Credit Reporting & Data



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How is the world doing on Credit Reporting and Data Analytics?

Credit Reporting: Better Credit Reporting = Better Borrowers in a More Stable Financial Ecosystem

Let’s move credit reporting move higher up on the financial inclusion agenda. It’s an essential risk management tool for providers, and it allows consumers to become ‘visible’ as creditworthy. It helps prevent over-indebtedness. We need more investment in credit reporting infrastructure, in data analytics innovations, and in the use of alternative data to bring thin-file customers into the system.

Our Assessment

Why It Matters

We have become big fans of credit reporting. It’s good for providers, as its predictive power makes it an essential tool in risk management. Credit reporting allows lenders to improve portfolio quality, increase credit volume, lower operational cost, establish a borrower’s financial identity and capacity to repay, and, ultimately, improve profitability.

And credit reporting is good for consumers—allowing them to become “visible” as creditworthy, and at the same time helping prevent them from becoming over-indebted. The benefit is especially clear for those more likely to be excluded. When lenders are able to base credit decisions on objective information, the result can be increased availability of credit to the poor and for micro and small businesses. All of this strengthens financial stability.

The recent report What Happens to Microfinance Clients Who Default makes a strong case that effective credit bureaus give financial service providers the confidence to treat customers who default more humanely (see “New Research Shows Credit Bureaus Allow Providers to Act More Humanely”). Of course, credit bureaus help prevent delinquency in the first place. The Credit Information Bureau Ltd. (India) claims that delinquency rates in India are currently at a historic low due to the availability of timely credit information for lending.

Credit reporting can affect cost and credit availability sector-wide. In South Africa, the launch of the National Loans Register in 2000 was accompanied by a drop in the cost of credit from 230 percent to 30 percent. After the introduction of a credit bureau, the likelihood that a business has access to finance increases, interest rates drop, maturity lengthens, and the share of working capital financed by banks increases. We can see the link between credit reporting and financial inclusion in this graph from the report By the Numbers, which shows a clear connection between the strength of a country’s credit reporting system based on the Global Microscope and the percentage of adults who borrowed in the past year according to the Global Findex. In a nutshell, the better the credit reporting system, the more borrowers. It’s a pretty clear correlation and should make people who care about financial inclusion take notice.

For the large numbers of BoP customers who for the first time are trying to establish creditworthiness, there is very promising news. Innovations in alternative data and data analytics leverage a wide range of information about prospective customers, going beyond financial service histories, and these techniques are being applied in experiments all over the world to assist thin-file customers. The innovations have the potential to enable many currently excluded people to gain access to financial services.

In this report we review the progress of traditional credit reporting and explore the likelihood that alternative data and data analytics will reshape the credit reporting ecosystem.

new research shows credit bureaus allow providers
to act more humanely

The Smart Campaign released research in January 2015 asserting that the fate of distressed borrowers depends less on the mercy of the institution to which they owe the money, and much more on the rules of the country where they live. The study looked at what happens when microfinance clients default in Peru, India, and Uganda, and drew the conclusion that lenders generally act humanely when the enabling environment is positive, including the presence of effective regulators; a culture that upholds fulfillment of debt obligations; and a well-functioning credit bureau. Where credit bureaus exist, borrowers know that lenders will see their defaults on their credit reports, and have incentives to maintain a positive credit history or risk losing access to credit in the future. Likewise, lenders have the assurance that borrowers will repay if at all possible. That confidence allows lenders to negotiate repayment rather than immediately adopting harsh practices.

Progress to Date: Not Quite Half Full
Progress Index Score: 4

The landscape of credit reporting is changing rapidly, both in terms of the kind of data and the entities analyzing and using that data. The availability of data has exploded, providing information beyond the financial data used by standard credit bureaus, to encompass alternative data sources from phone use history to utility payments. These data are being analyzed in new ways for consumers who were previously credit-invisible. And there are new actors at the table – new credit bureaus in developing markets as well as new entrepreneurs creating models for analyzing and selling data to financial service providers.

When we reviewed recent progress in credit reporting, we first considered a half-full/half-empty score.

