This report and infographic examine data from the 250+ eligible fintech applicants from the fourth Inclusive Fintech 50 competition to better understand the state of early-stage fintechs. CFI analyzes all applications to identify trends and to find innovations with disruptive potential. The massive scale that is only possible with digitalization matters greatly to the financial inclusion agenda, and this year’s IF50 applicants are already collectively reaching 54 million people, many of whom were previously underserved, across 101 countries of operation. The fintechs are young and small now, but as we’ve seen in past years, they grow to reach millions more people and raise millions more in investment. However, despite this tremendous outreach and potential, there are also areas that require attention: funding and gender gaps, inconsistent practices around data privacy and consent, and limited data collection for outcomes management.

Insights from the 2022 Inclusive Fintech 50 Applicant Pool

The <a href="https://www.inclusivefintech50.com" target="_blank" rel="noopener noreferrer">Inclusive Fintech 50</a> application data from the third year signals continued progress on innovations to onboard low-income customers, despite the challenges posed by the pandemic:
<ul>
 	<li><strong>Inclusive fintechs are using creative approaches to serve new customers</strong>. From retail partnerships that help drive customer acquisition, to insurance platforms offering micro-coverage, to native language chatbots, to enhanced biometric identity verification solutions, early-stage inclusive fintechs are pursuing outside-the-box solutions to reach un/underbanked people around the world.</li>
</ul>
Nevertheless, there are two areas of concern:
<ul>
 	<li><strong>Funding concentration persists</strong>. While fintech investments across emerging markets have been increasing, early-stage inclusive fintechs continue to face disparities based on geography, funding status, and gender.</li>
 	<li><strong>Potential customer risks persist around data usage</strong>. Although data is central to the business models of inclusive fintechs, some applicants require customer consent related to data, and some still do not.</li>
</ul>

Insights from the 2021 Inclusive Fintech 50 Applicant Pool

H.M. Queen Máxima of the Netherlands, the United Nations Secretary-General’s Special Advocate for Inclusive Finance for Development (UNSGSA), today co-hosted a virtual workshop with the Center for Financial Inclusion (CFI) at Accion to raise awareness and address algorithm biases for financial inclusion.

Queen Máxima and CFI Managing Director Mayada El-Zoghbi co-chaired the meeting, which convened leadership from select central banks and other subject matter experts. Both the UNSGSA and the Managing Director provided brief opening remarks. President and CEO of Accion Michael Schlein also offered brief remarks.

[caption id="attachment_43591" align="alignright" width="559"]<img class="size-full wp-image-43591" src="https://content.centerforfinancialinclusion.org/wp-content/uploads/sites/2/2021/12/unsgsa-cfi-workshop-algorithm-bias-web-story-foto-21.jpg" alt="" width="559" height="322" /> <em>UNSGSA Queen Máxima (top left) is pictured during a virtual workshop for central banks to address algorithm biases for financial inclusion, which the Special Advocate co-hosted with Center for Financial Inclusion Managing Director Mayada El-Zoghbi (top right). Also pictured are Office of the UNSGSA Director Pia Tayag (bottom left) and Accion President and CEO Michael Schlein. Other attendees are not shown, in accordance with Chatham House Rule.</em>[/caption]

Artificial intelligence (AI)-driven digital financial services hold tremendous potential for financial inclusion. For example, the rapid growth in mobile phone usage and increase in new customer data have resulted in novel methods to deliver financial services by leveraging AI and data — especially in emerging markets and economies.

However, these new innovations can be accompanied with new risks or reinforce previous biases and exclusion issues, with potentially harmful consequences for consumers. This is particularly relevant for vulnerable groups like the poor, women, smallholder farmers, and small businesses.

Attendees used the opportunity to exchange knowledge and learn lessons from the experiences of their counterparts from different institutions and countries on these issues. They were encouraged to examine how to more effectively diagnose problems and identify risks related to AI-driven digital financial services.

Participants also examined how governments could better monitor and mitigate the risks associated with using algorithms for credit and insurance products in their own markets. Further, attendees used the time to consider the role of the private sector in finding solutions and ensuring future innovations are safe and fair for consumers.

The workshop was designed to help participants better understand the risks associated with algorithm biases, as well as to create a research agenda to develop possible strategies and solutions to tackle these problems.

The meeting was conducted under Chatham House Rule. For further reading on the topic, please see CFI’s report, <a href="https://www.centerforfinancialinclusion.org/the-stories-algorithms-tell-bias-and-financial-inclusion-at-the-data-margins">"The Stories Algorithms Tell: Bias and Financial Inclusion at the Data Margins."</a>

UNSGSA and Center for Financial Inclusion Co-Host Virtual Roundtable for Central Banks to Tackle Algorithm Biases in Financial Services

<blockquote> “Our data is stored in servers, so government can make strict rules regarding not hampering privacy of citizens. We need to have trustworthy individuals in charge of managing the servers."</blockquote>
&nbsp;
<blockquote>“I felt scared [when looking at the data Google stores] – it wasn’t just that they were collecting my location, they were collecting a pattern of my locations so they knew where I would be at a certain time.”</blockquote>
These quotes illustrate a subtle but important difference in the approach to digital experiences expressed by men and women. The first comes from Prajit, a 57-year-old Indian man, and reflected a dispassionate policy-oriented viewpoint. The second comes from, Alison, an 18-year-old Asian woman in California. Her sense of personal violation is not unusual. From Ohio to Assam, a shared discourse of fear and invasion in digital experiences runs through many women’s digital worldviews.

Thanks to generous sponsorship from PayPal, we have spent the past several months speaking to a small sample of low- to middle-income men and women in the U.S. and India with the intent to probe themes relating to experience, behavior, and attitudes in the digital world, including digital financial services. These results add to a body of work -- such as work on the exposure of negative bias towards women in the algorithms used by digital lenders (see <a href="https://www.womensworldbanking.org/insights-and-impact/report-algorithmic-bias-financial-inclusion-and-gender-primer-opening-up-new-credit-to-women-in-emerging-economies/" target="_blank" rel="noopener noreferrer">here</a> and <a href="https://centerforfinancialinclusion.org/the-stories-algorithms-tell-bias-and-financial-inclusion-at-the-data-margins/">here</a>) -- about how women’s digital data can work against rather than for them.

Our conversations took place in two parts. In the first interview, we mapped out the digital lives of respondents. Through this mapping, we were able to capture the whole of respondents’ “portfolios” of digital tools and services -- including not only digital financial services, but also social media, e-commerce, communications, and any other digital tool or service that might capture and use customer digital data.

In preparing for the second conversation, we informed respondents about how their most-used providers kept -- and used -- specific data. For example, with users of any Google product, we explained -- and, where possible, showed -- how they could see in Google Takeout the locations they had been, their YouTube videos, their search activity, their email, their contacts, and many other pieces of data. We explained that this data helps to create user profiles that suppliers can then target.

We then had an open-ended conversation about what they knew -- or did not know -- and how they felt about this information. What emerged from these conversations was a bifurcation in digital philosophies, a gendered digital worldview perpetrated by and perpetuated in the specific discourses of these men and women, particularly in discussions of digital exposure.
<blockquote class="pullquote--right">What emerged from these conversations was a bifurcation in digital philosophies, a gendered digital worldview.</blockquote>
Men and women in our sample approached the topic of digital exposure -- the extent to which personal, demographic, and behavioral data is accessible or shared with digital service providers -- in very different ways.

In discussions about digital exposure, men overwhelmingly were philosophical. Their concerns lay in abstracted notions of right and wrong, what should be done, and by whom, and tended toward a generalized, high-level discourse.

For example, Collin, a 23-year-old Kenyan migrant living in New York City, spoke in terms of a moral code on the topic of the sale of personal data:
<blockquote class="blockquote">“[For a company to] share your secrets, it's something that it's not in line with accepted code of conduct.”</blockquote>
<h2>Through a Lens of Fear</h2>
Women, however, were more inclined to frame their exposure on a personal level and usually through a lens of fear. For these women, their concerns parallel the challenges and threats they encounter in their physical lives. They tended not to debate about morality or responsibility, or digital exposure as a society-level concern. Rather, they spoke at length -- and in visceral analogies -- about their safety and invasion of their privacy.

For example, Sonam, a 27-year old Indian woman working in banking, expressed personal fear when discussing real-time location tracking:
<blockquote class="blockquote">“You never know who can follow you from your location data, the thought is quite scary.”</blockquote>
Alisha, a 50-year-old woman from Texas, when informed that her phone or device is recording her, drew on lived experience and spoke of violation:
<blockquote class="blockquote">“It reminds me of when my home was broken into… and he rummaged through my bedroom drawers and that was the part that bothered me the most because he went through my underwear drawer… you went somewhere no one goes.”</blockquote>
Worse, women’s comments suggest they are even less sure how to protect themselves from these personal invasions in the digital world compared to invasions in the physical one. Exposure in their digital lives is a mirror to the risks they face in their physical lives – but they have less information about how they navigate them.

In response to threats, many women find it necessary to curtail their behavior and activities in the physical world to avoid feeling or being violated. While the digital world could -- and should -- be different, where women can take full part in all it has to offer without feeling threatened, the reality is starkly contrary. When it comes to physical safety, women provide advice to each other about how to protect themselves in different contexts – do not walk alone at night if you can avoid it; lock your car doors; if you put your drink down, do not pick it up again. These constraints are frustrating and limiting, but at least they are known.

While <a href="https://www.icrw.org/publications/technology-facilitated-gender-based-violence-what-is-it-and-how-do-we-measure-it/" target="_blank" rel="noopener noreferrer">technology-facilitated gender-based violence</a>, such as cyberbullying and online harassment, has been acknowledged and discussed, the difference here is that these women are not reacting to a stranger harassing them online. This is a sense of violation from a service they need to use to engage in their personal and business lives. The strategies for protecting oneself against this kind of invasion are nebulous at best. Indeed, the threats themselves are often unknown and obscured. And this lack of knowledge is perceived as a violation among the women we interviewed.

Danielle, for example, analogizes this lack of knowledge to date rape:
<blockquote class="blockquote">“If you’re a woman and someone drugs you and rapes you and you wake up and you don’t know that you’ve been drugged and raped. Then you see the video and you realize that this has happened, but before you see the video you did not even know you had been violated. So, I feel there’s some aspect of this that feels off about it — like I’ve been raped, and I don’t even know that I’ve been raped so I feel not only violated but tricked into not knowing.”</blockquote>
Through these conversations, a gendered narrative emerges that belies a split between men's and women’s digital worldviews. Worldviews that influence and determine their digital behaviors and lives. These interviews <a href="https://dalberg.com/our-ideas/privacy-line/" target="_blank" rel="noopener noreferrer">and others</a> suggest a common desire from many women who say they have or would like to curtail their activities on specific digital products because they are concerned about safety. But opting out of digital tools is at an end of a behavioral spectrum. Simply limiting the use of products creates a digital divide of its own.

Governments and digital service providers alike benefit from an increasingly digital population. For example, government-to-person transfer programs in developing countries are increasingly dependent on digital technologies to deliver services and provide an interface to the public. Digital service providers benefit from a large and growing consumer market. However, both governments and private providers bear increased responsibility in meeting expectations of digital safety for these benefits to be realized.

Both will fail if governments and providers do not better understand the nuances of consumer concerns. This is not currently being done. Eliciting concerns about data security and privacy must consider how experiences are gendered if we want to build – and maintain – trust among women.

Going forward, we will seek to further investigate the nature of women’s digital worldviews and their effects on digital behavior, especially in the realm of digital financial services. Specifically, we look to understand specific barriers women face in using digital services, investigate perceptions of the value of these services, and evaluate the design and function of digital services through a gendered lens.

Gender and Digital Worldviews: Divergent User Perspectives On Data Collection and Use

When Goldman Sachs came under fire for offering women lower lines of credit than men on the now <a href="https://www.nytimes.com/2019/11/10/business/Apple-credit-card-investigation.html" target="_blank" rel="noopener noreferrer">infamous Apple Card</a>, they defended the product against charges of sexism by explaining that gender had not been an input to the credit scoring model. If an applicant’s gender was never fed into the algorithm, how did credit decisions end up discriminating against women who had similar credit histories as men?

Gender-blind credit scoring is an example of what many AI bias researchers call “fairness through unawareness,” an approach that intentionally excludes data on sensitive attributes like race, ethnicity, religion, or sex with the goal of reducing discriminatory outcomes. Behind this approach is the idea that eliminating markers of different group identities will prevent basing decisions on those characteristics. This has led to failures in the past, notably <a href="https://cpb-us-e1.wpmucdn.com/sites.suffolk.edu/dist/3/1172/files/2014/01/Rice-Swesnik_Lead.pdf" target="_blank" rel="noopener noreferrer">redlining</a>. Recent research has shown it can also make <a href="https://arxiv.org/abs/2009.06251" target="_blank" rel="noopener noreferrer">discrimination harder to detect and address</a> in the era of algorithmic decisions.
<blockquote class="pullquote--right">“Fairness through unawareness” intentionally excludes data on sensitive attributes like race, ethnicity, religion, or sex with the goal of reducing discriminatory outcomes.</blockquote>
As algorithms <a href="https://www.centerforfinancialinclusion.org/the-stories-algorithms-tell-bias-and-financial-inclusion-at-the-data-margins" target="_blank" rel="noopener noreferrer">transform the financial sector</a>, we need a better understanding of how to mitigate against discriminatory outcomes to ensure that those left out of the digital ecosystem today do not face further financial exclusion. Otherwise, we may not know how many Apple Card equivalents exist in inclusive finance.

