Data sharing models: The potential for financial innovation and the risks that must be managed

July 12th, 2018

There is a range of new data sharing models emerging that could have a significant impact on financial innovation in emerging markets.

I have a confession: I don’t use Facebook, I’ve never been on Instagram, and I didn’t have a smartphone until iPhone was into generation 4. I am not an early digital adopter.

But I am fortunate enough to have a banking history that dates back to when I was 10 years old, an M-Pesa statement I can download with a few clicks of a shortcode and an email address, and range of other financial data I can use for my daily needs. I have also been unfortunate enough to be a victim of credit card fraud at least two times in my life. The point is, my alternative data may be low compared to my peers, but my financial history—both the good and the bad—is high.

Despite all the buzz about alternative data, I’m guessing that hundreds of millions of emerging market consumers may have no email, little social media usage, but a useful financial history at their local bank, micro-finance institution, or in the mobile money wallet on their phone.

However, too often the consumer has little visibility of this data, no way to access the data in digital format, and little power to restrict their financial service provider sharing this data with third-parties they are in a business partnership with.

Fortunately, this is changing fast. There are a range of new data sharing models emerging that could have significant impact on financial innovation in emerging markets. I recently conducted a global review of these data sharing models for the Bill & Melinda Gates Foundation, including a deep dive into the potential of these models for Kenya, Tanzania and Uganda.

For my research, I defined a data sharing model as:

A data sharing model is a service, platform, or product that collects and/or creates digital records for individuals including financial history and alternative data (e.g. web history or phone records); and allows individuals to make this data available to multiple third parties offering products and services.

Several governments across the globe have already mandated some form of data sharing in their markets, including open banking in the United Kingdom, the Law to Regulate Financial Technology Institutions in Mexico, and the DigiLocker in India. (See map above.) While these models are still in their early stages, they could help address some of the challenges financial consumers in emerging markets face in leveraging their financial history to increase the choice and suitability of financial products. Financial service providers would also be better able to assess these consumers’ needs.

There may be an even greater use case for data sharing models in markets like Kenya than the United Kingdom. There are a greater number of underserved financial consumers in these markets who lack access to web browsers or email addresses. With such limited access to their financial information, these consumers have to rely on firms such as mobile network operators (MNOs) or banks to share this data—who typically only share this with a select set of partners. With mandatory consumer rights to access and use their financial information, we may see more firms emerging that help consumers manage their information for greater choice and competition.

Private sector models are already emerging in East Africa. Some of the most exciting models are digitising information linked to the “real economy.” This includes apps that digitise savings groups, or record-keeping software for small businesses that also generate leads on financing based off their records, among many others noted in the full report, available here.

But these innovations will need clear rules to ensure consumers truly have control over their personal and financial information. Consider, for example, the credit scoring service MNO r Safaricom has piloted with several fintech lenders that includes data on mobile money, airtime and digital credit history (see figures 1 and 2).  Fintechs reported increasing lending limits up to 250% after using this data versus their traditional data-scraping models.

However, the data is not disaggregated and lender access to this data is at the discretion of the data holder; in this case the MNO. This means that consumers do not have as wide a choice of firms and products with whom they can share this data outside Safaricom’s commercial agreements. In addition, since the loan data includes loans originated by banks, it may also undermine the credit reference bureau system by offering a way for firms to access this data without participating in the credit bureau system, and by independently setting the cost of a credit scorecard at 100 Kenyan Shillings each.

This example demonstrates how private sector data sharing models may need to be complemented with new rules, or enforcement of existing rules, to ensure that the principles of consumer control and openness are enabled to facilitate increased financial access, innovation and product diversity. The recent announcement of a draft data privacy bill in Kenya, and the Data Privacy and Protection Bill already out for public comment in Uganda show policymakers are heading in the right direction. To complement these laws, financial sector authorities will likely need to develop their own versions of the new set of data sharing policies emerging globally. This includes addressing the challenge of large sections of the financial industry that are currently unregulated and not subject to banking laws on topics such as credit reporting or customer privacy rules. Democratisation of data in East Africa has high potential to improve access, innovation and competition, we just need to put the right policies in place to help these new models flourish.



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