There was plenty of reason to believe the glass was “half full,” because the growth and spread of credit reporting entities is very encouraging. Between 2004 and 2013, the total number of private-sector credit bureaus and public-sector credit registries nearly doubled from 109 to 192, covering 154 countries (of 189 measured in 2013). And more than 1.3 billion individuals and firms worldwide are now covered by a credit bureau, and 600 million by a credit registry. The role of the World Bank Group is of special note here. The World Bank led the charge to develop the “General Principles of Credit Reporting”, and the International Finance Corporation (IFC) has been tireless in strengthening credit reporting services in many countries. In FY2013 alone the IFC provided advisory services to over 60 countries and drafted or contributed to drafting 33 new laws and regulations. Also on the “full” side, the exciting developments in alternative data use and data analytics are spawning an ecosystem of innovators and anticipating the possibility of reaching millions of people not covered by traditional credit reporting methods.

But we ultimately settled on a slightly less optimistic score of 4, because the “empty” side is just too daunting.

Many of the new credit bureaus are in their early stages, and enormous gaps in coverage, reliability, and active use remain, especially for BoP market segments. In some countries, new laws are weakening existing private credit bureaus or they are being replaced with public credit registries, to the extent that credit reporting is going backward. It will require hard work and investment, especially in lower-income countries, to close those gaps. And, as exciting as the data revolution may be, few innovators have reached scale, while many are still working on proof of concept.

Donor and investor interest is haphazard, as there are too many unknowns to allow solid analysis of the new business models. Regulators have concerns about the lack of standards and are not able to keep up with the wide variety of new approaches. The private sector in turn has concerns about the uncertain regulatory environment. A number of big institutions are pursuing proprietary systems rather than participating in national credit bureaus. And no one is sure whether data analytics will provide affordable and reliably predictive results. Most important, how will data analytics work for BOP consumers? Will it provide an on-ramp to inclusion? Will data privacy and security issues turn the Promised Land into a nightmare for customers?

Over the longer term, our best bet is that traditional credit reporting providers will eventually absorb the best of the data innovations.

One thing we’re betting on in the nearer term is alternative data. As PERC, a think tank devoted to use of alternative data in credit reporting, says in Research Consensus Confirms Benefits of Alternative Data, many forms of alternative data, such as rental, utilities, and cell phone payments, definitively predict creditworthiness and could readily be incorporated into credit scoring models.

In this report we examine recent developments in traditional credit reporting, alternative data, and data analytics. Despite the big caveats we’ve mentioned, it’s worth watching this space: the learning, growth, and innovation curves are steep.

Between 2004 and 2013, the total number of private-sector credit bureaus and publicsector credit registries nearly doubled from 109 to 192, covering 154 countries (of 189 measured in 2013).

Traditional Credit Bureaus Are Growing, but Infrastructure Investment Is Needed

Most of the world’s countries now have some type of credit reporting (only 35 of 189 countries measured do not). New credit bureaus have launched in the past several years in Tajikistan, Cambodia, Vietnam, Tonga, Tanzania, Guyana, and Jamaica. In April 2014, Afghanistan’s new, fully electronic Public Credit Registry introduced its first online credit report, replacing a manual system that used outdated paperwork. Even in a new market such as Myanmar, a credit bureau is expected to be operational by June 2016 and serve about 3 million credit reporting inquiries by June 2020. And other models are emerging, with West Africa and the Asia-Pacific region among those innovating with cooperative regional approaches (see “Regional Credit Reporting That Crosses Borders” in previous section).

While it is important to bring credit reporting to the 35 countries who don’t have it, it is at least as large a challenge to improve the quality of the credit reporting systems in the dozens of countries where such systems are new, struggling, or lacking coverage of lower income clients. And in recent history there has been a troubling trend toward building public credit registries – even, in some cases, replacing private credit bureaus – despite the evidence that private credit bureaus are more effective. Meeting this infrastructure challenge requires the combined efforts of credit reporting entities, regulators, financial service providers, and funders.

Regulators in many countries – including Morocco, Cambodia, and India – have jumpstarted the industry by requiring all providers to contribute data. In all but 11 of the countries reporting to the World Bank Doing Business report, regulators require the use of positive as well as negative data, which significantly improves predictive ability and access to credit. In some countries key stakeholders work together, as in the launch of the MFI Credit Bureau Initiative in India (See sidebar “Crisis Triggers Fast Growth of Credit Reporting for Microfinance in India”).