This post explores the challenges and tradeoffs of using sensitive attribute data for detecting discrimination in the context of evolving data protection norms and regulations.
<h2>The Perils of Fairness through Unawareness</h2>
The idea may seem counterintuitive: if you remove gender from the data inputs of a credit model, how does the algorithm consistently assign a lower limit to women? The reason is that credit scoring algorithms are crunching larger amounts and new sources of data, which means that the model can inadvertently use proxies for sensitive attribute data in decisions, even if that was not the intention of the model developers. For instance, the <a href="https://journalofbigdata.springeropen.com/articles/10.1186/s40537-019-0180-9" target="_blank" rel="noopener noreferrer">type of phone</a> someone uses or the <a href="https://dl.acm.org/doi/10.1145/2721896.2721908" target="_blank" rel="noopener noreferrer">apps a person installs on their phone</a> can act as proxies for gender, age, or other characteristics.
<blockquote class="pullquote--left">Models can inadvertently use proxies for sensitive attribute data in decisions, even if that was not the intention.</blockquote>
A very simple method for testing algorithmic bias within a credit scoring model requires only a few variables like the actual default rate, the actual score of the individual when approved, and the variable you want to test with your algorithm, such as gender or race.
<h2>Data Tensions: Privacy vs. Anti-Discrimination</h2>
So, why isn’t this done? The answer lies in data limitations, sometimes based on very legitimate concerns about histories of injustice. It illustrates one of the challenges of detecting and monitoring for bias in algorithmic systems without infringing on privacy rights.

Many countries around the world prohibit collecting sensitive data or basing credit decisions on protected categories either under their banking regulations or under new data privacy legislation. In India, lenders are prohibited from discriminating on the <a href="https://www.rbi.org.in/Scripts/PublicationReportDetails.aspx?ID=764" target="_blank" rel="noopener noreferrer">grounds of sex, caste, or religion</a>. In the U.S., the Equal Credit Opportunity Act (ECOA) made it illegal for credit providers to discriminate based on sex, race, national origin, and other protected characteristics in response to widespread denials of credit to women and people of color. ECOA prohibits lenders from collecting this data in the first place, even for the purpose of detecting discrimination, because of fears it will be used improperly to further perpetuate bias in consumer lending. Research in the US shows that discriminatory trends have been <a href="https://arxiv.org/pdf/1912.06171.pdf" target="_blank" rel="noopener noreferrer">hard to detect in consumer lending</a> and that a lack of sensitive attribute data has also created enforcement challenges.

While not all lending regulations prohibit the collection of sensitive data, data privacy legislation introduces new limits on this data. The General Data Protection Regulation (GDPR), which has become the model for legislation in many developing markets, bars certain sensitive data from being collected or processed -- including data on race and ethnic origin, political opinions, philosophical beliefs, sexual orientation, and biometrics -- without individual consent.
<blockquote class="pullquote--right">Concerns about safely and properly using sensitive attribute data are valid given histories of discrimination and surveillance of minority groups in both wealthy and developing countries.</blockquote>
On top of GDPR, the European Commission has recently put forward <a href="https://digital-strategy.ec.europa.eu/en/library/proposal-regulation-laying-down-harmonised-rules-artificial-intelligence" target="_blank" rel="noopener noreferrer">draft legislation to regulate artificial intelligence</a>, with specific provisions for AI systems classified as high risk, which includes credit scoring. The draft legislation suggests that AI providers should process “special categories of personal data” to monitor and correct for bias in the public interest, but does not clarify collection practices or consent processes for such data. Concerns about safely and properly using sensitive attribute data are valid given histories of discrimination and surveillance of minority groups in both wealthy and developing countries. Changes in regulatory frameworks to allow for use of this data to mitigate against further discrimination require public trust bolstered by technical solutions that protect against misuse. Depending on a country’s history or in places experiencing active or simmering conflict, technical solutions may not be enough. For example, in a country like Rwanda where <a href="https://www.nytimes.com/2004/04/09/world/a-decade-after-massacres-rwanda-outlaws-ethnicity.html" target="_blank" rel="noopener noreferrer">ethnic distinctions are banned</a>, the tensions around sensitive identities make it difficult to fathom collecting and using such information, especially by the government.
<h2>Data Ecosystems in Emerging Markets: It’s Complicated</h2>
This tension between privacy and anti-discrimination may be exacerbated in developing markets by the <a href="https://centerforfinancialinclusion.org/rethinking-financial-inclusion-at-the-data-margins/" target="_blank" rel="noopener noreferrer">limited digital footprints</a> of customers at the data margins, as well as paltry knowledge on how data trails and protected groups intersect.

Sex-disaggregated data is still <a href="https://data2x.org/wp-content/uploads/2020/03/MappingGenderDataGaps_Economic.pdf" target="_blank" rel="noopener noreferrer">largely unavailable</a> in the financial sector and for many economic indicators in developing markets. Beyond availability, there is less understanding of how women’s lives and the barriers that shape their economic behaviors are reflected in data used for credit decisions. The reality is that gender, ethnic, or religious identities interact with other indicators (like income, asset accumulation, or technology use) and will impact individuals’ data trails in ways that may misrepresent individuals’ potential and result in disparate outcomes (i.e. access to a financial product). Fairness through unawareness approaches are blind to this intersectionality.
<h2>Where Do We Go From Here?</h2>
As an industry, we can do more to understand the data inputs for digital financial services and how socioeconomic realities present in these datasets, especially for traditionally excluded groups. There will still be tradeoffs between privacy and anti-discrimination, but managing those tradeoffs requires a conversation between providers, regulators, donors, and the public to identify what is possible and explore the right balance.

These conversations can start with the many open questions that exist from a technical perspective. For instance, can <a href="https://ieeexplore.ieee.org/document/8970908" target="_blank" rel="noopener noreferrer">third parties</a> play a role in securely storing sensitive data, or are there options to use <a href="http://proceedings.mlr.press/v80/kilbertus18a/kilbertus18a.pdf" target="_blank" rel="noopener noreferrer">encryption</a> or <a href="https://spectrum.ieee.org/artificial-intelligence/machine-learning/engineering-bias-out-of-ai" target="_blank" rel="noopener noreferrer">synthetic data</a> techniques? Can regulators develop tools that allow them to estimate the demographic characteristics of a dataset, like the <a href="https://www.consumerfinance.gov/data-research/research-reports/using-publicly-available-information-to-proxy-for-unidentified-race-and-ethnicity/" target="_blank" rel="noopener noreferrer">Consumer Financial Protection Bureau has done</a> in the U.S.? Can investors encourage investees to design monitoring and evaluation indicators to help answer questions about how their algorithms perform on inclusion?

While the road ahead may be complex, starting these conversations and bringing the public into them, especially those whose lives will be affected by algorithmic decisions, will be crucial for building trust. We need to engage with emerging research on possible solutions to see what might be appropriate in developing markets. At the very least, financial inclusion stakeholders should know enough to respond to any gender-blind or fairness through unawareness approaches in digital finance with healthy skepticism.
<blockquote>Starting these conversations and bringing the public into them, especially those whose lives will be affected by algorithmic decisions, will be crucial for building trust.</blockquote>

Reducing Bias in Algorithmic Decisions Cannot Rely on “Blind” Approaches

In 2020, CFI and Women’s World Banking began workstreams on algorithmic bias. This conversation between Alex Rizzi (CFI) and Sonja Kelly (Women’s World Banking) builds on recent reports by <a href="https://centerforfinancialinclusion.org/the-stories-algorithms-tell-bias-and-financial-inclusion-at-the-data-margins/" target="_blank" rel="noopener noreferrer">CFI</a> and <a href="https://www.womensworldbanking.org/insights-and-impact/report-algorithmic-bias-financial-inclusion-and-gender-primer-opening-up-new-credit-to-women-in-emerging-economies/" target="_blank" rel="noopener noreferrer">Women’s World Banking</a>. Below are their answers to some important questions about the future of AI and machine learning as they apply to financial inclusion.
<h3>Where are we now in the conversation on algorithmic bias? Is it too late to address this?</h3>
<strong>Alex</strong>: It’s just the right time! While it may feel like global conversations around responsible tech have been going on for years, they haven’t been grounded squarely in our field. For instance, there hasn’t been widespread testing of de-biasing tools in inclusive finance (though Sonja, we’re excited to hear about the results of your upcoming work on that front!) or mechanisms akin to credit guarantees to incentivize digital lenders to expand the pool of applicants their algorithms deem creditworthy. At the same time, there are a bunch of data protection frameworks being passed in emerging markets that are modeled on the European GDPR and give consumers data rights related to automated decisions, for example. These frameworks are very new, and it’s still unclear whether and how they might bring more algorithmic accountability. So it’s absolutely not too late to address this issue.

<strong>Sonja</strong>: I completely agree that now is the time, Alex. Just a few weeks ago we saw a <a href="https://www.federalreserve.gov/newsevents/pressreleases/bcreg20210329a.htm" target="_blank" rel="noopener noreferrer">request for information</a> here in the U.S. for how financial service providers use artificial intelligence and machine learning. It’s clear there is an interest on the policymaking and regulatory side to better understand and address the challenges posed by these technologies, which makes it an ideal time for financial service providers to be proactive about guardrails to keep bias from algorithms. I also think that technology enables us to do much more about the issue of bias -- we can actually turn algorithms around to audit and mitigate bias with very low effort. We now have both the motivation and the tools to be able to address this issue in a big way.
<h3>What are some trends leading us down the wrong path when it comes to algorithmic bias?</h3>
<strong>Sonja</strong>: At the risk of being too broad, I think the biggest trend is lack of awareness. Like I said before, fixing algorithmic bias doesn’t have to be hard, but it does require everyone -- at all levels and within all responsibilities -- to understand and track progress on mitigating bias. The biggest red flag I saw in our interviews contributing to our report was when an executive said that bias isn’t an issue in their organization. My co-author Mehrdad Mirpourian and I found that bias is always an issue. It emerges from biased or unbalanced data, the code of the algorithm itself, or the final decision on who gets credit and who does not. No company can meet all definitions of fairness for all groups simultaneously. Admitting the possibility of bias costs nothing, and fixing it is not that difficult. Somehow it slips off the agenda, and that is very discouraging to me.
<blockquote class="pullquote--left">Bias is always an issue</blockquote>
<strong>Alex</strong>: One of the concepts we’ve been thinking a lot about is the idea of how digital data trails may reflect or further encode existing societal inequities. For instance, we know that women are <a href="https://www.gsma.com/r/gender-gap/" target="_blank" rel="noopener noreferrer">less likely to own phones than men</a> and less likely to use mobile internet or certain apps; these differences create disparate data trails, and might not tell a provider the full story about a woman’s economic potential. And what about the <a href="https://centerforfinancialinclusion.org/rethinking-financial-inclusion-at-the-data-margins/" target="_blank" rel="noopener noreferrer">myriad of other marginalized groups</a>, whose disparate data trails are not clearly articulated?
<h3>Who else needs to be here in this conversation as we move forward?</h3>
<strong>Alex</strong>: For my colleague Alex Kessler and me, a huge takeaway from the exploratory work was that there are plenty of entry points to these conversations for non-data scientists, and it’s crucial for a range of voices to be at the table. We originally had this notion that we needed to be fluent in the code-creation and machine learning models to contribute, but the conversations should be interdisciplinary and should reflect a strong understanding of the contexts in which these algorithms are deployed.
<blockquote class="pullquote--right">There are plenty of entry points to these conversations for non-data scientists.</blockquote>
<strong>Sonja</strong>: I love that. It’s exactly right. I would also like to see more media attention on this issue. We know from other industries that we can increase innovation by peer learning. If sharing both the promise and pitfalls of AI and machine learning becomes normal, we can learn from it. Media attention would help us get there.
<h3>What are the immediate next steps here? What are you focused on changing tomorrow?</h3>
<strong>Sonja</strong>: When I share our report with external audiences, I first hear shock and concern about the very idea of using machines to make predictions about people’s repayment behavior. But our technology-enabled future doesn’t have to look like a dystopian sci-fi novel. Technology can increase financial inclusion when deployed well. Our next step should be to start piloting and proof-testing approaches to mitigating algorithmic bias. Women’s World Banking is doing this over the next couple of years in <a href="https://www.womensworldbanking.org/insights-and-impact/awardees-announced-as-part-of-data-org-inclusive-growth-and-recovery-challenge/" target="_blank" rel="noopener noreferrer">partnership with the University of Zurich and data.org</a> with a number of our network members, and we’ll share our insights as we go along. Assembling some basic resources and proving what works will get us closer to fairness.
<blockquote class="pullquote--left">Our technology-enabled future doesn’t have to look like a dystopian sci-fi novel.</blockquote>
<strong>Alex</strong>: These are early days. We don’t expect there to be universal alignment on de-biasing tools anytime soon, or best practices available on how to enforce data protection frameworks in emerging markets. Right now, it’s important to simply get this issue on the radar of those who are in a position to influence and engage with providers, regulators, and investors. Only with that awareness can we start to advance good practice, peer exchange, and capacity building.

<em>Follow CFI (<a href="https://centerforfinancialinclusion.us5.list-manage.com/subscribe/post?u=394352ae963270aef6c51680d&amp;id=9df382106a">newsletter</a>, <a href="https://www.linkedin.com/showcase/center-for-financial-inclusion-at-accion" target="_blank" rel="noopener noreferrer">LinkedIn</a>, and <a href="https://twitter.com/CFI_Accion" target="_blank" rel="noopener noreferrer">Twitter</a>) and Women’s World Banking over the coming months to stay up-to-date on algorithm bias and financial inclusion.</em>

Help Wanted: A Global Push Toward Algorithmic Fairness

Headlines late last year breathlessly chronicled the <a href="https://www.theguardian.com/business/2021/jan/23/the-strange-case-of-alibabas-jack-ma-and-his-three-month-vanishing-act" target="_blank" rel="noopener noreferrer">whereabouts</a> of former Alibaba CEO Jack Ma and tensions between Ma and the Chinese government. The missing billionaire, the last-minute <a href="https://www.nytimes.com/2020/11/06/technology/china-ant-group-ipo.html" target="_blank" rel="noopener noreferrer">cancellation of a history-making IPO</a>, and the <a href="https://entrepreneurshandbook.co/the-speech-that-cost-jack-ma-37-billion-dollars-5ad42393c9ba" target="_blank" rel="noopener noreferrer">speech</a> that apparently started this tailspin of events captured the attention of the world. But beyond the headlines, this story is part of a larger signal that China is sending to big tech: put on your helmets, because we are getting off the sidelines.
<blockquote class="pullquote--left">China to big tech: put on your helmets, because we are getting off the sidelines.</blockquote>
In the last four months, China has published a slew of regulations (some still in draft form) aimed at big tech and their outsized role in the economy. This includes the draft <a href="https://www.natlawreview.com/article/china-releases-draft-personal-information-protection-law" target="_blank" rel="noopener noreferrer">Personal Information Protection Law</a> (PIPL), new rules including capital requirements and caps for online lenders, as well as draft anti-trust rules for digital platforms. And, dramatically, China called off Ant Group’s globally anticipated IPO in November, in December launched an anti-trust probe into Ant’s ecommerce parent Alibaba, and in February 2021 told Ant to restructure itself into a financial holding company.

