in place.

For the Smart Certified cohort, PAR>90 increased slightly in EECA, EAP and LATAM between the pre and post periods. By contrast, PAR>90 decreased between the the two periods.

Table 6: Average of PAR>90 by Region for Pre and Post-Certification Periods with MIX Benchmark FY11-13 AVG

FY14-16 AVG

FY14-16 Regional AVG

Eastern Asia and Pacific

0%5

2%

3%

Eastern Europe & Central Asia

3%

4%

9%

Latin America

3%

4%

4%

South Asia

4%

1%

4%

The observations for PAR>30 are also applicable for PAR>90. For all regions the average PAR >90 for regional participants was equal or higher than for the Smart Certified cohort. While the delinquency rates are generally healthier for all Smart and regional participants, Smart Certified entities tended to have lower delinquency levels.

5

Portfolio at Risk>90 days (PAR >90): Represents the portion of loans greater than 90 days past due, including the value of all renegotiated loans (restructured, rescheduled, refinanced and any other revised loans) compared to gross loan portfolio. Indicates loans considered to be higher risk based on its current performance.

Loans in arrears over 90 days are seriously delinquent and have a high probability of not being collected.

Source: MIX Market

How does it impact other ratios?

This indicator is not an input for other performance ratios.

Why is this an important metric?

PAR>90 is a trigger for the percentage of loan balances that should be provisioned to mitigate risk. MicroRate recommends that institutions provision for 60% of loan balance that are in arrears for more than 90 days. While PAR>30 measures may be the same as PAR >90, a loan portfolio with seriously delinquent loans (loans affected by arrears of more than 90 or 180 days) is much riskier as the probability of collecting the delinquent portfolio decreases with more time.

Round to zero

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c. Risk Coverage Generally, FSPs seek to have 100% coverage of anticipated loan losses. The risk coverage ratio gives an indication of how prepared an institution is for a worst-case scenario – which would be 100% delinquency rate. Appropriate coverage is 100% of PAR>30 balance. A strong practice, particularly in the financial inclusion space, where many loans are not collateralized is to have a higher coverage ratio. For instance, when collateral-backed lending makes up the majority of an institution’s portfolio, a ratio well below 100% is common. For formalized institutions, regulations, particularly the tax code, usually set minimum limits on reserves. Given the mix of maturities and legal structures (NGOs, banks, etc.) we expect to see risk coverage of at least 100%.

For both the pre and post-certification periods, Smart Certified FSPs had excellent risk coverage, maintaining at least 100% of PAR>30 balance. In EAP, EECA, and LATAM, risk coverage declined in the post-certification period.

This may reflect improvement in local market conditions (i.e. clients are better able to pay their loans on time) or the cleaning up of an institution’s books. SA was the only region to see an increase in risk coverage in the post-certification period.

Table 7: Average Risk Coverage by Region for Pre and PostCertification Periods with MIX Benchmark FY11-13 AVG

FY14-16 AVG

FY14-16 Regional AVG

Eastern Asia and Pacific

4548%6

1267%

68%

Eastern Europe & Central Asia

237%

131%

55%

Latin America

200%

139%

109%

South Asia

205%

336%

83%

6 MBK Ventura has abnormal levels of risk coverage at 542% (2011), 16000% (2012), 16400% (2013); 9200% (2014)

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Risk Coverage: Allowance for loan impairment losses compared to portfolio overdue more than 30 days plus renegotiated loans. Measures how much of this portfolio at risk are covered by a financial institution’s impairment loss allowance, allowing to estimate how prepared a financial institution is to absorb credit loan losses at that point of time.

Source: MIX Market

How does it impact other ratios?

This indicator is not an input for other performance ratios.

Why is this an important metric?

Average risk coverage is an indication of how prepared an institution is to manage loss resulting from losses from delinquent loans. Risk ratios for regulated institutions are often set by banking regulators.

Institutions with very high risk coverage (over 200%) may be acting prudently to hedge against future downturns in the economy or to preempt poor portfolio performance.

In some cases, FSPs may also increase risk coverage in light of strong growth as PAR tends to increase and/or FSPs may be preparing for a decline in growth rates in the future that may lead to increase in portfolio at risk.

Source: MicroRate

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The Smart Certified entities tended to have higher Risk coverage in contrast to regional peers for the FY14 to FY16. This may partly reflect the strong internal practice or prudent risk management approaches of the certified cohort and/or the business models of larger regional players with more collateralized lending products.

EFFICIENCY AND PRODUCTIVITY Operating Expense Ratio Efficiency and Cost per Borrower Productivity Allocation Ratio In this section, we look at internally-driven performance indicators: operational efficiency (operating expense/loan portfolio), cost per borrower, and personnel allocation ratio. As firms grow their lending operations, there is a desire to reduce operating expense for every dollar lent out, reduce the cost of serving each borrower, and increase personnel allocation ratio. a. Operating Expense Ratio The operating expense ratio (OER) provides the best measure of the overall efficiency of a lending institution. It measures the institutional cost of delivering loan services compared to the average loan size of its portfolio.

Therefore, a general rule is the lower the operating expense relative to the loan portfolio the better the efficiency.

According to research conducted by MicroRate (2014), loan size has the largest impact on the OER. The lending methodology of an FSP can also significantly influence operational costs. In village banking, where average loan sizes are very small and training is high, operating expenses are typically substantially higher than for institutions primarily offering individual loan products. For financial inclusion practitioners, another significant contributor to operational expense is the location of clients. FSPs serving largely rural clients tend to incur higher operational costs as their clientele is more widely dispersed and therefore more expensive to reach. Operating costs are also positively correlated to salary levels, as is to be expected in a highly labor-intensive industry. MicroRate’s research suggests that personnel costs typically make up 50% of operating expenses. As FSPs gain efficiency, OER should decline.

Given the predominance of rural lending and village banking methodology, SA entities are expected to have higher OERs. Institutions in EAP should have lower OERs as FSPs mostly cater to individual banking in urban areas.

For firms in LATAM and EECA, lower OERs are also expected as they concentrate on urban areas with individual banking.

Operating Expense Ratio (OER): Total operating expense compared to average gross loan portfolio.

