1. An investment risk assessment method based on big data and artificial intelligence technology is characterized in that: the method comprises the following evaluation steps:

s1, firstly, collecting investment market data through big data, establishing a risk investment evaluation model, and providing risk investment analysis for users;

s2, registering the user as an investment platform user, filling in basic investment information, analyzing the basic user information and the current market investment condition by the risk assessment model, and listing appropriate investment projects;

s3, predicting the trend of future investment projects according to market investment data, and performing risk assessment;

s4, classifying the users according to the investment risk items through the investment risk assessment model, and managing the users;

s5, in the risk investment process, the risk investment evaluation model monitors and analyzes the investment risk of an investor in real time, and the safety of investment in the investment recruitment link of an investment institution is guaranteed through button cloud;

s6, in the risk investment process, real-time monitoring and early warning are carried out, the risk condition of a user is warned, and the user is helped to take corresponding measures in time through risk warning;

s7, before other investment projects begin, analyzing the conflict between the project to be invested and the invested project through the investment risk assessment platform, and analyzing a plurality of investments;

and S8, providing investment suggestions for users according to the investment situation, and reducing the investment risk.

2. The big data and artificial intelligence based investment risk assessment method according to claim 1, wherein said functions of the investment risk assessment model comprise user data collection, investment project enrollment, big data support, pre-investment analysis, in-investment monitoring, post-investment risk pre-warning, security maintenance and investment management in S1.

3. The investment risk assessment method based on big data and artificial intelligence technology as claimed in claim 1, wherein in said S2, the user performs operations including registration, exit, password modification, addition, disable, enable, edit and delete, the user' S basic information includes user funds, asset status, user age, user family members, work, investment cycle and investment expectation, and the list for the user to view includes user authority list, investment flow list, schedule list and approval list.

4. The investment risk assessment method based on big data and artificial intelligence technology as claimed in claim 1, wherein in said S2 and S3, through the analysis of comparing the user data with the market data, 3-6 recommended investment items are given, and the current investment situation of the investment items is analyzed;

analyzing the investment trend according to market rules and the current investment market, analyzing the risk of each investment, and listing three investment modes of large profit, small risk and high safety.

5. The investment risk assessment method based on big data and artificial intelligence technology as claimed in claim 1, wherein in said S4, the investment risk assessment model generalizes users of the same investment project and defines user management manner for the investment project;

managing user information, user operation progress and user approval conditions through an investment risk assessment model;

the user approval comprises My approval data, pending My approval data and My copying data.

6. The investment risk assessment method based on big data and artificial intelligence technology as claimed in claim 1, wherein in S5, the button cloud is used to ensure the security and convenience of data transmission during the confidential data transmission in the investment institution funding link;

the button cloud comprises functions of deeply combining with WeChat ecology, allocating different permissions to transaction roles, digital invisible watermarking, block chain source tracing sharing paths, inviting links during WeChat time, free from personal information registration, AI search and intelligent labeling.

7. The investment risk assessment method based on big data and artificial intelligence technology according to claim 6, wherein in the investment process, publicly disclosed fund information is captured through big data technology to generate a standardized fund database open sea;

service personnel acquire data through two modes of claiming from the public sea and allocating fund mechanisms by managers, so that follow-up information is perfected, and a follow-up process is online;

and the manager authority in the fund database is divided, and the manager checks and manages the investment service promotion condition of the team members and the condition of the cooperative users in real time.

8. The big data and artificial intelligence based investment risk assessment method according to claim 1, wherein in S6, the investment item is monitored in real time by the investment risk assessment model, and the risk is warned by the risk pre-warning;

the monitoring period is 0.5-1h, the market dynamics is updated once in each period, the market fluctuation is analyzed, and risk early warning is carried out;

the specific content of the risk early warning is as follows:

grade 1: the risk can be controlled, and the investment reduction amplitude is lower than 50% expected;

grade 2: the risk can be controlled, and the investment reduction amplitude is higher than 50% expected;

grade 3: the risk is uncontrollable, and the investment reduction amplitude is lower than the expected 50 percent;

grade 4: uncontrolled risk, investment reduction higher than expected 50%.

9. The method according to claim 1, wherein in step S7, before a user invests a new project, the user inputs a new investment project and personal information through an investment risk assessment model, and analyzes the investment proportion and the investment allocation of the new investment project to make the multiple investment projects cooperate with each other to help the user invest more reasonably through big data analysis to make the new investment project conflict with the original investment project.