The scale of big tech’s reach into China’s financial sector is worth reiterating. A billion <a href="https://www.cgap.org/research/publication/china-digital-payments-revolution" target="_blank" rel="noopener noreferrer">Chinese consumers</a> use Alipay, owned by Ant, to pay for everything from groceries (<a href="https://progressivegrocer.com/major-asian-supermarket-chain-adopts-alipay-mobile-wallet" target="_blank" rel="noopener noreferrer">even in the U.S.</a>) and utilities, to school tuition and traffic tickets. Alipay, and its competitor WeChat Pay (owned by TenCent), have deftly created business models that leverage increasing use of smartphones, allow for easy funding of digital wallets through linked bank accounts, and coax users into their digital ecosystem through low transaction fees and an ever-increasing array of services. Cross-selling through this ecosystem can be lucrative. For instance, Alibaba’s product Yu’E Bao rapidly became the largest money market fund in the world for a time.

More recently, Ant has received attention for facilitating hundreds of millions of online loans to consumers, many of whom could not qualify for bank-issued credit cards. Despite the mammoth amount of outstanding debt, Ant has taken on limited risk and acted as more of a facilitator than a lender. For instance, at the end of June 2020, Ant had approximately $267 billion in outstanding consumer debt, but just 2 percent of that amount was funded by Ant.

Whose portfolios are on the hook? Ant has partnered with more than 100 commercial lenders and regional banks, collecting fees on interest income from them, and utilized colossal troves of transactional Alipay data to facilitate underwriting. This frenzy of unsecured lending has raised concerns around the concentration of risk that sits with lenders and not facilitating platforms.
<blockquote class="blockquote">Ant has utilized colossal troves of transactional Alipay data to facilitate underwriting.</blockquote>
<h2>New Rules of the Road</h2>
New regulation from China’s Banking and Insurance Regulatory Commission clamps down on both sides of the online lending partnerships. For the lenders, regional banks are no longer permitted to lend outside their geographies, and there will be new caps on how much of a bank’s capital and portfolio can be lent online. And for the platforms, starting in 2022, they will have to fund <a href="https://www.reuters.com/article/us-internet-loans-china-banks/china-regulator-finalizes-guidelines-on-banks-internet-loan-businesses-idUSKBN2AK0F2" target="_blank" rel="noopener noreferrer">at least 30 percent</a> of every loan they make in concert with banks. These measures may take some needed steam out of the ballooning online lending market.

Digital platforms are also the subject of new draft <a href="https://www.reuters.com/article/us-china-internet-anti-monopoly/china-issues-new-anti-monopoly-rules-targeting-its-tech-giants-idUSKBN2A70DT" target="_blank" rel="noopener noreferrer">anti-monopoly rules</a> by the State Administration for Market Regulation, which targets practices such as the use of data and algorithms to offer different prices to different consumers, as well as self-dealing through elevating their in-house products compared to competitors who are selling on their platform. As they take comments on proposed revisions, antitrust authorities have increased the number of investigations and in recent months fined Alibaba, Tencent Holdings as well as smaller platforms like Pinduoduo and Meituan.

The PIPL, when approved, will be the country’s first comprehensive data protection regime applicable to all data processors, including big tech. The draft PIPL contains <a href="https://www.dataguidance.com/opinion/china-draft-pipl-and-gdpr-comparative-perspective" target="_blank" rel="noopener noreferrer">some similarities to the European GDPR</a>, including provisions for the legal basis for processing data and enumerating data rights for consumers such as the right to rectify data mistakes. PIPL diverges from GDPR in terms of a larger focus on data localization, however.

Taken in aggregate, the package of emerging regulations demonstrates resolve among Chinese authorities to get tougher in the face of the enormous market power of big tech, which during the pandemic only embedded itself further into daily life.

However, beyond the heavyweight bouts between big tech and political authorities and implications for the companies, it is important to monitor how consumers are impacted by the new rules. Hopefully, consumers will benefit from more responsible online lending practices, fewer scams and predatory pricing, and more communication around the use of their data. As one Chinese internet regulator stated, consumers should not be “<a href="https://www.wsj.com/articles/chinas-regulators-prepare-to-roll-out-new-antimonopoly-rules-11605013205" target="_blank" rel="noopener noreferrer">prisoners to algorithms</a>.” We’ll be closely watching the market to understand how fintechs and consumers are responding and to understand what lessons other markets might draw from the Chinese approach to checking the power of big tech.

In the meantime,  read our recent publication, <a href="https://centerforfinancialinclusion.org/the-stories-algorithms-tell-bias-and-financial-inclusion-at-the-data-margins/" target="_blank" rel="noopener noreferrer"><em>The Stories Algorithms Tell: Bias and Financial Inclusion at the Data Margins</em></a>, about how FSPs are using algorithmic data to make credit decisions, how those affect low-income consumers globally, and what regulators can and should do.

Regulatory Headwinds on the Horizon for Chinese Fintechs: Where Do Consumers Fit In?

Across all industries, predictive, data-driven algorithms -- mathematical recipes ranging from the simple to the complex -- are being used to tell stories about individuals and can drive high-stakes decisions: who receives a loan, what sentencing a judge will recommend, what therapeutics a doctor will provide.

In the financial services industry, the exploding data ecosystem has created billions of new stories. At the Center for Financial Inclusion (CFI), we are most interested in the ones they try to tell (or don’t tell) about low-income consumers.

This publication has two main objectives:
<ul>
 	<li>to ground some universal challenges on the use of algorithms, automated decisions, alternative data, and bias in the context of inclusive financial services</li>
 	<li>to present the current state of play among inclusive finance actors from desk research and interviews with a sample of fintechs, regulators, and other experts.</li>
</ul>
Our insights are aimed primarily at financial inclusion stakeholders who can influence the trajectory of the inclusive finance industry, with specific recommendations for regulators, investors, and donors. But anyone with an interest in algorithmic decision making or financial inclusion will find this publication thought provoking and useful.

The full publication is divided into the following sections:
<ul>
 	<li>The <strong>introduction</strong> explores algorithms and bias in inclusive finance, presents a framework for understanding algorithmic bias, and delves into what we want to know about algorithms, bias, and financial inclusion.</li>
 	<li>Section 1 is about <strong>data trails in the digital economy</strong>.</li>
 	<li>Section 2 digs into the <strong>risks of bias and emerging tools</strong> through the three categories: inputs, code, and context.</li>
 	<li>Section 3 lays out <strong>recommendations for inclusive finance stakeholders</strong> to advance evidence, solutions, and incentives for responsible algorithms.</li>
</ul>

The Stories Algorithms Tell: Bias and Financial Inclusion at the Data Margins

In emerging economies, the growth of mobile phone use has contributed to an explosion of data that can be fed into algorithms to make predictions about individuals, including who is creditworthy, and offer financial products and services. As of 2020, <a href="https://www.gsma.com/r/wp-content/uploads/2020/09/GSMA-State-of-Mobile-Internet-Connectivity-Report-2020.pdf" target="_blank" rel="noopener noreferrer">half of the world’s population used mobile internet</a> and digital finance offerings have grown in tandem, often framed as engines of financial inclusion. The massive growth in available data and companies to serve customers that had previously been invisible to the financial system might suggest that the problem of thin-file customers has been solved and long-standing financial inclusion gaps are closing.

But the truth is, we don’t know what the impact is yet.

So amidst the rush to generate and leverage new data trails, CFI is embarking on a learning agenda around financial inclusion at the data margins. In pursuit of that, we are rethinking assumptions, and learning from broader tech-oriented conversations about the intersection of alternative data, algorithms and digital profiling, and how these more technical issues interact with socio-economic and gender-oriented issues surrounding digital literacy, financial capabilities, and social norms.
<h2>What Does it Mean to Lend to a Phone Line?</h2>
In the context of financial inclusion, making people visible to the financial market nowadays increasingly means having a digital financial identity based on volumes of (mobile) data that’s both related and unrelated to the actual financial behaviors of an individual. The expansion of digital lending, for example, utilizes non-traditional mobile data such as SMS, device usage and model information, social network activity, contact lists, call logs, app use, location data, and more to construct a picture of an individual’s cash flow or income.

Some of these sources are intuitively linked to financial activity, such as SMS receipts for mobile wallet transactions. Other data -- referred to by some as <a href="https://www.upturn.org/static/files/Knowing_the_Score_Oct_2014_v1_1.pdf" target="_blank" rel="noopener noreferrer">“fringe” alternative data</a> -- like social media activity, is further removed and its value as a fair and accurate predictor of creditworthiness is less established.

Given that data-driven models leverage phone-specific variables, the limits on women’s phone use or migrants’ access to a SIM card will change the data trail they leave and, in turn, the decision that an algorithm may make about their access to a loan.
<blockquote class="pullquote--right">The limits on women’s phone use or migrants’ access to a SIM card may change the decision an algorithm makes about their access to a loan.</blockquote>
In developing economies, women are less likely to own a phone and <a href="https://www.gsma.com/mobilefordevelopment/wp-content/uploads/2020/05/GSMA-The-Mobile-Gender-Gap-Report-2020.pdf" target="_blank" rel="noopener noreferrer">access mobile internet</a>. Phone-sharing commonly acts as a barrier to phone ownership for women as well as other vulnerable groups like migrants or refugees. It’s prevalent due to cost constraints or gaps in identity documents required for registering a SIM card. What does it mean when an algorithm is facilitating lending to a phone line, rather than an individual? What are the implications of this and other extant barriers in determining how inclusive these new tools are?
<h2>Risks of Data Marginalization: Where to Begin?</h2>
In the U.S. and Europe, risks and evidence of data marginalization have prompted calls for greater oversight, but little research has documented what these risks look like in the data environments of developing markets. There is much that we need to learn:
<ul>
 	<li>How large is the risk of cementing exclusion in a data-driven financial system for consumers at the data margins?</li>
 	<li>What strategies and tools are available to companies, investors, and regulators to address these risks, and what resources and skills do they require to be effective?</li>
 	<li>What are the incentives for private sector companies to act on this risk?</li>
 	<li>Globally, we see strides made on data privacy and emerging digital rights, but how will people with limited digital capability be able to meet these new rights and responsibilities?</li>
</ul>
CFI and others, like our friends at <a href="https://www.womensworldbanking.org/insights-and-impact/report-algorithmic-bias-financial-inclusion-and-gender-primer-opening-up-new-credit-to-women-in-emerging-economies/" target="_blank" rel="noopener noreferrer">Women’s World Banking</a>, are beginning to address these questions and establish a learning agenda for the sector.

It is critical we set out on a path for answers now in this period of global data ecosystem transformation. As a fintech from Southeast Asia explained, “You can’t make those [anti-bias] changes when you’re doing a million loans a day… a little bit of a loss now and a gain later is better than taking a loss at that scale.”

Let this remark serve as a wake-up call for all development stakeholders that are building data solutions today not to lose sight of the people behind the mobile phones and to examine how technology and data can help us build an inclusive tomorrow.

This topic is one of CFI’s strategic pillars, so consider this the first mile of a learning journey that will take all of us to a better understanding of data risks and opportunities as they relate to financial inclusion. Stay tuned to this space, sign up for <a href="https://centerforfinancialinclusion.us5.list-manage.com/subscribe/post?u=394352ae963270aef6c51680d&amp;id=9df382106a" target="_blank" rel="noopener noreferrer">CFI email updates</a>, and follow us on social media for coming explorations of data risks and opportunities and how they affect low-income consumers.

Rethinking Financial Inclusion at the Data Margins

Perhaps more than ever, 2020 provided us an opportunity to reflect on that for which we are thankful. One thing we’re thankful for at CFI is our <a href="https://centerforfinancialinclusion.org/blog/" target="_blank" rel="noopener noreferrer">blog</a>, a place where CFI and our community of contributors share their unique perspectives and calls to action for inclusive finance. The 76 posts of 2020 offer incredible insights into a wide range of themes and projects across many geographies.

Not surprisingly, since late March, nearly every CFI post has covered or mentioned COVID-19 in some form or fashion. But the top 10 posts (by unique page views) also dove into topics such as data and consumer protection -- pillars of CFI’s <a href="https://centerforfinancialinclusion.org/reflecting-on-the-past-and-charting-a-new-direction/" target="_blank" rel="noopener noreferrer">new strategy</a> -- over-indebtedness in Kenya, internal migration, women’s financial inclusion (another key, cross-cutting CFI strategic focus area), a deep dive into resilience, and even how comics were used to spread COVID-19 awareness.

