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Fellow Exec Ed

Blog Post

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

Brief

When financial sectors are buffeted by sudden and dramatic external shocks, regulators strive to implement targeted regulatory responses to mitigate negative impacts -- and the shocks made by the pandemic were no exception.

The aim of this policy brief is to examine the types of regulatory flexibility adopted in response to the pandemic and provide early evidence on the impact of these measures.
<h3>The Purpose of This Brief</h3>
Based on desk research and interviews and exchanges with regulators and financial service providers (FSPs), this paper aims for the following:
<ul>
 	<li>Describe the main types of regulatory flexibility adopted in developing and emerging economies as a response to the pandemic.</li>
 	<li>Provide preliminary evidence of how regulatory flexibility has impacted low-income financial consumers and micro and small enterprises (MSEs), as well as the FSPs that serve them.</li>
 	<li>Draw some emerging lessons for regulators seeking to better prepare for the future.</li>
</ul>
This is the third in a <a href="https://www.centerforfinancialinclusion.org/series/policy-responses-to-covid-19-their-impacts-on-low-income-customers" target="_blank" rel="noopener noreferrer">series of policy briefs</a> that aim to analyze policy responses to COVID-19 to assess the impact of policies, both in the short- and long-term, on low-income customers of financial services and the financial service providers that work with them.

Regulatory Flexibility During the Pandemic: Emerging Lessons

Webinar

<h3>Join us on Thursday, March 18, at 9 am EST/3 pm CET as we discuss findings on regulatory policy during COVID, present emerging data from CFI’s research on the impact of COVID on MSMEs, and determine key lessons for policymakers.</h3>
The implications of the pandemic have been broad and far-reaching on low-income populations as well as on the financial service providers (FSPs) that serve them.

CFI’s latest policy brief, “<a href="https://centerforfinancialinclusion.org/regulatory-flexibility-during-the-pandemic-emerging-lessons/" target="_blank" rel="noopener noreferrer">Regulatory Flexibility During the Pandemic: Emerging Lessons</a>,” looks at prudential measures aimed at keeping credit flowing in the economy. These measures were particularly critical to the banking and microfinance sectors, which faced seriously deteriorating borrower repayment capacity, triggered by the uncertain recovery prospects of the global and local economies. A credit crunch would only make matters worse for financial service providers (FSPs) and customers alike.

CFI has also been capturing emerging data every other month on the impact of COVID-19 on the operations of MSMEs in Nigeria, India, Indonesia, and Colombia. Data captured for this research covered different periods in time in each of these markets, as the pandemic ebbed and flowed, and as policy measures were implemented and expired. CFI's recently published <a href="https://centerforfinancialinclusion.org/on-the-economic-frontlines-of-covid-19-early-insights-from-msmes-grappling-with-the-crisis/" target="_blank" rel="noopener noreferrer">analysis of the first wave of data</a> is organized by nine key insights.

The policy brief takes a close look at the following policy measures:
<ul>
 	<li>Flexibility for forborne loans, such as not requiring re-classification of non-performing loans due to COVID-19</li>
 	<li>Reduction of capital adequacy ratios and absolute capital requirements</li>
 	<li>Reduction of risk-weighting of MSME loans</li>
 	<li>Release of capital buffers</li>
 	<li>Reduction of reserve and liquidity requirements</li>
</ul>
By analyzing both the policy measures and the data on MSMEs, we aim to draw out lessons for policymakers on the measures that are likely to produce positive outcomes -- or at least reduce the harms of COVID -- on individuals and MSMEs.

CFI’s analysis also draws on interviews with FSPs, policymakers, and other stakeholders around the world and identifies early lessons on the impact of these measures on providers and the flow of credit in these economies.
<h2>Our Guests</h2>
<ul>
 	<li>
<h3><a href="https://www.mastercardcenter.org/our-team/payal-dalal" target="_blank" rel="noopener noreferrer">Payal Dalal</a>, Mastercard Center for Inclusive Growth</h3>
</li>
 	<li>
<h3><a href="https://www.cgap.org/about/people/rashmi-pillai" target="_blank" rel="noopener noreferrer">Rashmi Pillai</a>, FSD Uganda</h3>
</li>
 	<li>
<h3><a href="https://blogs.worldbank.org/team/syed-mohsin-ahmed" target="_blank" rel="noopener noreferrer">Syed Mohsin Ahmed</a>, Pakistan Microfinance Network</h3>
</li>
 	<li>
<h3><a href="https://www.centerforfinancialinclusion.org/bio/denise-dias" target="_blank" rel="noopener noreferrer">Denise Dias</a>, Financial Regulatory and Supervisory Consultant and CFI Author</h3>
</li>
 	<li>
<h3><a href="https://centerforfinancialinclusion.org/people/eric-noggle/" target="_blank" rel="noopener noreferrer">Eric Noggle</a>, Center for Financial Inclusion</h3>
</li>
</ul>
<h3>Moderator: <a href="https://centerforfinancialinclusion.org/people/mayada-el-zoghbi/" target="_blank" rel="noopener noreferrer">Mayada El-Zoghbi</a>, Center for Financial Inclusion</h3>

Live Discussion: COVID-19 Policy Measures and the Impact on MSMEs

Weathering the Storm II: A Case Study of Financiera FAMA

The data from CFI’s surveys on emerging-market MSMEs tells a stark tale: COVID-19 has closed 15 percent of all businesses; 83 percent of operating MSMEs have seen a dramatic decline in profits, leading to struggles covering operating expenses; 46 percent of closed MSMEs report government-imposed restrictions on movement as the most direct cause of their business closure. There is no obvious "best practice" coping strategy MSMEs are using, and it’s a tough road for many MSMEs trying to return to pre-pandemic financial health.

Armed with the right insights and data, however, policymakers and other ecosystem actors can target interventions that help rather than harm.

This brief contains insights needed to support MSME recovery. It summarizes and analyzes the first wave of data from a research project on the financial health of MSME owners/operators during COVID-19. At the program's core is a longitudinal, six-wave survey in four countries: Colombia, India, Indonesia, and Nigeria. In each country, CFI is surveying MSME clients at one financial institution participating in our <a href="https://centerforfinancialinclusion.org/understanding-covid19s-impact-on-financial-health-of-msmes/" target="_blank" rel="noopener noreferrer">partnership</a> with Mastercard every other month for one year.

Visit the <a href="https://centerforfinancialinclusion.org/covid-19-and-msmes-data-and-analysis-to-understand-impact/" target="_blank" rel="noopener noreferrer">COVID-19 and MSMEs: Data and Analysis to Understand Impact</a> program page to interact with the data dashboards and read other analyses.

On the Economic Frontlines of COVID-19: Early Insights From MSMEs Grappling With the Crisis

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Alex Kessler

This is the first in a series of blog posts that explores the endless-data era’s impacts on financial inclusion.

Denise Dias

Loretta Michaels

CFI conducted this work as part of our partnerships with the Mastercard Center for Inclusive Growth and Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH. 

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Garrett Jaso

Eric Noggle

This research is part of our partnership with the Mastercard Center for Inclusive Growth.

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