Credit Reporting & Data

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fully electronic Public Credit Registry introduced its first online credit report, replacing a manual system that used outdated paperwork.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.

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.

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.

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.”