Yet even when credit bureaus have appeared, many financial service providers do not actively participate. Credit bureau business models depend on active lender participation to generate fees, and low participation makes credit reports spotty and unreliable. It also results in higher prices for credit inquiries, which in turn discourages use. Many lenders that serve lower-income customers are reluctant to participate. Some do not want to make the investment to connect their systems with those of the credit bureau. Others are satisfied with their own credit underwriting and see the credit bureau report simply as an added cost. Still others are unwilling to share information with competitors.

IFC has done important work to bring stakeholders together and to build the credit reporting ecosystem, and its work has been supported by a number of governments' development agencies, including those of Australia, Austria, Canada, Italy, Japan, Luxembourg, the Netherlands, Norway, New Zealand, Switzerland, and the United Kingdom. Some private organizations have also been supportive, such as the Omidyar Network and Visa International. Yet the costs of building and improving public credit registries and of launching private credit bureaus – supported by regulation that ensures providers will participate in the system and cover its costs – require deeper investment at the country level.

An equally imposing challenge for new systems is ensuring data quality. Credit reporting systems “should be safe and efficient, and fully supportive of data subject and consumer rights,” as stated in the General Principles for Credit Reporting, yet not all systems currently achieve those standards. Of the 55 countries covered by the Global Microscope 2014, 87 percent have functioning credit reporting systems, but only 18 percent have effective systems, meaning that they are comprehensive, regularly updated, and accessed by providers. Even countries with mature credit reporting industries struggle to ensure that consumer data are accurate and used appropriately. (For more on “Good Practices in Credit Information,” see the World Bank Doing Business report. For an overview of the structures and governance of credit reporting in emerging markets, see Credit Bureaus in Emerging Markets: Overview of Ownership & Regulatory Frameworks, published by PERC.)

We would like to see credit reporting move up on the financial inclusion to-do list. Of 147 Maya Declaration commitments tabulated by the Alliance for Financial Inclusion since 2011, only 16 are related to credit information systems. Credit reporting is a must-have for an inclusive financial system.


Credit Reporting for Microfinance
in India

In 2010, the delinquency crisis in India’s Andhra Pradesh galvanized efforts to build credit reporting systems for microfinance in India. The IFC worked closely with the Microfinance Institutions Network (MFIN) and other stakeholders, with support from the Omidyar Network, to fast-track a comprehensive credit reporting system. The word “comprehensive” is important here, as there was high potential for market fragmentation with closed user groups in the rush to develop quick solutions. Instead, the system that launched promoted the comprehensive sharing of credit information among all MFIs nationally. The MFI Credit Bureau Initiative–India has achieved a high level of participation in a very short time. From the initiative’s launch in March 2011 until March 2014, 176 MFIs became members, with 129 submitting data at least monthly and 116 drawing data. (See the Credit Reporting Knowledge Guide for more examples of best practices.)

Alternative Data Is a No-Brainer

The most promising trend we see, both for publicly available credit bureaus and for individual lending institutions, is the increasing availability of new, alternative forms of data.

The evidence is unmistakable: alternative data can be predictive of future payment activity for no- and thin-file customers. Alternative data includes the payment and use information generated by consumers, including those who may not yet have access to formal financial services. It includes, for example, data on phone use and payments, utility use and payments, property rental, and participation in agricultural cooperatives. And potentially useful information is also generated through Internet and social media activity, but use of this data generally requires more specialized techniques (see next section).

In countries such as Colombia, China and Mexico, the availability of alternative data is already making people who were once credit-invisible now visible. In South Africa, the more the data types or data sets hosted by credit bureaus, the greater the economic benefit for businesses and individuals. In the United States, non-financial data, such as utility and telecom payment histories, has proved to be predictive of future delinquencies on traditional credit accounts (bank card or mortgages), potentially providing an on-ramp to credit for the one in five Americans without a credit score.

According to the Doing Business survey, 32 of 99 credit bureaus around the world distribute credit information from trade creditors, 41 from retailers, and 30 from utility companies. In April 2011, for example, two mobile phone companies and an electricity and gas company in Rwanda started providing credit information to the credit bureau, leading to an immediate 2 percent increase in the number of firms and individuals registered in its database.

So why isn’t alternative data used more often? Among other reasons, the owners of the data lack incentives to share it and don’t trust that the data will be protected. There are also important questions about who owns the data and has the right to monetize it. Regulators can help by implementing rules that permit non-financial providers of data to make their customer data available to lenders, and that encourage lenders to utilize alternative data in credit underwriting and other financial services.

