Digital economy: Data efficiency vs data privacy
SUERF, the independent, non-profit network association of central banks, supervisors, financial institutions, academic institutions, and financial sector practitioners, released a report regarding the benefits and costs derived from the entry of Big techs in finance. They go beyond the traditional approach of financial stability and competition, and extend also to a new trade-off between data efficiency and privacy, that will depend on preferences of society and will vary across jurisdictions, increasing the need to coordinate policies both at the domestic and international level.
- Market power risk: Big techs’ online-focused business models allow them to reach dominant market positions at unprecedented speed. The report mentions the case of Facebook or Tencent’s WeChat, in both cases took them less than five years to reach 50 million users. This ability to reach dominant market position could exclude potential financial competitors and could facilitate them to consolidate their position by raising barriers to new entrants. Big techs often serve as essential selling infrastructures for financial services providers, while at the same time compete with them on financial services.
- Risks Associated with the monopolistic use of data: The use of individual data by digital monopolies can also entail discriminations among their customers such as price discrimination (identifying the highest rate that a borrower would be willing to pay for a loan), unintended unethical discrimination (based on race or religion leading to greater inequality) or personal privacy breaches, when information is gathered without the informed consent of the consumer.
- At the domestic level, central banks and financial regulators may need to coordinate with competition and data protection authorities, and to address the policy challenges of Big techs by developing specific entity-based rules.
- At the international level, regulations on the use of personal data diverge widely (in the EU data rights are assigned to individuals while in the US companies have relatively free access to data), however as the digital economy expands across borders, there is a need for international cooperation on rules and standards, although only a few countries have a national data or artificial intelligence strategy.