The study, conducted by researchers at the Chinese University of Hong Kong, analyzed data on over 1 million loan applications from a Chinese online lending platform. They found that applicants who spoke a minority dialect were less likely to be approved for a loan, even after controlling for other factors such as credit history, income, and education.
The researchers believe that this discrimination is due to the fact that fintech companies often use artificial intelligence (AI) and machine learning algorithms to make decisions about loan applications. These algorithms are trained on data that is often biased against minority dialects. As a result, they are more likely to reject loan applications from people who speak a minority dialect.
This discrimination has a significant impact on the financial well-being of minority dialect speakers. It makes it more difficult for them to borrow money, start businesses, and invest in their education. This can lead to poverty, unemployment, and other social problems.
The researchers recommend that fintech companies take steps to address this discrimination. They should ensure that their AI and machine learning algorithms are not biased against minority dialects. They should also provide more support for minority dialect speakers, such as by offering financial literacy training and translation services.
The discrimination against people speaking minority dialects is a serious problem that needs to be addressed. Fintech companies have a responsibility to ensure that their products and services are accessible to everyone, regardless of their language or dialect.
