With their capacity to collect and analyze a diverse mass of data, tech giants are taking advantage of information asymmetry over traditional institutions to rapidly transform the financial landscape.
Already very present with their growing activities in payment applications, particularly in emerging economies, many large technology companies such as Alibaba, Amazon, Meta (Facebook), Alphabet (Google) and Tencent, have seen their activities in the sector financial gain macroeconomic importance in several countries. This is particularly true in China, Indonesia, Kenya and Korea, write the authors of a working paper published by the Bank for International Settlements (BIS).
Their business model highlights a feedback loop involving data collection and analysis, network externalities and their intertwined activities. A loop in which the big banks demonstrate much less efficiency. “With the exception of the payment system, they do not have operating activities with a high level of externalities”, which can be explained in particular by the separation of banking and commerce activities in many territories. “Banks thus essentially have access to the data of their transactional accounts,” underlines the document.
Through the gateway of payment services, the use of the mass of data generated by activity on e-commerce and social media platforms opens access to new markets, including financial services. , such as granting credit, insurance and savings and investment products. Services offered at lower fees and prices than those demanded by traditional players.
In this movement of expansion, the logical continuation of payments constitutes the granting of credit. In this niche, the tech giants offer the advantage of efficiency and inclusion, particularly among those excluded from the banking sector or in terms of access to credit. This potential access is even increased by a reduced need to resort to an accessory guarantee.
From their observations, BIS analysts show that the credit offered by digital giants reacts more to idiosyncratic shocks. “Not having to rely on an accessory guarantee in order to secure repayments, therefore not being linked to an asset, credit is little or not correlated to economic conditions or the price of houses, but more to the volume of transactions and the rating of the borrower. This can change the transmission mechanism of monetary policy,” they take care to emphasize in broad strokes.
Not having to rely on collateral in order to secure repayments, therefore not being linked to an asset, credit is little or not correlated to economic conditions or the price of houses, but more to transaction volume and borrower rating
This rich database makes it possible to scrutinize and monitor the borrower’s activity and habits, and even to increase predictive capacity in the event of an economic shock. Therefore, to facilitate the assessment of credit risk and its evolution over the life of the loan, at a lower cost than that absorbed by a traditional financial institution. A reduction in information and transaction costs which adds to their potential to lower barriers to inclusion.
And the risks…
At the same time, the business model of big tech companies is not without the potential to create risks of market domination, price and algorithmic discrimination, and to harm data privacy or threaten lives. private, list the authors: “the use of algorithms can encourage these giants to exploit behavioral bias in their favor and to manipulate consumer preferences”.
The list goes on. Access to a wide range of personal data can lead to exclusion of higher risk groups and discrimination against minorities or based on age. Also, given the nature of their business model, “when they obtain a captive consumer base, they can abuse their dominant position to prevent the entry of competitors, increase transfer costs…”
They can also use their wealth of data to exercise price discrimination between consumers. Use them not only to assess the consumer’s credit quality, but also their ability to pay and to measure the extent to which they are willing to pay their borrowing or insurance costs.
We’re not getting out. “The activities of large technology companies in the financial domain therefore lead to complex trade-offs between public policy objectives” such as financial stability, competition and privacy. And require greater coordination between national and international authorities. Especially since the great diversity of their activities and the services offered cover several fields of regulation housing as many regulatory bodies that do not always have the habit or reflex of interacting with each other.
A complexity that increases in an open cross-border environment, in the virtual absence of norms or standards on a global scale.