Measures all costs incurred to deliver loans (personnel and administrative expenses as well as non-cash expenses such depreciation and amortization).

Source: MicroRate, 2014

How does it impact other ratios?

This indicator is not an input for other performance ratios.

Why is this an important metric?

Efficiency and productivity ratios are readily comparable across institutions and allow management to understand how they fare relative to peers with similar business models. According to MicroRate (2014) efficiencies gained due to scale is not significant after a FSP reaches 5 million in assets. In general, costs tend to increase with business growth as financial inclusion organizations tends to have labor intensive business models compared to traditional banking. Therefore, understanding internal efficiencies gained post certification along with sustained business growth should be of great interest to management. In terms of the costs of getting SMART certified, gaining internal efficiencies while experiencing business growth should be a positive factor on deciding whether or not to get certified.

Source: MicroRate

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For each Smart Certified regional cohort, a decline in OER is observed between the pre and post certification periods. This would suggest that these institutions are gaining greater efficiency over time as GLP and the number of borrowers increased for each regional cohort. Reducing OER as GLP and borrowers grow implies that operational expenses were at least stable during the period analyzed.

Table 8: Average OER by Region for Pre and Post Periods with MIX Benchmark FY11-13 AVG

FY14-16 AVG

FY14-16 Regional AVG

Eastern Asia and Pacific

15%

10%

7%

Eastern Europe & Central Asia

18%

15%

10%

Latin America

25%

23%

16%

South Asia

14%

11%

9%

For the FY14-16 period, the regional benchmark group has lower OER relative to the Smart Certified FSPs. This is expected as the Smart Certified cohort has a higher dispersion of larger operations with longer market tenures. As such operational costs are expected to be larger due to : higher salaries (cohort has lower personnel allocation ratio), more training costs, and more administrative costs for a diversified product offering. b. Cost per Borrower Cost per borrower is another measure of internal operational efficiency. It breaks down the operational expense to the unit of a borrower. Because cost per borrower does not take into account the value of the loan portfolio, it is a more balanced efficiency measure than the OER which may be skewed by large loan sizes. Since the size of the loan portfolio is not incorporated into the denominator of cost per borrower, institutions with larger loans do not automatically appear more efficient, as is commonly the case with the OER. In fact, the growth of the loan portfolio tends to have an inverse relationship to OER and cost per borrower. As the loan portfolio increases, OER decreases, while the Cost per borrower tends to increase. However, over time as the institution’s gain internal efficiencies, cost per borrower should trend down.

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Cost per Borrower: Total operating expense distributed among average number of borrowers. Represents the average cost of maintaining an active borrower.

Source: MicroRate, 2014

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Cost per borrowers is driven by the type of lending methodology that is core to an FSP’s business model. MicroRate (2014) has observed that in mature markets, the average cost per borrower for village-banking is significantly lower than the cost per borrower for FSPs using an individual lending methodology. This is because the clients bear the responsibility of selecting the individuals that form the group (as opposed to a loan officer) and also because these groups require lower operating costs. Village bank loan officers can collect repayments in one meeting, whereas officers administering individual loans must visit every borrower.

How does it impact other ratios?

This indicator is not a direct input for other performance ratios. However, it may be used with other internal factors to understand market growth or retraction at any period in time.

All regions in the Smart Certified cohort, except SA, experienced a significant decline in the average cost per borrower between the pre and post-certification periods. In South Asia, the cost per borrower was noticeably lower than other regions, which may be due to the larger prevalence of village-banking used by that region’s FSPs as well as other lower costs inputs such as labor. The small increase in the average cost per borrower of the SA cohort may reflect the faster rate of growth in borrowers compared to the regional benchmark as shown in Table 3 above. The higher costs may be attributed to the SA cohort reaching more clients. It is also notable that EIU Microscope data shows that the regulatory environment across the South Asian region improved significantly (See Appendix D). Increased regulation may also have led to increased costs.

Why is this an important metric?

Cost per borrower is used for Internal target setting and benchmarking. FSPs track cost per borrower over time to understand if cost for servicing each borrower decreases or increase over time.

Table 9: Average Cost per Borrowers by Region for Pre and Post Periods with MIX Benchmark FY11-13 AVG*

FY14-16 AVG**

FY14-16 Regional AVG

Eastern Asia and Pacific

$ 190

$ 152

$ 64

Eastern Europe & Central Asia

$ 290

$ 208

$ 263

Latin America

$ 271

$ 245

$ 284

South Asia

$ 23

$ 30

$ 21

If industry data are available, management may also use this indicator to benchmark against other FSPs.

Cost per borrower in EAP and SA is higher than the regional benchmarks.

In the case of EAP, the Smart Certified cohort has large institutions serving businesses attributing to higher costs whereas the regional benchmark has higher concentrations of village-banking clients (MicroRate, 2014). For the

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SA cohort, the significant growth of borrowers and increased regulatory environment may still be drivers for the higher costs observed compared to the regional peers. In EECA and LATAM, the Smart Certified cohort had a lower average cost per borrower relative to the regional peers. c. Personnel Allocation Ratio Personnel allocation is a measure of staff productivity focused on the core business of the FSP. As institutions’ expand their core business activities, they often increase staff roles directly tied to bringing in new clients and expanding the relationships with existing customers. Both new client acquisition and increased business opportunities with existing clients serve to increase revenues. This ratio captures the productivity of the institution’s staff—the higher the ratio, the more productive the institution’s staff. Indirectly, the ratio says a fair amount about how well the FSPs have adapted processes and procedures for the administration of its products and services. Low staff productivity does not necessarily mean that employees are not working hard. It may show that they are tied up in excessive paperwork and procedures.

MicroRate’s (2014) research indicates that an FSP using group lending methodology can have a 50% higher productivity compared to an institution that focuses on individual lending. This is to be expected given the differences in the average loan amount between the two products and the increased time required to analyze an individual loan. Financial service practitioners with a more diverse offering of products, such as insurance and deposits, may also have more administrative processes and staff. Also, extremely high productivity rates are no longer encouraged as it sacrifices quality and due care of processing loans and training clients.

Personnel ratios for all members of the Smart cohort remained flat or showed minimal growth between the pre and post-certification periods.

