In 2011, Women’s World Banking launched the Gender Performance Initiative (GPI) to create an empirical, comparable set of universal standards to measure how effectively microfinance is serving women, both as clients and staff. The GPI framework enables institutions to better understand the financial behavior and needs of low-income women, create products and services that meet those needs, and potentially understand outcomes for women and their households. Under this initiative, we identified key performance indicators around gender and piloted these metrics with 3 regionally and organizationally diverse institutions to better understand 1) if the indicators were operationally feasible to collect and report on and 2) which indicators could enable an institution to demonstrate that it was serving women “well.”
By the end of the pilots we had established a full framework of approximately 25 indicators that MFIs could use to better understand how well they are serving women.Yet, we knew that the wider industry needed a smaller set of key gender performance indicators. This set of indicators had to be feasible for MFIs to report on a regular basis and comparable across institutions and markets. Thus we set out to define and test what we call the “select few” indicators...
Currently, the industry uses a limited set of gender indicators, confined to % women borrowers and several simple organizational diversity metrics. By using the learnings from the pilots, and conducting further testing, as Micol will discuss shortly, we were able to determine the 5 key indicators that will allow us as an industry to better understand how we serve women.
Here we look at “why” these indicators can enable financial institutions to better understand how well they are serving low-income women...Now I will go into a bit more depth on each of these....using data from MFIs to demonstrate what these indicators can tell us.
When an institution measures % of new women borrowers, we can see whether the institutions is maintaining an intent to reach women.Here we see 2 MFIs, with very different trends. In MFI 1, the institution has maintained a steady outreach to women clients (between 60% and 70% of all new clients were women for the past 5 years). MFI 2 has a very different story. Here we can see how drastic changes in the number of new women clients the institution reached over the past 10 years has significantly contributed to the decline in their current outreach to women. And while MFI2 has begun increasing its outreach again since 2007, they still have not reached an equitable level of men and women clients.
Itis important to understand the size of the loans female vs. male clients are receiving. Here are two different ways of looking at the data. At MFI 1, we see that at the smallest loan sizes (amount disbursed), women are accessing 50% of the loans, however as the loan sizes increase, less and less women are accessing these products. There may be good reasons for this disparity – perhaps the women in that market are in lower-return businesses and have a smaller capacity to repay. Yet, an institution that claims to focus on women needs to understand these differences to ensure that there are not unintended biases in lending practices.At MFI 2, we see less inequality in loan sizes (although men do have higher loans on average), but it is interesting to see that the trend holds across rural and urban populations....
As a proxy for client satisfaction with products and services, we need to understand if we are retaining women clients in particular. At this institution, while overall retention rates are down, women have always exhibited higher loyalty. This is also interesting for an institution from the business perspective, as it is generally understood that retaining old clients is more cost effective than acquiring new ones...
At MFI 1, we can see that women are better repayers up front, however this difference tapers off as the loans approach write-off. While the male loans are eventually recovered, the type of data is critical for an institution that needs to consider costs of collection...At MFI 2, we see that women are better repayers at all loan sizes except the largest, commercial loans. Yet, these commercial loans actually skew the overall PAR data. For example, when looking at PAR30 by gender at this institution, we see 5% for women vs. 4.8% for men. Yet, these large, commercial loans (where men hold 80% of the loans), represent only 1% of clients. The majority of clients (93%) have loans in the smallest three categories, where women have significantly lower PAR. Analysis like this shows that PAR30 by gender is a critical analysis for institutions to conduct, however may be difficult to standardize at the industry level... (more here)
When looking beyond pure diversity metrics, we think it is critical to look at staff retention by gender as a proxy for how well you are serving your internal women clients – your women staff. These particular graphs show % women and men staff by join year, not retention per se, however can demonstrate the value of collecting this type of data...(more here)
Gender Performance - Celina Kawas, Women's World Banking
What is Gender Performance?
With 74% of MFIs claiming to target women, and over half declaring women’s
empowerment or gender equality as an objective:
How can we hold ourselves accountable to the financial inclusion and
empowerment principles we advocate?
How can we understand if financial institutions are serving women well?
The Gender Performance initiative aims to develop, monitor, and analyze
more and better gender-based social and financial performance indicators.
How do we measure how well we are serving women?
In this context, we tested indicators to measure:
• Outreach to low-income women
• Diversity of products and services to meet women’s lifecycle
• Quality of service
• Protection of women clients
• Gender diversity within financial institutions
• Financial performance
• Can we build the business case for serving low-income women?
• Social performance
• Are there any outcomes for women that we can track through
data collected by MFIs?
The Next Phase in Measuring Gender Focus
• % women borrowers
• % women staff
• % women managers
• % women board
GPI “Select Few”
• % new women
• Average loan size per
• Women borrower
• PAR>30, by gender
• Staff retention
rate, by gender
The “Select Few” Gender Performance Indicators
% new women
•“% women borrowers” provides a snapshot of an organization’s outreach to women.
•% new women borrowers indicates the direction in which an organization is moving.
Average loan balance
per woman borrower
•Average loan balance is commonly used as a simple and comparable proxy for measuring depth
•Disaggregating by gender can o ensure that the organization is reaching low-income women.
•Retention is a proxy for customer satisfaction with products and services. Institutions that seek
to serve women well must look at disaggregated retention data.
Portfolio at risk >30,
rates, by gender
•Gender has long been one of the most important variables to measure financial risk.
•Disaggregated financial data enables an institution to better understand its portfolio.
•Staff retention is critical to productivity and maintaining operational efficiency.
•Institutions must disaggregate retention data to understand if workplace conditions are meeting
% new women borrowers
New clients (MFI 2)
New client distribution (MFI 1)
Average loan balance per woman borrower
Client Distribution by Loan Size (MFI 1)
Average Loan Size (MFI 2)
2 - 3.9 4 - 7.9 8 - 29.9 30 - 85 Overall
Female borrower retention rate
Portfolio at risk >30, by gender
PAR by client gender (MFI 1)
PAR 30 by loan size (MFI 2)
PAR 30 PAR 60 PAR 90 PAR 180 PAR 360
0.1 - 1.9 2 - 3.9 4 - 7.9 8 - 29.9 30 - 85 Overall
Staff retention rates, by gender
Number of LOs, by join year (MFI 1)
Number of LOs, by join year (MFI 2)
• Partnership with the MIX to test select few indicators
• Disseminating and promoting adoption of “select few”
• Industry Initiatives