What counts as financial inclusion? Reporting the number of active accounts in a country is a common way to measure progress in financial inclusion. But as access to, and uptake of, accounts increases, we need more powerful indicators to help us understand the dynamics of how people use financial services, and digital financial services in particular.

At <a href="https://i2ifacility.org/">insight2impact</a>, we’ve spent the last four years exploring these questions and have tested our measurement frameworks and emergent indicators on both demand-side survey data and transactional data in Mexico and Nigeria. We also went further by linking the data sets for the same person to analyze a more complete picture of people’s financial lives, both within and outside of formal financial services. What we found was both curious and transformative for our thinking on how we measure financial inclusion.
<h2>Frequency as a Means to Track Digitization</h2>
The first step to financial inclusion is <a href="http://www.worldbank.org/en/topic/financialinclusion/overview">having access to a transactional account</a>. If I choose to take up an account, I’m able to store money or send and receive payments, but if I use my account very rarely, am I still financially included? Maybe I receive a payment and immediately withdraw it all at an ATM. What if all the transactions I need to do can only be done in cash?

Analyzing frequency of usage gives us an indication of how populations are (or aren’t) switching to digital channels for transacting. We analyzed bank transaction data in Mexico to better understand financial service usage patterns. Debit-card usage by customers was relatively high, with 78 percent using their cards weekly, but 60 percent of monthly card usage occurred at ATMs to withdraw cash, not for purchases via POS or online. The frequency of ATM vs non-ATM card usage paints a more realistic picture of digitization in Mexico. It’s a picture of incomplete digitization, with cash remaining central for most people.

Secondly, we linked the transaction data to survey responses to compare people’s online vs offline transaction behavior. This revealed that most people still use cash for their regular expenses, even if they have a bank account. The graph below shows both banked and unbanked people’s cash usage for regular expenses such as rent and bills, and daily expenses such as groceries and transport. Cash was ubiquitous, regardless of gender, socio-economic segment or account ownership. By only counting the accounts, we would miss the scale of non-digital financial lives.

Counting More than Accounts: What Can Frequency of Transactions Tell Us About Financial Inclusion?

Latin America and The Caribbean

Mexico

Nigeria

Sub-Saharan Africa

Access Usage Gap

Data Analytics

Enabling Environment

Financial Capability

Financial Technology

Payments

Personal Financial Management

Blog Post

As a means of reaching underserved customers at low cost, financial institutions have designated authority and responsibility to banking agents to deliver financial products and services. Agent banking is a model for delivering financial services whereby an institution — be it a financial service provider or a mobile network operator — partners with a retail agent to extend services in remote or hard-to-reach areas.
<blockquote>Innovative financial institutions are streamlining and digitizing their processes, and utilizing real-time data and analytics to increase both the efficiency and effectiveness of agent networks.</blockquote>
Despite the growing volume of agents, the agent network model is rife with utilization and operational challenges. The good news is that technology offers financial institutions an opportunity to make agent models more efficient and productive for themselves and their customers. Based on in-depth interviews with industry experts and senior bank officers, and supplemented by a review of the literature, this brief examines the role of technological innovation as a potential driver for improving the quality and maximizing the productivity of agent models.

We found it useful to study this topic across two time-horizons: the short-and long-term; and from the perspectives of the main stakeholders in the agent network triad: the financial institution, the agent, and the customer. This structure allows us to account for two key trends: 1) the diminishing role of cash as a payment form, and 2) an increasing readiness of institutions to embrace digital transformation. It also allows us to explore commonly-cited challenges with agent networks through an illustrative, hypothetical narrative lens, giving voice to each stakeholder group. The narratives are accompanied by real-world examples of how technological integration and innovation has helped to improve and streamline processes within agent networks. Finally, we anticipate that in a future financial services ecosystem that is digital and cashless or cash-lite, we will see the role of the agent evolving from transaction processors to solution providers.

Leveraging Technologies to Improve the Quality and Maximize the Productivity of Agent Models

Institute of International Finance

MetLife Foundation

Mainstreaming Financial Inclusion: Best Practices

Agent Banking

Banks

Delivery Channels

Financial Service Providers

Fintechs

Partnerships

Rural Populations

Telcos

Underserved Groups

Report

There’s much anticipation that combining new data and artificial intelligence will transform the pace of financial inclusion and the scale at which it’s possible.

It’s easy to see why. AI is being used to rapidly perform tasks that would otherwise require endless hours of human labor. It can, for example, sift through and analyze enormous volumes of <a href="https://www.centerforfinancialinclusion.org/to-bank-the-unbanked-start-using-alternative-data">non-traditional sources of data</a> to expand access to credit. It can digitally verify identities, detect fraud, and <a href="https://www.centerforfinancialinclusion.org/juntos-harnesses-artificial-intelligence-to-improve-customer-engagement-for-bbva-bancomer-and-bancolombia">improve customer engagement</a>.

Institutions view AI as a tool that could greatly expand the number of customers they serve without having to scale their workforces by anywhere near as much.

This reasoning is compelling, but it obscures a wider point: the technologies that drive automation require people with specialized technical skills to implement, monitor, and refine them. These people are, for now at least, in very short supply.

We’re the authors of an upcoming report investigating the risks that will arise as financial institutions increasingly embrace AI (to be published by the <a href="http://www.csfi.org/">Centre for the Study of Financial Innovation</a> [CSFI] later this year). Our research suggests that one of the most fundamental of these risks - and a threat to institutions, their customers, and the financial system as a whole - is a pervasive skills gap.
<h2>The Data Scientist Problem</h2>
Last year, the CSFI’s "<a href="https://www.centerforfinancialinclusion.org/finance-for-all-wedded-to-fintech-for-better-or-worse">Finance for All</a>" report surveyed respondents from the financial inclusion sector on the 20 greatest “banana skins” – risks financial inclusion professionals believe pose the greatest challenges for service providers. At the top of the rankings was technology: the risk that the industry fails to take advantage of new technologies or implements them poorly.

Meanwhile, one of the fastest rising risks was talent: the ability (or not) of service providers to attract and retain suitably qualified staff. In 2016, it ranked 15th; last year it was 8th. But this ranking, if anything, understates its importance. In many ways talent risk lies at the heart of technology risk.

A <a href="https://www.centerforfinancialinclusion.org/accelerating-financial-inclusion-with-new-data-2">report</a> published last year by the CFI and the <a href="https://www.iif.com/">Institute of International Finance</a> (IIF) found:

“Banks face a tremendous shortage of experienced data scientists and engineers, as well as AI experts, all of whom are needed to help convert big data “noise” into meaningful insights. Even relatively basic data skills are lacking in many major institutions, resulting in wasted resources, project delays, and squandered opportunities.”

Who are these people in short supply, and why do their skills matter?

Data scientists write the algorithms that underpin AI applications and determine which data should be used as inputs. They work with data engineers, architects, and operations specialists to test, implement, and monitor these algorithms on an ongoing basis for flaws and failings. Before doing any of this, they must work closely with the business in order to gain a detailed understanding of customer requirements. In other words, they define what it is the AI should do.

There is a global shortage of data scientists. A recent study by LinkedIn, for example, <a href="https://economicgraph.linkedin.com/resources/linkedin-workforce-report-august-2018">found</a> that “demand for data scientists is off the charts” in the US. It identified a deficit of more than 150,000 professionals. The Chinese shortfall is predicted to reach 1.5 million vacant positions by 2020.
<blockquote>This shortage is especially pronounced in the developing countries, which tend to have higher levels of financial exclusion.</blockquote>
This shortage is especially pronounced in the developing countries, which tend to have higher levels of financial exclusion. For example, in 2017 it was <a href="https://www.itproportal.com/features/a-snapshot-of-data-scientist-jobs-around-the-world/">estimated</a> that there were just 300 to 400 data scientists in the whole of Thailand - and a current deficit of around 1 million people in the Asia Pacific region as a whole. A further concern is that the gap between leading AI centers and the rest of the world is likely to diverge rather than converge over the coming years. A <a href="https://www.mckinsey.com/~/media/McKinsey/Featured%20Insights/Artificial%20Intelligence/Notes%20from%20the%20frontier%20Modeling%20the%20impact%20of%20AI%20on%20the%20world%20economy/MGI-Notes-from-the-AI-frontier-Modeling-the-impact-of-AI-on-the-world-economy-September-2018.ashx">report</a> by the consultancy McKinsey found that increasing adoption of AI threatens to: “widen gaps between countries, companies, and workers.”
<h2>Traditional Financial Institutions Could Struggle to Attract Technical Talent</h2>
Data scientists and other AI specialists with in-demand skills are likely to have competing opportunities for well-paid and exciting work from many different industries. Nimble fintech start-ups with business models that use AI to rapidly scale financial services in previously unreachable markets may be an attractive destination. However, staff of Accion’s fintech investment funds report that talent acquisition ranks very high on the challenges their investee companies face.

More traditional financial institutions - from banks to MFIs - could find it even harder to sell themselves. A large number of respondents to the Finance for All survey were concerned that traditional institutions are not offering enough to attract and retain ambitious talent – in terms of compensation, challenging work, and advancement opportunities. A respondent at an MFI in Zimbabwe predicted, “There will be increased mobility of skilled staff to more challenging and rewarding institutions, as well as more technologically mobile institutions.” In particular, skilled technical people who might otherwise be interested in the industry are frustrated by legacy IT systems and infrastructure, which make it difficult to perform even basic IT tasks - let alone collect and analyze new kinds of data and collaborate with external AI providers.
<h2>Consequences of Not Attracting the Right People</h2>
For those service providers seeking to develop their own AI capabilities - particularly the largest financial institutions - the challenge is twofold. They need to attract a sufficiently deep pool of technical talent to avoid rushing solutions to markets that are buggy and vulnerable to outages and hacking. They also need to attract the right people – data scientists who understand the financial inclusion sector and can help build applications designed to meet the needs of customers, rather than building clever solutions in search of a problem. The need to find skilled technical people with relevant domain expertise makes a small pool of prospective candidates even smaller.

But it isn’t just the innovators that need to get this right. The majority of institutions that don’t intend to develop their own AI capabilities are also threatened by the absence of specialist knowledge – because they will <a href="https://www.centerforfinancialinclusion.org/how-financial-institutions-and-fintechs-are-partnering-for-inclusion-lessons-from-the-frontlines-2">increasingly form partnerships</a> with fintechs.

To form successful partnerships, these institutions need to know which AI applications and third-party providers can be adapted to their business models - and, equally importantly, which should be avoided. They need to understand how to shape a strategy around AI: to what extent and in what ways they should rely on third party solutions, and the capital outlay and time needed to implement them. There are myriad other risks brought about by the decision to employ AI, from how to protect sensitive data to how to comply with regulatory requirements. It is difficult to mitigate these risks without specialist knowledge.