10. The investment risk assessment method based on big data and artificial intelligence technology according to claim 1, wherein after the early warning of the investment risk occurs, the investment risk assessment model combines the actual investment situation, the current market quotation, the historical data and the market forecast quotation of the user to analyze the post-investment quotation of the user, and analyzes the difference between the current investment quotation and the investment expectation of the user, so as to provide the post-investment advice for the user and reduce the investment loss.

Background

The investment risk is called wind investment for short, also called entrepreneurship investment for translation, and mainly refers to a financing mode for providing fund support for an initial enterprise and obtaining shares of the enterprise, the investment risk is a form of private equity investment, the investment risk is a professional investment company, which is formed by combining a group of people with science and technology and financial related knowledge and experience, and provides funds to the people needing the funds by a mode of directly investing to obtain the equity of the investment company, and the funds of the wind investment is mostly used for investing new entrepreneurship or enterprises which are not on the market;

however, the risk assessment of the investment project is troublesome at present, so that a user can not conveniently and simply and intuitively know the risk condition, the time consumption for the user to know the risk is long, and the risk cannot be timely taken, so that the investment loss is large.

Disclosure of Invention

The invention provides an investment risk assessment method based on big data and artificial intelligence technology, which can effectively solve the problems that the current assessment of investment risk in the background technology is troublesome, the risk assessment of investment projects is inconvenient, a user can not conveniently and simply and intuitively know the risk condition, the time consumption of knowing the risk of the user is long, and the risk cannot be timely taken to take measures, so that the investment loss is large.

In order to achieve the purpose, the invention provides the following technical scheme: an investment risk assessment method based on big data and artificial intelligence technology comprises the following assessment steps:

s1, firstly, collecting investment market data through big data, establishing a risk investment evaluation model, and providing risk investment analysis for users;

s2, registering the user as an investment platform user, filling in basic investment information, analyzing the basic user information and the current market investment condition by the risk assessment model, and listing appropriate investment projects;

s3, predicting the trend of future investment projects according to market investment data, and performing risk assessment;

s4, classifying the users according to the investment risk items through the investment risk assessment model, and managing the users;

s5, in the risk investment process, the risk investment evaluation model monitors and analyzes the investment risk of an investor in real time, and the safety of investment in the investment recruitment link of an investment institution is guaranteed through button cloud;

s6, in the risk investment process, real-time monitoring and early warning are carried out, the risk condition of a user is warned, and the user is helped to take corresponding measures in time through risk warning;

s7, before other investment projects begin, analyzing the conflict between the project to be invested and the invested project through the investment risk assessment platform, and analyzing a plurality of investments;

and S8, providing investment suggestions for users according to the investment situation, and reducing the investment risk.

According to the above technical solution, in S1, the functions of the investment risk assessment model include user data collection, investment project parking, big data support, pre-investment analysis, in-investment monitoring, post-investment risk early warning, security maintenance, and investment management.

According to the above technical solution, in S2, the operation performed by the user includes registration, exit, password modification, addition, deactivation, enabling, editing, and deletion, the basic information of the user includes user funds, asset condition, user age, user family members, work, investment period, and investment expectation, and the list viewed by the user includes a user authority list, an investment flow list, a progress list, and an approval list.

According to the technical scheme, in the S2 and S3, 3-6 recommended investment projects are given through the comparative analysis of user data and market data, and the current investment situation of the investment projects is analyzed;

analyzing the investment trend according to market rules and the current investment market, analyzing the risk of each investment, and listing three investment modes of large profit, small risk and high safety.

According to the technical scheme, in the S4, the investment risk assessment model summarizes the users with the same investment project and customizes a user management mode for the investment project;

managing user information, user operation progress and user approval conditions through an investment risk assessment model;

the user approval comprises My approval data, pending My approval data and My copying data.

According to the technical scheme, in the S5, the security and the convenience of data transmission are guaranteed in the confidential data transmission process in the investment institution investment link through the button cloud;

the button cloud comprises functions of deeply combining with WeChat ecology, allocating different permissions to transaction roles, digital invisible watermarking, block chain source tracing sharing paths, inviting links during WeChat time, free from personal information registration, AI search and intelligent labeling.

