Big tech in finance: opportunities and risks
It is still early days for large technology companies or “big techs” in financial services, but given their size and customer reach, these have the potential to spark rapid change in the financial system. This edited speech provides an initial assessment of the benefits and costs, and lays out a number of questions that deserve more attention.
The big techs were one of the topics during the recently-concluded Bank for International Settlement’s annual general meeting held in Basel, Switzerland. The discussion centred on their entry into financial services even with already established platforms in their respective businesses.
Big techs’ entry into finance introduces new elements into the risk-benefit equation. Some are old issues of financial stability and consumer protection in new settings, which can be addressed by adapting or expanding existing regulation. But there are also important new elements. Public policy towards big techs in finance needs to build on a more comprehensive approach that draws on financial regulation, competition policy and data privacy regulation.
The “DNA” of big techs’ business model
The business model of big techs rests on enabling direct interactions among a large number of users. An essential by-product of their business is the stock of user data. The data are then utilised as input to offer a range of services that exploit natural network effects, generating further user activity. Increased user activity then completes the circle, as it generates yet more data. We dub this the “data-network-activities” loop – or the “DNA” loop.
The DNA loop is self-reinforcing. More data generates stronger network effects, which elicit more activity, leading to yet more data. This means that big tech firms with an established platform have a running start when they venture into financial services.
The source of their competitive advantage depends on the nature of their existing platform. Big techs with e-commerce platforms collect data from the activity of sellers and buyers, and can combine them with financial and consumer habit information. These can be a valuable input into credit scoring models, especially for loans to small and medium-sized enterprises (SMEs) and consumer loans. Big techs with large social media platforms have data on individuals and their preferences, as well as their network of connections. Big techs with search engines do not observe connections directly, but typically have a broad base of users and can infer their preferences from their online searches. Both in the case of social media and in internet search, the big tech can use the information on users’ preferences for marketing financial products, or to serve as a supermarket for third-party financial services, such as in insurance.
Big data and financial inclusion
All of these advantages can expand financial services to users who were previously excluded. Take the example of lending. Screening borrowers for creditworthiness is a costly activity for lenders. Many SMEs in developing economies often do not have audited financial statements. Borrowers who lack basic documentation or are in regions without bank branches get left out of the formal financial sector. Big techs are in their element in this kind of setting. They can tap relevant information from their existing platforms and overcome the informational problems.
Another impediment to credit is the cost of monitoring and enforcement of loans. Banks usually require borrowers to pledge collateral to deal with the risk of default. Big techs can address issues of monitoring and enforcement in a different way. For example, it may be relatively easy for a big tech to deduct the (monthly) payments on sales revenues that flow through its payment account. Also, if the big tech is dominant, the simple threat of a downgrade or an exclusion from its ecosystem will be a powerful sanction against the borrower.
This could explain why, unlike banks, big techs’ supply of corporate loans does not correlate with asset prices much. In other words, the supply of credit from the big tech lender seems far less sensitive to the housing market than the credit decisions of banks.
Issues for financial regulation
There are many benefits of big techs. But there are also costs. Part of the costs are old issues in financial regulation in new settings. In this case, the response calls for the regulations to be adapted to the new setting. If such adaptation rapidly outruns the existing letter of the regulations, then a revamp of those regulations will be necessary. The general guide is to follow the risk-based principle and adapt the regulatory toolkit in a proportionate way.
A good example is the payment system, where big techs may already have become systemically relevant institutions. In China, big techs’ role as payment firms is mirrored by their role in money market fund (MMF) products, where users maintain their payment balances in money market funds. In turn, these MMFs mainly invest in unsecured bank deposits. Around half of the assets are bank deposits and interbank loans with a maturity of less than 30 days, which introduces potentially systemically important linkages between big techs and the banking system. A large redemption shock could transmit to the banking system through deposit withdrawals. To address these risks, the authorities in China have introduced a number of new rules, including rules requiring clearing on a common, public platform for all payment firms, as well as a cap on instant redemptions.
Market power and competition
Big techs introduce new elements that go beyond traditional financial regulation. The DNA loop, which lies behind the benefits of big techs, is also the very feature that brings costs associated with market power and data privacy. Once a captive ecosystem is established, potential competitors have little scope to build rival platforms that can mount an effective challenge to the incumbents. Dominant platforms can consolidate their position by raising entry barriers or by positioning their platforms as “bottlenecks” for a host of services, which could favour their own products at the disadvantage of other providers. Other practices such as product bundling or cross-subsidisation could further reduce competition. These are issues that are more familiar to competition authorities and economists working on industrial organisation, rather than financial regulators.
A second, important dimension has to do with data. One way to approach the problem is the decentralised (or Coasian) approach that assigns property rights over data to the customers. Customers could then decide which providers they choose to share data with and which to sell data to.
However, the DNA feedback loop challenges a smooth application of the decentralised Coasian approach. Big techs can obtain additional data from their own ecosystems in social networking, search engines and e-commerce that are outside the financial services they operate. Since data have increasing returns to scope and scale, big techs will be able to make far more effective use of any incremental data.
For these reasons, the competitive playing field may be levelled out more effectively by placing well designed limits on the use of data. Introducing some additional rules regarding privacy – while at the same time allowing selectively for the sharing of some types of data – could enhance effective competition by curbing the DNA loop.
One example is the various forms of open banking regulations that have been adopted around the world, and second is the European Union’s General Data Protection Regulation (GDPR). Open banking gives authorised third-party financial service providers direct access to bank customer data. They also set common technical standards for application programming interfaces. To the extent that they entail the transfer of data ownership from big techs to customers, both regulations can be seen as measures intended to facilitate greater effective market contestability.
At the same time, some of the new regulations limit the scope of data-sharing. Open banking regulations selectively restrict the range of data that can be transmitted. There are also restrictions on who can access the data. Similarly, the GDPR requires customers’ active consent before a firm can use their personal data. Both types of restrictions can be seen as barriers to big techs’ entry into finance.
Policy coordination and a need for learning
Given the many new challenges, the public policy approach will need to be joined up.
First, there is a need for closer cooperation between national authorities, namely competition authorities, financial regulators, and data protection authorities. Currently, their mandates and approaches are not always compatible.
Second, as the digital economy expands across borders, there is a need for international cooperation on rules and standards. The recent proposal by Facebook to launch a digital currency, Libra, has underscored the importance of cross-border cooperation.
Innovation is here to stay, and much of it will bring great benefits. With those benefits clearly in sight, some degree of disruption and structural change of the financial system should not only be tolerated but be welcomed. However, disruption for disruption’s sake is something that we should greet with greater caution. More than ever, clear thinking is essential to reap the benefits of financial inclusion and efficiency while mitigating the risks.
Hyun Song Shin is the Bank for International Settlements’ economic adviser and head of research.
Keywords: Big Techs, Consumer Protection, Financial Regulation, Data, Payment, Financial Services, Financial System
Institution: Bank For International Settlements, European Union’s General Data Protection Regulation