These rules need to go hand in hand with sufficient protections of consumer data. In the early days of credit reporting, credit bureaus collected information about people’s health, personal habits, and morals – including their marital troubles and sex lives. That was a level of “alternative” or “non-financial” data that the global community now resoundingly agrees should be off-limits. Yet, in the United States, that change came about only after outrage over the intrusion into customer privacy led to the passage of the Fair Credit Reporting Act of 1960. Enthusiasm over the strong benefits of alternative data needs to be tempered with appropriate controls.

Alternative data can be used both by traditional credit reporting service providers and by the new data analytics entrepreneurs. The terms alternative data, big data, and data analytics are frequently confused, but it is important to distinguish between the new types of data becoming available (alternative data) and the manner in how this data is analyzed (data analytics), as well as the uses of that data (see “ A Credit Reporting Cheat Sheet ” below). New analytic techniques have emerged to take advantage of the new flood of information, and the entrepreneurs who are applying these techniques may well upend the traditional credit bureau model, as discussed in the next section. For now, we simply underline the point that alternative data is a potential credit lifeline for new and thin-file customers, and any organization concerned with credit reporting should be working to incorporate it.

Alternative data is a potential credit lifeline for new and thin-file customers, and any organization concerned with credit reporting should be working to incorporate it.

Data Analytics Are Promising but Unproven

We’re excited about the potential of data analytics to leverage information culled from Internet searches, social media, mobile apps, etc., using sophisticated algorithms that can identify creditworthy people who might otherwise be left out of the system. The new data analytic techniques could be applied in traditional credit bureaus (to the benefit of the market as a whole), but more often, the entrepreneurs who deploy these techniques are either operating their own lending operations or partnering with individual lenders to enhance the lenders’ credit underwriting. Their effect on the larger credit reporting ecosystem remains to be seen.

GO Finance, operating in Tanzania, and Konfio, in Mexico, are online lenders whose models are based on data analytics. GO Finance leverages digital data and mobile money channels to underwrite and manage loans for small and medium-sized enterprises (SMEs), particularly targeting farmer cooperatives and others in the agricultural value chain. Konfio uses credit algorithms based on alternative data to help micro and small businesses obtain working capital loans. Konfio’s digital platform allows for low-cost customer acquisition and rapid credit assessment, enabling the company to offer lower rates. Demyst Data, by contrast, partners with financial institutions – global banks, online lenders, and card issuers. It analyzes online, social, and internal data to help its partners lend to thin-file, underbanked customers. Alibaba’s Ant Financial and its new Sesame Credit (see sidebar “Credit Reporting with Big Data: Alibaba’s Sesame Credit") use proprietary customer data drawn from non-banking transactions to support lending, with Alibaba’s e-commerce business, financial service provider (Ant), and credit reporting service (Sesame Credit) all arms of the same conglomerate.

For data analytics to reach its enormous potential, there are big questions that need to be worked out. Is it really predictive? Will it really enable more BoP customers to obtain credit? Will customers’ rights to data privacy be protected? How can data analytics be effectively regulated?

In the United States in 2014, a National Consumer Law Center (NCLC) study, Big Data: Big Disappointment for Scoring Consumer Credit Risk, found shocking inaccuracies – “dirty data” – and significant opportunities for discrimination rather than a dramatic wave of new customers entering the financial system. The NCLC made some important recommendations for regulators to consider, including testing the accuracy of the data and the predictive ability of the algorithms as well as screening for compliance with consumer protection laws and ensuring that there is no potential for discrimination. The NCLC advises policymakers to focus on a basic question: does this use of big data improve choices for customers?

There are also important questions about the rise of proprietary models. If the increasing availability of data and new technologies makes it possible for financial institutions to use data without going through third-party credit reporting service providers, there are significant risks of losing the “public good” aspects of the system. Credit reporting systems that are open to all help build an ecosystem that motivates customers to behave responsibly, prevents over-indebtedness, and contributes to the kind of shared information that changes the market culture.

The market is evolving in multiple ways. In the case of Sesame Credit, the intention is to sell the data to other providers, including not only financial institutions but also car dealers, hotels, and even an online dating service (see sidebar “Credit Reporting with Big Data: Alibaba’s Sesame Credit"). Banco Azteca in Mexico has already followed much the same path, moving from using group-generated data to creating a publicly available credit bureau, albeit with more conventional analytics. Given the number of new licenses for private credit bureaus, the hope is for a system in which competition leads to open access rather than a proliferation of closed systems.