According to the technical scheme, in the investment process, publicly disclosed fund information is captured through a big data technology, and a standardized fund database open sea is generated;

service personnel acquire data through two modes of claiming from the public sea and allocating fund mechanisms by managers, so that follow-up information is perfected, and a follow-up process is online;

and the manager authority in the fund database is divided, and the manager checks and manages the investment service promotion condition of the team members and the condition of the cooperative users in real time.

According to the technical scheme, in the step S6, the investment items are monitored in real time through the investment risk assessment model, and the existing risks are warned through risk early warning;

the monitoring period is 0.5-1h, the market dynamics is updated once in each period, the market fluctuation is analyzed, and risk early warning is carried out;

the specific content of the risk early warning is as follows:

grade 1: the risk can be controlled, and the investment reduction amplitude is lower than 50% expected;

grade 2: the risk can be controlled, and the investment reduction amplitude is higher than 50% expected;

grade 3: the risk is uncontrollable, and the investment reduction amplitude is lower than the expected 50 percent;

grade 4: uncontrolled risk, investment reduction higher than expected 50%.

According to the technical scheme, in the step S7, before the user invests a new project, the user inputs a new investment project and personal information through an investment risk assessment model, and through big data analysis, the investment conflict between the new investment project and the original investment project, and the analysis is performed on the investment proportion and the investment allocation of the new investment project, so that a plurality of investment projects can cooperate with each other, and the user is helped to invest more reasonably.

According to the technical scheme, after the early warning of the investment risk occurs, the investment risk assessment model combines the actual investment situation, the current market quotation, the historical data and the market forecast quotation of the user, analyzes the later investment quotation of the user, analyzes the difference between the current investment quotation and the user investment expectation, provides the later investment suggestion for the user, and reduces the investment loss.

Compared with the prior art, the invention has the beneficial effects that:

1. the investment risk assessment model is used for monitoring investment projects in real time, risk early warning levels are set, monitoring and analysis are carried out according to periods, when risks are met in investment, the risks are analyzed through big data in time, the risk levels are assessed, controllable risks and uncontrollable risks are distinguished, fluctuation range between the risks and expectation is determined, a user can grasp the risks more quickly, specific levels and fluctuation range of the risks are known, the user can timely and intuitively know early warning of the risks, reasonable measures are provided for the user to refer to when early warning occurs, and investment loss is reduced.

2. By setting the investment risk assessment model, user data and resident investment items are collected, investment analysis, investment monitoring, risk assessment, safety maintenance and investment management are carried out, a user can conveniently carry out risk assessment, the user can be helped to select proper investment items, the user investment is more reasonable, the selection time of the user investment is saved, and the user can know the investment content more clearly.

3. When multiple investments are carried out, a new investment project is analyzed, the new investment project and an original investment project are combined and analyzed, the investment risk of a user is evaluated, reasonable investment distribution is carried out on multiple investments of the user, the user is helped to carry out more reasonable investment, and therefore different investment projects are not easy to conflict and more reasonable investment is carried out.

Drawings

The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention.

In the drawings:

FIG. 1 is a flow chart of the steps of the evaluation method of the present invention.

Detailed Description

The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.

Example 1:

as shown in fig. 1, the present invention provides a technical solution, a method for evaluating investment risk based on big data and artificial intelligence technology, comprising the following evaluation steps:

s1, firstly, collecting investment market data through big data, establishing a risk investment evaluation model, and providing risk investment analysis for users;

s2, registering the user as an investment platform user, filling in basic investment information, analyzing the basic user information and the current market investment condition by the risk assessment model, and listing appropriate investment projects;

s3, predicting the trend of future investment projects according to market investment data, and performing risk assessment;

s4, classifying the users according to the investment risk items through the investment risk assessment model, and managing the users;

s5, in the risk investment process, the risk investment evaluation model monitors and analyzes the investment risk of an investor in real time, and the safety of investment in the investment recruitment link of an investment institution is guaranteed through button cloud;

s6, in the risk investment process, real-time monitoring and early warning are carried out, the risk condition of a user is warned, and the user is helped to take corresponding measures in time through risk warning;

s7, before other investment projects begin, analyzing the conflict between the project to be invested and the invested project through the investment risk assessment platform, and analyzing a plurality of investments;

and S8, providing investment suggestions for users according to the investment situation, and reducing the investment risk.