In EAP and LATAM, there were small increases in the average personnel allocation, perhaps reflecting increases in certain types of administration. In SA, personnel allocation was constant across the pre and post certifications and EAP Certified entities saw an increase in personnel allocation in the two timeframes.

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Personnel Allocation: Number of loan officers divided by total personnel. Measures the allocation of staff to activities directly involved in a financial institution’s lending process, the core business operation of a financial institution.

Source: MicroRate, 2014

How does it impact other ratios?

This indicator is not a direct input for other performance ratios.

Why is this an important metric?

In order for FSPs to succeed they must learn to maximize productivity by using the least amount of resources to process the greatest volume of loans in a way that does not sacrifice portfolio quality or customer service. This critical equilibrium of efficiency and productivity must be paramount at every level of the MFI and a key measure of operational management.

Source: MicroRate, 2014

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Table 10: Average of Personnel Allocation by Region for Pre and Post-Certification Periods with MIX Benchmark FY11-13 AVG

FY14-16 AVG

FY14-16 Regional AVG

Eastern Asia and Pacific

45%

48%

50%

Eastern Europe & Central Asia

44%

41%

30%

Latin America

43%

46%

46%

South Asia

58%

58%

61%

Except for the EECA cohort, the averages for FY14 to FY16 for Smart Certified regional cohort were in line or slightly less efficient than regional peers. In EECA, there is an 11% difference, on average, between the certified entities and the regional players. As EECA was experiencing a financial recession it is possible that the lack of demand leads to a reduction in loan officers while the admin staff remained the same for regional FSPs.

FINANCIAL MANAGEMENT Financial management

D/E Ratio: Total liabilities compared to equity.

Measures the overall leverage that FSPs has incurred to finance its portfolio and other assets and also how much cushion it has to absorb losses after all liabilities are paid.

Source: MIX Market

Debt-to-Equity Ratio Financial Revenue/Assets Financial Expense/Assets

Paying attention to the financial management of an organization provides key insights into the management’s ability to utilize monetary resources efficiently. This balances consideration such as managing overhead cost, strategic growth, and strengthening an organization’s balance sheet to meet its current and future needs. a. Debt-to-Equity Ratio The debt-to-equity (D/E) ratio provides an indication of a firm’s ability to manage its liabilities (primarily creditors and depositors for FSPs) in comparison to its equity position. For example, a D/E of one would suggest that every dollar of debt is covered by every dollar of equity. Such an institution may be deemed safe as it has adequate equity to pay its liabili-

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How does it impact other ratios?

This indicator is not a direct input for other performance ratios.

Why is this an important metric?

D/E is of primary interest to institutional lenders assist indicates the riskiness of an institution in terms of capital adequacy to cover debt obligations. Mismanagement can lead to either freezing of further lending by current debt lenders and/or prevent getting more funds.

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ties. D/E should be analyzed in the context of industry benchmark. If D/E is increasing, it may reflect the FSPs enhanced capacity to access debt capital based on its equity strength. By contrast, a too low ratio is likely a sign of inefficiency in leveraging its equity position whereas a high D/E ratio may indicate that an institution is high-risk and approaching its borrowing limits.

The data in Table 11 below shows that institutions’ D/E across all the Smart Certified cohort generally increased after certification. This may imply that certified FSPs were able to access more debt capital in the period following certification. The exception is LATAM where certified FSPs accessed less debt capital in the post-certification period. The decrease in D/E in LATAM may be due to the maturity of the market and the Certified entities, as well as changing investor interest in regions.

Table 11: Average D/E by Region for Pre and Post-Certification Periods with MIX Benchmark FY11-13 AVG

FY14-16 AVG

FY14-16 Regional AVG

Eastern Asia and Pacific

6.82

7.58

2.63

Eastern Europe & Central Asia

4.24

4.97

5.03

Latin America

4.73

4.34

4.59

South Asia

6.48

7.08

5.12

Institutions in EAP and SA have higher D/E compared to their regional counterparts, perhaps partly reflecting the number of NBFIs and NGOs in the certified cohort. Data from CGAP covering the 2014 to 2016 timeframe also shows increased debt investments in these two regions. LATAM Smart Certified entities had comparable D/E levels relative to their peers. The EECA’s Certified entities had slightly lower D/E compared to their regional counterparts. This can be explained by the lower equity position of the Smart cohort though they carried similar debt levels to the regional peer group.

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b. Financial Revenue/Assets and Financial Expense/Assets Over time, institutions want to see financial expense/assets decline and financial revenue/assets increase. However, there are cases where it is acceptable for financial expense/ assets to increase in line with financial revenue/ assets. In the latter situation, as long as expenses increase at a lower rate than revenue, the company still gains increasing profits and internal equity.

In EAP and EECA, there were declines of the financial revenue generated from core business activities as a percent of average assets between the two timeframes. Financial expense as a percentage of assets increased in EAP and EECA. The decline in financial revenue and an increase in financial expense may reflect the institutions’ effort to attract new capital (which may not immediately generate revenues).

In LATAM and SA, financial revenue/assets increased across the pre and post-certification periods. Against the regional counterparts, the Smart Certified entities (except EAP) seem more profitable as they offered higher revenue per dollar of assets.

Table 12: Average FR/Assets by Region for Pre and Post-Certification Periods with MIX Benchmark FY11-13 AVG

FY14-16 AVG

FY14-16 Regional AVG

Eastern Asia and Pacific

26%

23%

29%

Eastern Europe & Central Asia

23%

21%

19%

Latin America

35%

36%

29%

South Asia

22%

23%

20%

Table 13 shows that financial expense decreased as a percentage of assets for LATAM and SA. This could imply that the FSPs in LATAM and SA are accessing lower-cost capital. This suggests that they are deemed less risky relative to the pre-certification period as there is greater trust in their stability. In fact, some of the certified FSPs have either issued an initial public offering or are in consideration of doing so.

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Financial Revenue/Assets: Total financial revenue divided by average assets. Represents the total revenue generated by a FSP’s core business operations as a percentage of its assets.

Income for interest, fees and commissions for financial services, other operational income as well as gains (losses) on financial assets (realized or unrealized) and foreign exchange gains and losses are considered for its calculation.