This is especially important in a climate where institutional survival may depend on the ability to adapt to new technologies. Alongside the fintechs that provide effective and useful solutions will be others that are prematurely hyped. Todd Farrington, Director at Symbiotics S.A. in Mexico, observed in Finance for All, “The proliferation of fintech solutions is promising, but many algorithms remain insufficiently back-tested, many companies young and overly ambitious.” Decision makers at partnering institutions who are under pressure need people who can demystify the rapidly changing technological environment.

There are also potential implications for market structures. The concentration of AI talent in developed economies could lead to more multinational financial institutions – or fintech start-ups that originate in developed countries – capturing large underserved markets and undermining the competitiveness of local operators. If foreign entrants gain decisive market share via first mover advantage, they’re likely to benefit from economies of scale that domestic competitors will find difficult to overcome.
<blockquote>If foreign entrants gain decisive market share via first mover advantage, they’re likely to benefit from economies of scale that domestic competitors will find difficult to overcome.</blockquote>
<h2>Prioritize Data Science Training</h2>
These are not questions with straightforward answers. The training of many more data scientists and other AI specialists needs to be prioritized, in financial institutions’ boardrooms and at a national level. The South African government, for example, <a href="https://businesstech.co.za/news/government/267135/government-wants-one-million-data-scientists/">said</a> last year that it would train one million young people in data science skills over the next decade. Firms will have to get better at attracting technical staff, by improving incentives and overhauling antiquated IT infrastructure.

The crucial point is that the industry needs to prioritize bridging this skills gap immediately, and for the longer term. Otherwise, we may well find that the key factor limiting the benefits of the AI revolution in financial inclusion is not the technology or the data, but the ability to attract the right people.

Is Human Talent the Limiting Factor? Financial Inclusion, New Data and AI

“How much money do people typically imagine they should have when saving for emergency needs? Is that different from what they need for the children’s education? What kinds of conversations are field staff having?

These and similar questions are quite familiar to financial institutions trying to mobilize long-term savings from low-income clients through their field staff. In this blog post, we share the story of how mobile application usage data allowed <a href="http://www.sajidafoundation.org/">SAJIDA Foundation</a>, an <a href="https://optixproject.org/">OPTIX</a> partner from Bangladesh to gain insights into member-staff conversations without actually being there: a kind of virtual “fly on the wall”. They gained an unprecedented look into how financial planning really unfolds as they sought to tailor a term-deposit product to people’s needs.

In October 2017, <a href="https://nextbillion.net/cross-sell-done-well-how-one-finance-app-found-a-balance-between-digital-and-human-touch/">we introduced the Financial Advisory Services (FAS) mobile app</a> designed to allow field officers at SAJIDA Foundation to identify members (as SAJIDA calls its clients) with longer-term savings potential, structure conversations around life goals, and simulate scenarios to arrive at appropriate amounts and terms for the term-deposit savings account.

Built into the FAS app is the capability to collect detailed usage data, including when and where the app was used, what actions were undertaken, and what information was entered to simulate scenarios. Any interaction on the device, such as the click of a button, filling in a text field, or submitting a form, is recorded. More than 20 officers used the FAS in 2017 and undertook 11,793 actions on the app. By threading together consecutive actions, we can approximately reconstruct actual conversations.
<h3>FAS app frames conversations as intended…and then some</h3>
When starting a conversation, field officers mention most of the savings goals the FAS offers (Figure 1). Users were able to choose from a list of eight specific goals and one “other.” These goals are chosen based on qualitative research with members and staff, and appear to be a fairly accurate representation of member savings goals. “Emergency Needs” is the most common, featuring in 31 percent of the conversations. The icon “For Children” comes second, at 25 percent. “Livestock” features in only 1 percent of the conversations, leading us to question its permanence on the goal screen.

An App, a Conversation and a New Account: A Novel Approach to Term Deposits in Dhaka

Bangladesh

Customer Centricity

Saving

This webinar features CFI Fellow Patrick Traynor — Professor in the Department of Computer and Information Science and Engineering (CISE) at the University of Florida. Our conversation will provide an overview of data privacy and security issues in online lending, highlight specific deficiencies as identified in our three-pronged analysis of over 50 digital finance providers, and provide recommendations for providers so they can ensure that consumers have the best possible protections of their personal data.

This research raises important concerns about how digital finance companies currently address data privacy and security issues and points to areas for improvement when creating strong defense mechanisms and privacy policies that protect consumer data. By examining digital lenders’ privacy policies, the mechanisms for securing the connections between customers’ mobile devices and the internal servers that process and store that data, and the terms of service of their offerings, Patrick's report aims to identify how well providers are addressing these data privacy and security vulnerabilities and lays the groundwork for future research that can assist companies, consumers, and regulators in improving security standards for digital finance.

Webinar: Digital Finance and Data Security

CFI Research Fellows Program

Digital Credit

Digital Financial Services

Webinar

&gt; Posted by Maha Khan and Marissa Dean, <a href="http://www.financedigitalafrica.org/about/">FiDA Partnership</a>

Big data is a big buzzword in the digital finance community. As more people weave digital technology into their lives, financial service providers (FSPs) can use the data generated from these digital interactions (e.g., mobile money transactions, SMS messages, mobile app activity, etc.) to create more tailored financial products and to attract new customers previously excluded from formal financial services. <a href="https://www.centerforfinancialinclusion.org/publications-a-resources/browse-publications/1030-accelerating-financial-inclusion-with-new-data">Accelerating Financial Inclusion with New Data</a>, a joint report from the Center for Financial Inclusion at Accion (CFI) and the Institute of International Finance (IIF), discusses the types of data sources and tools that FSPs can use to better understand and serve low-income and hard-to-reach clients.

To understand how FSPs—ranging from banks and mobile network operators (MNOs) to Fintechs—use (or don’t use) big data analytics, the Mastercard Foundation <a href="http://www.financedigitalafrica.org/about/">Partnership for Finance in a Digital Africa</a> (FiDA) conducted <a href="http://www.financedigitalafrica.org/research/2018/03/can-big-data-shape-financial-services-in-east-africa/">research in East Africa</a> in late 2017. Interviews with a range of organizations suggest that these companies have been relying on analytics of traditional or big datasets, but there is a slow (but steady) uptake of big data and analytics. As a result, there has been an expansion of products and services leveraging alternative data sources. According to the interviews, four factors constrain rapid growth in this sector:
<ul>
 	<li>Lenders have a limited use case for third-party data</li>
 	<li>Organizations are pursuing partnership models in lieu of transactional relationships</li>
 	<li>Most of the organizations interviewed are still testing, refining and experimenting with which datasets are most predictive, as well as validating their analytical models</li>
 	<li>Most banks and fintechs believe a business case that is strategy- and leadership-led is essential to the uptake of big data and analytics.</li>
</ul>
Nevertheless, there are companies in sub-Saharan Africa that are leveraging big data analytics to grant small amounts of credit to customers via a mobile wallet or airtime account. For instance, M-Shwari, a combined savings and loan product, was one of the first to experiment with developing algorithms based on mobile behavior data in order to offer low-value credit to customers in 2013. In December 2017, M-Shwari announced that they will segment customers who repay their loans on time and have positive savings behavior.

However, FiDA’s interviews with financial services providers found that <a href="http://www.financedigitalafrica.org/blog/2018/06/virtue-and-value-in-mobile-operator-big-data/">mobile behavior data has significant limitations</a> as the data does not give a holistic picture of an individual’s spending or device behavior. But more specifically, MNOs don’t share behavior data freely, and for good reasons. Their perception of regulation on data sharing is that MNOs cannot give individualized information to third parties without consent from the customer and the regulator. Additionally, and perhaps most importantly, MNOs believe that selling raw customer data would erode their hard earned customer trust.

Moreover, as algorithms based on behavioral data become more prevalent, providers will find themselves constantly playing a game of cat and mouse with fraudsters who want to take advantage of the all-digital nature of these products in order to scale successful fraud schemes to high volume. This is the flip side of big data, which is normally thought of as a way to scale successful products to high volume.

[caption id="attachment_25859" align="alignright" width="317"]<img class=" wp-image-25859 alignright" src="https://content.centerforfinancialinclusion.org/wp-content/uploads/sites/2/2018/08/harvesting-inc-mapped-cropland-e1534776447996.png" alt="harvesting-inc-mapped-cropland" width="317" height="254" /> Cropland in Maharashtra, India, mapped from satellite imagery. (Credit: Harvesting Inc.)[/caption]

The absence of a marketplace to profitably exchange big data—for example, between fintechs and FSPs—could indicate that it’s too early for big data exchanges or transactions. Nevertheless, progress will come gradually, and partnerships among mobile network operators, banks, and fintechs will be crucial to success. At the end of the day, organizations will need to weigh the value of being a pioneer against the current market challenges. In fact, FiDA recently published a <a href="http://www.financedigitalafrica.org/research/2018/07/launching-into-space-using-satellite-imagery-in-financial-services/">case study on satellite imagery in financial services</a>, and will be publishing a second one (on psychometric assessments in lending) that presents the journeys of fintechs that have integrated big data in their business and product offerings, and how they have partnered with financial institutions to implement these analytics. FiDA is excited to see CFI and IIF explore the potential of big data and analytics in financial services and will keenly watch this space.

&nbsp;

Why Big Data Is a Big Can of Worms

This post is one of five entries related to the report “<a href="http://www.centerforfinancialinclusion.org/publications-a-resources/browse-publications/1030-accelerating-financial-inclusion-with-new-data">Accelerating Financial Inclusion with New Data</a>,” a collaboration between CFI and the Institute of International Finance (IIF).

One might think that with the explosion of new types of data and advanced analytics there would be an abundance of low-hanging fruit for financial service providers to feast on. While the excitement about the potential of non-traditional data may be justifiable, the reality is that the hard work of building the networks to derive value from such data is just getting underway. Just as the invention of the automobile required the development of roads, signage, lighting, laws and regulations, so too will data need its own groundwork before it can bring transformative change to the financial system and society at large.

