The Office of the Leading Group for the Special Remediation of P2P Peer-to-Peer Lending Risks (hereinafter referred to as the Remediation Office) issued the Notice on Doing a Good Job in the Special Remediation and Acceptance of P2P Peer-to-Peer Lending Risks (hereinafter referred to as the Notice), which clearly explained the transfer of creditor's rights, and the low-frequency transfer of creditor's rights between lenders to solve the liquidity problem should be considered as compliance. In other words, the intelligent investment system for this purpose is also allowed to run.

If users choose intelligent investment system, they must complete the evaluation of personal age, financial status, loan experience, risk preference and risk tolerance according to the system requirements, so that the system can make accurate risk assessment for users through various data and match appropriate assets for users.

Risk assessment questionnaire

A qualified questionnaire covers the lender's loan planning, loan experience, risk awareness level and risk sensitivity, considers a lender's subjective risk preference through multiple dimensions, and then uses the data accumulated on the platform to polish the lender's objective strength evaluation model through machine learning. The combination of the two can complete the fine and accurate user risk portrait of the lender.

Portrait of users after risk assessment

After the lender conducts a questionnaire survey, the system will make a risk assessment through the answers selected by the lender, and provide accurate suggestions for the participants on the types of risk tolerance as a reference.

Risk tolerance types and suggestions

Customers with different risk tolerance correspond to assets with different risk levels. Through the risk assessment of lenders, platform lenders can have a clear and correct understanding of their risk tolerance, and then make lending decisions. Therefore, it is particularly important to choose a good product. Just like Honglibao, Dehong's financial intelligent investment system, based on big data analysis and quantitative financial model, according to the requirements of lenders' risk tolerance level and style preference, using theoretical models such as intelligent algorithm combination optimization, it automatically provides users with risk lending strategies, matches corresponding creditor's rights, and allows lenders to obtain fixed-term lending returns through creditor's rights transfer. Then, among the platforms developed with technology and finance as the leading forces, p2p online lending platforms tend to be in the forefront.