Source: MIX Market

How does it impact other ratios?

This indicator is not a direct input for other performance ratios.

However, it should be viewed in conjunction with financial expense/assets and poverty outreach. FSPs may need to sacrifice resources to pay financial expenses or consider poverty outreach goals as they try to generate financial revenue from assets.

Why is this an important metric?

FR/assets ratio measures the value of a company’s financial revenue relative to the value of its assets. It can be used as an indicator of how well an FSP is using its assets to generate financial revenue. A higher ratio is more favorable, as a lower one most likely implies financial management issues.

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Table 13: Average Regional FE/Assets by Region for Pre and Post-Certification Periods with MIX Benchmark FY11-13 AVG

FY14-16 AVG

FY14-16 Regional AVG

Eastern Asia and Pacific

8%

8%

7%

Eastern Europe & Central Asia

7%

8%

5%

Latin America

6%

6%

6%

South Asia

9%

9%

6%

Compared to regional counterparts, financial expense of Smart Certified entities is slightly higher in proportion to their assets.

Table 14: Growth of Assets by Region for Pre and PostCertification Periods with MIX Benchmark FY14-16 CAGR

FY14-16 CAGR Regional Benchmark

Eastern Asia and Pacific

21%

17%

Eastern Europe & Central Asia

-3%

-20%

Latin America

7%

-1%

South Asia

30%

59%

PROFITABILITY The profitability of FSPs can be analyzed using return on assets (ROA) and return on equity (ROE). As with other financial indicators, understanding how institutions compare to market benchmarks is important. ROE is an indicator of a company’s ability to generate earnings on its investments or the equity obtained from shareholders. By contrast, ROA is a measure of how well a company uses its resources, such as physical assets like equi-

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Financial Expense/Assets: Total financial expenses divided by average assets. This ratio helps to determine the proportion of total financial expense incurred by a FSP to fund its assets. Total interest, fees and commissions incurred on all liabilities including deposit accounts held by the financial institution, as well as gain (losses) from financial liabilities and the gain or loss on the net monetary position are considered for its calculation.

Source: MIX Market

How does it impact other ratios?

This indicator can be viewed in conjunction with OER and Portfolio Yield to evaluate how funding expenses contribute to the costs faced by clients.

Why is this an important metric?

This metric provides insight into the funding structure of an FSP. If interest expense becomes too high, it may be an indication that the organization is approaching its capacity to leverage commercial debt. An FSP funded primarily by donations or by equity will have a lower FE/Assets as compared to one funded heavily through borrowing. Higher funding expenses translates to higher lending rates. Management should monitor this in light of an organization’s growth strategy and financial inclusion goals.

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pment and property, to generate profits. If an institution raises equity but also takes on debt, ROA and ROE should be evaluated together. The nominal yield on the gross loan portfolio is a direct measure of the revenues collected from lending activities of an institution. a. Return on Assets Return on Assets Profitability

Return on Equity Yield on Gross Portfolio (nominal)

Management monitors ROA to determine if the entity is using its assets efficiently to generate profits, relative to prior years and peers. In a competitive landscape, maintaining a strong ROA relative to the market may help to attract investors.

SA was the only region to see an increase between the pre and post-certification periods. The Smart Certified entities in LATAM, EAP, and EECA saw relatively flat ROAs across the periods. This may be explained in part by the maturity of the FSPs and business models with modest profitability levels.

Table 15: Average ROA by Region for Pre and Post-Certification Periods with MIX Benchmark FY11-13 AVG

FY14-16 AVG

FY14-16 Regional AVG

Eastern Asia and Pacific

5%

5%

-4%

Eastern Europe & Central Asia

2%

1%

1%

Latin America

5%

5%

3%

South Asia

1%

4%

3%

A comparison of the Smart Cohort to regional peers does, however, show that the Smart Certified FSPs in the post-certification period performed better than or in line with regional peers.

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Return on Assets (ROA): Net operating income (less of taxes) compared to average assets. Measures how the FSP is managing its assets to optimize its profitability. This ratio is net of income taxes and excludes donations and non-operating items.

Source: MIX Market

How does it impact other ratios?

Equity on balance sheet is liabilities subtracted from assets.

Therefore, ROA and ROE should be seen in conjunction to each other.

For example, if liabilities remain stable, an increase in asset would mean an increase in equity.

Why is this an important metric?

Management desires to make the best use of assets possible.

Consequently, it is expected that return on the assets on an FSP will show increasing returns, if well managed. A decline in return is usually a signal that profitability is lessening. In some years when there is more investment in assets, ROA will appear to be smaller.

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Table 16: Growth of ROA by Region for Pre and Post-Certification Periods with MIX Benchmark FY11-13 AVG

FY14-16 AVG

FY14-16 Regional AVG

Eastern Asia and Pacific

18%

6%

-72%

Eastern Europe & Central Asia

20%

16%

-24%

Latin America

8%

26%

-1%

169%

50%

3%

South Asia

A comparison of the FY14 to FY16 ROA growth (or decline) of the Smart Certified entities show that they performed in line or better than regional participants, on average. In other words, the Smart Certified cohort are using their assets to generate profits at a higher level compared to their peers. b. Return on Equity ROE is another factor to which investors pay significant attention. As a consequence, management also tracks this information to determine the organization’s competitiveness in the broader landscape. In general, both investors and management desire to see ROE increase over time.

Between the pre and post-certification periods, the Smart cohort, with the exception of EAP, saw a decrease in ROE. The decline in the post-certification periods may be explained by some of the earlier observation made regarding other KPIs. In those regions, internal cost indicators were either reduced or remained flat, while businesses experienced growth in investments, GLP, and number of borrowers (meaning more profits in dollars were added to equity). This suggests that at a minimum, the FSPs in these regions remained profitable at roughly the same rate. At the same time, equity which is cumulative (as it accumulates from the inception of a company) must have seen some growth, unless it was paid out to shareholders in the case of those organized as banks. With the increase in equity and relatively flat profitability, the ROE ratio would decline as it is calculated as net income (for the year) divided by equity. Global economic trends and regional/national events may also have impacted the business climate may be a contributor to the downward shift.