Happy reading, and happy new year!
<h2>1. <a href="https://centerforfinancialinclusion.org/pandemics-and-natural-disasters-what-can-we-learn-from-past-disasters-to-help-with-todays-pandemic/" target="_blank" rel="noopener noreferrer">Pandemics and Natural Disasters: What Can We Learn from Past Disasters to Help with Today’s Pandemic?</a></h2>
Two weeks after the WHO declared the COVID-19 outbreak a pandemic, Managing Director <a href="https://centerforfinancialinclusion.org/people/mayada-el-zoghbi/" target="_blank" rel="noopener noreferrer">Mayada El-Zoghbi</a> wrote about how this crisis compares to previous ones: namely, the Indonesian tsunami of 2004 and the Pakistan earthquake of 2013. She pointed out that households experience shocks similarly, regardless of the cause, and that the systemic nature of the shocks means that the firms and FSPs that serve them need to measure and implement the right responses to meet the challenge. She also predicted that the pandemic would be a “tipping point” for platform financial service provision.
<h2>2. <a href="https://centerforfinancialinclusion.org/what-is-the-future-of-microfinance-q-and-a-with-paul-dileo/" target="_blank" rel="noopener noreferrer">What Is the Future of Microfinance? Q and A with Paul DiLeo</a></h2>
This year was a tipping point for microfinance, too, noted <a href="https://centerforfinancialinclusion.org/people/paul-dileo/" target="_blank" rel="noopener noreferrer">Paul DiLeo</a> in this interview with CFI. DiLeo is the Managing Director of Grassroots Capital Management and a veteran faculty member of CFI <a href="https://centerforfinancialinclusion.org/board-leadership-for-impact-program-overview/" target="_blank" rel="noopener noreferrer">board governance training</a>. He is also coeditor of a recently published volume, “The Future of Microfinance.” DiLeo suggested that investors in this space resist the temptation to move on to the next “bright, shiny object” in financial inclusion and continue to support microfinance to preserve social missions and benefit target populations.
<h2>3. <a href="https://centerforfinancialinclusion.org/resilience-and-the-three-phases-of-response-brac/" target="_blank" rel="noopener noreferrer">Resilience and the Three Phases of Response</a></h2>
In May, BRAC’s microfinance director <a href="https://centerforfinancialinclusion.org/people/shameran-abed/" target="_blank" rel="noopener noreferrer">Shameran Abed</a> and <a href="https://centerforfinancialinclusion.org/people/laurie-j-spengler/" target="_blank" rel="noopener noreferrer">Laurie J. Spengler</a>, the CEO of Courageous Capital Advisors, wrote that resilience is the “connective tissue” between the three phases of response: relief, recovery and rebuild. The authors advocate for assessing resilience through two lenses, opportunity and risk, and point out that the pandemic is an opportunity to invest in resilience because “recurring dividends will be realized by all.”
<h2>4. <a href="https://centerforfinancialinclusion.org/data-globalization-vs-data-localization/" target="_blank" rel="noopener noreferrer">Data Globalization vs. Data Localization</a></h2>
Before the pandemic hit, CFI’s <a href="https://centerforfinancialinclusion.org/people/ethan-loufield/" target="_blank" rel="noopener noreferrer">Ethan Loufield</a> and Credit Suisse’s <a href="https://centerforfinancialinclusion.org/people/shweta-vashisht/" target="_blank" rel="noopener noreferrer">Shweta Vashisht</a> wrote about how the flow of data across borders is a contentious issue countries encounter when developing data protection laws and regulations. They present arguments for data localization, but ultimately conclude that data can, and should, be allowed to flow across borders with the right frameworks in place.
<h2>5. <a href="https://centerforfinancialinclusion.org/data-consent-lets-share-the-burden-for-effective-consumer-protection/" target="_blank" rel="noopener noreferrer">Data Consent: Let’s Share the Burden for Effective Consumer Protection</a></h2>
Also part of the <a href="https://centerforfinancialinclusion.org/data-protection-and-financial-inclusion-why-it-matters-introduction/" target="_blank" rel="noopener noreferrer">Data Protection and Financial Inclusion: Why It Matters</a> series, this post argues that it’s futile for small tech to keep up with high-standard consent practices, and that the path from data consent principles to implementation is, for low-capacity environments, “littered with landmines.” Vashisht and Loufield conclude that successful solutions need to be shouldered by both consumers and providers.
<h2>6. <a href="https://centerforfinancialinclusion.org/q-and-a-using-comics-for-covid-19-awareness/" target="_blank" rel="noopener noreferrer">Q and A: Using Comics for COVID-19 Awareness</a></h2>
<a href="https://centerforfinancialinclusion.org/people/graham-a-n-wright/" target="_blank" rel="noopener noreferrer">Graham A.N. Wright</a>, founder of MSC, sat down with CFI to discuss a series of informative comics his team produced to get the word out about the dangers of COVID. The colorful comics, complete with protagonists warning clients about the hazards of the virus and how they can help knock it out, informed how real-life group meetings and staff visits have been conducted.
<h2>7. <a href="https://centerforfinancialinclusion.org/support-for-indias-migrants-during-covid-19-navigating-potential-gaps-in-the-system/" target="_blank" rel="noopener noreferrer">Support for India’s Migrants During COVID-19: Navigating Potential Gaps in the System</a></h2>
The lockdown in India had massive impacts, perhaps for none more than internal migrant workers, who left for home villages in droves when work dried up. This post warned that system-wide social payments challenges boded poorly for these vulnerable workers due to, among other reasons, ATM access constraints and domicile restrictions of state governments. The post was authored by <a href="https://centerforfinancialinclusion.org/people/shashank-shreedharan/" target="_blank" rel="noopener noreferrer">Shashank Shreedharan</a> and <a href="https://centerforfinancialinclusion.org/people/jithin-jose/" target="_blank" rel="noopener noreferrer">Jithin Jose</a> of LEAD.
<h2>8. <a href="https://centerforfinancialinclusion.org/its-time-to-protect-kenyans-from-a-digital-lending-laboratory/" target="_blank" rel="noopener noreferrer">It’s Time to Protect Kenyans from a Digital Lending Laboratory</a></h2>
CFI’s <a href="https://centerforfinancialinclusion.org/people/alex-kessler/" target="_blank" rel="noopener noreferrer">Alex Kessler</a> warns readers that the breakneck growth in mobile lending and aggressive debt collection and debt stress have raised enormous consumer protection red flags. This article offers key statistics on mobile money’s exponential growth there, highlights the need for consumer protection-oriented algorithms, and suggests calls to action for regulators.
<h2>9. <a href="https://centerforfinancialinclusion.org/reimagining-inclusive-finance-with-women-in-mind/" target="_blank" rel="noopener noreferrer">Reimagining Inclusive Finance With Women In Mind</a></h2>
In this <a href="https://centerforfinancialinclusion.org/about/what-we-do/financial-inclusion-week/" target="_blank" rel="noopener noreferrer">Financial Inclusion Week</a> post, we meet Carla, a fictitious -- but very realistic -- mother of three young children living in a village in Tanzania. Carla’s story is like that of millions of poor women in the Global South who are excluded from financial products that weren’t designed for them. CFI gender lead <a href="https://centerforfinancialinclusion.org/people/julia-arnold/" target="_blank" rel="noopener noreferrer">Julia Arnold</a> asks our community if we are listening to women enough, and implores our sector to design and deliver financial products and services with the Carlas of the world in mind. She also provides early thinking around CFI’s gender work in 2021 and beyond.
<h2>10. <a href="https://centerforfinancialinclusion.org/can-financial-inclusion-moderate-impacts-to-coronavirus/" target="_blank" rel="noopener noreferrer">Can Financial Inclusion Moderate Impacts of Coronavirus?</a></h2>
It’s fitting that we round out the 2020 list with our very first COVID response post, written by research lead <a href="https://centerforfinancialinclusion.org/people/eric-noggle/" target="_blank" rel="noopener noreferrer">Eric Noggle</a> and published on March 20. While alarm bells in the media had sounded long before, this was one of the early posts in the inclusive finance space that offered a clear call to action for this “major stress test,” namely, getting as much money as possible into the hands of those who need it most -- and doing so as quickly as possible. How did governments of the world do? Read our December <a href="https://centerforfinancialinclusion.org/rapid-response-for-social-payments-during-covid-19/" target="_blank" rel="noopener noreferrer">policy brief</a> for examples of many governments that innovated quickly to get social payments into the literal and digital hands of citizens.
<h3>We hope you continue to read and share views from our blog in 2021. For a sneak peek into the kind of content you'll see, revisit these Financial Inclusion Week posts (plus #9) related to our top priorities for inclusive finance:</h3>
<h3>• “<a href="https://centerforfinancialinclusion.org/financial-services-are-needed-to-help-low-income-people-mitigate-and-adapt-to-climate-change/" target="_blank" rel="noopener noreferrer">Financial Services are Needed to Help Low-Income People Mitigate and Adapt to Climate Change</a>” By Eric Noggle
• “<a href="https://centerforfinancialinclusion.org/covid-19-ushers-in-new-challenges-for-consumer-protection/" target="_blank" rel="noopener noreferrer">COVID-19 Ushers in New Challenges for Consumer Protection</a>” By Lauren Braniff
• “<a href="https://centerforfinancialinclusion.org/data-for-inclusive-finance-delivering-on-the-promise-for-consumers/" target="_blank" rel="noopener noreferrer">Data for Inclusive Finance: Delivering on the Promise for Consumers</a>” By Alexandra Rizzi and Alex Kessler</h3>

Daryl  Collins

Derry Moore

Alex Kessler

Jacobo Menajovsky

Alexandra (Alex) Rizzi

Sonja Kelly

Ezra Mannix

Chrissy Martin Meier

Simon Agez

Matthew  Barger

Simone di Castri

Mayada El-Zoghbi

Eric Noggle

Madeleine Longwell

Maha Khan

Carrie Ruh

China

East Asia and Pacific

Nigeria

Sub-Saharan Africa

Indonesia

Alternative Data

Credit

Data Analytics

Delivery Channels

Digital Financial Services

Financial Service Providers

Financial Technology

Fintechs

Insurance

Payments

Remittances

Blockchain and Cryptocurrency

Challenges and Crises

Enabling Environment

Human Centered Design

Consumer Protection

Appropriate Product Design and Delivery

Underserved Groups

Women

Credit Provision

Digital Credit

Policy, Regulation and Government Initiatives

Privacy

Responsible Digital Finance

Underwriting

Partnerships

Trends

Mobile Banking

Pensions and Retirement Saving

Saving

Financial Inclusion Strategy

Entrepreneurs of MSMEs

Resilience

Financial Health

MSME/SME Finance

Equity Investing

Impact Investing

Valuation

Report

Announcement

Blog Post

Brief

China’s economy has experienced tremendous growth in recent years, with a booming micro, small, and medium enterprise (MSME) market. There are over 50 million MSMEs in China that collectively account for over 60% of China’s GDP and over 50% of the government’s tax income. These businesses create 80% of total employment in China’s urban areas.

Despite China’s overall economic growth, the need to foster full financial inclusion is still imperative. In 2010, 38 million MSMEs lacked access to formal financial services, forcing them to borrow informally from friends, family, and moneylenders.

COVID-19 has reinforced the importance of financial services in helping people navigate the effects of the pandemic and lay the foundations for recovery. The rapidly changing context presents a unique opportunity for fintechs and other digitally driven business models to step in and onboard new customers to meet this evolving demand.

The 2020 iteration of the Inclusive Fintech 50 competition maintained the core value proposition of the 2019 initiative — a transparent methodology, independent judging panels comprised of industry experts, and a strong focus on inclusion — while iterating to ensure relevance in a particularly challenging year. The 2020 competition attracted 403 qualified applicants operating in 111 countries and reaching 116 million customers.

Drawing on the data submitted by the 2020 cohort of applicants, this paper provides insights as to how early-stage fintechs are adapting to the current economic uncertainty and continuing to advance financial inclusion and resilience for the estimated 3 billion financially underserved people worldwide.

Follow CFI and #InclusiveFintech50 for updates on Inclusive Fintech 50. For more information about the competition, insights from previous cohorts, and more, visit <a href="http://www.inclusivefintech50.com">InclusiveFintech50.com</a>.

Inclusive Fintech 50 White Paper [2020]

The four largest tech companies reported more than <a href="https://www.nytimes.com/2020/07/30/technology/tech-company-earnings-amazon-apple-facebook-google.html" target="_blank" rel="noopener noreferrer">$28 billion in profits</a> in the second quarter of 2020. In the last 5 years, revenues of the world's largest tech companies have grown by <a href="https://www.mbres.it/it/publications/report-websoft" target="_blank" rel="noopener noreferrer">118 percent</a> versus only 10 percent by traditional manufacturing. Data is their “<a href="https://www.bernstein.com/Bernstein/EN_US/Research/Publications/Instrumentation/BigDatasHolyGrail.pdf" target="_blank" rel="noopener noreferrer">holy grail</a>,” (consumer personal data generates more than <a href="https://www.barrons.com/articles/why-google-and-facebook-could-dominate-big-data-51602622199" target="_blank" rel="noopener noreferrer">$50 billion in annual revenue</a> just in data broker and marketing data services) to the point that we could actually call those companies -- Apple, Facebook, Alibaba, Amazon, and others -- “digital multinationals.”

As these digital multinationals move into the lucrative and data-rich finance business, the authorities mandated to supervise the financial market -- to preserve the resilience of the financial sector, foster competition, and protect users -- are ill-equipped to oversee them.
<blockquote>The authorities mandated to supervise the financial market are ill-equipped to oversee digital multinationals.</blockquote>
This is an issue because the digital multinationals that increasingly shape our economies and societies, often in a legislation and oversight vacuum, have sought conquest of the financial system and its large -- and largely profitable -- data swathes. Alphabet (Google), Alibaba, Amazon, Apple, Facebook, and Tencent offer financial services, either wallets associated with their main products, or as standalone products.
<h2>Examples of Digital Multinationals’ Big Moves Into Financial Services</h2>
Tencent, for example, has two integrated payment platforms, Tenpay and WeChat Pay (also known as WePay) that are often referred to as a single payments platform and control <a href="https://www.forbes.com/sites/ywang/2018/03/28/is-alipay-losing-to-wechat-in-chinas-trillion-dollar-payment-war/#4662fc418822" target="_blank" rel="noopener noreferrer">40 percent of the mobile payments market</a> in China, making it the second-largest payments platform after Alibaba’s Alipay. Tencent integrates WeChat Pay into its growing ecosystem of WeChat mini programs and online-to-offline services, which offer food deliveries, online shopping, ride hailing, and other services to the messaging platform's 1.06 billion monthly active users. Alibaba's affiliate, Ant Financial, integrates Alipay into Alibaba’s Taobao and Tmall marketplaces. Both Tencent and Ant Financial are increasingly investing in, or partnering with, retailers that offer special discounts to WeChat Pay or Alipay users, and also offer microloans and wealth management products.