According to the above technical solution, in S1, the functions of the investment risk assessment model include user data collection, investment project parking, big data support, pre-investment analysis, in-investment monitoring, post-investment risk early warning, security maintenance, and investment management.

According to the above technical solution, in S2, the operation performed by the user includes registration, exit, password modification, addition, deactivation, enabling, editing, and deletion, the basic information of the user includes user funds, asset condition, user age, user family members, work, investment period, and investment expectation, and the list viewed by the user includes a user authority list, an investment flow list, a progress list, and an approval list.

According to the technical scheme, in S2 and S3, 6 recommended investment projects are given through comparative analysis of user data and market data, and the current investment situation of the investment projects is analyzed;

analyzing the investment trend according to market rules and the current investment market, analyzing the risk of each investment, and listing three investment modes of large profit, small risk and high safety.

According to the technical scheme, in S4, the investment risk assessment model summarizes users with the same investment project and customizes a user management mode for the investment project;

managing user information, user operation progress and user approval conditions through an investment risk assessment model;

the user approval comprises My approval data, pending My approval data and My copy data.

According to the technical scheme, in S5, the security and the convenience of data transmission are guaranteed in the confidential data transmission process in the investment institution investment link through the button cloud;

the button cloud comprises functions of deeply combining with WeChat ecology, allocating different permissions to transaction roles, digital invisible watermarking, block chain tracing sharing paths, inviting linking in WeChat time, free from personal information registration, AI (Artificial intelligence) search and intelligent labeling;

the button cloud runs through the SaaS platform, and the technical means of the SaaS platform and local deployment replace the transmission process of the easily leaked files in the paper data room, so that the cooperation cost of both transaction parties is reduced, and the money collecting efficiency and the safety are improved.

According to the technical scheme, in the investment process, publicly disclosed fund information is captured through a big data technology to generate a standardized fund database open sea;

service personnel acquire data through two modes of claiming from the public sea and allocating fund mechanisms by managers, so that follow-up information is perfected, and a follow-up process is online;

and the manager authority in the fund database is divided, and the manager checks and manages the investment service promotion condition of the team members and the condition of the cooperative users in real time.

According to the technical scheme, in S6, the investment items are monitored in real time through the investment risk assessment model, and existing risks are warned through risk early warning;

the monitoring period is 0.5h, the market dynamics is updated once in each period, the market fluctuation is analyzed, and risk early warning is carried out;

the risk early warning is grade 1: the risk can be controlled, and the investment reduction is 10 percent expected.

According to the technical scheme, in S7, before the user invests a new project, the user inputs a new investment project and personal information through an investment risk assessment model, through big data analysis, the investment conflict between the new investment project and an original investment project is realized, and the investment proportion and the investment allocation of the new investment project are analyzed, so that a plurality of investment projects can cooperate with one another, and the user is helped to invest more reasonably.

According to the technical scheme, after the early warning of the investment risk occurs, the investment risk assessment model combines the actual investment situation, the current market quotation, the historical data and the market forecast quotation of the user, analyzes the later investment quotation of the user, analyzes the difference between the current investment quotation and the user investment expectation, provides the later investment suggestion for the user, and reduces the investment loss.

Example 2:

as shown in fig. 1, the present invention provides a technical solution, a method for evaluating investment risk based on big data and artificial intelligence technology, comprising the following evaluation steps:

s1, firstly, collecting investment market data through big data, establishing a risk investment evaluation model, and providing risk investment analysis for users;

s2, registering the user as an investment platform user, filling in basic investment information, analyzing the basic user information and the current market investment condition by the risk assessment model, and listing appropriate investment projects;

s3, predicting the trend of future investment projects according to market investment data, and performing risk assessment;

s4, classifying the users according to the investment risk items through the investment risk assessment model, and managing the users;

s5, in the risk investment process, the risk investment evaluation model monitors and analyzes the investment risk of an investor in real time, and the safety of investment in the investment recruitment link of an investment institution is guaranteed through button cloud;

s6, in the risk investment process, real-time monitoring and early warning are carried out, the risk condition of a user is warned, and the user is helped to take corresponding measures in time through risk warning;

s7, before other investment projects begin, analyzing the conflict between the project to be invested and the invested project through the investment risk assessment platform, and analyzing a plurality of investments;

and S8, providing investment suggestions for users according to the investment situation, and reducing the investment risk.

