MICROFINANCE & POVERTY

Transcription

1 MICROFINANCE & POVERTY 13 November 2014

2 GET TO KNOW YOUR PANELISTS Scott Brown, President and CEO of VisionFund International (Moderator) JD Bergeron, Director of Truelift Julie Peachey, Director of the Social Performance Management Center at Grameen Foundation Aldo Moauro, Executive Director of MicroFinanza Rating

3 Moving from Data to Action Julie Peachey Grameen Foundation Director, Social Performance Management Center Measurement, Data Quality and Analysis

4 How many of you use or promote use of a poverty measurement tool? The PPI?

5 What is the Progress out of Poverty Index? What is the PPI? A poverty measurement tool for organizations with a mission to serve the poor 10 easy-to-answer questions and a scoring system Why use the PPI? With the PPI, your organization can:

6 How Organizations Use the PPI Measure poverty outreach Target and screen Track poverty movement Evaluate programs Develop products Uncover client insights Perform market research Create customer profiles

7 Who uses the PPI?

8 If you don t know where you are going, you won t ever get there. #emw2014

9 The Business Case Data Collection Use of Findings Action

10 Market Research Better understand your clients so that you may develop products and services that meet their needs. Poverty Level Percent of clients that have a mobile phone Under $1.25/day poverty line 12.5% Between $1.25/day and $2.50/day poverty line 20.3% Above $2.50/day poverty line 67.2%

11 Answering Strategic Questions Is coffee a viable business for this farmer? Customer Profiling and Segmentation A Most Likely to be Poor 12% B 27% C 34% D Least likely to be Poor 27% Family Size Years of Education Illiteracy 20% 12% 11% 8% Farm Area (Ha) Production (Kg) 3,701 4,774 5,430 10,207 Productivity(Kg/Ha) 1,421 1,137 1,551 1,180

12 Economic Viability Analysis Farmer Segmentation No. of Farmers Additional Kg needed to break poverty line Not viable business ,756 kg Currently viable business 483-7,665 kg Viable + productivity kg Viable + productivity + area 51 +6,718 kg Total general 881 Average productivity: Non viable farms: 1361 Kg/ha Viable farms:1808 Kg/ha

13 #emw2014 VISIONFUND TRACKING POVERTY OVER TIME 1. Initial findings seem to show that more people move out of poverty with more time: VF Ethiopia: 1yr - 11% VF Philippines 2yrs- 14% VF Ecuador 3 yrs 24% 2. Data quality is vital In VF Ghana, poor data collection produced erroneous results. Ensuring data quality is key. 3. Current PPI scorecards are critical VF Cambodia s outdated scorecard gives questionable data. 13 VISIONFUND INTERNATIONAL WORKING WITH WORLD VISION TO PROVIDE FINANCIAL SERVICES TO THE POOR

14 #emw2014 VISIONFUND TRACKING POVERTY OVER TIME Data can be viewed by comparing changes in different variables like loan type. VF Ethiopia saw a decrease in poverty for all 3 loan types, especially individual loans. AND by individual question within the 10-question scorecard. All loan methodologies reported increased access to latrines, especially community bank members. 14 VISIONFUND INTERNATIONAL WORKING WITH WORLD VISION TO PROVIDE FINANCIAL SERVICES TO THE POOR

15 Quality of Data PPI Certification and the Standards of Use Automated Data Collection

16 Call to Action Poverty data is useful for everyone: Investors, lenders, donors MFI management MFI clients But it needs commitment and support from you: Until the business case is fully appreciated and MFIs make the investment on their own Capacity building for use of not only PPI data, but other social/impact data Poverty data is at risk Because the PPI is a public good, organizations can download and use for free Without a permanent funding model to continue to update scorecards and provide technical expertise, the future of the tool is at risk

17 Learn more at Find the PPI for your country. 2. Download PPI documents. 3. Download learning materials. 4. Get help from PPI Specialists. Also available: case studies, blog, instructional videos, and more.

18 Poverty outreach results from social ratings Aldo Moauro Executive Director, MicroFinanza Rating State of Practice

19 Source of data Source of data: surveys on clients of MFIs conducted as part of the comprehensive social ratings of MFIs carried out in the period Number of comprehensive social rating data included = 60 Clients surveyed: new clients Poverty line used: 2$PPP/day poverty line DISCLAIMER: the analysis is valid for the sample only and is not meant to be generalized to the sector. A larger number of cases will help answering the poverty outreach question in a more complete 2014 MFR Srl all rights reserved

20 Poverty outreach: global % non-poor clients % poor clients Transparency opportunity: the poverty outreach message communicated by the industry may not always be reflected in 2014 MFR Srl all rights reserved

21 Poverty outreach: regional Regional differences in poverty outreach: higher in Africa and Asia, lower in ECA and LAC, partly reflecting the different poverty rates in the 2014 MFR Srl all rights reserved

22 Poverty outreach: mission (Country poverty rate MFI poverty rate) = Country poverty rate 21 MFIs with poverty in mission 39 MFIs without poverty in mission Deeper outreach results in poverty oriented MFIs: poverty rate among clients of poverty oriented MFIs is higher than the outreach of the non-poverty oriented 2014 MFR Srl all rights reserved