Facebook, the world’s leading social media network outside China, has started to roll out Facebook Pay to 2 billion WhatsApp users. In August, the Central Bank of Brazil first authorized, <a href="https://www.bloomberg.com/amp/news/articles/2020-06-23/brazil-s-central-bank-suspends-whatsapp-payments" target="_blank" rel="noopener noreferrer">and then stopped</a>, Facebook from providing payment services to <a href="https://venturebeat.com/2020/06/15/facebook-brings-payments-to-whatsapp-starting-in-brazil/" target="_blank" rel="noopener noreferrer">120 million WhatsApp users</a> in Latin America’s largest market. The bank said it had reversed its original decision to ensure competition in the payment system market, allowing the regulator more time to evaluate potential risks to the country’s payment infrastructure, and to work out whether WhatsApp is compliant with regulation. The WhatsApp payment service was also tested in <a href="https://www.techradar.com/in/news/whatsapp-pay-roll-out-will-be-further-delayed-heres-why" target="_blank" rel="noopener noreferrer">India</a> and Mexico.

Google, which has been in payments since Google Checkout’s launch in 2006, offers retail, peer-to-peer (P2P) and bill payments with Google Pay, and has partnered with eight banks to integrate digital banking. While U.S. adoption has been slow, in India -- where a whopping 98 percent of smartphones run on Android -- Google Pay has enjoyed stupendous growth, with 67 million active users as of September 2019 and $110 billion in annualized payments volume. Importantly, Google has focused on payments to boost engagement and capture data, not to reap fees -- although it takes a <a href="https://www.mobiloud.com/help/knowledge-base/what-are-apple-and-googles-fees-and-revenue-share-percentage-on-in-app-purchases-and-subscriptions" target="_blank" rel="noopener noreferrer">30 percent margin</a> on all sales within the Google Play app store.

Finally, Apple, the world’s most valuable company, uses Apple Pay to enhance the iOS platform and capture a greater share of its customers. It also takes a juicy fee on payments made in its app store.
<h2>A Capabilities Gap That’s Miles Wide</h2>
The analytical and technical capabilities of these firms far exceed those of the authorities charged with regulating them. The firms are using artificial intelligence and cloud computing to exploit the data of their users through surveillance capitalism and data mining. This is done exclusively to increase shareholders' value. Meanwhile, central banks and other agencies, which are already barely equipped for the oversight of the more traditional financial sector, are now being charged with overseeing products of digital multinationals they are not familiar with. Most supervisors rely on outdated tools such as Excel, and the uptake of new supervisory technologies is still slow. We witness astonishing delays in data validation and a scarcity of insights generated to conduct risk-based supervision and contain fraud. The roll out of reliable predictive models is also unavailable to most financial authorities. Benoît Cœuré, the new head of the Bank for International Settlements (BIS) Innovation Hub has highlighted the risks, challenges, and opportunities for financial authorities in a recent <a href="https://www.bis.org/speeches/sp200819.pdf" target="_blank" rel="noopener noreferrer">speech</a>, a call to action for the digital transformation of the public authorities that administer the financial sector.
<blockquote>We witness astonishing delays in data validation and a scarcity of insights generated to conduct risk-based supervision and contain fraud.</blockquote>
In the “<a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3595344." target="_blank" rel="noopener noreferrer">data stack</a>” paper that I co-authored with Arend Kulenkampff and Matt Grasser before the pandemic, and in the 2018 <a href="http://www.r2accelerator.org" target="_blank" rel="noopener noreferrer">RegTech for Regulators Accelerator</a> (R2A) <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3249283" target="_blank" rel="noopener noreferrer">white paper</a>, we pointed at the risks of the “big data divide” between digital multinationals and financial authorities, and discussed the importance of upgrading supervisory technologies (suptech) and making new approaches to digital transformation mainstream. We also presented possible solutions to extend the benefits of the adoption of artificial intelligence (AI) and other technologies to increase competition and support innovation in the financial sector.
<h2>Pandemic Increases Urgency</h2>
I believe that the pandemic has made these demands even more urgent, and point at some priorities that financial authorities and multilateral and philanthropic organizations should consider in light of the value of financial data in today’s context, the power dynamics that are shifting with the deepening of the data divide, and the pressing need for upgrading financial supervision.

The lockdowns and physical distancing measures that governments have put in place in response to the pandemic make urgent the need for action. This year, a significant share of the world’s population was forced to work remotely and is spending more time online than ever before. During early shelter-in-place orders in the United States, daily users of Facebook increased 12 percent year over year to 1.79 billion. Monthly usage across its family of apps, which also includes Instagram and WhatsApp, rose 14 percent to 3.14 billion. And Facebook’s mostly ad-based business rose along with them: the company’s revenue was up 11 percent year over year. More than ever before, the majority of us rely on e-commerce, social media, online communications platforms, and remote, cashless transactions. This translates into growth of profit and power for the giant digital multinationals: in its fiscal 2020 third quarter, Apple posted quarterly revenue of $59.7 billion, an increase of 11 percent from the same quarter one year ago. In the quarter that ended in July, Alibaba delivered revenue growth of 34 percent, year over year.

On the regulatory side, the recently conducted <a href="https://www.jbs.cam.ac.uk/insight/2020/new-global-covid-19-fintech-study-launches/" target="_blank" rel="noopener noreferrer">World Bank-CCAF Global COVID-19 FinTech Regulatory Rapid Assessment Survey</a> (results forthcoming) will give insights into what sort of action will be needed by revealing key internal challenges for supervisors that have emerged during the pandemic. Check back here in the coming weeks for a link to those results.
<h2>Risks to Consumers</h2>
These trends represent an increased risk to consumers. First, without the right tools to identify and weigh risk, it will be challenging (impossible?) for financial authorities to supervise the rising digital-native financial sector and the giant digital multinationals. The <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3596276">automation of compliance reports</a> and tools to effectively monitor the health of financial service providers (FSPs) accessing granular and timely data are priorities, particularly at a time when on-site supervision is constrained. <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3596276" target="_blank" rel="noopener noreferrer">Digital channels for complaints</a> (e.g., chatbots), and other tools to create better insights into the customer experience, are also needed.
<blockquote>Digital channels for complaints, and other tools to create better insights into the customer experience, are also needed.</blockquote>
Second, digital multinationals may snuff out the smaller, innovative FSPs, applying the same <a href="https://www.ft.com/content/39b5c3a8-4e1a-11ea-95a0-43d18ec715f5" target="_blank" rel="noopener noreferrer">“buy and kill” tactics</a> that have already come under scrutiny in other sectors, posing risks of concentration, and slowing down innovation. This tactic may bring new, much needed, competition into the financial sector at first. Some of them may provide their services for free to retain customers, boost engagement, and capture data, benefiting affordability. However, the long-term impact of the “buy and kill” tactics could be that smaller, innovative, local fintech startups that aim to serve niches of the market -- in some cases, those focused on addressing the needs of more vulnerable segments of the population -- get mopped up.

To correct the imbalance of power between giant digital multinationals and data-poor FSPs, and to counteract the emerging big data divide, a level playing field needs to be established for financial data access and usage. (This includes other data -- from telecoms, for example -- that is relevant for financial customers to make choices, and relevant for FSPs to design and roll out new products).
<h2>A Potential Solution</h2>
One way to level this playing field is a new <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3595344." target="_blank" rel="noopener noreferrer">Open Data Commons</a>, which guarantees access to rich and plentiful data to all market players and customers, and equips them with tools to make them meaningful and actionable. This establishes a shared data platform for the generation, exchange, and dissemination of insights to serve specific use cases for FSPs, customers, and other stakeholders.

&nbsp;

Financial Authorities’ Tools Must Evolve to Catch Up with “Digital Multinationals”

<img class="alignright wp-image-40142 size-thumbnail" src="https://content.centerforfinancialinclusion.org/wp-content/uploads/sites/2/2020/10/grateful-emoji-283-150x150.jpg" alt="grateful " width="150" height="150" />
<h2>Grateful</h2>
I am feeling an incredible level of gratitude to all the people who participated in Financial Inclusion Week last week. We had more than 1,200 people register for FIW’s various events. The agenda featured more than 40 sessions covering a broad spectrum of topics, time zones, and regions. Each and every session required planning and coordination. A huge thanks goes to all of our partners who chose to participate and share their learning and experiences during FIW.
<h2><img class="alignleft size-thumbnail wp-image-40143" src="https://content.centerforfinancialinclusion.org/wp-content/uploads/sites/2/2020/10/monocle-5-150x150.png" alt="" width="150" height="150" />Curious</h2>
I am already a major advocate for women’s financial inclusion and believe the inclusive finance industry needs to get more sophisticated on this topic. The CFI <a href="https://youtu.be/MxXWHaNhYcY" target="_blank" rel="noopener noreferrer">podcast on social norms</a>, the Caribou Digital session on <a href="https://www.youtube.com/watch?v=SbIBJO_7cJs&amp;feature=youtu.be" target="_blank" rel="noopener noreferrer">features that drive women’s usage of DFS</a>, and the Pinbox session, "<a href="https://youtu.be/b2ulPv9INEA" target="_blank" rel="noopener noreferrer">Saving the Next Generation from Old Age Poverty</a>" (especially women, who live longer) were eye-opening. I am curious to see where our collective focus on this topic will take us.
<h2><img class="alignright size-thumbnail wp-image-40144" src="https://content.centerforfinancialinclusion.org/wp-content/uploads/sites/2/2020/10/tempted-heart-eyes-emoji-150x150.png" alt="heart eyes emoji " width="150" height="150" />Tempted</h2>
There were so many sessions to choose from that there were moments I felt like a kid in a candy store. Fortunately, the sessions have all been recorded and I can go back to the ones I missed and catch up on them (and I will have a full year to do that). I’ve even mapped out a plan of action for when I’ll get up to speed on what I missed. This week, I plan on listening to the Inclusive Finance India <a href="https://youtu.be/E0Snagg7TYM" target="_blank" rel="noopener noreferrer">session on remittances</a> and GSMA’s session, "<a href="https://www.youtube.com/watch?v=B3Khho7Bgac&amp;feature=youtu.be" target="_blank" rel="noopener noreferrer">Beyond One Billion: Exploring the State of Mobile Money in Africa</a>."
<h2><img class="alignleft wp-image-40145" src="https://content.centerforfinancialinclusion.org/wp-content/uploads/sites/2/2020/10/connected-emoji-300x268.png" alt="connected emoji" width="184" height="164" /></h2>
<h2>Connected</h2>
We have all been struggling to adjust to our new, social-distanced and Zoom-based world, and I was worried that more virtual events might be difficult. I was surprised at how connected I felt to the inclusive finance industry. I learned so much from the various panelists, whether it was the elaborate -- yet achievable -- <a href="https://www.youtube.com/watch?v=FLWs9JMdj7M&amp;feature=youtu.be" target="_blank" rel="noopener noreferrer">ideas posed by Sarah Gammage</a> on the role of financial services in mitigating climate risk and supporting livelihood adaptation, or <a href="https://www.youtube.com/watch?v=qjVT1EaN3QE&amp;feature=youtu.be" target="_blank" rel="noopener noreferrer">David Medine’s insightful explanation</a> as to why consent-based systems are no longer relevant for addressing data usage and data privacy concerns. There’s been a lot of talk that this industry has become more fragmented as we each dig deeper into specific silos, but this week showed me the power of coming together. It takes some effort, but the results are evident.
<h2><img class="alignright size-thumbnail wp-image-40146" src="https://content.centerforfinancialinclusion.org/wp-content/uploads/sites/2/2020/10/tired-emoji-150x150.png" alt="tired emoji" width="150" height="150" />Tired</h2>
But, alas, I am human and not a complaints bot or <a href="https://www.youtube.com/watch?v=9tXAN0oicVE&amp;feature=youtu.be" target="_blank" rel="noopener noreferrer">algorithm</a>, like the ones covered in some sessions. This means by the end of the week I was tired after an incredibly packed agenda and so many interactive sessions.
<h2><img class="alignleft size-thumbnail wp-image-40149" src="https://content.centerforfinancialinclusion.org/wp-content/uploads/sites/2/2020/10/cry-emoji-4-150x150.png" alt="cry emoji" width="150" height="150" />Sad</h2>
That’s why my next emoji is complex. Despite my tiredness, I am sad to see FIW 2020 come to an end. I hope that this community that has come together to share and learn from one another can somehow keep the momentum going. At CFI, we will certainly do our best to engage and learn from our partners.
<h2></h2>
<h2><img class="alignright wp-image-40150" src="https://content.centerforfinancialinclusion.org/wp-content/uploads/sites/2/2020/10/lightbulb-emoji-2-300x292.png" alt="inspired lightbulb emoji " width="161" height="157" />Inspired</h2>
My final emoji is my overwhelming sense of inspiration. I hope you found FIW as inspiring a learning event as I did. From our first day with the panel, "<a href="https://www.youtube.com/watch?v=im7EP5TtGdA" target="_blank" rel="noopener noreferrer">Serving Low Income Households Impacted by Climate Change</a>," to the last day with Aspen Institute’s session, "The Road to 2030: An Action Agenda for Inclusive Financial Systems," I am inspired that so many organizations are already thinking about and taking action on some of the toughest challenges that poor people face during this extraordinary time in history.

&nbsp;

Financial Inclusion Week and My Emoji Roller Coaster Ride

The Rizzi family recently returned to the US after living in Italy for three years, during which time a love for all things pizza was cemented. I could write a whole blog about the best Roman pizzeria (it's Roscioli), so when a colleague told us, the data team, about a recent <a href="https://news.stanford.edu/2017/08/03/pizza-privacy-stanford-economist-examines-paradox-digital-age/" target="_blank" rel="noopener noreferrer">study about pizza and data privacy</a> – MIT undergraduates were willing to relinquish their friends’ personal information in exchange for a free pizza – we were interested.