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Return on Equity (ROE): Net Operating Income (less of taxes) compared to average equity measures a FSP’s ability to build equity through retained earnings.

This ratio is net of income taxes and excludes donations and nonoperating items.

Source: MIX Market

How does it impact other ratios?

This indicator is not a direct input for other performance ratios.

Why is this an important metric?

FSPs often require funding from investors as they grow GLP. As a measure, ROE allows management to track the organization’s competitiveness in the broader landscape. Both investors and management desire to see ROE increase over time.

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Table 17: Average of ROE by Region for Pre and PostCertification Periods with MIX Benchmark FY11-13 AVG

FY14-16 AVG

FY14-16 Regional AVG

Eastern Asia and Pacific

28%

30%

20%

Eastern Europe & Central Asia

10%

7%

6%

Latin America

23%

19%

13%

South Asia

58%

22%

20%

However, in each region, the Smart cohort had higher ROE compared to regional averages.

Yield on Gross Portfolio: Financial revenue from loans compared to average gross loan portfolio aids in estimating the FSPs ability to generate revenues from interest, fees and commissions on the gross loan portfolio. Income from late fees and penalties are also included.

Source: MIX Market

How does it impact other ratios?

This indicator is not a direct input for other performance ratios.

a. Yield on Gross Portfolio The yield on portfolio is the simplest measure of an FSP’s profitability. Given that lending represents the core business activity, it is important to understand how revenues from lending activities grow over time. While this is an important measure for management, it is also significant data for investors.

The yield on gross portfolio is generally expected to increase over time, especially as GLP increases. However, as institutions gain efficiency and/ or gain access to lower cost capital, they may share some of the benefits with borrowers in the form of lower interest rates. Lower interest rates may make the FSPs more competitive in the market and help them to grow the base of borrowers and correspondingly the loan portfolio.

Why is this an important metric?

The return on gross portfolio is a direct measure of how profitable the core lending activities of an institution are. To attract investor capital, management needs to show that portfolio yield generally increases over time.

In the post-certification period, the Smart cohort experienced a decrease in yield on gross portfolio. Alongside the efficiencies denoted by better than average ROA in comparison to regional peers, it seems that the Smart Certified cohort passed on some of the efficiency savings to clients. The implied lower interest rates may explain why several Smart cohorts had a higher growth rate in terms of GLP and number of borrowers.

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Table 18: Average of Yield on Gross Portfolio for Pre and Post-Certification Periods with MIX Benchmark FY11-13 AVG

FY14-16 AVG

FY14-16 Regional AVG

Eastern Asia and Pacific

33%

28%

35%

Eastern Europe & Central Asia

29%

28%

24%

Latin America

40%

38%

29%

South Asia

25%

25%

24%

Except for EAP, the Smart cohort had higher average yield than the regional benchmark for FY14 to FY16.

The higher yields on portfolio may be reflective of the base of clients being served by the certified groups.

CONCLUSION Since the inception of the Smart Campaign in 2013, the Partnership for Responsible Financial Inclusion has served as a strategic partner in the campaign’s success. In May 2018, the Smart Campaign announced the landmark achievement of reaching 100 Smart Certified FSPs globally. This success was largely made possible through the cumulative impact of the PRFI network. In fact, PRFI member organizations comprise 51 of the 100 Smart Certified entities—collectively adopting client protection standards for 71% of the total clients across Certified entities. The purpose of this research study was to analyze financial data from 22 Smart Certified entities in an effort to better understand the business case for certification.

This study leveraged the EIU Microscope reports to control for external macroeconomic factors that may have otherwise directly inflated or deflated the performance of the cohort members analyzed. Our research has concluded that mixed performance is observed between the completion of Smart Certification and an entity’s success post-certification across five key performance areas: outreach, portfolio quality, efficiency and productivity, financial management, and profitability. Success is defined as an entity’s enhanced ability to outperform a regional benchmark of FSPs. Our findings indicate that Smart Certification most likely positively impacted the cohort’s outreach, portfolio quality and internal efficiency related KPIs. Evidence from two regions within the cohort showed that Smart Certified entities are more likely to experience higher gross loan portfolio growth in comparison to the regional benchmark. Furthermore, for regions impacted by macroeconomic downturns, Smart Certification appears to potentially serve as a protective strategy for dampening negative rates of GLP reduction. A comparison of results for the Smart Certified cohort against the regional benchmark shows the same or better portfolio quality across all regions. Although delinquency rates across the benchmark universe were relatively low, Smart Certified

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entities had particularly low levels. This is perhaps because Certified entities outperformed the benchmark on risk coverage metrics which may be due to the conservative risk management policies associated with certification (see Principle 2: Prevention of over-indebtedness).

Notably, efficiency and productivity analysis revealed underperformance across all metrics compared to MIX benchmark although they improved internally between pre and post periods. For the period analyzed, the regional benchmark experienced lower operating expense ratios and higher costs per borrower. This underperformance could perhaps be due to the Smart Certified cohort’s higher concentration in rural village banking—an expensive service offering. Personnel ratios for the Smart cohort remained flat or showed minimal growth between the pre and post-certification periods.

Smart Certified entities displayed inconclusive financial management results due to complexities in the cohort’s organizational structures and varying maturity levels. The cohort’s D/E outperformed the benchmark in two regions and underperformed relative to the benchmark in the remaining two regions. This discrepancy is perhaps explained by the concentration of NBFIs and NGOs in the certified cohort in some regions and higher concentrations of regulated financial institutions in the remaining regions. A decline in the financial revenue of Smart Certified entities post-certification could be due to the cohort’s increased investment in attracting new sources of capital which may have a longer return on investment horizon.

Still, compared to regional counterparts, most Certified entities outperformed the benchmark by achieving higher revenue per dollar of assets.

Certified FSPs experienced mixed results for profitability KPIs. Three of the four regions analyzed experienced a flat or decreased ROAs and ROEs post-certification. A decreased yield on the gross portfolio was also experienced. This could perhaps be due to internal activities such as reducing interest and improving cost-savings for clients, or external global macroeconomic trends and regional events that led to a tightening of lending practices across the industry.

