Building Data Ecosystems for Financial Inclusion

What does it take to go from data silo to data flow?

This post is one of five entries related to the report “Accelerating Financial Inclusion with New Data,” 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.

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.

Our recently released report, Accelerating Financial Inclusion with New Data, 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 report 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 report 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.”

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.

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 partnerships between financial institutions and fintechs. 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.

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