Should we chalk the results up to college students’ love of late-night snacks? Not exactly. This year, the Ipsos Global Trends survey across 33 countries found that despite growing concern around big data, nearly <a href="https://www.ipsosglobaltrends.com/2020/02/data-dilemmas/" target="_blank" rel="noopener noreferrer">half of respondents said they would trade their information away</a> in return for personalized services and products. This was a 7 percent increase since the last time the survey was conducted in 2013. It’s easy to assume that this implies that people don’t care about data protection, but it fails to account for the frequently zero-sum choice presented to consumers for whom access to vital products and services increasingly relies on digital gatekeepers. The financial inclusion field is no exception.
<h2>Unchecked Superpowers?</h2>
For the unbanked and underbanked and those that work with them, the explosion of available data, data-crunching services and data-enabling regulatory schemes bring unprecedented potential. A BFA paper called certain artificial intelligence applications "<a href="https://bfaglobal.com/wp-content/uploads/2019/03/FIBR-Artificial_Intelligence_FINAL_MAY2018-1.pdf" target="_blank" rel="noopener noreferrer">practical superpowers</a>" and the possibilities to unlock wealth and opportunity for the poor indeed seem extraordinary – from prospecting and credit scoring for thin-file consumers to well-timed nudges for saving, from fraud management and complaint chatbots to access to e-commerce platforms and <a href="https://www.cgap.org/blog/open-banking-7-ways-data-sharing-can-advance-financial-inclusion" target="_blank" rel="noopener noreferrer">open banking regimes</a>. At CFI, we feel the case has been <a href="https://centerforfinancialinclusion.org/accelerating-financial-inclusion-with-new-data-2/" target="_blank" rel="noopener noreferrer">well-articulated</a> for supporting a myriad of <a href="https://www.cgap.org/research/publication/using-satellite-data-financial-inclusion" target="_blank" rel="noopener noreferrer">data-driven tools</a> and will continue to be made.
<blockquote>Data-driven tools must also be examined for their risks, pitfalls and unintended consequences.</blockquote>
Our perspective is that for these opportunities for financial inclusion to be fully realized, they must also be examined for their risks, pitfalls and unintended consequences for low-income consumers. This lens is not meant to throw a wet blanket on innovation and enthusiasm, but to have a clear-eyed focus in a world where data is <a href="https://cloudian.com/blog/getting-a-handle-on-data-growth/#:~:text=According%20to%20IDC%2C%20the%20world's,all%20this%20data%20the%20same." target="_blank" rel="noopener noreferrer">growing by the zetabyte</a> (10^21) every month, where tens of thousands of individuals become digital immigrants every day and where innovation <a href="https://www.centerforfinancialinclusion.org/data-consent-lets-share-the-burden-for-effective-consumer-protection" target="_blank" rel="noopener noreferrer">races ahead of traditional guardrails</a> on data protection and privacy.

Our vision is that digitization is catalytic for the poorest and most vulnerable consumers, not just those who are already on the pathway to digital inclusion. Looking at developed markets where smartphone ownership is widespread, we still see vulnerable communities trapped in a state of <a href="https://socialchangenyu.com/review/the-surveillance-gap-the-harms-of-extreme-privacy-and-data-marginalization/" target="_blank" rel="noopener noreferrer">data marginalization</a>, due to gaps in technology access, fear of documentation, or failures of mainstream data collection mechanisms. As the use of alternative data to drive financial products grows and other data tracking systems, such as biometrics, expand, developing countries may see more data silos and failures in capturing a holistic picture of the lives of the poor.

We see evidence of this when looking at the consumer base of digital credit products, which tend to be <a href="https://www.centerforfinancialinclusion.org/making-digital-credit-truly-responsible" target="_blank" rel="noopener noreferrer">younger men living in urban areas</a>. There are many reasons why women may not be accessing these products, but failing to account for <a href="https://www.gsma.com/mobilefordevelopment/wp-content/uploads/2020/05/GSMA-The-Mobile-Gender-Gap-Report-2020.pdf" target="_blank" rel="noopener noreferrer">limits on women’s use of smartphones</a> is a structural barrier to collecting accurate data to use in digital credit decision models. Pushing for rapid onboarding to digital finance without an understanding of these dynamics could lead to a more entrenched digital divide, unintentionally excluding those who could benefit most from new products and services because of their incomplete digital footprints.
<blockquote>CFI plans to build on its experience in financial consumer protection to focus on key questions around data and financial inclusion.</blockquote>
CFI plans to build on its decade of experience in financial consumer protection to focus on key questions around the promise of data and financial inclusion. And we are raising several of these issues as part of <a href="https://pheedloop.com/fiw2020/virtual/" target="_blank" rel="noopener noreferrer">Financial Inclusion Week 2020</a>.
<h2>Hot Topics</h2>
<h3>Responsible Algorithms</h3>
The data-driven predictions in the financial inclusion space that have grabbed the most headlines in recent years have been on <a href="https://www.accion.org/digital-lenders-can-help-unlock-full-financial-inclusion" target="_blank" rel="noopener noreferrer">consumer creditworthiness</a>. In economies where there is less access to reliable financial data, providers are leveraging other sources, the bulk of which come from mobile phones but can also include social media, geospatial data, etc., in order to make underwriting decisions. Today there is limited visibility into the type of data that financial service providers are collecting and how they are using it, with few incentives for transparent data practices.

CFI is interested in examining how financial inclusion actors approach the use of algorithms and automated decision-making, especially using alternative data, as their use becomes ever more pervasive in the industry. Within this arena are several important topics, including how to effectively measure capacity to repay with alternative data as well as how to mitigate against biased decisions. Although algorithms and automation don’t necessarily lead to discrimination, bias can occur at <a href="https://medium.com/impact-engineered/understanding-bias-in-algorithmic-design-db9847103b6e" target="_blank" rel="noopener noreferrer">varying stages</a> – from the data sources, processing, model development, or outputs. And there are heightened risks that biases, which could undermine financial inclusion goals, could arise from data that does not paint a full enough picture of a low-income person or customer segment.
<blockquote>Algorithms are not designed to be interpretable or explainable.</blockquote>
Compounding this, algorithms are not designed to be interpretable or explainable, and are often treated as trade secrets that are only understood by few within an organization. Data protection frameworks have emerged in developed markets that empower consumers with data rights vis-à-vis automated decision-making, and rely heavily on <a href="https://gdpr-info.eu/art-22-gdpr/" target="_blank" rel="noopener noreferrer">consent</a>. As the principles in these frameworks percolate into emerging markets, we wonder what constraints and barriers there are in their implementation.
<h3>Beyond Consent</h3>
While notice, choice and informed consent have been the traditional approach to data privacy, those concepts seem ill-equipped for our data-driven world. For instance, you probably already knew that the apps you use monitor your location to send you custom advertisements, but did you know that a <a href="https://www.wired.com/story/wired-guide-personal-data-collection/" target="_blank" rel="noopener noreferrer">hedge fund might also buy</a> that geolocation data to figure out which stores you like? Or that there is a whole industry of data brokers – scraping, compiling and collating bits of data about you to monetize and make predictions about your behavior? <a href="https://www.fastcompany.com/90310803/here-are-the-data-brokers-quietly-buying-and-selling-your-personal-information" target="_blank" rel="noopener noreferrer">Acxiom</a>, one of the biggest, operates in more than 62 markets and has information on over 2.5 billion consumers. Especially for low-income or vulnerable consumers, who are both often targets for data collection efforts and less likely to understand or use basic privacy protections, consent-based approaches seem insufficient. New approaches beyond consent are <a href="https://www.cgap.org/events/beyond-consent-why-new-approaches-data-protection-and-privacy-digital-age-are-needed" target="_blank" rel="noopener noreferrer">clearly needed for data</a> protection in financial inclusion (and beyond), but what might those look like in practice, who bears the cost for them and who determines their efficacy?

We hope you continue to engage us and challenge us on these issues, not only during this <a href="http://www.financialinclusionweek.org" target="_blank" rel="noopener noreferrer">Financial Inclusion Week</a>, but as we roll out our new <a href="https://centerforfinancialinclusion.org/reflecting-on-the-past-and-charting-a-new-direction/" target="_blank" rel="noopener noreferrer">strategy</a>. There will always be tension – sometimes healthy, sometimes unhealthy – in the use of technology for inclusive finance: will it make better lives within reach? Or will technology overstep and infringe on privacy rights….or worse?

Data for Inclusive Finance: Delivering on the Promise for Consumers

Though Nigeria’s government has set ambitious goals for financial inclusion, the majority of its people lack a formal bank account. Accion has worked in the country since 2007 to expand access to financial services.

Data from across the financial inclusion industry shows the economic upheaval COVID-19 is causing throughout Nigeria. <a href="https://www.centerforfinancialinclusion.org/msmes-in-lagos-struggle-due-to-covid-19-but-remain-positive" target="_blank" rel="noopener noreferrer">In addition to data collected by CFI</a>, we examined the results of four other surveys of COVID-19’s impact throughout the country. When considered collectively, the data tells a story in which the public health crisis has led to policies which slowed economic activity. Consequently, income has declined—for employers and employees alike—and there appears to be massive reductions in available work. The data also suggests Nigerians’ capacity to respond is finite as households draw down savings and struggle to repay debts, exacerbating their struggle to put enough food on the table.
<h2>Survey Summary</h2>
CFI looked at five surveys that have been conducted since COVID-19 reached Nigeria. A summary of those surveys—including sample size, notes on sampling method, survey dates, and major topics covered—is available in Table 1.

There are three things to highlight about this set of surveys which are meaningful when interpreting the results. First, the survey methods used varied, and <a href="https://news.gallup.com/opinion/methodology/233291/why-phone-web-survey-results-aren.aspx" target="_blank" rel="noopener noreferrer">these different modes have shown to yield different responses to the same question in other studies</a>. BFA used an online survey, GeoPoll’s survey was delivered via SMS to its database of respondents while CFI, i2i, and the World Bank conducted surveys by phone.

Second, the samples target different populations of interest and the selection methodology differed. BFA used a sample of paid, online respondents while GeoPoll relied on its database of mobile subscribers who tend to be younger, more literate, and wealthier than the population at large. CFI’s sample of MSMEs were clients of Accion Microfinance Bank in Lagos. Only i2i and the World Bank surveys were nationally representative. This diversity can help give confidence in patterns we identify: <em>there is strong circumstantial evidence the trend is true</em> if all five surveys show a similar trend with a similar magnitude. A downside, though, is that because of the heterogeneity in methods, circumstantial is the best we can do—this is not an empirical comparison.

Third, these surveys happened at proximate but not identical times. BFA’s survey was the earliest and the <em>initial</em> World Bank survey, which includes two waves, also happened shortly after the pandemic struck. i2i’s longitudinal survey was conducted <em>during a two-and-a-half-month period</em>. These differences are relevant because of the immediacy of COVID-19’s impact. Even differences of a few weeks could have had meaningful effects on responses.

Nigerians Are in Desperate Need of Relief as COVID-19 Reduces Wealth and Stresses Coping Strategies

Micro, small, and medium enterprises (MSMEs) in Indonesia are suffering in the wake of COVID-19 according to data collected by CFI. Seventeen percent of the businesses in the sample have closed, and 85 percent of those that continue to operate estimate their profits have decreased, often by 50 percent or more.

Owners of the MSMEs that were operating at the time of the survey remained optimistic despite the economic downturn. Almost two-thirds reported they were covering their business expenses with revenue and thought they could keep their doors open for another three months based on how things were going. In addition to altering their business practices to stay open, the data on owners’ use of financial tools suggests that they are drawing down their financial resources, raising concerns that they have little cushion for the months ahead.

From July 13 to August 8, 2020, CFI conducted phone interviews with a random sample of <a href="https://bina-artha.com/" target="_blank" rel="noopener noreferrer">Bina Artha Ventura (BAV)</a> clients in Indonesia. BAV, which is <a href="https://www.accion.org/mastercard-and-accions-partnership-to-unlock-millions-of-underserved-microbusinesses" target="_blank" rel="noopener noreferrer">participating in Accion’s partnership with Mastercard</a>, is a microfinance institution that uses a group lending methodology to serve entrepreneurs, mostly women, who predominantly live in rural areas. CFI completed 730 interviews, 660 of which were with female MSME owners. Two-thirds of the owners ran sole proprietorships while 31 percent ran microenterprises (one to 10 employees). Those microbusinesses employed an average of three people before the pandemic. MSMEs in the sample have been operating for almost eight years on average. Most businesses were grocery or food stands, although farming and the sale of household goods were also common. This is one of six surveys CFI is conducting in Indonesia as part of its <a href="https://www.centerforfinancialinclusion.org/covid-19-and-msmes-data-and-analysis-to-understand-impact" target="_blank" rel="noopener noreferrer">ongoing effort to study the impact of COVID-19 on the financial health of MSMEs</a>. As with data from CFI’s first survey in Nigeria, the data from this survey is <a href="https://www.centerforfinancialinclusion.org/covid-19-and-msmes-data-and-analysis-to-understand-impact/indonesia" target="_blank" rel="noopener noreferrer">presented in this interactive dashboard</a>.
<h2>Survey Insights</h2>
<h4>Nearly one in five women-led businesses have closed. They were almost twice as likely to close as male-led businesses.</h4>
<blockquote>Of the women-led microbusinesses that closed, 78 percent said they were completely confident that they would reopen in the future, but only 57 percent of the women-led sole proprietorships that closed said the same.</blockquote>
Since COVID-19 struck Indonesia, 18 percent of women-led businesses in the sample have closed. These closures have proportionally impacted businesses of different types and sizes, and they have been driven largely by a drop in customer demand, likely the result of restrictions on movement being enforced in the country. The owners of these businesses were generally confident that they would be able to restart their business in the future, but there were major differences based on how large the businesses were prior to the pandemic. Of the women-led microbusinesses that closed, 78 percent said they were completely confident that they would reopen in the future, but only 57 percent of the women-led sole proprietorships that closed said the same. Importantly, women-led businesses were almost twice as likely to close as male-led businesses. Of the 70 male-led businesses in the sample, only 10 percent had shuttered their operations.
<h4>COVID-19 has led to dramatic declines in profits, but roughly two-thirds of businesses say they are covering their expenses.</h4>
<blockquote>70 percent of operating businesses reported a decrease in profits of 50 percent or more.</blockquote>
Businesses generally did well in the year before the pandemic struck. Fifty-six percent of respondents reported their profits increased compared to the year before while 38 percent said they had stayed the same. Only 5 percent of people said their profits had declined, but that number has skyrocketed since COVID-19: 85 percent of businesses reported that their profits have declined compared to pre-pandemic levels. Those declines have been dramatic, with 70 percent of operating businesses reporting a decrease in profits of 50 percent or more. While profit levels shrunk dramatically, owners were confident that they would be resilient to this shock. Sixty-three percent of owners said they were covering their expenses just with business revenue and think they could continue operating for at least three months based on how things were going.
<h4>MSMEs are trying to survive by changing business practices to boost revenue and cut costs, including reducing their labor force.</h4>
<blockquote>Half of operating microenterprises reported that they cut employees.</blockquote>
MSME owners are employing a mix of revenue-boosting and cost-cutting measures to ensure their revenues continue covering their expenses. For instance, a third of all operating businesses reported offering discounts to stimulate sales while a fifth chose to raise prices instead. Almost a fifth of businesses started a delivery service since the pandemic began. Cost-cutting measures were also common. For those businesses with employees, reducing the size of their workforce and work hours for staff was an important strategy. Half of operating microenterprises reported that they cut employees, leading to a 42 percent reduction in employment within this segment. This action likely had downstream effects. Many owners reported that they were working longer hours to meet customer demand or make ends meet, potentially a result of a reduced workforce.
<h4>In addition to their businesses, owners’ households are enduring, but data on financial tools suggests their margin of error is small.</h4>
Three-quarters of households reported that they were covering all their expenses with non-debt income sources. Severe food insecurity – defined as people going to bed hungry because of a lack of money – was relatively low at 10 percent. In comparison, CFI’s survey of urban MSME owners in Lagos, Nigeria found that 34 percent of owners reported severe food insecurity in their households.

