The future of banking in light of technological disruption has been high on the agenda of banking sector analysts, policy makers and researchers. The Libra announcement by Facebook has raised the urgency of the topic
of digital currencies in central bank corridors around the world. As most banking/corporate finance researchers, I have somewhat contributed to this literature by (i) looking
at the effects of financial innovation in banking more generally (finding both a stability-reducing and growth-enhancing effect) and (ii) analysing the real sector effects of
mobile money in Kenya. While both studies are (by their empirical nature) backward-looking, I am also getting involved in more conceptual discussions, both on the inclusion as on the stability side. So, in the next few months, I will publish some thoughts
on the future of banking and technological disruption on my blog – all of this purely my own thoughts, but often based on other people’s research.
innovation has been around for centuries and often has had disruptive effects. The introduction of the ATM in the 1970s allowed US banks facing geographical constraints to undermine them and ultimately contributed to the liberalisation of branching restrictions
in the US. Financial innovation often comes in the form of new types of intermediaries. As discussed by Laeven, Levine and Michalopoulos (2015), specialized investment banks
emerged to facilitate the construction of vast railroad networks in the 19th and 20th centuries across North America and Europe, screening and monitoring borrowers on behalf of disperse and distant investors. In the second half of the
20th century, venture capital funds arose to finance IT start-ups, characterized by limited if any tangible assets that could be used as collateral and thus requiring patient investment capital and close screening and monitoring as well as technical
advice. Today’s disrupters are FinTech and BigTech companies, although there is a big difference between the two. FinTech refers to technology-enabled innovation in financial services with associated new business models, applications, processes
or products, all of which have a material effect on the provision of financial services. While often undertaken by independent start-ups they do not really compete against banks – to the contrary, banks encourage experimentation in this space and
often take over successful companies. BigTech companies, on the other hand, are large existing companies whose primary activity is in the provision of digital (platform) services, rather than financial services; for these companies financial services
is thus an add-on service. A critical difference between BigTech companies and other large companies that (want to) branch out into financial services (e,.g, Banco Azteca in Mexico, Walmart in the US) can be summarised with the acronym DNA, an expression
coined by the BIS – data, network and artificial intelligence. Banks have always relied on their ability to collect and process hard and soft information about borrowers; BigTech firms have such data readily available from their non-financial
business with customers; artificial intelligence allows them to also convert soft information into hard information. Several papers have shown that information collected this way is better in predicting default than information shared between banks in credit
registries (e.g., here and here). In addition, given their platform character, BigTechs enjoy network economies, helping to reduce transaction
costs and allowing better diversification. This provides the chance for BigTech companies to enter areas so far dominated by banks, including retail banking.
increasing accumulation of data raises important questions on the use of such data but also the ownership of data. The Open Banking initiative in the EU allows customers to share data across different
banking institutions. The question is whether this should be expanded to BigTech companies, especially when they move into financial service provision. It also raises concerns on new risk sources, such as cyber risk, and might require a stronger focus of regulators
on consumer protection.
The possibility to use an increasing amount of data also raises question on how they are being used. The financing constraint
view has argued that more data allows more efficient provision of financial services and allows reaching households and small enterprises that so far have been excluded due to their lack of collateral and audited accounts. Credit registries are typically seen
as critical component of the institutional infrastructure underpinning financial deepening, as they allow clients to build up reputation collateral. On the other hand, there is increasing evidence that such data can also be used for client-specific targeting.
More data allow price discrimination and targeted shrouding, where the latter is more consequential in finance, given intertemporal nature of contracts. I recently had the honour of discussing a paper by Antoinette
Schoar showing exactly that for credit card offers in the US: Less educated consumers receive more back-loaded terms (low teaser interest rate but high late-payment fees), and more shrouded offers, exploiting behavioural biases.
In summary, the financialisation of the modern economy and society seems to give way to the digitalisation of finance. This offers great opportunities for innovation and increased
competition in the financial sector, but also lots of public policy challenges. In a future blog entry, I will focus more on the stability challenges.