> Posted by Susy Cheston, Senior Advisor, CFI
Data analytics is a big story these days, and we’re excited about its potential. In fact, we discuss its promise in the Technology, Addressing Customer Needs, and Credit Reporting sections of the FI2020 Progress Report. In terms of credit reporting, data analytics start-ups claim that their algorithms can cull information from Internet searches, social media, mobile apps, and so on to identify creditworthy people who might otherwise be left out of the system.
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 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 for credit reporting, there are big questions that need to be worked out. Is it really predictive? Will it really enable more customers at the base of the pyramid 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 options 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 good news, in that light, is that data analytics providers are not likely to overturn traditional credit bureaus. A far more likely scenario is that credit bureaus will start adopting data analytic techniques, and will acquire the most promising start-ups. That would be an exciting development, as the entrepreneurs who deploy these techniques today are either operating their own lending operations or partnering with individual lenders to enhance the lenders’ credit underwriting. That means their work is not transforming the larger credit reporting ecosystem.
The FI2020 Progress Report rates credit reporting & data analytics as a 4 out of 10 in its current state around the world. As I’m writing this post, the “People’s Vote” is a little more optimistic, with a score of 5. We invite you to cast your vote. Of course, data analytics is not the only story in the report on credit reporting. We also describe the latest accomplishments in establishing credit bureaus and making them work for the base of the pyramid, as well as lauding advances in the adoption of alternative data. If you’re not sold on the importance of data to financial inclusion, you might head to the “Why It Matters” section of the FI2020 Progress Report on Credit Reporting as a starting place. Though if you’ve read this far in this post, you likely already recognize how credit reporting & data analytics could be the most underappreciated drivers of inclusion.
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