While this is encouraging, a closer look at the financial tools owners are using to cope with the crisis suggests that conditions are likely to worsen. For example, 22 percent of owners sold a household asset to keep their business running. Of the households that sold an asset, only 63 percent reported being able to cover their expenses compared to 79 percent who did not sell an asset. Similarly, 47 percent of MSME owners reported skipping a loan payment, and those owners were less likely to have covered their household expenses by a similar margin compared to those who had made their payments.
<blockquote>Savings also appears to have collapsed in the months since the pandemic hit.</blockquote>
Savings also appears to have collapsed in the months since the pandemic hit. Since March, only 38 percent of people reported saving while 53 percent reported withdrawing money from savings. In the year prior to the pandemic, 84 percent of people reported saving compared to 54 percent who said they withdrew money. While the comparison is not one-to-one because of the different periods, it is certainly not encouraging, especially because savings is another indicator of households’ ability to cope. Ninety percent of owners who had saved since March reported being able to cover their household expenses compared to only 67 percent of owners who had not saved.

Collectively, this analysis implies respondents have dwindling financial options. Only so many assets can be sold, and savings will dry up if not replenished. Debts not repaid choke future lines of credit. These underlying patterns may help to explain a less optimistic sentiment shared by respondents: 79 percent said they could only cover their essentials for a month or less if their income sources dried up.
<h2>Summary and Reflections</h2>
Since the pandemic reached Indonesia in March, 17 percent of businesses have closed, profits have collapsed, and employment has plummeted. Women-owned businesses have been hit especially hard, with 18 percent of them closing compared to only 10 percent of male-owned businesses. Owners who managed to keep their business open reported a high degree of confidence in their ability to continue operating, relying on a mix of revenue-boosting and cost-cutting business practices to ensure their revenues continue to at least meet their expenses. This has helped stave off catastrophe at home, where food insecurity remains low and people continue to cover their household expenses.

However, data on the use of financial tools suggests owners and their households have little margin for error in the months ahead. Selling household assets, skipping loan payments, and net savings withdrawal activity indicate that respondents are already relying heavily on financial tools to meet their basic needs. Without a change in their circumstances, it is unlikely that MSME owners will be able to replenish these resources. Thus, it is reasonable to expect a worsening financial situation in the months ahead.

<em>This survey is part of our partnership with <a href="https://www.accion.org/mastercard-and-accion-partner-to-unlock-growth-for-millions-of-underserved-microbusinesses-around-the-world" target="_blank" rel="noopener noreferrer">Mastercard Center for Inclusive Growth</a> to understand the impact of COVID-19 on MSMEs.</em>

MSMEs in Indonesia Are Surviving but COVID-19 Leaves Little Margin for Error

This is the second part of CFI’s blog series exploring 2019 data from <a href="https://www.inclusivefintech50.com/" target="_blank" rel="noopener noreferrer">Inclusive Fintech 50</a> and <a href="https://www.themix.org/fintech-benchmarks" target="_blank" rel="noopener noreferrer">Results of the Fintech Benchmarks Proof-of-Concept</a> to shed light on current gender disparities in the fintech industry -- both at the management level and in their customer base. This blog post focuses on the role fintechs can play in designing products with women in mind, and thus help to close the gender gap in financial inclusion. It is structured around two broad observations and concludes with several recommendations for fintechs and researchers.
<h2>1. There is a gender gap in the customer base served by fintechs</h2>
<blockquote>The median fintech had only 36 percent female customers.</blockquote>
The Inclusive Fintech Benchmarks data reveals a gender gap in the customer base served by inclusive fintechs. Given the social aim of these fintechs, gathering critical demographic information is paramount to product design and meeting customer needs. However, only 20 out of 45 fintechs recorded sex-disaggregated data on their customer base. Among these 20 fintechs, the median fintech had only 36 percent female customers. This again drives home the need for such data, in particular to understand whether women were specifically targeted, and if so, which strategies were most effective. And if women were not specifically targeted, it would also be useful to understand how these female customers were attracted in the first place.

Perhaps it is not surprising that these fintechs have a low female customer base. Women in developing economies are <a href="https://globalfindex.worldbank.org/" target="_blank" rel="noopener noreferrer">9 percentage points</a> less likely to have a bank account than men, <a href="https://www.gsma.com/r/gender-gap/" target="_blank" rel="noopener noreferrer">8 percent less</a> likely to own a mobile phone, and <a href="https://www.vitalvoices.org/2019/09/international-literacy-day-the-literacy-gender-gap/" target="_blank" rel="noopener noreferrer">7 percentage points</a> less likely to be literate. These gaps in financial and digital literacy are much wider in certain regions, such as South Asia and East Africa.

Access to financial services is a key enabler for women to achieve financial independence and economic empowerment. However, women face unique and often intertwined barriers in accessing financial services, including but not limited to regulatory constraints (i.e. registrations requiring national ID cards), the aforementioned low <a href="https://gflec.org/wp-content/uploads/2017/07/The-Gender-Gap-in-Financial-Literacy-A-Global-Perspective-Report.pdf?x87657" target="_blank" rel="noopener noreferrer">financial</a> and <a href="http://www.oecd.org/internet/bridging-the-digital-gender-divide.pdf" target="_blank" rel="noopener noreferrer">digital literacy</a> levels compared to men, and social norms that may restrict their mobility and financial decision-making autonomy. One of the biggest barriers women face in accessing financial services is the <a href="http://mujeresinnovadoras.com/wp-content/uploads/2018/09/Exploring-Fintech-Solutions-for-Women.pdf" target="_blank" rel="noopener noreferrer">lack of money or regular income</a>.

However, mobile money has the potential to narrow the gender gap in financial inclusion. An analysis of the Findex 2017 data by <a href="https://www.gsma.com/mobilefordevelopment/blog/the-promise-of-mobile-money-for-further-advancing-womens-financial-inclusion/#_ftn2" target="_blank" rel="noopener noreferrer">GSMA</a> finds that countries with high mobile money usage have indeed narrowed the gender gap in financial inclusion. By transacting digitally, women do not need to travel to inconvenient locations or where they feel unsafe, and they can make payments securely and privately. A <a href="https://www.gsma.com/mobilefordevelopment/wp-content/uploads/2019/12/IRC_Report_R_WebSpreads.pdf" target="_blank" rel="noopener noreferrer">study conducted</a> on the <a href="https://www.rescue.org/" target="_blank" rel="noopener noreferrer">International Rescue Committee’s</a> (IRC) mobile money cash-aid programs in rural Sindh, Pakistan found that IRC’s consistent financial and digital literacy trainings played a crucial role. Female clients were not only able to use mobile money to receive their cash-aid, but appreciated the convenience, privacy and speed of mobile money.

Globally, however, women are still <a href="https://www.gsma.com/mobilefordevelopment/wp-content/uploads/2019/03/GSMA-Connected-Women-The-Mobile-Gender-Gap-Report-2019.pdf" target="_blank" rel="noopener noreferrer">33 percent less likely</a> than men to own a mobile money account, mainly attributed to lower rates of mobile phone ownership and lack of access to identity documents. Some state governments in India, for example, have <a href="https://epod.cid.harvard.edu/article/mobile-phone-gender-gap-why-does-it-matter-and-what-can-we-do" target="_blank" rel="noopener noreferrer">initiated programs to subsidize phone ownership</a>, which helps to address the access gap but not the usage gap. Efforts to overcome women’s barriers to accessing financial services need to be coordinated, recognizing that women are not a homogenous group or customer segment. Fintechs are uniquely positioned to help close the gender gap in financial inclusion while also serving an untapped market that represents a large potential revenue source.
<h2>2. Female-led fintechs are more likely to target female clients and other underserved populations</h2>
<blockquote>Female-led fintechs appear more likely to serve female clients.</blockquote>
The 2019 Inclusive Fintech 50 data reveals that female-led fintechs target different markets than non-female-led fintechs. The Inclusive Fintech Benchmarks sample of 20 fintechs further shows that female-led fintechs appear more likely to serve female clients. The median female-led fintech had a customer base that was 58 percent female, compared to 35 percent female for fintechs that did not have women in leadership positions.

Diverse organizational leadership provides numerous benefits. For fintechs, female leaders can play a pivotal role in designing and marketing financial products to meet the needs of women. Although female-led and non-female-led fintechs in the Inclusive Fintech 50 2019 data target broadly defined “underserved” customers at similar rates, female-led fintechs are more likely to support micro, small, and medium enterprises (MSMEs), as well as farmers and rural households. Fintechs that do not have women in leadership positions are more likely to instead target their products to the general public, which may not produce as great an impact on financial inclusion.

&nbsp;

<img class="aligncenter wp-image-39779 size-full" src="https://content.centerforfinancialinclusion.org/wp-content/uploads/sites/2/2020/09/Primary-Target-Market-of-Female-Led-Fintechs-V2.png" alt="" width="1059" height="678" />

Additionally, segmenting and targeting more female customers represents a market growth opportunity for fintechs. Much like sex-disaggregated client data, segmentation also forces providers to understand the specific needs of their target customers and the unique barriers they face. For instance, <a href="https://www.financedigitalafrica.org/wp-content/uploads/2018/02/FiDA-Snapshot-9-Best-practices-in-big-data-analytics.pdf" target="_blank" rel="noopener noreferrer">JazzCash Pakistan</a> wanted to understand how to improve women’s mobile wallet usage. In exploring this, their research partners, Women’s World Banking and ideas42, found that female and male customers used JazzCash accounts in very similar ways and that the real problem was not usage but acquisition. Female customers accounted for only 15% of new account openings, likely due to marketing campaigns aimed at men. With further research, the team was able to design solutions to accelerate the acquisition of new female customers.
<h2>Recommendations</h2>
<h3>For Fintechs</h3>
<ul>
 	<li>In order to ensure that they include female customers, fintechs must gather data on the gender makeup of their customer base. As mentioned earlier, among the 45 fintechs in the Inclusive Fintech 50 Benchmarks report, only 20 could report the number of female customers served, indicating a data gap. Having this data would enable fintechs to track their contribution to female financial inclusion and identify areas for growth.</li>
 	<li>Fintechs must be intentional about including female customers when designing products. They would benefit from thinking about whether their product is designed in a way that excludes women, even if it is unintentional. This can only be accomplished by conducting market research on female customer segments to better understand their needs, preferences and barriers. It is imperative that providers design compelling use cases to meet women’s financial needs. Addressing this gender gap can also represent a commercial opportunity. For instance, if mobile operators could close the gender gap in mobile ownership and use in low and middle-income countries by 2023, this would provide an <a href="https://www.gsma.com/mobilefordevelopment/wp-content/uploads/2019/03/GSMA-Connected-Women-The-Mobile-Gender-Gap-Report-2019.pdf" target="_blank" rel="noopener noreferrer">estimated $140 billion in additional revenue</a> to the mobile industry.</li>
 	<li>Fintechs should also consider gender when marketing and selling fintech products. For instance, <a href="https://www.womensworldbanking.org/insights-and-impact/its-as-easy-as-a-b-c-how-a-b-testing-helped-onboard-more-women-customers-through-mobile-account-referrals/" target="_blank" rel="noopener noreferrer">JazzCash Pakistan recently tested behaviorally informed text messages</a> to encourage current JazzCash users to send more referrals to women. Forthcoming data from <a href="https://www.themix.org/relay-fintech" target="_blank" rel="noopener noreferrer">RELAY</a>, a fintech data solution developed by MIX, will examine the share of female agents among fintechs that rely on an agent network.</li>
</ul>
<h3>For Researchers</h3>
<ul>
 	<li>Further research should examine the role of fintechs in serving women. Some questions to explore further can include: how to monitor the performance of fintechs; how to co-create products and solutions with female customers; effective marketing strategies to onboard women; the relationship between fintechs and the SME credit gap; and whether credit scoring algorithms introduce gender bias.
<blockquote>Fintech products alone will not produce meaningful change in the lives of women.</blockquote>
</li>
 	<li>Additional research is needed on the intersection between female financial inclusion and the societal and regulatory constraints that women face. Fintech products alone will not produce meaningful change in the lives of women without addressing broader disparities in digital and economic inclusion.</li>
</ul>
We are excited to delve deeper into the 2020 Inclusive Fintech 50 data to answer some of the questions we were not able to answer based on the 2019 data here. Nevertheless, this two-part blog post has highlighted several important ways in which advancing women’s inclusion in the fintech space, both at the leadership level and among the customer base, is not only the right thing to do, but also the smart thing to do.

