More online lending platforms are expected to topple in China as local governments around the country release new withdrawal lists and guides.
Regional governments including Shanghai, Sichuan and Shenzhen have all publicly released withdrawal lists for online lending entities within their respective jurisdictions.
Reasons for inclusion on withdrawal lists include cancellation, loss of contact and voluntary withdrawal.
The launch of the real-time data reporting system by the Chinese government has provided a clear pretext for local government to drive clean up of the online lending sector.
The Anhui province government recently released the “Online Loan Withdrawal Guide (Trial)” (网络借贷退出指引（试行）), which calls for the withdrawal of online lending entities that are not included in real-time data monitoring.
Shanxi province has called for all online lending entities within the province to complete real-time data connection, and that those online lending entities that do not complete connection with the system on schedule should withdraw from the market.
“Withdrawal of online lending institutions that are not included in real-time data monitoring does not mean that those platforms which are included in monitoring will not be withdrawn,” said Xue Hongyan (薛洪言), chair of the Internet Finance Centre of the Suning Financial Research Institute to Economic Information Daily.
Zhang Yexia (张叶霞), head of the Wangdai Zhijia Research Institute, said that the withdrawal lists make it easier for lenders to identify risk and understand the condition of lending platforms, serving as a means for protecting the lawful rights and interests of lenders and actively resolving industry risk.
“[It] will help to accelerate industry clearance, and cleansing of the market environment.”
Zhang expects the withdrawal of online lending platforms to accelerate the release of more withdrawal lists and withdrawal guides, and regulators to drive the majority of institutions to clean up risk by means of active liquidation, suspension of operations or changes in development models.