Any change of this magnitude also requires large-scale collaboration to ensure that the infrastructure and standards put in place are broadly applicable across technologies, data types, industries and countries. As such, alongside the many in-house and bilateral initiatives afoot across various providers and markets, there needs to be a much more holistic and collaborative approach to developing data ecosystems that can align principles, practices and standards to facilitate the flow of data through value chains and across geographies.
<blockquote>Complexity and fragmentation across a growing number of holders of data and in legal and regulatory environments makes it essential to work at an ecosystem level to allow data to flow more freely.</blockquote>
Our recently released report, <a href="https://www.centerforfinancialinclusion.org/publications-a-resources/browse-publications/1030-accelerating-financial-inclusion-with-new-data">Accelerating Financial Inclusion with New Data</a>, discusses various impediments to unlocking data’s potential, ranging from determining which types of data to leverage to how to access it, to where data can be stored and how to integrate it with existing data and systems. For example, mobile network operators are often reluctant to engage in agreements with third parties to share mobile phone data, known as call detail records, because of regulatory ambiguity about what can be shared – and to retain a competitive advantage. Social media companies restrict the data third parties can access, and some have policies that prohibit the use of their data for credit scoring. Other obstacles include varying regulation of cross-border data flows, a shortage of specialized expertise in data management and analytics, and a lack of standardization. All of this results in complexity and fragmentation across a growing number of holders of data and in legal and regulatory environments, making it essential to work at an ecosystem level to allow data to flow more freely.

Fortunately, a number of developments reflect this ecosystem-building approach. A recent Brookings Institution <a href="https://www.brookings.edu/research/regulating-for-a-digital-economy-understanding-the-importance-of-cross-border-data-flows-in-asia/">report</a> addressing cross-border data flows in Asia explained that despite the enormous economic benefits brought on by the global flow of data, governments are increasingly turning to what is referred to as data localization to restrict data flows. At the same time, however, the report provides some examples of solutions that facilitate the free flow of data among countries with different approaches to privacy. Citing the Cross-Border Privacy Rules developed by the Asia-Pacific Economic Cooperation (APEC) forum, it says, “A key benefit of the APEC regime is that it enables personal data to flow freely even in the absence of two governments having agreed to formally recognize each other’s privacy laws as equivalent. Instead, APEC relies on businesses to ensure that data collected and then sent to third parties either domestically or overseas continues to protect the data consistent with APEC privacy principles.” Various other frameworks of this nature have emerged as well, which are helping to build the connections needed for our increasingly data-driven economies to thrive.

In a new <a href="https://www.slideshare.net/slideshow/embed_code/key/mK7BOSft2scEUj">report</a> exploring trends in how data is being shared in emerging markets, Rafe Mazer, a consultant specializing in consumer protection and competition in financial services, addresses the emergence of a variety of public and private sector-led data sharing models and offers a set of considerations for assessing their fit for different country contexts. The report identifies the challenge posed by the concentration of data in “data silos” and says, “In these data silos the firm that generates or collects the data on the consumer defines the terms of use of the data up front in a way that limits the consumer’s right to access this data or share it, while giving wide-ranging and often ill-defined rights to the firm to share and sell consumers’ account data to third party service providers.” Mazer emphasizes the need for providers, policymakers and others to replace these silos with open data sharing models and concludes that “the single most important action to support data sharing in emerging markets is likely to be policy reforms, as experiences in other markets point to a need to compel certain minimum levels of data sharing for these models to reach a national scale.”
<blockquote>We hope to see more holistic and collaborative approaches to developing data ecosystems that can align principles, practices and standards to facilitate the flow of data.</blockquote>
While significant progress has already been made in finding innovative ways to leverage non-traditional data, much of what has taken place to date has been through internal experimentation or bilateral arrangements, such as <a href="https://www.centerforfinancialinclusion.org/publications-a-resources/browse-publications/872-how-financial-institutions-and-fintechs-are-partnering-for-inclusion">partnerships between financial institutions and fintechs</a>. Looking ahead, we hope to see an expansion of comprehensive multi-party arrangements that can help to channel the ever-increasing flows of new data into our broader efforts to advance financial inclusion.

Building Data Ecosystems for Financial Inclusion

Alternative Data

Policy, Regulation and Government Initiatives

Privacy

With the explosive growth of data and the breakneck pace of digitization, mainstream financial service providers (FSPs) are increasingly turning to new and alternative data sources and analytics tools to more efficiently reach emerging markets and help bring the world’s 1.7 billion underserved people into the formal financial system. This “new data,” largely separate from traditional credit bureau data, represents a tremendous opportunity for commercial banks to identity new customers, many of whom were previously “credit invisible,” and to better understand and serve the needs of their existing client base. However, the path to greater data utilization is not always clear, as FSPs must weigh the benefits of embracing a data-centric approach with significant operational challenges, including changing a risk-adverse banking culture, recruiting top technical talent, upgrading legacy IT infrastructure and navigating a complex regulatory environment. Building upon in-depth interviews with banks, fintechs and other actors, <a href="http://bit.ly/Data4FI">Accelerating Financial Inclusion with New Data</a>—the newest joint report from the Center for Financial Inclusion at Accion (CFI) and the Institute of International Finance (IIF), supported by MetLife Foundation—examines the data landscape and evaluates the progress FSPs have made in innovating around data and areas where they have faced obstacles.
<blockquote>
<h4>The path to greater data utilization is not always clear, as providers must weigh the benefits of embracing a data-centric approach with significant operational challenges.</h4>
</blockquote>
The sheer volume of data now available to mainstream FSPs is truly immense, with some estimates projecting the size of the digital universe to increase five-fold between 2015 and 2020.

<img class="alignnone size-full wp-image-25687" src="https://content.centerforfinancialinclusion.org/wp-content/uploads/sites/2/2018/06/2_twittercharts.png" alt="Growth of Global Data Graphic" width="1020" height="512" />

Emerging technologies such as artificial intelligence and blockchain will only enhance providers’ ability to analyze both traditional and non-traditional data. For providers looking to break into emerging markets, leveraging alternative data—which includes, but is not limited to data derived from social media, email, utility payments history, mobile phone and e-commerce activity, and psychometric test results—is a necessity.

It is difficult, in practice, to collect alternative data, convert it into a format which can be readily analyzed, and extract actionable insights without collaborating extensively with external partners or building up internal capacity.

But as our interviews with banks and fintechs revealed, it is difficult, in practice, to collect this data, convert it into a format which can be readily analyzed, and extract actionable insights without collaborating extensively with external partners or building up internal capacity. Banks and fintechs commonly source non-traditional data from third party providers (such as utility companies, social media companies, and mobile network operators), frequently a time-consuming process which is further complicated by data privacy, protection and ownership regulations, KYC requirements, anti-money laundering statutes and the like. FSPs sometimes end up deploying multiple solutions for various jurisdictions/countries to comply with these rules. For example, Artoo—a customer relationship management (CRM) solutions company working with microfinance and other lending institutions in India—had to switch from using Amazon Web Services to another local cloud service provider to satisfy Indian data localization laws that mandate the retention of customer data within the country’s borders.

<img class=" size-full wp-image-25688 aligncenter" src="https://content.centerforfinancialinclusion.org/wp-content/uploads/sites/2/2018/06/5_twittercharts.png" alt="The data journey infographic" width="1020" height="1167" />

Ultimately, FSPs might find that only some alternative data types are useful, as their utility is contextual and depends heavily upon the particular product or use case in question. There is no “one-size-fits-all” solution for tapping into underserved markets.

Despite the constraints, <a href="http://bit.ly/Data4FI">our research</a> also shows that many FSPs have found success utilizing new data sources and analytics tools. Our report details four snapshots highlighting different products and approaches to data-driven innovation:
<ul>
 	<li>As China’s first private online-only bank, WeBank has capitalized on its connections to tech giant Tencent and utilizes an iterative approach to incorporating social media data into its loan decisioning processes.</li>
 	<li>In Mexico, BBVA Bancomer has pursued partnerships with fintechs to test new alternative credit scoring and customer engagement strategies in combination with internal efforts to change customers’ use of transactional products, such as checking and savings accounts.</li>
 	<li>Following in the footsteps of Bangladesh’s Grameen Bank, Grameen America has taken a high-touch approach by collecting data directly from customers, instead of using credit scores and other external data sources for its lending decisions.</li>
 	<li>SCB Abacus has spun off entirely from Siam Commercial Bank to achieve greater flexibility and autonomy needed to pursue digital innovation.</li>
</ul>
These examples, and others featured throughout the report, underscore the benefits for banks and fintechs of data-centric innovation and proactive engagement with the broader ecosystem of players in this space, including financial regulators and other policymakers.

<a href="http://bit.ly/Data4FI">Accelerating Financial Inclusion with New Data</a> represents a concerted effort to evaluate the impact and potential of new data and analytics techniques for financial inclusion, and illuminate how mainstream financial institutions and fintechs have adapted their strategies to reach underserved customers in this increasingly data-centric world.

&nbsp;

&nbsp;

Accelerating Financial Inclusion with New Data

Blockchain and Cryptocurrency

<h6>LEGACY AND NEW FINANCIAL SERVICE PROVIDERS HAVE A LOT TO GAIN FROM NEW DATA</h6>
<h3>The traditional boundaries separating players in adjacent industries are blurring, and the future market for financial services is up for grabs.</h3>
There are many internal and external challenges that providers must address for the promise of new data to be fully realized. From getting the right culture and technical talent in place to engaging with regulators and partners on data sharing and management, there are numerous obstacles to negotiate in capitalizing on the explosion of new data to reach underserved and unserved markets with new commercially viable solutions.

This report is intended to help mainstream financial institutions accelerate their efforts to confront these challenges and future-proof themselves for what the data revolution has in store, but may be useful to other financial service providers as well. However, this report is not an attempt to provide a “how-to” guide for navigating the various stages of the data value chain—there are too many contingencies to prescribe a “one-size-fits-all” solution. Instead, it is an effort to shed light on the potential of data to improve financial services for the underserved.

After launching and operating mobile money businesses in a number of markets over the last ten years, I was aware of the necessity of protecting consumers. I knew it was a regulatory priority alongside important issues such as AML and interoperability, but that’s where I left it: in the compliance box, while I waited to be told what to do. All the consumer protection literature I read gave me the same heavy feeling, laden as it is with long lists of requirements: protect customer’s funds from loss and fraud, ensure proper disclosure and transparency, keep their data private, make sure customers can have their complaints resolved, and so forth. These looked like the core business processes I needed to implement anyway, so I felt we would be in fine shape if we were ever to have a supervisory inspection. I never looked any deeper.

In the days when enabling regulation meant “Please leave us alone to grow,” I kept my head turned firmly in the direction of my business goals, growing a base of active customers to reach scale, and then taking advantage of those network effects. After all, financial inclusion was also an objective we shared with the regulator, and as long as we were growing they maintained a light touch.

Now that mobile money and other digital financial services (DFS) are more pervasive with millions of customers entering the formal financial world for the first time and graduating from using basic transactional accounts to more advanced services like digital credit, we are seeing more and more providers entering the market, eager to reap the opportunity for profits at the base of the economic pyramid. Increased competition, the fintech explosion, and exceptional growth in financial inclusion are all great, of course, but we must ensure that we are building an industry that is sustainable in the long term, and not harming vulnerable customers. Now is the time for consumer protection to take the DFS stage, front and center.