According to the above technical solution, in S1, the functions of the investment risk assessment model include user data collection, investment project parking, big data support, pre-investment analysis, in-investment monitoring, post-investment risk early warning, security maintenance, and investment management.

According to the above technical solution, in S2, the operation performed by the user includes registration, exit, password modification, addition, deactivation, enabling, editing, and deletion, the basic information of the user includes user funds, asset condition, user age, user family members, work, investment period, and investment expectation, and the list viewed by the user includes a user authority list, an investment flow list, a progress list, and an approval list.

According to the technical scheme, 5 recommended investment projects are given through comparative analysis of user data and market data in S2 and S3, and the current investment situation of the investment projects is analyzed;

analyzing the investment trend according to market rules and the current investment market, analyzing the risk of each investment, and listing three investment modes of large profit, small risk and high safety.

According to the technical scheme, in S4, the investment risk assessment model summarizes users with the same investment project and customizes a user management mode for the investment project;

managing user information, user operation progress and user approval conditions through an investment risk assessment model;

the user approval comprises My approval data, pending My approval data and My copy data.

According to the technical scheme, in S5, the security and the convenience of data transmission are guaranteed in the confidential data transmission process in the investment institution investment link through the button cloud;

the button cloud comprises functions of deeply combining with WeChat ecology, allocating different permissions to transaction roles, digital invisible watermarking, block chain tracing sharing paths, inviting linking in WeChat time, free from personal information registration, AI (Artificial intelligence) search and intelligent labeling;

the button cloud runs through the SaaS platform, and the technical means of the SaaS platform and local deployment replace the transmission process of the easily leaked files in the paper data room, so that the cooperation cost of both transaction parties is reduced, and the money collecting efficiency and the safety are improved.

According to the technical scheme, in the investment process, publicly disclosed fund information is captured through a big data technology to generate a standardized fund database open sea;

service personnel acquire data through two modes of claiming from the public sea and allocating fund mechanisms by managers, so that follow-up information is perfected, and a follow-up process is online;

and the manager authority in the fund database is divided, and the manager checks and manages the investment service promotion condition of the team members and the condition of the cooperative users in real time.

According to the technical scheme, in S6, the investment items are monitored in real time through the investment risk assessment model, and existing risks are warned through risk early warning;

the monitoring period is 0.6h, the market dynamics is updated once in each period, the market fluctuation is analyzed, and risk early warning is carried out;

the risk early warning is grade 2: the risk can be controlled, and the investment reduction is 65% expected.

According to the technical scheme, in S7, before the user invests a new project, the user inputs a new investment project and personal information through an investment risk assessment model, through big data analysis, the investment conflict between the new investment project and an original investment project is realized, and the investment proportion and the investment allocation of the new investment project are analyzed, so that a plurality of investment projects can cooperate with one another, and the user is helped to invest more reasonably.

According to the technical scheme, after the early warning of the investment risk occurs, the investment risk assessment model combines the actual investment situation, the current market quotation, the historical data and the market forecast quotation of the user, analyzes the later investment quotation of the user, analyzes the difference between the current investment quotation and the user investment expectation, provides the later investment suggestion for the user, and reduces the investment loss.

Example 3:

as shown in fig. 1, the present invention provides a technical solution, a method for evaluating investment risk based on big data and artificial intelligence technology, comprising the following evaluation steps:

s1, firstly, collecting investment market data through big data, establishing a risk investment evaluation model, and providing risk investment analysis for users;

s2, registering the user as an investment platform user, filling in basic investment information, analyzing the basic user information and the current market investment condition by the risk assessment model, and listing appropriate investment projects;

s3, predicting the trend of future investment projects according to market investment data, and performing risk assessment;

s4, classifying the users according to the investment risk items through the investment risk assessment model, and managing the users;

s5, in the risk investment process, the risk investment evaluation model monitors and analyzes the investment risk of an investor in real time, and the safety of investment in the investment recruitment link of an investment institution is guaranteed through button cloud;

s6, in the risk investment process, real-time monitoring and early warning are carried out, the risk condition of a user is warned, and the user is helped to take corresponding measures in time through risk warning;

s7, before other investment projects begin, analyzing the conflict between the project to be invested and the invested project through the investment risk assessment platform, and analyzing a plurality of investments;

and S8, providing investment suggestions for users according to the investment situation, and reducing the investment risk.

