The core business of traditional business credit agency, namely the sale of credit transaction data to credit bureaus, has shrunk to a very small part of the revenue of credit bureaus. Due to heavy investment in acquiring new data sources involving social media, mobile communications, wearable devices and virtual interviews, and building advanced artificial intelligence and data analysis capabilities, traditional credit bureaus are developing data and data analysis businesses in markets beyond financial credit on a large scale, including employment, rental, retail and government. Fintech institutions follow the same pattern, gradually consolidating from a large number of players into a few large platforms/institutions and a group of small institutions, while conducting data business in the financial and credit areas as well as in the non-financial areas.
“Big data” and advanced analytical technology have been widely used in the field of credit information services, financial and non-financial data and highly complex analytical tools for credit institutions, leasing agencies and employers to provide in-depth insight and evaluation of credit entities, decision-making efficiency has been greatly improved. At the same time, the borrowing costs faced by high-risk credit entities have increased significantly, and the borrowing opportunities have decreased significantly. Consumer understanding of how data is used is at a low level.
Although traditional credit agencies still play an important role in the market, credit institutions have gradually established their own third-party data sources, advanced data analysis capabilities and third-party cooperation channels, reducing their dependence on traditional credit agencies. A large number of non-traditional data are used in credit decision-making, and market efficiency has been greatly improved, which can maintain strong credit demand in a less-than-ideal economic operating environment.
Consumers accept the fact that their data is used by commercial organizations and are not very concerned about the rights they should have over their personal data. Few people regularly check their credit reports and understand the use of personal data by businesses. Credit bureaus’ revenue from consumer services has suffered.
There is some debate as to whether more efficient credit decisions are always good for the economy, as the heavy use of data and algorithms puts those at high risk or those unwilling to share data at a relative disadvantage. The question of the relevance of alternative data to forecast targets also often bothers consumer advocacy groups.
The excessive personalization of credit products and the widespread use of “big data” have also caused controversy. Potential risks could include credit institutions consciously pushing inappropriate products or services to specific groups of consumers to grab profits, or data errors that lead to consumers being deprived of the right to borrow, rent, or work. The ubiquity of consumer surveillance caused by “big data” deprives consumers of their freedom of expression and drives consumers away from the digital society.
Post time: Dec-04-2023