But how can we make sure that consumer protection in DFS will become like breathing: a natural, automatic, even unconscious act? How can we make it business as usual?

A one-size-fits-all approach does not work. What’s rational for one set of consumers or one type of product might not be for another. And over-regulation and enforcement can lead to product withdrawal if financial services providers feel the compliance cost is too high, leading to less choice and perhaps forced exclusion for the most vulnerable. While consumer protection regulations and market conduct supervision are an important part of the solution, they are just one part.

So where then is the opportunity for making consumer protection an automatic reflex instead of a compliance issue? I believe it can only exist in the markets themselves. It is naïve to think we can achieve perfect competition in financial services markets, however, I do believe we can educate DFS providers to realize that consumer protection goals and their own business goals are completely aligned.

When I was in-market chasing active customers, if you asked me what the most important condition was for success, I would answer without hesitation: it is trust. But the thing is, I could never define what trust truly was, and whether we had achieved it. I believed we built consumer trust with a great product and brand, honest marketing, and a visible, high-quality agent network. While this was not entirely wrong, as demonstrated by the fact that the mobile money businesses I was involved with are successful with millions of active customers, we did spend a lot of time going two steps forward and one step back, burning a lot of vulnerable customers along the way. There is too much collateral damage in the drive for financial inclusion.

I have spent the last year putting together a course for the <a href="https://digitalfrontiersinstitute.org/the-institute/">Digital Frontiers Institute</a> (DFI) on consumer protection in DFS. Looking back at my provider-side days, I wish I knew then what I know now. I should have dug a little deeper into consumer protection and realized just what it was: a robust definition of trust in DFS, and a way to achieve it! Perhaps then we might have only gone one step forward and no steps back, carefully building up a customer base that felt more in control, more informed, and more active. And perhaps we would have achieved much faster incremental growth rates. As an added benefit, it would have provided the perfect scope of work for every customer-centricity program I had to work on.

Consumer protection is no longer in my compliance box, it’s now firmly in the revenue sustainability driver box: a significant part of any DFS business strategy to drive scale and higher customer activity rates. To share what I have learnt about consumer protection and how it relates to DFS business strategies, DFI is offering my four-week online course on <a href="https://digitalfrontiersinstitute.org/the-institute/consumer-protection-business-strategy/">Consumer Protection as a Business Strategy</a>, which will first be available in February 2018 and then again later in the year.

Have you read?

<a href="https://cfi-blog.org/2017/06/05/the-smart-campaign-promotes-stronger-client-protection-and-sector-collaboration-in-uganda/">The Smart Campaign Promotes Stronger Client Protection and Sector Collaboration in Uganda</a>

<a href="https://cfi-blog.org/2017/08/03/the-microfinance-ceo-working-group-reports-out-consumer-protection-by-the-millions-and-other-updates/">The Microfinance CEO Working Group Reports Out: Consumer Protection By the Millions and Other Updates</a>

<a href="https://cfi-blog.org/2017/12/19/nigeria-needs-to-include-consumer-protection-in-its-ambitious-financial-inclusion-plans/">Nigeria Needs to Include Consumer Protection in Its Ambitious Financial Inclusion Plans</a>

&nbsp;

&nbsp;

Consumer Protection in Digital Financial Services – Core Not Compliance

Consumer Protection

Responsible Digital Finance

Eric Noggle

Senior Research Director 

Alissa Fishbane

Amin Khairy

Andrew Fixler

Anita Gardeva

Apis Partners

Ashirul Amin

Bruce J

Carol Caruso

Dennis Ferenzy

Dylan Lennox

Elisabeth Rhyne

Eric Zuehlke

Ethan Loufield

Hannah Sherman

Ignacio Mas

Isabelle Carboni

Jacqueline Foelster

Keyur  Patel

Maha Khan

Mark Pickens

Marshall Lincoln

Nadia van de Walle

Patrick Traynor

Somen Saha

Sonja Kelly

Steve Wright

Susy Cheston

Tess Johnson

Brazil

Chile

China

Kenya

Mongolia

Pakistan

Philippines

Rwanda

Serbia

Thailand

United Kingdom

United States

Zimbabwe

Appropriate Product Design and Delivery

Credit

Financial Inclusion Strategy

Fraud

Human Centered Design

Impact Investing

Insurance

Interest Rates

Mobile Banking

MSME/SME Finance

Nano Loans

Over-indebtedness

Pensions and Retirement Saving

Remittances

Risk Management

Trends

Underwriting

Press Release

Most of Mexico’s people lack access to a formal bank account. Accion has worked in Mexico for decades to create a thriving and competitive financial sector that embraces innovation and protects its clients.

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.

Hannah McCandless

&gt; Posted by Dr. Katharine Kemp, Research Fellow, UNSW Digital Financial Services Regulation Project

The following post was <a href="http://www.ifmr.co.in/blog/2017/08/22/big-data-financial-inclusion-and-privacy-for-the-poor/">originally published</a> on the IFMR blog. 

<img class="alignright wp-image-24028" src="https://centerforfinancialinclusionblog.files.wordpress.com/2017/08/thumb_a98e715cf75d4c2ca7eea8e88847d4ba.jpg" alt="" width="365" height="243" />Financial inclusion is not good in itself.

We value financial inclusion as a means to an end. We value financial inclusion because we believe it will increase the well-being, dignity and freedom of poor people and people living in remote areas, who have never had access to savings, insurance, credit and payment services.

It is therefore important to ensure that the way in which financial services are delivered to these people does not ultimately diminish their well-being, dignity and freedom. We already do this in a number of ways – for example, by ensuring providers do not make misrepresentations to consumers, or charge exploitative or hidden rates or fees. Consumers should also be protected from harms that result from data practices, which are tied to the provision of financial services.

Benefits of Big Data and Data-Driven Innovations for Financial Inclusion

“Big data” has become a fixture in any future-focused discussion. It refers to data captured in very large quantities, very rapidly, from numerous sources, where that data is of sufficient quality to be useful. The collected data is analysed, using increasingly sophisticated algorithms, in the hope of revealing new correlations and insights.

There is no doubt that big data analytics and other data-driven innovations can be a critical means of <a href="http://www.pc.gov.au/inquiries/completed/data-access/report" target="_blank" rel="noopener noreferrer">improving the health, prosperity and security of our societies</a>. In financial services, new data practices have allowed providers to serve customers who are poor and those living in remote areas in new and better ways, including by permitting providers to:
<ul>
 	<li>Extend credit to consumers who previously had to rely on expensive and sometimes exploitative informal credit, if any, because they had no formal credit history;</li>
 	<li>Identify customers who lack formal identification documents;</li>
 	<li>Design new products to fit the actual needs and realities of consumers, based on their behaviour and demographic information; and</li>
 	<li>Enter new markets, increasing competition on price, quality and innovation.</li>
</ul>
But the collection, analysis and use of enormous pools of consumer data has also given rise to concerns for the protection of financial consumers’ data and privacy rights.

Potential Harms from Data-Driven Innovations

Providers now not only collect more information directly from customers, but may also track customers physically (using geo-location data from their mobile phones); track customers’ online browsing and purchases; and engage third parties to combine the provider’s detailed information on each customer with aggregated data from other sources about that customer, including their employment history, income, lifestyle, online and offline purchases, and social media activities.

Data-driven innovations create the risk of serious harms both for individuals and for society as a whole. At the individual level, these risks increase as more data is collected, linked, shared, and kept for longer periods, including the risk of:
<ul>
 	<li>Inaccurate and discriminatory conclusions about a person’s creditworthiness based on insufficiently tested or inappropriate algorithms;</li>
 	<li>Unanticipated aggregation of a person’s data from various sources to draw conclusions which may be used to manipulate that person’s behaviour, or adversely affect their prospects of obtaining employment or credit;</li>
 	<li>Identity theft and other fraudulent use of biometric data and other personal information;</li>
 	<li>Disclosure of personal and sensitive information to governments without transparent process and/or to governments which act without regard to the rule of law; and</li>
 	<li>Harassment and public humiliation through the publication of loan defaults and other personal information.</li>
</ul>
Many of these <a href="http://www.cgap.org/blog/making-case-privacy-poor" target="_blank" rel="noopener noreferrer">harms are known to have occurred</a> in various jurisdictions. The reality is that data practices can sometimes lead to the erosion of trust in new financial services and the exclusion of vulnerable consumers.

Even relatively well-meaning and law-abiding providers can cause harm. Firms may “segment” customers and “personalise” the prices or interest rates a particular consumer is charged, based on their location, movements, purchase history, friends and online habits. A person could, for example, be charged higher prices or rates based on the behaviour of their friends on social media.

Data practices may also increase the risk of harm to society as a whole. Decisions may be made to the detriment of entire groups or segments of people based on inferences drawn from big data, without the knowledge or consent of these groups. Pervasive surveillance, even the awareness of <a href="https://www.jstor.org/stable/23252125?seq=1#page_scan_tab_contents" target="_blank" rel="noopener noreferrer">surveillance, is known to pose threats</a> to freedom of thought, political activity and democracy itself, as individuals are denied the space to create, test and experiment unobserved.

These risks highlight the need for perspective and caution in the adoption of data-driven innovations, and the need for appropriate data protection regulation.

The Prevailing “Informed Consent” Approach to Data Privacy

Internationally, many data privacy standards and regulations are based, at least in part, on the <a href="https://www.priv.gc.ca/en/opc-actions-and-decisions/research/explore-privacy-research/2016/consent_201605/" target="_blank" rel="noopener noreferrer">“informed consent”</a> – or “notice” and “choice” – approach to informational privacy. This approach can be seen in the Fair Information Practice Principles that originated in the U.S. in the 1970s; the 1980 OECD Privacy Guidelines; the 1995 E.U. Data Protection Directive; and the Council of Europe Convention 108.

Each of these instruments recognise consumer consent as a justification for the collection, use, processing and sharing of personal data. The underlying rationale for this approach is based on principles of <a href="http://scholarship.law.gwu.edu/cgi/viewcontent.cgi?article=2093&amp;context=faculty_publications" target="_blank" rel="noopener noreferrer">individual freedom and autonomy</a>. Each individual should be free to decide how much or how little of their information they wish to share in exchange for a given “price” or benefit. The data collector gives notice of how an individual’s data will be treated and the individual chooses whether to consent to that treatment.

This approach has been <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2533057" target="_blank" rel="noopener noreferrer">increasingly criticised</a> as artificial and ineffectual. The central criticisms are that, for consumers, there is no real notice and there is no real choice.

