UNSGSA -UN Secretary-General’s Special Advocate for Inclusive Finance for Development

Washington, DC

Keynote address at Turning Data into Action for Women’s Financial Inclusion event

How Can Data Propel Financial Inclusion for Women?

Ladies and gentlemen, I am very pleased to join you to discuss how we can build strong gender-disaggregated data.

As the UN Secretary-General’s Special Advocate for Inclusive Finance for Development, I have been making the case for ten years that data is essential to achieve financial inclusion. Just a few hours ago I helped launch the latest edition of the Global Findex, which I have supported from its earliest days. It has become one of the most powerful tools we have to measure our progress.

Now, thanks to the Women’s Financial Inclusion Data Partnership, we’ve gathered to advance further on data—this time with a targeted focus on women.

Before we focus on the numbers, let me address a question some of you may have—why do women need special attention when it comes to financial inclusion?  

Women’s financial inclusion is important for at least three reasons.

First, women are essential to achieve wider development progress. When women control finances, they spend more money on necessities like health, education, nutritious food, and child welfare.

Second, it is good stability policy. Women on average are stronger savers than men so they are more likely to use savings to invest in their priorities. This can reduce risks of economic setbacks and strengthen overall social and economic stability.

Third, it is good business. Unbanked women represent a huge untapped market for financial institutions. Plus, women pay back loans at higher rates than men, they are stronger savers, and they are loyal customers.

Nonetheless, new Global Findex data show the gender gap in financial services is stuck at 7 percentage points—9 points in developing countries. This has not changed since 2011! In South Asia, the gap is 11 points.

Also women-owned businesses are not well served.Globally, around 80 percent of formal, female-owned MSMEs do not get the financing they need.  

The causes of these gender gaps are complex and come from both the demand and supply sides.

On the demand side, they include economic and social barriers that restrict women’s independence, lower access to the official IDs required by banks, and lower ownership of the kinds of collateral needed to get loans. Women also have lower financial and digital literacy on average.

On the supply side, they include products and services that are seldom designed to meet the specific needs of women, which include privacy, security, convenience, and low cost.

So how do we begin to address the gender gap?

To solve women’s financial exclusion, our starting point should be data. We need demand-side insights into women customers complemented by supply-side insights into financial providers. Progress will come when we address both sides at the same time.

Let’s look quickly at where we stand with the demand-side data.

New Findex numbers tell us that financial inclusion for women continues to be a big challenge. The statistics are getting better but 35 percent still do not have an account, 41 percent in developing countries.

But Findex data also allow us to see opportunities. India, for example, has been able to reverse its trend thanks in part to its biometric ID. So this is a program that can be copied in other countries. Indeed indeed reduced the gender gap from 20 percentage points to 6 points.

Findex figures are not the only demand-side data countries need in order to serve women. Customer-centric policymaking demands more granular consumer data to understand women’s pain points in using financial services and to more effectively shape regulation. Country-specific surveys allow for deeper insights—and more targeted action.

Mexico has been using its own demand-side gender data since 2012 to identify problems with access, channels, and usage. Concerned about big gender gaps in rural areas, policymakers expanded cash transfer programs targeting low-income rural women specifically, with the result that now, more rural women than men have financial accounts! This is a type of policy that has worked.

Financial institutions also need demand-side data because often they do not know their female customers. A Women’s World Banking survey of 29 institutions showed that two-thirds had not given consideration to women as a distinct market segment.

When Australia’s Westpac Bank began to focus on women, their data revealed that women didn’t feel banks treated them with respect. Their research gave them guidance on women’s financial concerns—with savings and bill paying, for example—their comfort level with debt, and their need for financial mentors. The result has been a highly successful sub-brand designed around women’s needs.

Supply side data, on the other hand, is an equally powerful tool to address gender disparities—this time by charting the behaviors of services providers rather than clients.

On a global level, the IMF’s Financial Access Survey has announced that building on its pilots it will include gender data as an integral part of its future rounds—this is going to be a great addition! Just 27 countries were able to report fully in the recently released report but that number should keep rising. I am very happy we have launched the FAS gender-disaggregated data pilot.

In addition to the FAS a small but growing number of national governments are collecting their own supply-side gender data.

Chile has been the leader on this front since 2002. Its supply-side data has generated a shifting picture of women’s saving, borrowing, account balances and more. Just last year, this data indicated that banks were charging women 15 percent higher interest, even though they have lower non-performing loan rates. The implications for action are now being fully considered.

Tanzania is at an earlier stage of data generation. Its new, second-generation financial inclusion strategy will focus closely on women and they are asking all providers to submit gender-disaggregated data. And Egypt, Kenya, Rwanda, and Zambia are also developing plans to advance supply-side gender data.

In closing, I’d like to leave you with some concrete suggestions for what we can do to move forward.

Policymakers, including central bankers—You have an essential role to play when it comes to supply-side gender data. You have the power to request and champion the reporting of this data by providers. But even a high-level commitment like yours may not be followed through—it is not uncommon to find a disconnect between a central bank’s supervisory side and its statistical side. So beyond showing political will, you need to ensure good coordination. It is also important that relevant government agencies follow up on the information you glean from this data.

For financial service providers—I want to emphasize that serving women is good for your business. I encourage you to garnish and use data to become more customer-centric. Complemented by qualitative surveys, data is the essential tool you will need to reach women, understand their financial concerns and needs, and develop services that can earn their loyalty. Today, many providers have no idea about the gender composition of their clients. According to GSMA, just 23 percent of mobile network operators know this! I assure you, we can do more together.

Finally, for all of us—We are talking about data today, but numbers are not, ultimately, the point. What matters is that we analyze this data and understand its implications. And that we act on what we learn to address the long-standing gender inequalities that are holding us back. When we are making decisions based on evidence rather than perceptions, we will truly be making a difference.

I wish you all the best of sucess. I am looking forward to hearing your plans and I will be there to support you. Thank you.