Paper Short Abstract:

I study how Chinese low-income debtors who live on digital credit create informal strategies to scam predatory platforms in the fin-tech black market. It explores how the illegitimacies and informalities of the digital economy generate new financial subjectivities among precarious populations.

Paper Abstract:

Since 2014, thousands of digital lending platforms have sprung up in China. In the absence of regulation, they have come up with a business model called "cash loans" to target low-income customers and make quick profits. The "cash loan" is an unsecured microcredit product similar to payday loans. But it is enhanced with features such as data-driven instant approval, digital money transfers, predatory interest rates, and remote debt collection. The model has been characterized by the media as a "debt scam" that leads to personal over-indebtedness. There are news stories of young people committing suicide due to the intense moral pressure caused by violent debt collection calls and predatory interest rates of 300-500%. Today, even under heavy regulation, there are still similar digital lending platforms operating in the fintech black market. The lending apps that promise easy approval of microloans have also cultivated a particular group of users who rely on multiple sources of digital credit to make a living. They have become "professional debtors," borrowing from new sources of credit to cover old debts. This paper focuses not only on how digital credit platforms manipulate users, but also on how some users, understanding the informality and illegitimacy of certain credit practices, have managed to hack the fintech black market by creating "fake data points" that cheat the algorithmic models of risk assessment and other informal strategies against debt collectors. It explores how the illegitimacies and informalities of the digital economy generate new financial subjectivities among precarious populations.