Including Women Customers in “Inclusive Fintech”

Fintech startups have leveraged technology to lower transaction costs and reach underserved populations. These technologies can <a href="https://www.worldbank.org/en/results/2013/04/01/banking-on-women-extending-womens-access-to-financial-services" target="_blank" rel="noopener noreferrer">expand</a> financial services to women, who are often <a href="https://www.ifc.org/wps/wcm/connect/news_ext_content/ifc_external_corporate_site/news+and+events/news/bridging+the+gender+gap+in+access+to+finance" target="_blank" rel="noopener noreferrer">excluded</a> from formal financial services. The COVID-19 pandemic makes it even more critical to address gender equity, as <a href="https://www.womensworldbanking.org/insights-and-impact/building-resilience-how-to-ensure-women-are-not-left-behind-as-a-result-of-covid-19/" target="_blank" rel="noopener noreferrer">evidence</a> indicates women have been disproportionately impacted by the economic impacts of the virus. While fintechs can play an important role in designing accessible and meaningful solutions for marginalized populations, they can also run the risk of exacerbating the digital divide, including the mobile <a href="https://www.gsma.com/mobilefordevelopment/resources/mobile-gender-gap-report-2019/" target="_blank" rel="noopener noreferrer">gender gap</a>.

This two-part blog post explores data from <a href="https://www.inclusivefintech50.com/" target="_blank" rel="noopener noreferrer">Inclusive Fintech 50</a> and <a href="https://www.themix.org/publications/fintech-benchmarks-report" target="_blank" rel="noopener noreferrer">Results of the Fintech Benchmarks Proof-of-Concept</a> to shed light on current gender disparities in the fintech industry – both at the management level and in their customer base. We provide initial insights and recommendations for investors and fintechs on overcoming some of these challenges. We hope the research community digs deeper into the disparities we highlight to understand the nuanced and sometimes intertwined barriers that female founders face, as well as how fintechs can serve the needs and preferences of female clients.

Two key insights emerge from the data focusing on early-stage fintechs:
<ul>
 	<li>Female-led fintechs face unique challenges when raising funds, but when they do, they demonstrate greater revenue generating potential compared to fintechs without women in leadership positions.</li>
 	<li>Perhaps not surprisingly, there is a gender gap in the customer base served by fintechs, and there is significant room for them to grow by addressing this gap.</li>
</ul>
In this first post, we will focus on the first point. Below are five broad observations.
<h2>1. Women are underrepresented among fintech CEOs and founders.</h2>
Female-founded companies are traditionally underrepresented in venture capital funding, and the fintech industry is no exception. In 2019, companies with a female CEO <a href="https://www.allraise.org/assets/pitchbook_all_raise_2019_all_in_women_in_the_vc_ecosystem.pdf" target="_blank" rel="noopener noreferrer">represented 11 percent of all venture capital deals</a> made globally (this increases to 20 percent if a female founder is included). However, only 7 percent of fintech VC deals had a woman in a CEO position.
<blockquote>Women are particularly underrepresented in fintechs founded in certain regions.</blockquote>
The 2019 Inclusive Fintech 50 data present a similar trend: 19 percent of the 400 applicants are female led, as defined by at least one female founder or executive. Women are particularly underrepresented in fintechs founded in certain regions – Middle East and North Africa (MENA) has the lowest share of female-led fintechs (only 8 percent), while Latin America and Caribbean and Sub-Saharan Africa stand marginally better at 15 percent and 11 percent, respectively. Furthermore, the data does not examine founders by country of origin, and female founders from developing countries may face unique barriers. As one female fintech founder from Sub-Saharan Africa explained: “A lot of the funding goes to foreign male founders. That’s one of the biggest challenges.”

<img class="aligncenter size-full wp-image-39748" src="https://content.centerforfinancialinclusion.org/wp-content/uploads/sites/2/2020/08/Number-of-female-fintech-leaders-region.png" alt="graph" width="887" height="641" />

It’s important to put this data in the broader context of women’s representation in the workforce. Financial services have long been <a href="https://www.ftadviser.com/opinion/2019/12/04/financial-services-15-year-gender-diversity-failure/" target="_blank" rel="noopener noreferrer">dominated by men</a>. There is a misconception and unconscious bias that women do “better” in roles like HR, marketing and implementation versus strategy and innovation. For instance, according the <a href="http://www3.weforum.org/docs/WEF_GGGR_2020.pdf" target="_blank" rel="noopener noreferrer">World Economic Forum</a>, women make up about 26 percent of workers in data and AI roles, 15 percent in engineering roles and 12 percent in cloud computing roles, compared to 40 percent in marketing, 37 percent in sales, and 35 percent in product development.

It’s also no secret that women – particularly women of color – are underrepresented in educational programs, like MBAs, that can provide them a stepping stone into the financial services industry. While 2019 saw an increase in the number of female MBA applicants, socio-cultural values and norms can influence a woman’s ability and decision to attend higher educational programs. Programs like <a href="https://girlswhocode.com/">Girls who Code</a> and <a href="https://girlsintech.org/">Girls in Tech</a> are working towards eliminating the gender gap in technology and recruiting/encouraging young women to enter the tech industry.
<h2>2. Female-led fintechs generate higher revenues than those without women in leadership positions.</h2>
The 2019 Inclusive Fintech 50 data did not survey fintechs on revenue per customer, but preliminary evidence from the Fintech Benchmarks Proof-of-Concept reveals that female-led fintechs generate higher revenues. Among the sample of 45 fintechs, female-led ones had nearly three times the revenue per customer of non-female-led fintechs, but also three times the cost per customer. This year’s Inclusive Fintech 50 data will examine whether this trend holds true in a larger sample.
<blockquote>Among the sample of 45 fintechs, female-led ones had nearly three times the revenue per customer.</blockquote>
These findings add to the evidence of the strong relative performance of female-led fintechs, and are consistent with research across sectors demonstrating the revenue potential of female-led companies. For example, <a href="https://www.bcg.com/publications/2018/why-women-owned-startups-are-better-bet.aspx" target="_blank" rel="noopener noreferrer">research from BCG</a> finds that female-founded startups generate 10 percent higher revenue than their male peers over a five-year period. Similarly, a study of 3,000 top global companies by Credit Suisse shows that female leadership is associated with <a href="https://www.wgea.gov.au/sites/default/files/documents/csri-gender-3000.pdf" target="_blank" rel="noopener noreferrer">higher profitability and superior financial returns</a>.
<h2>3. Female-led fintechs are able to raise funds at similar rates to their counterparts, but disparities persist in certain regions, namely, those with wide financial inclusion gender gaps.</h2>
The BCG study also revealed that female-founded startups raise less than half of what male-founded startups raise. A Harvard Business Review piece <a href="https://hbr.org/2017/06/male-and-female-entrepreneurs-get-asked-different-questions-by-vcs-and-it-affects-how-much-funding-they-get" target="_blank" rel="noopener noreferrer">echoes</a> the same conclusion – female founders are asked more challenging and skeptical questions during pitches, which leads to lower funding. This practice may be traced back to the stereotypes women face of not being the “right fit” for the role/sector.
<blockquote>Female-led inclusive fintechs raise 24 percent more than non-female-led startups.</blockquote>
The data from Inclusive Fintech 50 presents a more optimistic picture. At the median, female-led inclusive fintechs raise 24 percent more than non-female-led startups. This trend is largely driven by funding in formal investment rounds, echoing research in the U.S. from the <a href="https://startupsusa.org/women-founded-venture-backed-startups/#main-findings" target="_blank" rel="noopener noreferrer">Center for American Entrepreneurship</a> that once a female-founded startup is funded, it receives similar funding to male-founded startups in additional fundraising rounds.

<img class="aligncenter wp-image-39735 size-full" src="https://content.centerforfinancialinclusion.org/wp-content/uploads/sites/2/2020/08/meadian-annual-amount-raised-by-female-fintech-leaders-1.png" alt="" width="899" height="654" />

However, we again see that there are stark differences across geographies. The median female-led fintech raises approximately three-fourths as much as non-female-led fintechs in Latin America, two-thirds as much in East Asia and Pacific, and nearly one-third as much in South Asia. In Sub-Saharan Africa and North America, female-led fintechs raise more at the median than non-female-led fintechs, though they raise 74 percent as much in Sub-Saharan Africa when measuring the average rather than the median, as noted in this <a href="https://www.themix.org/publications/measuring-funding-flows-for-digital-financial-inclusion" target="_blank" rel="noopener noreferrer">white paper</a>. In Europe and Central Asia, there is no observed gap in funding.

Perhaps it is not surprising that these regions also have a large gender gap in broader financial inclusion. For instance, the <a href="https://www.gsma.com/mobilefordevelopment/blog/the-promise-of-mobile-money-for-further-advancing-womens-financial-inclusion/#_ftn2" target="_blank" rel="noopener noreferrer">gender gap in mobile money usage</a> is 25 percent in Latin America, 21 percent in East Asia and Pacific, and 75 percent in South Asia. In these regions, the same <a href="https://blogs.worldbank.org/voices/gender-gap-financial-inclusion-three-ways-shrink-it" target="_blank" rel="noopener noreferrer">regulations and social norms</a> that prevent women from opening bank accounts may also provide additional hurdles for female entrepreneurship in a male-dominated industry.
<h2>4. Female-led fintechs have less funds available to get started, but receive a boost from angel investors.</h2>
During the initial stage, female-led fintechs have less capacity to invest personal funds into their ventures than non-female-led fintechs – they can put in only 19 percent of what a non-female-led fintech does (see figure below). As a result, many female founders and CEOs can fail to make it to formal funding rounds, thereby reducing the number of female-led fintechs from the start.

<img class="aligncenter wp-image-39736 size-full" src="https://content.centerforfinancialinclusion.org/wp-content/uploads/sites/2/2020/08/median-annual-amount-raised-female-led-fintech-BY-FUNDING-STAGE.png" alt="graph" width="891" height="647" />

These findings are consistent with a <a href="https://www.goldmansachs.com/citizenship/10000women/news-and-events/10kw-progress-report/progress-report-full.pdf" target="_blank" rel="noopener noreferrer">study by Goldman Sachs</a> that found that female entrepreneurs in emerging markets often do not seek external financing due to challenges of navigating the process or perceptions of likelihood of success.

Female-led fintechs have performed particularly well with angel investors. Another recent <a href="https://www.tandfonline.com/doi/abs/10.1080/13691066.2020.1747692" target="_blank" rel="noopener noreferrer">study</a> found that female entrepreneurs have greater success receiving funding from angel funders than from early-stage and late-stage VCs. The Inclusive Fintech 50 data show a similar trend, with the median female-led fintech raising 80 percent more than non-female-led fintechs at the angel investor stage.
<h2>5. The network effect is weaker for female-led fintechs.</h2>
Fintechs that are “networked” – part of a fintech hub, incubator, accelerator, or award – raise <a href="https://www.themix.org/publications/measuring-funding-flows-for-digital-financial-inclusion" target="_blank" rel="noopener noreferrer">more funding than non-networked fintechs</a>. However, female-led fintechs managed to raise only 8 percent more if they were networked. Meanwhile non-female-led fintechs raised 43 percent more if they were networked. This trend is consistent with a report which found that <a href="https://www.ifc.org/wps/wcm/connect/topics_ext_content/ifc_external_corporate_site/venture+capital/vc-resources/vc-gender-financing" target="_blank" rel="noopener noreferrer">accelerators widen the equity financing gap</a>, with male-led startups experiencing a 2.6 times increase in funding raised post-acceleration relative to female-led startups.
<blockquote>Female-led fintechs managed to raise only 8 percent more if they were networked.</blockquote>
Additionally, a study that employed network analysis to <a href="https://endeavor.org/content/uploads/2015/06/Fostering-Productive-Entrepreneurship-Communities.pdf" target="_blank" rel="noopener noreferrer">assess the collective impact of entrepreneurship communities</a> found that start-ups that received experience, mentorship, or investment from an entrepreneur who has led a company to scale were approximately two times more likely to achieve top performance. It would be prudent to explore further what this means for female entrepreneurs who may face barriers accessing entrepreneurship communities that may be male-dominated.

<img class="aligncenter wp-image-39737 size-full" src="https://content.centerforfinancialinclusion.org/wp-content/uploads/sites/2/2020/08/networked-multiplier-of-female-led-fintechs.png" alt="graph" width="845" height="614" />
<h2>Recommendations</h2>
<h3>For Investors</h3>
<ul>
 	<li>Investors have the potential to address this underrepresentation by investing in more female-led, early-stage fintechs, particularly in regions such as Asia and Latin America. Investors can not only seek out fintechs with strong programs that support female leadership, but also screen out those that do not. As described above, there is evidence that female-led fintechs produce higher revenues.</li>
 	<li>In order to address funding disparities for female-led fintechs in early stages, investors can adopt gender lens investing, particularly when providing grant funding. This will build upon work done by DFS Lab, Flourish Ventures, FinEquity, and Women’s World Banking, who have sponsored a female-focused fintech competition.</li>
 	<li>Incubators and accelerators can also support early-stage, female-led fintechs by actively recruiting female startups and supporting them in raising funding and also assessing whether their programs themselves are female-friendly.</li>
 	<li>Gender-diverse hiring practices and implicit bias training are vital for investors and incubators/accelerators to reach these goals. Moreover, while we were not able to distinguish between women of color founders and white women, evidence on the institutional barriers and discrimination that people of color face likely apply to the fintech space. Implicit bias trainings play an important role in raising awareness on lending practices.</li>
</ul>
<h3>For Researchers</h3>
<ul>
 	<li>Research organizations can provide valuable evidence to build a case for investment in female-led fintechs and the nuanced barriers that female-led fintechs face. Building upon work by organizations such as Women’s World Banking, researchers can demonstrate that female-led fintechs produce strong financial returns while also making unique contributions to financial inclusion.</li>
 	<li>Additional research is needed to examine the challenges faced by female fintech founders. Inclusive Fintech 50 data sheds light onto funding amounts received by female fintechs, but it does not address potential disparities in the likelihood of receiving funds, or other discrimination that female founders -- particularly women of color -- may face.</li>
</ul>
Be on the lookout for the next post, when we will discuss how fintechs may be able to close the gender gap in financial inclusion for their users.

Including Women in “Inclusive Fintech”