In today’s world of invisible and pervasive data collection and surveillance capabilities, data aggregation, complex data analytics and indefinite storage, <a href="https://www.priv.gc.ca/en/opc-actions-and-decisions/research/explore-privacy-research/2016/consent_201605/" target="_blank" rel="noopener noreferrer">consumers no longer know or understand</a> when data is collected, what data is collected, by whom and for what purposes, let alone how it is then linked and shared. Consumers do not read the dense and opaque privacy notices that supposedly explain these matters, and could not read them, given the hundreds of hours this would take. Nor can they understand, compare, or negotiate on, these privacy terms.

These problems are exacerbated for poor consumers who often have more limited literacy, even less experience with modern uses of data, and less ability to negotiate, object or seek redress. Yet we still rely on firms to give notice to consumers of their broad, and often open-ended, plans for the use of consumer data and on the fact that consumers supposedly consented, either by ticking “I agree” or proceeding with a certain product.

The <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2784123" target="_blank" rel="noopener noreferrer">premises of existing regulation are therefore doubtful</a>. At the same time, some commentators question the relevance and priority of data privacy in developing countries and emerging markets.

Is data privacy regulation a “Western” concept that has less relevance in developing countries and emerging markets?

Some have argued that the individualistic philosophy inherent in concepts of privacy has less relevance in countries that favour a <a href="http://www.tandfonline.com/doi/abs/10.1080/10572317.2007.10762729" target="_blank" rel="noopener noreferrer">“communitarian” philosophy of life</a>. For example, in a number of African countries, “ubuntu” is a guiding philosophy. According to ubuntu, “a person is a person through other persons”. This philosophy values openness, sharing, group identity and solidarity. Is privacy relevant in the context of such a worldview?

Privacy, and data privacy, serve values beyond individual autonomy and control. Data privacy serve values which are at the very heart of “communitarian” philosophies, including compassion, inclusion, face-saving, dignity, and the humane treatment of family and neighbours. The protection of financial consumers’ personal data is entirely consistent with, and frequently critical to, upholding values such as these, particularly in light of the alternative risks and harms.

Should consumer data protection be given a low priority in light of the more pressing need for financial inclusion?

Some have argued that, while consumer data protection is the ideal, this protection should not have priority over more pressing goals, such as financial inclusion. Providers should not be overburdened with data protection compliance costs that might dissuade them from introducing innovative products to under-served and un-served consumers.

Here it is important to remember how we began: financial inclusion is not an end in itself but a means to other ends, including permitting poor and those living in remote areas to support their families, prosper, gain control over their financial destinies, and feel a sense of pride and belonging in their broader communities. The harms caused by unregulated data practices work against each of these goals.

If we are in fact permanently jeopardising these goals by permitting providers to collect personal data at will, financial inclusion is not serving its purpose.

Solutions

There will be no panacea, no simple answer to the question of how to regulate for data protection. A good starting place is recognising that consumers’ “informed consent” is most often fictional. Sensible solutions will need to draw on the full “toolkit” of privacy governance tools (Bennett and Raab, 2006), such as appropriate regulators, advocacy groups, self-regulation and regulation (including substantive rules and privacy by design). The solution in any given jurisdiction will require a combination of tools best suited to the context of that jurisdiction and the values at stake in that society.

Contrary to the approach advocated by some, it will not be sufficient to regulate only the use and sharing of data. Limitations on the collection of data must be a key focus, especially in light of new data storage capabilities, the likelihood that de-identified data will be re-identified, and the growing opportunities for harmful and unauthorised access the more data is collected and the longer it is kept.

Big data offers undoubted and important benefits in serving those who have never had access to financial services. But it is not a harmless curiosity to be mined and manipulated at the will of those who collect and share it. Personal information should be treated with restraint and respect, and protected, in keeping with the fundamental values of the relevant society.

Image credit: Accion

Have you read?

<a href="https://cfi-blog.org/2017/06/28/why-do-privacy-policies-matter-for-digital-credit/">Why Do Privacy Policies Matter for Digital Credit?</a>

<a href="https://cfi-blog.org/2017/05/01/how-secure-is-data-used-in-digital-credit/">How Secure Is Data Used in Digital Credit?</a>

<a href="https://cfi-blog.org/2017/05/15/data-are-not-neutral-part-1-of-2/">Data Are Not Neutral (Part 1 of 2)</a>

Big Data, Financial Inclusion and Privacy for the Poor

Washington, D.C. (January 13, 2017) — The Center for Financial Inclusion at Accion (CFI), the Institute of International Finance (IIF) and MetLife Foundation, together with the International Finance Corporation (IFC) as a technical partner, announced today a two-year initiative to help advance the financial services industry's ability to reach unserved and underserved populations

Center for Financial Inclusion at Accion, Institute of International Finance and MetLife Foundation Launch Project to Help Financial Industry Overcome Barriers to Financial Inclusion

International Finance Corporation

The majority of Kenyans have mobile money accounts; their activity demonstrates digital financial services’ potential. Accion helps Kenyan innovators harness emerging technologies to create new financial services.

The following is part of the Smart Campaign’s #FintechProtects mini campaign. We’re raising awareness about responsible digital financial services, spotlighting work from the Smart Campaign and others, and engaging with industry actors on how fintech can move forward in a way that’s best for clients. For more information on #FintechProtects, and to get involved, <a href="https://cfi-blog.org/2016/09/14/fintechprotects-keeping-clients-first-in-digital-finance/">click here</a>.

Digital credit is growing fast in developing markets, particularly in Sub-Saharan Africa. Lenders such as <a href="http://www.safaricom.co.ke/personal/m-pesa/do-more-with-m-pesa/m-shwari">M-Shwari</a>, Jumo, M-Pawa, Eazzy Loan, Branch, EcoCashLoan, Timiza, KCG M-Pesa and others are attracting interest and investment. They are seen as having the potential to improve financial access and to make banking with poor clients more feasible and sustainable through technology that reduces underwriting and infrastructure costs. They offer small or nano loans starting as low as $5 or $10 dollars, make use of simple mobile user interfaces, and provide funds in real-time.

The Smart Campaign and others <a href="http://www.cgap.org/publications/doing-digital-finance-right">such as CGAP</a> have been carefully looking at client protection risks in the burgeoning digital credit space, particularly in relation to transparency and informed consent. Other potential consumer protection issues include the implications of data analytics rather than traditional repayment capacity analysis as a basis for underwriting, high interest rates, and lack of rigorous regulation in many markets. The Smart Campaign is conducting small research projects to identify consumer protection concerns and good practices for mitigating them. Ultimately, we would like to see standards of care developed for digital credit products.

Using the <a href="http://smartcampaign.org/about/smart-microfinance-and-the-client-protection-principles">Client Protection Principles</a> as a framework, we have identified several consumer risks where deeper research, industry discussions, and consensus-building are needed.
<ul>
 	<li>Appropriate Product Design and Delivery: “Pushy” Sales and Marketing: The sales and promotion strategies used by mobile lenders include “push” marketing methods such as bulk SMS messages. In more developed markets, our Client Voice research identified pushy unsolicited offers as a tactic that customers dislike, but more important (and especially for clients new to formal credit), unsolicited offers can lead clients to over-borrow. We wonder whether customers’ should have opt-out options to avoid such offers. The Smart Campaign is interested in working to better define “aggressive sales” and “deceptive marketing” in the context of digital credit.</li>
</ul>
<ul>
 	<li>Avoiding Over-Indebtedness: Damaging Credit Scores for Early Adopters: In the early stages of a digital credit roll-out, the lender is often still tweaking its underwriting algorithms. In the process, early adopter clients who are not good credit bets may be approved, and then punished through blacklisting with credit bureaus when they cannot repay. We see <a href="http://www.nation.co.ke/business/Pain-of-Kenyans-blacklisted-for-amounts-as-small-as-Sh100/996-3374952-k2dkdvz/">an example</a> of this in Kenya where hundreds of thousands of Kenyans have been blacklisted through the country’s credit reference bureaus for outstanding mobile loans of less than Sh200 (approximately $2). The credit bureaus charge about $20 for clients to clear their names. The Smart Campaign is interested in exploring guidelines to prevent adverse reporting to credit bureaus for clients that fail to repay due to inadequate appraisal.</li>
</ul>
<ul>
 	<li>Fair and Respectful Treatment: Big Data and Potential Discrimination: The use of big data and alternative data in credit underwriting may be <a href="http://www.nytimes.com/2015/01/19/technology/banking-start-ups-adopt-new-tools-for-lending.html">helpful</a> for increasing financial access to thin file customers, but there are also concerns about potential discrimination arising from these proprietary algorithms. Digital lenders use predictive models based on demographics, web presence, mobile activity, and other similar variables. These models often rely on automated software algorithms that are learning as they process more data. Discrimination may arise through this complex, rapidly evolving process. If a variable is predictive, the algorithm will incorporate it. This raises the possibility of discrimination based on ethnicity, religion, political affiliation, age, etc. The Smart Campaign is interested in learning more about how data analytics firms are building in protections against discrimination on such characteristics.</li>
</ul>
One broad concern cuts across all the Client Protection Principles: With digital, who is responsible for the client? The degree and direction of influence between digital lenders and their partners can create client protection gray areas. Should the digital lender be required to ensure that the mobile network operator (MNO) or other partner improves transparency, responsible pricing, or protection of client data? A particular focus area concerns who ensures fair dealing and appropriate behavior from banking agents? Who is ultimately responsible for securing and protecting against the unauthorized spread of client data? Do the service level agreements that guide roles and responsibilities in a partnership between a lender and an MNO, clarify responsibilities and requirements to ensure that end clients are treated fairly? The Smart Campaign is interested in exploring the levers that can be used in such relationships to influence adherence to consumer protection responsibilities.

Have you read?

<a href="https://cfi-blog.org/2015/02/04/keeping-score-the-client-protection-principles-vs-the-u-s-subprime-auto-loan-market/">Keeping Score: The Client Protection Principles vs. the U.S. Subprime Auto Loan Market</a>

<a href="https://cfi-blog.org/2016/05/31/smes-speak-out-on-online-lending-if-you-build-the-website-they-will-come-but-they-might-be-a-little-confused/">SMEs Speak Out on Online Lending</a>

<a href="https://cfi-blog.org/2016/09/14/fintechprotects-keeping-clients-first-in-digital-finance/">#FintechProtects: Keeping Clients First in Digital Finance</a>

Digital Credit in Africa: Are Nano Loans Safe for Consumers?

The Smart Campaign

Vitas Argimon

&gt; Posted by Vitas Argimon, Credit Suisse Global Citizen Volunteer

This post is part of a multi-post series focused on partnerships between commercial banks and financial technology startups.