23 Poverty outreach: some gaps MFI poverty rate country poverty rate MFI poverty rate < half of country poverty rate Room for improvement in poverty outreach of poverty oriented MFIs 38% MFI poverty rate country poverty rate or «around» country poverty rate 62% MFI poverty rate < country poverty rate (29% MFI poverty rate < half country poverty 2014 MFR Srl all rights reserved

24 Use of findings: actions suggested Collect data for clients poverty level measurement Define a dashboard of indicators and benchmarks for poverty level measurement Introduce effective incentives for MFIs to do that (i.e. investment covenants, regulations, selfregulations by networks) Consolidation of specific industry norms/standards (i.e. PPI and Truelift)

25 The Big Picture JD Bergeron Director, Truelift

26 Social businesses need to be accountable for what they do. We track financial performance in detail but the social side is often measured by a few stories and lots of photos.

27 TRUELIFT PRO-POOR PRINCIPLES 1 Purposeful Outreach to People Living in Poverty 2 Products & Services that Meet the Needs of Poor Clients 3 Tracking Progress of Poor Clients

28 Categories addressed in each Principle 4.Use of Findings 3.Results Achieved 1.Intent and Strategy 2.Measurement, Data Quality, & Analysis

29 Truelift and the PPI; Measurement, Data Quality and Analysis Indicator 3.2 The Institution has systems to ensure that data collected is of robust quality. [If using the PPI] The institution conforms to the PPI standards of use. The institution has robust data to monitor poverty outreach Data should be verified as part of existing quality management systems, The person checking the data is not the same person responsible for entering the data originally. Relevant PPI Standards of Use include: Training of Staff, Procedure for data collection and quality checks and Data storage

30 RESULTS ACHIEVED Indicator 12.2: Through client feedback evidence, the institution demonstrates relevance, appropriatene ss, and quality of products and services aimed at poor clients. Examples of practical findings and analysis relating to target clients Analysis should include services used to serve intended goal Positive feedback on amounts and terms Areas to adapt are identified

31 Guidelines: This indicator requires the reporting of client feedback to include specific analysis for poor, vulnerable clients on the following points: Sources of Information: a) Specific Use of the service Documents: Client satisfaction and feedback reports b) Satisfaction and Feedback on different aspects of the service Staff/Department Responsible: Research & Development

32 Example of Good Compliance: Full and specific reporting includes suggestions from poor clients on improving the relevance of services for them. Feedback is reported on specific issues and includes specific suggestions from poor clients. Client satisfaction surveys find >80% of poor clients are satisfied. Example of Partial Compliance from African MFI: Although client feedback is carried out as part of our monitoring activities, the poorest are not specifically targeted. Scores for satisfaction are not collected quantitatively, but qualitatively, and are reported to senior management on a regular basis. Example of Partial Compliance from Bolivian MFI: Client feedback and areas of improvement on financial services characteristics are collected (amount, repayment frequency, group size, etc.) through satisfaction and exit surveys. Results are classified by product (group loan, health loan, etc.) but not by poor and non-poor clients. The MFI has made its products evolved based on the results of these surveys.

33 USE OF FINDINGS Indicator 18.2: Through the use of data and conclusions from that data, the MFI is enabled to monitor the progress of poor clients, and think strategically about further adding value Board and senior management make specific decisions as a result of findings Responses are made to any findings of weakness Certain skills and services are added as a result Specific products are improved

34 Guidelines: This indicator underlines the use of data and the conclusions from the data to achieve the following points: a) To think strategically about expanding good practice Sources of Information: Documents: Board meetings and strategic plans b) To address any gaps identified Staff/Department Responsible: Board, CEO, Senior Management

35 Example of Good Compliance: With data showing the risks of ill health affecting progress, an MFI introduced a new nonfinancial service for health education and low cost medical services for its clients, recognizing the importance of this particularly for the poor segments they work with. Example of Good Compliance from Cambodian MFI: Conducted training needs assessment in 2014 to identify the real social problems that our clients are facing and mapping the existing social welfare services in the operational target areas. From the results, we came up with the initiative to develop the social training modules for both clients and nonclients. This initiative has been piloted for 3 month (Jul-Oct'14) in 3 branches; and it will be rolled out to all branches after the pilot test is a success. Example of Partial Compliance from African MFI: Board and Senior management have requested e.g. follow up research on why better off clients do not perform as well as poorer clients; additional research to be done and actions to be taken.

36 Truelift Indicators Tool Framework: Results Summary Example of a Completed Assessment

37 USE OF FINDINGS Use of Data & Findings in: Due Diligence Identifying New Investees Assessing Target Markets Monitoring Strategic Decision Making

38 POVERTY OUTREACH & RESULTS PERFORMANCE DATA MONITORING: A Driver for Transparency & Improvement Pro-Poor Organizations recognized by PPI & Truelift Certifications: Are data driven Set poverty outreach and performance goals Monitor their achievements Pro-Poor Investors Reinforce the use of social performance, poverty outreach and results data Advocate for developing better markets

39 Q&A