According to the above technical solution, in S1, the functions of the investment risk assessment model include user data collection, investment project parking, big data support, pre-investment analysis, in-investment monitoring, post-investment risk early warning, security maintenance, and investment management.

According to the above technical solution, in S2, the operation performed by the user includes registration, exit, password modification, addition, deactivation, enabling, editing, and deletion, the basic information of the user includes user funds, asset condition, user age, user family members, work, investment period, and investment expectation, and the list viewed by the user includes a user authority list, an investment flow list, a progress list, and an approval list.

According to the technical scheme, 5 recommended investment projects are given through comparative analysis of user data and market data in S2 and S3, and the current investment situation of the investment projects is analyzed;

analyzing the investment trend according to market rules and the current investment market, analyzing the risk of each investment, and listing three investment modes of large profit, small risk and high safety.

According to the technical scheme, in S4, the investment risk assessment model summarizes users with the same investment project and customizes a user management mode for the investment project;

managing user information, user operation progress and user approval conditions through an investment risk assessment model;

the user approval comprises My approval data, pending My approval data and My copy data.

According to the technical scheme, in S5, the security and the convenience of data transmission are guaranteed in the confidential data transmission process in the investment institution investment link through the button cloud;

the button cloud comprises functions of deeply combining with WeChat ecology, allocating different permissions to transaction roles, digital invisible watermarking, block chain tracing sharing paths, inviting linking in WeChat time, free from personal information registration, AI (Artificial intelligence) search and intelligent labeling;

the button cloud runs through the SaaS platform, and the technical means of the SaaS platform and local deployment replace the transmission process of the easily leaked files in the paper data room, so that the cooperation cost of both transaction parties is reduced, and the money collecting efficiency and the safety are improved.

According to the technical scheme, in the investment process, publicly disclosed fund information is captured through a big data technology to generate a standardized fund database open sea;

service personnel acquire data through two modes of claiming from the public sea and allocating fund mechanisms by managers, so that follow-up information is perfected, and a follow-up process is online;

and the manager authority in the fund database is divided, and the manager checks and manages the investment service promotion condition of the team members and the condition of the cooperative users in real time.

According to the technical scheme, in S6, the investment items are monitored in real time through the investment risk assessment model, and existing risks are warned through risk early warning;

the monitoring period is 0.8h, the market dynamics is updated once in each period, the market fluctuation is analyzed, and risk early warning is carried out;

the risk early warning is grade 3: uncontrollable risk, investment reduction of 33% expected;

according to the technical scheme, in S7, before the user invests a new project, the user inputs a new investment project and personal information through an investment risk assessment model, through big data analysis, the investment conflict between the new investment project and an original investment project is realized, and the investment proportion and the investment allocation of the new investment project are analyzed, so that a plurality of investment projects can cooperate with one another, and the user is helped to invest more reasonably.

According to the technical scheme, after the early warning of the investment risk occurs, the investment risk assessment model combines the actual investment situation, the current market quotation, the historical data and the market forecast quotation of the user, analyzes the later investment quotation of the user, analyzes the difference between the current investment quotation and the user investment expectation, provides the later investment suggestion for the user, and reduces the investment loss.

Example 4:

as shown in fig. 1, the present invention provides a technical solution, a method for evaluating investment risk based on big data and artificial intelligence technology, comprising the following evaluation steps:

s1, firstly, collecting investment market data through big data, establishing a risk investment evaluation model, and providing risk investment analysis for users;

s2, registering the user as an investment platform user, filling in basic investment information, analyzing the basic user information and the current market investment condition by the risk assessment model, and listing appropriate investment projects;

s3, predicting the trend of future investment projects according to market investment data, and performing risk assessment;

s4, classifying the users according to the investment risk items through the investment risk assessment model, and managing the users;

s5, in the risk investment process, the risk investment evaluation model monitors and analyzes the investment risk of an investor in real time, and the safety of investment in the investment recruitment link of an investment institution is guaranteed through button cloud;

s6, in the risk investment process, real-time monitoring and early warning are carried out, the risk condition of a user is warned, and the user is helped to take corresponding measures in time through risk warning;

s7, before other investment projects begin, analyzing the conflict between the project to be invested and the invested project through the investment risk assessment platform, and analyzing a plurality of investments;

and S8, providing investment suggestions for users according to the investment situation, and reducing the investment risk.