[caption id="attachment_21893" align="alignright" width="370"]<a href="https://centerforfinancialinclusionblog.files.wordpress.com/2016/08/figure-11.jpg"><img class="wp-image-21893" style="border:0 solid #000000" src="https://centerforfinancialinclusionblog.files.wordpress.com/2016/08/figure-11.jpg" width="370" height="237" /></a> (click to enlarge)[/caption]

Today’s financial sector narrative pits the new guy against the old guy. In the case of financial services, this narrative, as it is often portrayed, places commercial banks, the legacy providers, in direct competition with startups, with both parties vying for customers in a game defined by technological advances. While this narrative sometimes plays out in real life, it leaves out the complex ecosystem of interaction between the old and the new. In fact, when it comes to reaching new customer segments, old players are increasingly turning to startups.

In <a href="http://www.centerforfinancialinclusion.org/fi2020/roadmap-to-inclusion/the-business-of-financial-inclusion">The Business of Financial Inclusion: Insights from Banks in Emerging Markets</a>, CFI and the Institute of International Finance reveal that commercial banks are partnering with fintech startups in their efforts to reach the unbanked and underbanked. As challenges by tech-enabled competition mount, banks are seeking to link-up with startups as they see opportunities to reach new markets, bring down costs, and/or enhance their service offerings. Startups offer agility, a proclivity for risk-taking, and a disruptive mindset. On the other hand, banks already have the customer scale, comprehensive product portfolio, robust infrastructure, deposit insurance, branding, and experience/expertise. (See a full list of the relative strengths of banks and startups at right.) The combination of these strengths can be especially enabling when seeking out previously unreached population segments because the business models for serving those segments often depend on technologies that bring down costs. Startups can offer banks the tools they need to serve lower-income customers that would be difficult to serve within the confines of their traditional banking models. At the same time, many startups need access to customers and financial resources that banks can provide.

As part of my work as a Credit Suisse Global Citizen Volunteer, I mapped the landscape of partnerships between commercial banks and fintech startups, with a focus on those aimed at expanding services to reach the unbanked. I found four primary areas in which these partnerships are enhancing operations: blockchain and digital payments; lending and credit scoring; KYC and compliance; and financial capability building.

[caption id="attachment_21887" align="aligncenter" width="621"]<a href="https://centerforfinancialinclusionblog.files.wordpress.com/2016/08/figure-2.jpg"><img class="wp-image-21887" src="https://centerforfinancialinclusionblog.files.wordpress.com/2016/08/figure-2.jpg" alt="figure.2" width="621" height="349" /></a> (click to enlarge)[/caption]

While fintech startups and commercial banks offer great opportunities to each other to improve processes and expand operations, the challenges to forming successful partnerships can sometimes get in the way. The legacy systems that serve as the basis for bank operations remain a big obstacle to effective integration of applications provided by startups. Clunky IT platforms, deeply engrained company processes, and tough or murky regulatory environments make change very difficult and costly.

Partnerships may also present risks to commercial banks. Banks strive to have regulation-proof, air-tight procedures – and may shudder at the quick and dirty approach taken by some startups. One specific area of contention is data. Not surprisingly, banks are very protective of client identifying data, even when working with startups that need the data as part of their business model, for example, when carrying out alternative credit scoring.  Banks are wary that startups may be susceptible to hackers and cybercrime. Additionally, banks have a vested interest in keeping client data proprietary for competitive reasons. Partnerships centered on lending present their own set of challenges, including the question of which party (the startup or the bank) is considered the “lender” under law, and, in the case of innovative credit scoring models, concerns surrounding overindebtedness. Synchronizing bank protocols for risk management, may be essential to partnerships with startups.

It is important to remember that even in the face of the risks and challenges listed above, commercial banks are finding a way to partner with fintech startups, and at an increasing rate. As discovered in interviews with 24 banks as part of the <a href="http://www.centerforfinancialinclusion.org/fi2020/roadmap-to-inclusion/the-business-of-financial-inclusion">Business of Financial Inclusion</a> report, these partnerships are part of complex strategies to reach the unbanked and underbanked. They are challenging the dominant narrative about the battle between old and new, and offering another way to build a more inclusive financial ecosystem.

Have you read?

<a href="https://cfi-blog.org/2015/04/24/fintech-for-fi2020-a-conversation-on-aligning-technology-and-partnerships-for-financial-inclusion/">FinTech for FI2020: A Conversation on Aligning Technology and Partnerships for Financial Inclusion</a>

<a href="https://cfi-blog.org/2016/07/21/new-cfi-and-iif-report-reveals-banks-are-leading-financial-inclusion/">New CFI and IIF Report Reveals Banks Are Leading on Financial Inclusion</a>

<a href="https://cfi-blog.org/2016/08/23/zidishas-take-on-peer-to-peer-lending/">Zidisha's Take on Peer-to-Peer Lending</a>

Commercial Banks Are Partnering With Fintechs to Reach the Unbanked

&gt; Posted by Hannah Sherman, Project Associate, CFI

In a world of rapid change, few organizations have all the capabilities needed to accomplish every aspect of their business. This is true for commercial banks, which often find success in adapting to new opportunities through partnering. CFI’s most recent publication, <a href="http://www.centerforfinancialinclusion.org/fi2020/roadmap-to-inclusion/the-business-of-financial-inclusion">The Business of Financial Inclusion: Insights from Banks in Emerging Markets</a>, a joint publication with the Institute of International Finance (IIF), illustrates how banks use partners to adopt new technologies and reach previously underserved markets.

The report, based on interviews with the financial inclusion leads at 24 banks, shines a spotlight on the role of banks as leaders in financial inclusion and discusses their specific strategies related to technology, data, financial capability, partnerships, and other issues.

The report found that banks create a variety of partnerships. The banks in our survey partner with telcos, payments companies, insurance companies, microfinance institutions, retailers, and consumer-goods companies. They work closely with governments for G2P payments and with international development agencies and donors that provide start-up capital for new financial inclusion initiatives. They also contract with digital technology providers such as data analytics companies, back-office systems providers, digital channel providers, financial capability providers, and other fintech firms.

Among many other areas, banks often use partnerships to improve on the following:

<ul>
 	<li>Customer acquisition</li>
 	<li>Customer engagement and support</li>
 	<li>Distribution and payments</li>
 	<li>Enhanced product offerings</li>
 	<li>Back office systems and data analytics</li>
 	<li>Financial partnerships</li>
 	<li>Ecosystem development</li>
</ul>
For example, BBVA partners with the data analytics startup Destacame to extend credit access to low-file customers in Latin America. Destacame enables underbanked individuals to build a credit score based on their history of paying everyday bills like those for electricity or gas. BBVA also <a href="http://www.femsa.com/en/press/bbva-bancomer-cardholders-can-make-cash-withdrawals-at-oxxo">joined</a> with OXXO, Mexico’s largest convenience store chain, to expand services access. BBVA clients are able to make cash withdrawals at any of OXXO’s 12,000 stores in the country, without the requirement of making a separate purchase. The partnership helps BBVA build on its agent network of 25,000 agents in Mexico and increase banking penetration in rural areas. OXXO is making progress in offering the cash withdrawal service to cardholders of other banks, too. In CFI’s <a href="http://www.centerforfinancialinclusion.org/fi2020/roadmap-to-inclusion/innovations-in-financial-capability">study on the financial capability landscape</a>, a similar partnership between Banamex  and OXXO (the Saldazo card) is profiled.

To increase the ease of which customers can access payments, the Commercial International Bank (CIB) in Egypt relies on smart phones in a partnership with Mastercard and Fawry, an electronic payment network. Egypt has over 100 percent mobile penetration, 10 percent bank account penetration, and 26 percent smart phone penetration – there are more smart phones than bank accounts. <a href="http://www.cibeg.com/English/Personal/waystobank/Pages/CIB-Smart-Wallet.aspx">Smart Wallet</a> is CIB’s e-wallet app, supported by Mastercard, that enables customers to use their phones to make payments and purchases, transfer money, deposit and withdrawal. CIB’s partnership with Fawry has enabled 50,000 merchant outlets in Egypt to accept Smart Wallet payments.

A three-way partnership between Fidelity Bank Ghana, Airtel, and Tiaxa is behind the recent <a href="http://africa.airtel.com/wps/wcm/connect/africarevamp/africa/home/media/press-releases/airtel+ghana+airtel+money+partners+with+fidelity+bank+and+tiaxa+to+launch+airtel+money+bosea">launch</a> of a nano-loan product offered through the Airtel Money wallet in Ghana. Fidelity Bank and Airtel had partnered previously in offering Airtel Money, Airtel’s comprehensive mobile money platform. (Fidelity Bank also works with MTN, another mobile network operator, on mobile money.) <a href="https://www.tiaxa.com/">Tiaxa</a> is a global leader in nano credits, providing small loans in more than 20 countries both as airtime for prepaid mobile subscribers and as cash through mobile money. In Ghana, the nano-loan partnership enables eligible Airtel Money subscribers to instantly borrow up to GHC 200 (~US$ 51) for last-minute needs, like extra funds for an emergency purchase.

A number of banks have made very strong financial partnerships, the most successful of which have been with microfinance organizations. Microfinance institutions (MFIs) serve poor and low-income customers that banks may not be able to serve, especially with credit. Many banks find it more compatible with their business models to fund MFIs with debt, equity, or purchase of their loan portfolios. In this way banks can participate in financial inclusion indirectly. In some cases, the banks are actually majority owners. Of the banks interviewed for the report, Citi, Standard Chartered, Banco de Crédito del Perú (BCP), Habib Bank Limited (HBL), HSBC India, and Santander Brasil, among others, have all invested in MFIs or other financial institutions.

In addition, a number of banks are working to develop the ecosystem in which they operate. One example of this is the Association of Banks of Peru (ASBANC), which worked together with banks, telcos, and the government to create <a href="https://cfi-blog.org/2016/02/17/bim-the-first-fully-interoperable-mobile-money-platform-now-live-in-peru/">BiM</a> (Billetera Movil), the world’s first fully interoperable national payments platform. Among our surveyed banks, BCP was deeply involved in the development and marketing of the BiM e-wallet. BCP contributed to the process in collaboration with over 30 other financial institutions and four major telecommunications companies.

In Colombia, Bancolombia joined with 10 other public, private, and academic partners to create a center for big data and data analytics as part of the <a href="http://www.mintic.gov.co/portal/604/w3-article-14678.html">CAOBA Initiative</a>, and to improve their data analytics capacity. CAOBA is a public-private partnership to create a center for big data and data analytics in Colombia, building capacity to use alternative data to reach unserved and underserved populations.

While the specific collaboration models change from one bank to another, there is one overarching message: partnerships can be the key for many banks as they attempt to reach unbanked and underbanked customers in emerging markets.

For more, read <a href="http://www.centerforfinancialinclusion.org/storage/documents/IIF_CFI_Report_FINAL.pdf">The Business of Financial Inclusion: Insights from Banks in Emerging Markets</a>.

Have you read?