As the Smart Campaign continues to experience growth, PRFI is dedicated to encouraging our membership network and local partners to achieve certification. This initial analysis of KPIs across 22 Smart Certified entities unveiled some positive outcomes in business performance that highlight measurable benefits for and the FSP’s business success. In the least, no net negative impact was observed in business growth and maintaining profitability erasing any doubts of management incurring the costs of getting certified. We strongly believe an even stronger business case will emerge as future analysis of KPIs is undertaken.

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REFERENCES EIU (Economist Intelligence Unit). 2011. Global Microscope 2014: The enabling environment for financial inclusion. Sponsored by MIF/IDB, CAF, ACCION and Citi. EIU, New York, NY. EIU (Economist Intelligence Unit). 2012. Global Microscope 2014: The enabling environment for financial inclusion. Sponsored by MIF/IDB, CAF, ACCION and Citi. EIU, New York, NY EIU (Economist Intelligence Unit). 2013. Global Microscope 2014: The enabling environment for financial inclusion. Sponsored by MIF/IDB, CAF, ACCION and Citi. EIU, New York, NY EIU (Economist Intelligence Unit). 2014. Global Microscope 2014: The enabling environment for financial inclusion. Sponsored by MIF/IDB, CAF, ACCION and Citi. EIU, New York, NY EIU (Economist Intelligence Unit). 2015. Global Microscope 2014: The enabling environment for financial inclusion. Sponsored by MIF/IDB, CAF, ACCION and Citi. EIU, New York, NY EIU (Economist Intelligence Unit). 2016. Global Microscope 2014: The enabling environment for financial inclusion. Sponsored by MIF/IDB, CAF, ACCION and Citi. EIU, New York, NY MicroRate. 2014. Technical Guide: Performance & Social Indicators for Microfinance Institutions. Fetched from: http://www.microrate.com/media/downloads/2014/05/MicroRate_-Technical-Guide-20142.pdf MIX. 2014. Global outreach & Financial Performance Benchmark Report – 2014. Fetched from: http://www. themix.org/mixmarket/publications/2014-global-outreach-and-financial-performance-benchmark-report MIX. 2015. Global outreach & Financial Performance Benchmark Report – 2015. Fetched from: http://www. themix.org/mixmarket/publications/2015-global-outreach-and-financial-performance-benchmark-report MIX. 2016. Global outreach & Financial Performance Benchmark Report – 2016. Fetched from: http://www. themix.org/mixmarket/publications/2016-global-outreach-and-financial-performance-benchmark-report

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APPENDIX A: SMART CLIENT PROTECTION PRINCIPLES Principle 1: Appropriate Product Design & Delivery •

The provider offers products and services that are suited to client’s needs.

•

The provider monitors suitability of products, services and delivery channels.

•

A policy of documented process are in place to prevent aggressive sales techniques and forced signing of contracts.

Principle 2: Prevention of over-indebtedness •

The provider has a sound policy and well-documented process for loan approvals and makes decisions using appropriate information and criteria.

•

The provider uses credit reporting information, when feasible in the local context.

•

Provider’s senior management and board monitor the market and respond to heightened over-indebtedness risk.

•

The provider maintains sound portfolio quality.

•

The provider incentivizes staff to approve quality loans.

Principle 3: Transparency •

Policy and documented process are in place to require transparency on product terms, conditions and pricing.

•

The provider communicates with clients at an appropriate time and through appropriate channels.

•

The provider takes adequate steps to ensure client understanding and support client decision making.

Principle 4: Responsible Pricing •

The provider is managed sustainably to provide services in the long term.

•

The provider’s pricing policy is aligned with the interest of clients.

•

The provider’s financial ratios do not signal pricing issues. (if outside the ranges, provider must be asked to explain and justify.)

Principle 5: Fair and respectful treatment of clients •

The provider promotes and enforces fair and respectful treatment of clients in line with a code of conduct.

•

The provider has a policy and documented processes to avoid discriminating against protected categories in selecting clients and setting terms and conditions.

•

Loans are collected by staff and collection agents in an appropriate manner.

•

The provider has effective systems to prevent and detect fraud.

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•

Insurance claims are processed in a fair and timely manner.

•

The provider management and oversight support fair and respectful treatment of clients.

Principle 6: Privacy of client data •

Clients are informed about data privacy and consent to the use of their data.

Principle 7: Mechanisms for complaints resolution •

The provider has an effective system in place to receive and resolve client complaints.

•

The provider informs clients about their right to complain and how to submit a complaint.

•

The provider uses information from complaints to manage operations and improve product and service quality.

Fetched From: https://www.smartcampaign.org/about/smart-microfinance-and-the-client-protection-principles Note: The scoring criteria terminology has changed over the years in this research paper. We have matched the 2016 definition to prior years.

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APPENDIX B: MIX DEFINITIONS OF KEY PERFORMANCE INDICATORS Indicator

Indicator Definition

Formula

Portfolio Quality

Portfolio at Risk > 30

Represents the portion of loans greater than 30 days past due, including the value of all renegotiated loans (restructured, rescheduled, refinanced and any other revised loans) compared to gross loan portfolio. The most accepted measure of a financial institution’s portfolio quality.

(Outstanding balance, portfolio overdue > 30 days + Renegotiated loans)/ Gross loan portfolio

Portfolio at Risk > 90

Represents the portion of loans greater than 90 days past due, including the value of all renegotiated loans (restructured, rescheduled, refinanced and any other revised loans) compared to gross loan portfolio. Indicates loans considered to be higher risk based on its current performance.

(Outstanding balance, portfolio overdue > 90 days + Renegotiated loans) / Gross Loan Portfolio

Risk Coverage

Allowance for loan impairment losses compared to portfolio overdue more than 30 days plus Impairment loss renegotiated loans. Measures how much of allowance/ this portfolio at risk are covered by a financial institution’s impairment loss allowance, allowing to PAR > 30 days estimate how prepared a financial institution is to absorb credit loan losses at that point of time.

Efficiency & Productivity

Operating Expense

Total operating expense compared to average gross loan portfolio. Measures all costs incurred to deliver loans (personnel and administrative expenses as well as non-cash expenses such depreciation and amortization).