We don’t adhere with the prediction that traditional credit bureaus are becoming obsolete. Instead, we believe that the innovations that are transforming traditional models will most likely lead to productive partnerships involving both old and new players. (See Michael Turner’s opinion piece in the FI2023 Roundup e-magazine and his blog post, “More Credit Information Sharing in Emerging Markets: A Call to Action!”) And this will be a good thing.

Credit Reporting with
Big Data: Alibaba's
Sesame Credit

E-commerce in China opens up new credit reporting models in a country where many people do not have a credit history.

Data Privacy Laws have
Global Momentum

Automated credit approvals can be computed in a matter of seconds – even when a consumer or business owner does not know data is being collected. This is an issue not only for consumers, but also for commercial credit reporting, which is not always covered under consumer protection laws.

Helping Consumers Thrive in a Credit Reporting Ecosystem

New and financially fragile customers may need help in navigating a system in which credit reports govern their access to financial services. Credit building programs support people to build or repair their credit histories. Credit Builders Alliance puts it this way: “A good credit history is not only an asset, it is the means to greater and more sustainable financial stability, savings and asset building opportunities.” Typically, credit building programs offer loans and secured credit cards designed to help customers who make on-time repayments to build a positive credit history. Sometimes the first step in improving financial health is for a consumer simply to learn about his or her credit score. This is the starting point for CreditMantri, a financial advisory service in India that helps consumers that are underbanked, credit negative, or new to formal financial services. The company uses an automated web platform and call center to help consumers access their credit reports, understand their credit scores, improve their creditworthiness, restructure outstanding debt, and get access to relevant products and services from lenders and financial institutions. Intoo, in Brazil, works with SMEs that typically do not have access to financing, helping them to build credit profiles and then connecting them to a wide network of banks and financial institutions.

Credit Karma allows consumers in the United States to monitor their credit reports and scores for free, while offering them tools – and suggestions based on their credit profile – to improve them. Its business model is based on presenting tailored product ads from financial companies. According to its founder Ken Lin, if a consumer buys one of the advertised products, “. . . we should make money, you should save money, and the bank should get a new customer. The loser in the equation was that bank that was charging too much.”

A good credit history is not only an asset, it is the means to greater and more sustainable financial stability, savings and asset building opportunities.

Credit Builders Alliance

A Call to Action

Our main message on credit reporting is simple: move credit reporting higher up on the financial inclusion agenda. This message is especially directed at governments that need to take the lead in bringing stakeholders together and crafting supportive regulations so that robust credit reporting systems can develop. And the task includes supporting financial institutions so they can use credit reporting effectively, and supporting consumers to understand and navigate the credit reporting landscape.

Our second message, almost as insistent, is for all actors working in credit reporting to embrace alternative data, and especially to direct its power to identify creditworthy customers among the currently excluded.

As for the new data analytic–based business models, we urge regulators to watch this space and be prepared – as viable business models emerge, but not before – to work with providers and consumer advocates to craft appropriate data privacy, ownership, and use regulations. We will be watching the space with high expectations, too.

A Credit Reporting Cheat Sheet

First Access: Mobile Data and Informed Consent

First Access is a startup that uses prepaid mobile phone history to assess borrower creditworthiness on behalf of microfinance institutions. Customers grant consent for access to their phone records, and First Access’s algorithm analyzes that history to generate a loan recommendation that is texted to the institution’s loan officer in mere seconds.



Lead Author

Susy Cheston

Center for Financial
Inclusion at Accion

This report draws on insights gained through interviews with industry experts and comments by reviewers. These contributors are gratefully acknowledged below, but we want to make clear that the positions expressed are our own. The opinions in this report do not necessarily reflect the views of the contributors nor do we intend to imply any endorsement by the institutions they represent.

We express our thanks to:
Elisabeth Rhyne, lead contributor and editor, Center for Financial Inclusion at Accion

Click here for the complete list of contributors to the FI2023 Progress Report.

For a curated list of resources on Credit Reporting & Data, check out the FI2023 Resource Library.

For an up-to-date collection of blogs on Credit Reporting & Data, check out the CFI blog.