<a href="https://cfi-blog.org/2016/07/13/new-video-susy-cheston-interviews-dr-william-derban-on-the-business-of-financial-inclusion/">New Video: Susy Cheston Interviews Dr. William Derban on “The Business of Financial Inclusion”</a>

<a href="https://cfi-blog.org/2016/07/07/the-business-of-financial-inclusion-insights-from-emerging-market-banks/">The Business of Financial Inclusion: Insights from Emerging Market Banks</a>

<a href="https://cfi-blog.org/2016/07/19/banks-in-financial-inclusion-improving-the-customer-experience/">Banks in Financial Inclusion: Improving the Customer Experience</a>

The Business of Financial Inclusion: Banks that Partner go Farther and Deeper

Mastercard

Financial Inclusion 2020

&gt; Posted by Sonja Kelly, Director, CFI

A recent Facebook promotion by a U.K. coffee shop offered,  “Like us on Facebook and get a free coffee!” This line would totally get me. Wait… all I have to do is click one little button, and I can save $2? Sign me up!

A free cup of coffee, however, was not the only thing that customers received when they liked the coffee shop’s Facebook page. They also got a very “personalized” experience, complete with the barista at the coffee shop rattling off their job, religion, birthdate, address, mother’s maiden name, and more.

Check out the video that documented the customers’ experiences here:

<a href="http://www.independent.co.uk/news/uk/home-news/facebook-fraud-risk-personal-information-like-page-data-to-go-short-film-a7120061.html"><img class="aligncenter wp-image-21573" style="border:0 solid #000000" src="https://centerforfinancialinclusionblog.files.wordpress.com/2016/07/coffee.png" width="601" height="317" /></a>

(My favorite part is when the barista says to the customer, “Oh, we know everything about you, Martin.”)

As part of the <a href="http://www.centerforfinancialinclusion.org/programs-a-projects/cfi-and-accion-research-fellows">CFI Fellows Program</a> one of our fellows, AJ Mowl, has been looking at some of the pros and cons of leveraging consumer data for financial inclusion. As she has relayed to me some of the basic facts about big data, I have become more and more aware of just how big big data is—and what the consequences are when I trade access to my data for services.

LinkedIn, for example, learns all about my professional network, and in exchange it provides me with access to a place to exchange ideas and connect with colleagues. I was totally fine with that until I heard that Microsoft was <a href="http://news.microsoft.com/2016/06/13/microsoft-to-acquire-linkedin/">buying</a> LinkedIn in part to sell its products. <a href="http://www.wsj.com/articles/microsoft-gains-link-to-a-network-1465922927">According to Microsoft Chief Executive Satya Nadella</a>, LinkedIn will help Microsoft as it goes into sales meetings—arming them with the full bios of customers—data that would usually only be available to a person’s accepted network. Or it could super-charge Microsoft’s customer relationship management, allowing them to systematically and individually target consumers who are in particular industries or have particular jobs. Or it could integrate LinkedIn into Office products like Outlook so those I correspond with could have more data on me, my job description, my work history, and my references (to be frank, I would find this helpful as a user of the data, but I’d like to have a little more control over how my own data is viewed by others).

As another example, consider how our internet service providers use our browsing data. A few weeks ago, I searched for a “Pack ‘n Play” (portable crib) for my baby daughter. All of a sudden, the ads on the sides of my browser were full of Pack ‘n’ Plays. I ended up clicking through to one that was lower priced and slightly better than the original one I had searched for. Thanks, big data!

When I shop at the grocery store, I get coupons on the back of my receipt highlighting items that the store thinks I should buy, based on the purchase history on my credit card. Because I bought cold medicine they assume I’ll want tissues, and I can take $1 off a pack of four! Where this becomes more controversial is when <a href="http://www.forbes.com/sites/kashmirhill/2012/02/16/how-target-figured-out-a-teen-girl-was-pregnant-before-her-father-did/#37d4fdfd34c6">Target knows your daughter is pregnant</a> before you do.

Big data is indeed big, it knows me way too well, and it is here to stay. There is only so much tinkering I can do with my privacy settings on Facebook, only so much shopping I can do “off the grid” using just cash, only so much censoring I can do of my LinkedIn profile before it hampers my career.

In light of the reality of big data, and thinking about financial services, there are two pretty important questions that emerge to me. First, are the institutions I engage with interacting with my data in a responsible way? Second, is the use of big data making me, as a customer, feel uncomfortable?

Responsible use of data by financial institutions is a serious issue. The White House issued a <a href="https://www.whitehouse.gov/sites/default/files/microsites/ostp/2016_0504_data_discrimination.pdf">report</a> recently that questioned whether big data use in credit decisions could lead to discrimination. The algorithms that comb through those big piles of data are often assumed to be objective. But in reality, they directly mirror the subjective inputs of their creators. In other words, in credit decisions, it is the coders that ultimately determine who is a credit risk and who isn’t. Hopefully the criteria they choose are not ones like race, religion, or sexual preference. But they may include close proxies with the same result. Who in the institution is responsible for thinking about discrimination? Who is going to hold the financial institution accountable? How can I know if I am being discriminated against, and what are my recourse mechanisms?

The second issue is more one about consumer comfort. When I go into a store, I don’t love overbearing sales clerks who constantly watch me and ask repeatedly “Is there anything I can help you with?” In the same way, consumers of financial services shouldn’t have to feel like they’re constantly being monitored. As a customer, I want to take the lead—I don’t want to feel that the institution is manipulating me into particular products or decisions. I want help, but I don’t want an institution to “hover” over me.

Sure, big data is big. And it’s here to stay. But I’m eager to know how the industry can be reflective as big data becomes more integrated into our financial services.

Stay tuned—CFI Fellow AJ Mowl will be releasing her report on big data this fall.

Have you read?

<a href="https://cfi-blog.org/2014/04/07/is-bigger-data-better/">Is Bigger [Data] Better?</a>

<a href="https://cfi-blog.org/2016/06/24/we-want-you-to-think-about-big-questions/">We want YOU... to think about big questions</a>

<a href="https://cfi-blog.org/2015/11/25/quality-data-at-the-heart-of-strengthening-financial-inclusion-of-women/">Quality Data at the Heart of Strengthening Financial Inclusion of Women</a>

“Oh, we know everything about you.”

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.

&gt; Posted by Tim Tsang, Positive Planet China
<h3>A need for formal credit in China</h3>
<a href="https://centerforfinancialinclusionblog.files.wordpress.com/2016/06/untitled_1.png"><img class="wp-image-21416" src="https://centerforfinancialinclusionblog.files.wordpress.com/2016/06/untitled_1.png" width="551" height="248" /></a>

Between 2011 and 2014, <a href="http://www.worldbank.org/en/programs/globalfindex">180 million adults</a> (aged 15+) became new bank account holders in China. Yet in 2014, only <a href="http://www.worldbank.org/en/programs/globalfindex">9.6 percent</a> of Chinese adults, or less than 110 million, actually accessed credit from a financial institution, which includes credit unions, microfinance institutions, and cooperatives as well as banks. The incongruity across such statistics highlights both the progress made and the challenges remaining on China's path to a more financially inclusive economy.

The need for reform is as important as ever with China's growing credit industry. During its economic slowdown, China has looked to <a href="https://www.bcgperspectives.com/content/articles/globalization-growth-new-china-playbook-young-affluent-e-savvy-consumers/">spur growth through consumer spending</a> and should continue to see consumer lending steadily grow. The rigidity and costliness of China's financial institutions, however, have hindered addressing consumers' growing credit demand, leaving a discernable credit gap. Instead, in a big way consumers have resorted to informal and nontraditional sources of loans. This largely holds true for both urban and rural borrowers, with roughly <a href="http://www.worldbank.org/en/programs/globalfindex">a third</a> of Chinese adults borrowing in 2014.

Among China’s informal lenders, family or friends are still the most common for financing individual loans, but “shadow banking” institutions, most notably P2P and online lending companies, have cropped up in recent years to try to capture this untapped market. As less regulated institutions, these shadow banks almost uniformly offer higher-risk, high-interest loans, rather than provide a sustainable and transparent alternative to banks.

The reliance on informal and nontraditional sources of lending in part <a href="http://www.chinadaily.com.cn/bizchina/tech/2016-01/27/content_23269761.htm">reflects</a> more young, high-risk consumers looking for credit, but it also is a symptom of a lack of available information. Lenders often have no access to the borrower's financial history much less their reasoning for borrowing money.
<h3>Solving the credit gap through online data</h3>
Closing China's formal credit gap requires a scalable system for credit evaluation. China's current solution of the Credit Reference Agency, a centralized credit agency, falls short. While it has profiles of over 800 million individuals, many are reportedly filled with no more than basic information such as names and ID numbers. In fact, only <a href="https://www.fitchratings.com/site/pressrelease?id=997017">350 million</a> – less than one third of the over 1 billion Chinese adults – have credit records. By comparison, <a href="http://qz.com/519737/all-chinese-citizens-now-have-a-score-based-on-how-well-we-live-and-mine-sucks/">89 percent</a> of the adult population in the U.S. has a credit score.

As the flag-bearer for China's internet finance and mobile payment movement via its Alipay service, Alibaba-affiliate <a href="http://knowledge.ckgsb.edu.cn/2015/08/05/finance-and-investment/can-alibabas-ant-financial-disrupt-chinas-financial-industry/">Ant Financial</a> is trying to provide an innovative solution. By leveraging its IT expertise, Ant Financial is trying to do to credit scoring what it has done to payments. Its solution: Sesame Credit.

<a href="https://cfi-blog.org/2015/09/24/discrimination-and-credit-underwriting-in-the-age-of-social-media/">New credit scoring</a> businesses have been cropping up around the world recently. What sets this new credit score apart is the scale and depth of <a href="http://www.cgap.org/blog/microfinance-e-commerce-big-data-and-china-alibaba-story">Alibaba’s</a> e-commerce data to which Ant Finance has direct access. The big data gathered from these e-commerce and payment platforms are far more insightful for credit-based decision-making than what most other nontraditional businesses are claiming to achieve with social media or other forms of non-economic, online activity.

Tapping into the Alibaba ecosystem gives Sesame Credit access to data on over <a href="http://www.alizila.com/alibaba-group-reports-quarterly-and-fy2016-results/">400 million</a> annual active users and <a href="http://technode.com/2015/01/29/alibabas-finance-arm-officially-launches-credit-scoring-service-sesame-credit/">37 million</a> small businesses that buy and sell via its online marketplaces, as well as payment histories of over <a href="http://www2.alizila.com/ant-financial-unveils-alipay-90-super-app">400 million</a> annual active Alipay users. This expertise in cloud and data management is then coupled with other traditional credit scoring information sources such as bank and government records. That Ant Financial can further utilize data from Alibaba’s many other businesses, capitalize on the group’s expansive human and IT resources, and leverage its China gravitas to win important, strategic partnerships means it has real potential in bolstering China's future credit infrastructure.
<h3>Is it a tool for the underserved?</h3>
Sesame Credit has shown early promise in its ability to expand access to credit. Ant Financial has already been providing loans to businesses showing strong sales performance on its platforms, and “Sesame scores” are clearly an attempt to standardize and expand on this model.