According to the above technical solution, in S1, the functions of the investment risk assessment model include user data collection, investment project parking, big data support, pre-investment analysis, in-investment monitoring, post-investment risk early warning, security maintenance, and investment management.

According to the above technical solution, in S2, the operation performed by the user includes registration, exit, password modification, addition, deactivation, enabling, editing, and deletion, the basic information of the user includes user funds, asset condition, user age, user family members, work, investment period, and investment expectation, and the list viewed by the user includes a user authority list, an investment flow list, a progress list, and an approval list.

According to the technical scheme, in S2 and S3, 6 recommended investment projects are given through comparative analysis of user data and market data, and the current investment situation of the investment projects is analyzed;

analyzing the investment trend according to market rules and the current investment market, analyzing the risk of each investment, and listing three investment modes of large profit, small risk and high safety.

According to the technical scheme, in S4, the investment risk assessment model summarizes users with the same investment project and customizes a user management mode for the investment project;

managing user information, user operation progress and user approval conditions through an investment risk assessment model;

the user approval comprises My approval data, pending My approval data and My copy data.

According to the technical scheme, in S5, the security and the convenience of data transmission are guaranteed in the confidential data transmission process in the investment institution investment link through the button cloud;

the button cloud comprises functions of deeply combining with WeChat ecology, allocating different permissions to transaction roles, digital invisible watermarking, block chain tracing sharing paths, inviting linking in WeChat time, free from personal information registration, AI (Artificial intelligence) search and intelligent labeling;

the button cloud runs through the SaaS platform, and the technical means of the SaaS platform and local deployment replace the transmission process of the easily leaked files in the paper data room, so that the cooperation cost of both transaction parties is reduced, and the money collecting efficiency and the safety are improved.

According to the technical scheme, in the investment process, publicly disclosed fund information is captured through a big data technology to generate a standardized fund database open sea;

service personnel acquire data through two modes of claiming from the public sea and allocating fund mechanisms by managers, so that follow-up information is perfected, and a follow-up process is online;

and the manager authority in the fund database is divided, and the manager checks and manages the investment service promotion condition of the team members and the condition of the cooperative users in real time.

According to the technical scheme, in S6, the investment items are monitored in real time through the investment risk assessment model, and existing risks are warned through risk early warning;

the monitoring period is 1h, the market dynamics is updated once in each period, the market fluctuation is analyzed, and risk early warning is carried out;

the risk early warning is grade 4: the risk is uncontrollable, and the investment reduction is 82% expected.

According to the technical scheme, in S7, before the user invests a new project, the user inputs a new investment project and personal information through an investment risk assessment model, through big data analysis, the investment conflict between the new investment project and an original investment project is realized, and the investment proportion and the investment allocation of the new investment project are analyzed, so that a plurality of investment projects can cooperate with one another, and the user is helped to invest more reasonably.

According to the technical scheme, after the early warning of the investment risk occurs, the investment risk assessment model combines the actual investment situation, the current market quotation, the historical data and the market forecast quotation of the user, analyzes the later investment quotation of the user, analyzes the difference between the current investment quotation and the user investment expectation, provides the later investment suggestion for the user, and reduces the investment loss.

According to the analysis of the risk classes according to examples 1-4, the following tables are prepared:

as can be seen from the comparison between the fluctuation times and the initial difference, the fluctuation times in the embodiments 1 and 2 are 1, which is less than the fluctuation times in the embodiments 3 and 4, and the corresponding initial difference is also smaller, so that the investments in the embodiments 1 and 2 are stable, the fluctuation is smaller, the investment risk is smaller, the risks are controllable, the rules of the investment market are met, and the gradual recovery can be realized through market adjustment;

as can be seen from the comparison of the data in the embodiments 1 to 4, the embodiments 1 to 4 all meet the requirements of the risk level, and the early warning function of the risk level provides a good risk early warning function for the investment user, so that when the risk occurs, the risk level is timely evaluated through big data, the investment user can know the controllability of the risk and know the difference between the risk and the expectation, and the investment user can conveniently take different countermeasures according to the risk situation, can specifically and pertinently deal with the risk, and accordingly, the investment loss caused by the risk is reduced.

Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.