Cost per Borrower

Total operating expense distributed among average Operating expense/ number of borrowers. Represents the average cost Average number of active of maintaining an active borrower. borrowers

Personnel Allocation Ratio

Number of loan officers divided by total personnel.

Measures the allocation of staff to activities directly involved in a financial institution’s lending process, the core business operation of a financial institution.

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Operating expense / Average gross loan portfolio

Number of loan officers / Number of personnel

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Indicator

Borrowers per Loan Officer

Indicator Definition Total number of active borrowers divided by number of loan officers. Aids to assess the loan officers’ productivity by measuring the average caseload of borrowers managed by each loan officer.

Formula Number of active borrowers / Number of loan officers

Financial Management

Debt to Equity Ratio

Total liabilities compared to equity. Measures the overall leverage that FSPs has incurred to finance its portfolio and other assets and also how much cushion it has to absorb losses after all liabilities are paid.

Total Liabilities/ Total Equity

Financial Revenue/ Assets

Total financial revenue divided by average assets.

Represents the total revenue generated by a FSP’s core business operations as a percentage of its assets. Income for interest, fees and commissions for financial services, other operational income as well as gains (losses) on financial assets (realized or unrealized) and foreign exchange gains and losses are considered for its calculation.

Financial revenue/ Average assets

Financial Expense/ Assets

Total financial expenses divided by average assets.

Aids to determine the proportion of total financial expense incurred by a FSP to fund its assets.

Total interest, fees and commissions incurred on all liabilities including deposit accounts held by the financial institution, as well as gain (losses) from financial liabilities and the gain or loss on the net monetary position are considered for its calculation.

Financial expense on funding liabilities / Average assets

Profitability

Return on Assets

Net operating income (less of taxes) compared to average assets. Measures how the FSP is managing its assets to optimize its profitability.

This ratio is net of income taxes and excludes donations and non-operating items.

Return on Equity

Net operating income (less of taxes) compared to average equity. Measures a FSP’s ability to build equity through retained earnings. This ratio is net of income taxes and excludes donations and nonoperating items.

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(Net operating income, less Taxes)/ Average assets

(Net operating income, less Taxes)/ Average equity

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Indicator

Indicator Definition

Financial revenue from loans compared to average gross loan portfolio. Aids to estimate the FSP’s Yield on Gross Portfolio ability to generate revenues from interest, fees and (nominal) commissions on the gross loan portfolio. Income from late fees and penalties are also included.

Formula Financial revenue from loans/ Average gross loan portfolio

Outreach

Gross Loan Portfolio

All outstanding principals due for all outstanding client loans. This includes current, delinquent, and renegotiated loans, but not loans that have been written off. It also includes off balance sheet portfolio.

Number of Borrowers

The number of individuals or entities who currently have an outstanding loan balance with the FSP or are primarily responsible for repaying any portion Not applicable of the gross loan portfolio. Individuals who have multiple loans with FSPs are counted as a single borrower.

Average balance/ Average GNI per capita

Average outstanding loan balance compared to local GNI per capita to estimate the outreach of loans relative to the low-income population in the country.

The indicator measured with GNI per capita that is calculated in national currency is usually converted to U.S. dollars at official exchange rates for comparisons across economies, although an alternative rate is used when the official exchange rate is judged to diverge by an exceptionally large margin from the rate actually applied in international transactions. To smooth fluctuations in prices and exchange rates, a special Atlas method of conversion is used by the World Bank.

Total deposits compared to assets. Aids to Deposits to Total assets determine the portion of FSPs assets that are funded by deposits.

Not applicable

Average outstanding balance / GNI per capita

Total Deposits / Total Assets

Fetched From: https://www.themix.org/glossary Note: In cases of missing data, MIX formula were used to calculate ratios.

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APPENDIX C: COHORT OF CERTIFIED FSPS AND KEY CHARACTERISTICS BY REGION. Region

Name

Legal Structure

Certified Since

Tier

Percent of Asset by region

Maturity (years)

Eastern Asia and Pacific PRASAC

NBFI

2015

1

55%

22

XacBank

Bank

2015

1

39%

16

MBK Ventura

NBFI

2014

1

6%

14

Eastern Europe & Central Asia IMON INTERNATIONAL

NBFI

2014

1

28%

18

FINCA Kyrgyzstan

Bank

2015

2

27%

22

OBS

Bank

2014

1

21%

15

Kompanion

Bank

2014

1

16%

13

AFK

NGO

2015

2

3%

18

Microinvest

NBFI

2015

2

4%

14

Latin America BancoSol

Bank

2013

1

62%

25

BanCompartir

Bank

2014

1

11%

20

Fundaciรณn Delamujer

NGO

2014

1

9%

31

EDPYME Raiz

NBFI

2014

1

8%

18

Banco ADOPEM

Bank

2015

1

6%

35

Crezcamos

NBFI

2013

1

3%

11

Pro Mujer - MEX

NGO

2013

2

1%

16

South Asia Grameen Bank

Bank

2013

1

59%

34

Ujjivan

NBFI

2013

1

27%

13

LOLC

NBFI

2013

1

5%

9

Arohan

NBFI

2015

1

4%

11

Cashpor

NGO

2013

1

3%

20

Kashf Foundation

NGO

2015

1

2%

21

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APPENDIX D: MICRORATE TIER DEFINITIONS This reference was used in this case study. The primary proxy used for analysis for size based on total assets.

Description

Sustainability

Size (Total Assets)

Transparency

Tier 1

Tier 2

Tier 3

Mature, financially sustainable, and large MFIs that are highly transparent

Small or medium sized, slightly less mature MFIs that are, or are approaching profitability

Start-up MFIs or small NGOs that are immature and unsustainable

Positive ROA for at least 2 of the last 3 years AND

Positive ROA for at least 1 of the 3 years and other years>-5% OR

No ROA<-5% in the last 3 years >$50 million Regulated Financial Institution OR Rated at least once in the last two years

The rest

Positive trend in RoA in last 2 years and >-5% $5 million - $50 million

<$5 million

Audited Financial Statements for at least the last 3 years.

The rest

Scoring Guidelines: The MFI is assigned the lowest tier for all three criteria All indicators must be calculated with the latest data available.