[caption id="attachment_21417" align="alignright" width="331"]<a href="https://centerforfinancialinclusionblog.files.wordpress.com/2016/06/untitled_2.png"><img class="wp-image-21417" style="border: 0 solid #000000" src="https://centerforfinancialinclusionblog.files.wordpress.com/2016/06/untitled_2.png" width="331" height="183" /></a> (click to enlarge)[/caption]

Of course, a good Sesame Credit score is contingent on adequate use of one or more of its data-generating services, most of which fundamentally require ownership of a smartphone or computer.  Rural residents are thus at an inherent disadvantage when it comes to Sesame Credit, as just one third of the countryside are online and only <a href="https://home.kpmg.com/xx/en/home/insights/2015/12/harvesting-china-rural-consumers.html">32 percent</a> own a mobile phone, according to KPMG.

Nevertheless, Ant Financial has shown its intent to build a rural user base by investing in the countryside's data-generation. Its investment into <a href="http://www.cgap.org/blog/postal-savings-bank-china-inclusive-finance-rural-china">the Postal Savings Bank of China</a> (PSBC), which has the largest network of branches in China, will <a href="http://technode.com/2015/09/07/alibabas-china-post/">provide</a> the credit reporting with vital financial information on rural users.

Further, an expansion of its businesses to rural areas should only equate to more data-crunching possibilities to better serve this population. Alibaba, still the key party behind Sesame Credit’s data network, has heavily invested in rural infrastructure to expand its market potential to increasingly rural and remote locations. For instance, it has built rural service centers in over <a href="http://www.allchinatech.com/alibaba-financial-report-cainiao-logistics-a-boon-to-revenue/">14,000 villages</a> and has even developed a rural-focused online shopping platform, "Rural Taobao." These service centers help deliver products within villages and are outfitted with computers, providing greater access to the internet. To meet the logistics burden of reaching rural residents, Alibaba’s related business arm formed a strategic alliance with China Post, allowing online shoppers to collect packages from <a href="http://www.advangent.com/2015/04/08/china-post-5000-self-collect-outlets-for-alibabas-logistic-network-cainiao/">5,000 postal outlets</a>. Within the next three to five years, Alibaba hopes constructing more such centers will expand its services to over <a href="http://www.straitstimes.com/asia/east-asia/china-e-commerce-firms-tapping-rural-dollar">100,000 villages</a>. After developing a history using these services, rural residents may then gain newfound opportunities to borrow and invest as the integrated businesses funnel customers to Ant Financial.
<h3>Too soon to tell</h3>
The sum of Ant Financial and Alibaba’s advantages may soon make it one of the most powerful success stories in global financial inclusion efforts. But chances are it will never be a magic bullet – it is unlikely that everyone can be plugged into Alibaba’s businesses. At this point, it remains hard to imagine what Sesame Credit will ultimately become. Sesame Credit has already innovated into non-financial uses that are simultaneously novel and concerning: a visa processing tool, a matchmaking moniker, and flight and hotel booking perks, among many others. This gives Sesame Credit the look and feel of a gimmicky loyalty program for Alibaba customers. Further, little information in the public realm can firmly prove that Sesame Credit scores are actually providing much insight into credit worthiness beyond what Ant Financial had already directly provided in terms of discerning credit worthiness of e-commerce businesses.

Adding to the complexity of the topic, there is also much fear and speculation that the government will fashion Alibaba’s work on scoring into a surveillance scheme. Plans for a more centralized credit scoring system are already in the works, and some signs point to Alibaba having no choice but to assist in this process. What is clear now, however, is that Sesame Credit must first prove itself effective and reliable before any of the extenuating circumstances become too relevant. The potential for positive change is there. Now Ant Financial must try to realize it.

This post was jointly-published with <a href="http://nextbillion.net/">NextBillion</a>.

Have you read?

<a href="https://cfi-blog.org/2015/09/15/insights-into-an-evolving-peer-to-peer-lending-industry-in-china/">Insights into an Evolving Peer-to-Peer Lending Industry in China</a>

<a href="https://cfi-blog.org/2016/02/16/why-we-arent-surprised-that-ezubo-the-p2p-lender-in-china-is-a-ponzi-scheme/">Why We Aren’t Surprised that Ezubo, the P2P Lender in China Is a Ponzi Scheme</a>

<a href="https://cfi-blog.org/2015/07/28/new-surveys-fill-data-void-in-chinas-microfinance-industry/">New Surveys Fill Data Void in China’s Microfinance Industry</a>

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<a href="#_ftnref6" name="_ftn6"></a>

&nbsp;

How New Credit Scores Might Help Bridge China’s Credit Gap

Mapping the Invisible Market

Partnership for Responsible Financial Inclusion

&gt; Posted by Susy Cheston, Senior Advisor, CFI

<img class="alignright wp-image-21146" style="border:0 solid #000000" src="https://centerforfinancialinclusionblog.files.wordpress.com/2016/04/kgfs.jpg" alt="" width="330" height="185" />A lot of money is being spent on financial education—and we’d like to see it spent more effectively. We still don’t know all that is needed about what works, but based on our <a href="http://www.centerforfinancialinclusion.org/publications-a-resources/browse-publications/724">scan of the current landscape</a> for financial capability-building innovations, we can already recommend six major shifts in how financial capability resources are deployed.

The first three recommendations relate to who is building financial capability.
1. Bring financial capability efforts closer to the actual use of financial services by enabling providers to take a greater role.
2. Shift the expectation that the government is responsible for financial capability to an expectation of shared responsibility among all stakeholders, including financial service providers and other institutions.
3. Engage organizations serving BoP constituencies, from government social service agencies to employers to non-profits.
This calls for “all hands on deck.” We argue, first and foremost, that providers can and should take a primary role in building financial capability, as they are best equipped to reach customers at teachable moments and to help them learn by doing. Many providers are already spending significant resources on financial education. They could have a much greater return on their investment if they focused those resources on embedding financial capability into product design and delivery, looking at all the touch points in the customer experience as opportunities to help customers use products more successfully.

Fortunately, there are some easy wins, such as the use of nudges, reminders, and default options that bring high impact for very little cost. Other shifts may take more time but are worth the investment. For instance, customer data analytics can yield detailed segmentation so that interventions can be tailored to customers. At the same time, data analytics can support two-way communication so that providers can hear from customers directly and at the time convey important information to them. BBVA/Bancomer is one of a number of banks working with Juntos, a service provider specialized in data analytics for financial capability-building. Juntos provides BBVA/Bancomer customers with reminders through SMS messages. The good news for providers is that technology opens up tremendous opportunities to build capability—at relatively low per customer cost.

One legitimate concern is whether or not providers—and their front-line staff—have the capacity to build financial capability. If front-line staff are not themselves financially capable, it may be hard for them to explain services to customers. At this point, few financial service providers have deep expertise in financial capability-building, and even less in behaviorally-informed approaches. While investing in such expertise may pay off over time, a faster solution may be to bring in consultants specialized in the design of financial capability interventions or service providers that interface directly with the financial institutions’ customers. Over the long term, investments in building the financial capability of front-line staff and agents may pay off. Organizations such as Microfinance Opportunities have found success in providing aids such as scripts or flip books that help front-line staff and agents communicate correctly with customers.

We found a number of providers that are embedding behavioral insights into their financial services. Janalakshmi, a microfinance institution in India is working on a number of fronts, including developing easy-to-remember rules of thumb to communicate through mobile phones, using in-depth household data to customize advice, and providing one-on-one counseling. KGFS incorporates tailored financial advice into its service model. Some commercial banks are also innovating, as is the case with the Saldazo transactional account of Banamex in Mexico, which uses text messaging and a call center to inform customers, answer queries, collect information, and encourage product use. Customers who provide their mobile number receive an SMS after each transaction with messages that encourage account usage and provide tips.

A strong role for providers does not absolve governments of their responsibility. One natural role is to build behavioral principles into national financial inclusion and financial education strategies and into school curricula. At the same time, we see opportunities for governments to shift their focus toward equipping and enabling providers and other actors, including reducing barriers to innovation. These efforts must be supported by a strong client protection framework—one that helps draw the line between building capability and overly aggressive marketing tactics, so that customers are protected and providers are clear about their limits. Governments that provide G2P payments electronically also have a huge opportunity to use a direct deposit into an account as a teachable moment—one that leads to active use of accounts and becomes an on-ramp to other financial services.

We believe there is a role for all stakeholders, and urge the many service providers who work with people at the base of the pyramid to play their part to build financial capability and connect people to providers. This includes employers, social service organizations, hospitals and clinics, and others who connect with people during critical life events.

The remaining three recommendations have to do with the paradigm shift toward behavior and keeping customers and their needs at the center.
4. Incorporate proven elements that support behavior change into existing financial education and financial capacity efforts.
5. Measure results rigorously.
6. Foster customer-led financial capability.
We call on all actors—including financial education experts—to close the gap between knowing and doing by focusing their efforts on customers’ behavior. We have identified <a href="https://cfi-blog.org/2016/04/12/a-change-in-behavior-innovations-in-financial-capability/">seven behaviorally-informed practices</a> that we believe are a good start. But we also believe that these practices need a lot more refinement based on evidence of what works and what doesn’t—evidence that can only come about if those who work on building capability do the hard job of developing metrics for impact based on outcomes not just outputs. In other words, too much of what we know is how many participants receive messages, rather than what actions they take as a result.

Our final recommendation addresses the perspective of customers. We cannot presume to know what matters most to customers, what problems they are trying to solve, or how they would like to be contacted. Throughout our survey, we heard from many people who think deeply about what financial capability means from a customer perspective—and who caution us about the need to approach this work with humility. That means, above all, listening to customers, and developing feedback loops so that our efforts match what customers need in order to achieve healthy financial behaviors that support their goals.

Have you read?

<a href="https://cfi-blog.org/2016/04/12/a-change-in-behavior-innovations-in-financial-capability/">A Change in Behavior: Innovations in Financial Capability</a>

<a href="https://cfi-blog.org/2013/07/22/clearing-the-path-to-financial-capability-in-latin-america/">Clearing the Path to Financial Capability in Latin America</a>

<a href="https://cfi-blog.org/2014/02/25/mobile-microinsurance-products-and-financial-capability/">Mobile Microinsurance Products and Financial Capability</a>

Six Recommendations on Financial Capability

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