Fetched from: http://www.microrate.com/media/downloads/2013/04/MicroRate-Whitepaper-Microfinance-Institution-Tier-Definitions.pdf

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APPENDIX E: EIU MICROSCOPE SCORING OF ENABLING ENVIRONMENT The table summarizes the EIU Microscope financial inclusion score for the years covered in this case study.

Eastern Asia and Pacific

2011

2012

2013

2014

2015

2016

43.97

48.07

51.90

52.00

53.00

49.00

MBK Ventura

Indonesia

39.2

44.3

46.5

55

56

55

PRASAC

Cambodia

50.9

55.7

60.3

56

55

47

XacBank

Mongolia

41.8

44.2

48.9

45

48

45

Eastern Europe & Central Asia

43.83

40.17

35.40

41.33

44.00

45.00

AFK

Kosovo

43.83

40.17

35.40

41.33

44.00

45.00

FINCA Kyrgyzstan

Kyrgyzstan

45.2

42.1

35.1

43

47

48

IMON INTERNATIONAL

Tajikistan

41.1

36.3

36

38

38

39

Kompanion

Kyrgyzstan

45.2

42.1

35.1

43

47

48

Microinvest

Moldova

n/a

n/a

n/a

n/a

n/a

n/a

OBS

Serbia

n/a

n/a

n/a

n/a

n/a

n/a

57.17

59.90

61.79

72.71

74.14

74.86

46.1

46.1

53.6

48

51

52

56

56

58.5

85

86

89

64.7

71.8

69.8

58

60

56

56

56

58.5

85

86

89

67.8

79.8

82.5

87

90

89

56

56

58.5

85

86

89

53.6

53.6

51.1

61

60

60

43.77

46.40

50.70

56.17

63.50

68.50

Latin America Banco ADOPEM

Dominican Republic

BanCompartir

Colombia

BancoSol

Bolivia

Crezcamos

Colombia

EDPYME Raiz

Peru

Fundación Delamujer

Colombia

Pro Mujer - MEX

Mexico

South Asia Arohan

India

43.1

45.7

52

61

71

78

Cashpor

India

43.1

45.7

52

61

71

78

Grameen Bank

India

43.1

45.7

52

61

71

78

Kashf Foundation

Pakistan

62.8

67.4

69.7

58

64

63

LOLC

Srilanka

27.4

28.2

26.5

35

33

36

Ujjivan

India

43.1

45.7

52

61

71

78

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APPENDIX F: EIU MICROSCOPE MATRIX AND RELEVANT SMART CLIENT PROTECTION PRINCIPLE Relevant SMART EIU Microscope Indicators Principle*

2011

2012

2013

2014

2015

2016

P1

Government Support for Financial Inclusion

x

x

x

x

x

x

P3

Regulatory and Supervisory Capacity for Financial Inclusion

x

x

x

x

x

x

P4

Prudential Regulation

x

x

x

x

x

x

P2, P4

Regulation and supervision of credit portfolios

x

x

x

x

x

x

P1

Regulation and supervision of deposit-taking activities

x

x

x

x

x

x

Regulation of insurance targeting low-income populations

x

x

x

x

x

x

P3, P5

Regulation and supervision of branches and agents

x

x

x

x

x

x

n/a

Requirements for non-regulated lenders

x

x

x

x

x

x

P1

Electronic Payments

 n/a

n/a

n/a

x

x

x

P2, P6, P5

Credit Reporting systems

x

x

x

x

x

x

P3, P5, P7

Market Conduct Rules

x

x

x

x

x

x

P7

Grievance redress and operation of dispute-resolution mechanisms

x

x

x

x

x

x

n/a

Adjusting factor: Stability

x

x

x

x

x

x

P1, P3, P4

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APPENDIX G: TIME OF RELEVANT MACROECONOMIC EVENTS The events listed in the timeline represent major macroeconomic events impacting lending, prepayment and overall growth.

Macroeconomic Events 2017

New Regulatory Standards Introduced in EECA

GREXIT & BREXIT: weakening emerging economy

2016

2015

2014

Liquidity crunch & repayment issues following demonetization in India

Worsening of global economy due to political instability in USA

ECA impacted by European Economic crisis decline in borrowers in GLP

Collapse of all price and low inflation accompanied by worseing of economy

2013

Worsening of Eurozone debt crisis

2012

Downgrading of American Bonds

2011

Eurozone Debt Crisis Started

Headwinds of housing crisis and banking collapse slowing down

Indian Microfinance crisis: Pakistan Repayment crisis 2010

Compiled from: The Guardian and EIU Global Microscope yearly publications

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APPENDIX H: MISSING DATA POINTS Operational and Financial Metrics of Cohort by Region Eastern Europe & Central Asia

2011

2012

PAR>90 days

2013

2014

2015

1

Risk Coverage (PAR>30)

1

1

Cost per Borrower

1

1

Personnel Allocation Ratio

1

1

Borrowers per Loan Officer

1

Financial Revenue/Assets

1

Financial Expense/Assets

1

Return on Assets

1

Return on Equity

1

Yield on Gross Portfolio (nominal)

1

1

Average loan balance/Average GNI per capita Latin America

2016

1 2011

2012

2013

2014

2015

PAR>30 days

2016 1

PAR>90 days

1

Risk Coverage (PAR>30)

1 1

OPEX Loan \Loan Portfolio

1

1

Cost per Borrower

1

1

Personnel Allocation Ratio

1

1

1

Borrowers per Loan Officer

1

1

1

Financial Revenue/Assets

1

Financial Expense/Assets

1

Return on Assets

1

Return on Equity

1

Yield on Gross Portfolio (nominal)

1

Average loan balance/Average GNI per capita South Asia

1 2011

2012

2013

2014

2015

2016

PAR>30 days

2

1

PAR>90 days

2

Risk Coverage (PAR>30)

3

2

Personnel Allocation Ratio

1

Borrowers per Loan Officer

1

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The Center for Financial Inclusion acts as the Secretariat for the Partnership for Responsible Financial Inclusion Center for Financial Inclusion at Accion 1101 15th Street NW, Suite 400 Washington, DC 20005 USA responsiblefinancialinclusion.org