Talent body fluid subsidy application and redemption method and device

Abstract

The invention relates to the technical field of big data, and particularly provides a talent body fluid subsidy application and redemption method and device.Firstly, a user management module performs user identity verification and authority management of an applicant, an auditor and a manager, and a data acquisition module performs data exchange with an external system through a standard API interface; automatic collection of user information is realized; then, a data analysis module carries out deep analysis on the user data collected by the data acquisition module, and a subsidy matching module clarifies subsidy objects, conditions, quotas and application process information; and finally, the application processing module performs automatic processing of an application process and automatic data verification, and the fund redemption module establishes an instant payment system to realize payment of subsidy fund. Compared with the prior art, accuracy and efficiency can be improved, the process is simplified, efficiency is improved, and justice is ensured.

Description

Technical Field

[0001] The present invention relates to the field of big data technology, and specifically provides a method and device for applying for and cashing in talent subsidies. Background Art

[0002] In today's globalization and knowledge economy, talent has become the core element to promote social and economic development. In order to attract and retain high-level talents, promote scientific and technological innovation and industrial upgrading, and continuously increase investment in talent introduction and training, various talent subsidies have been created, aiming to provide necessary support for talents through economic incentives, solve their worries, and stimulate their innovation and creativity.

[0003] However, the traditional subsidy application process has many drawbacks. First of all, the cumbersome process is the primary problem. Applicants need to prepare a large amount of paper materials and submit them one by one to multiple relevant departments for review according to the established process. This process is not only time-consuming and laborious, but also prone to repeated trips due to incomplete materials or non-compliance with requirements, which increases the burden on applicants.

[0004] Secondly, the long application cycle and low efficiency are also prominent problems of the traditional application process. Since it needs to go through multiple levels of review by multiple departments and there is a lack of effective information sharing mechanism between departments, the review process is lengthy and the application cycle is greatly extended. This not only affects the applicant's fund use plan, but also reduces the efficiency of execution.

[0005] Furthermore, information opacity and lack of data sharing are important reasons for duplicate claims and fraudulent claims. In the traditional claim model, there is a lack of effective data exchange and sharing mechanisms. This gives some lawless elements an opportunity to make duplicate claims or fraudulent claims by forging materials or taking advantage of information differences, which seriously undermines fairness. Summary of the invention

[0006] The present invention aims at addressing the deficiencies of the above-mentioned prior art and provides a method for applying for and cashing talent subsidies which is highly practical.

[0007] A further technical task of the present invention is to provide a talent subsidy claiming and redeeming device which is reasonably designed, safe and applicable.

[0008] The technical solution adopted by the present invention to solve its technical problem is:

[0009] A method for applying for and cashing talent subsidies, firstly, a user management module verifies the user identity and manages the authority of applicants, reviewers and managers, and a data collection module exchanges data with an external system through a standard API interface to realize automatic collection of user information;

[0010] Then, the data analysis module conducts in-depth analysis of the user data collected by the data collection module, and the subsidy matching module clarifies the subsidy objects, conditions, amounts and application process information;

[0011] Finally, the claim processing module automates the claim process and data verification, and the fund cashing module establishes an instant payment system to realize the receipt of subsidy funds.

[0012] Furthermore, in the user management module, the applicant needs to register an account in the system, fill in basic information, and submit it to the system. The system verifies the identity of the user by comparing the information submitted by the user with the preset verification rules or information in the database;

[0013] The system assigns a set of basic permissions to each role, allowing users to modify basic information while restricting modifications to sensitive information and recording users' login time, IP address, and login result information.

[0014] Furthermore, the data collection module exchanges data with external systems through a standard API interface to realize automatic collection of user information. The collected information includes but is not limited to social security payment records, academic degree certificates, real estate holdings, marital status and tax information, meeting the needs of enterprises or individual users for comprehensive information verification, risk assessment or personalized services.

[0015] Furthermore, the data analysis module uses gradient boosting trees and neural network machine learning algorithms to build an evaluation model based on historical data and expert knowledge, conducts in-depth analysis of user data collected by the data acquisition module, extracts key features from the preprocessed data according to the specific requirements of the subsidy, and performs necessary feature conversion and selection.

[0016] Furthermore, the subsidy matching module first performs a preliminary screening to quickly exclude ineligible subsidies based on the basic conditions of the applicant. Furthermore, the algorithm uses fuzzy matching technology to handle edge cases of conditions, and continuously optimizes the matching strategy using reinforcement learning by continuously collecting feedback on matching results.

[0017] Furthermore, after the applicant submits the application form, the system of the application processing module automatically performs data integrity and consistency verification, preliminarily screens the application according to preset rules, excludes applications that are obviously not eligible for subsidies, and intelligently allocates review tasks according to the reviewer's expertise and current workload;

[0018] For qualified and undisputed applications, they will be automatically approved and enter the fund redemption process;

[0019] When an application is questionable or does not meet the standards, it will be automatically flagged and transferred to professional reviewers for in-depth review;

[0020] After the review is completed, the review result notification will be automatically sent to the applicant, recording the detailed process and results of each review, providing an appeal channel for rejected applicants, and supporting the review process.

[0021] Furthermore, the fund cashing module establishes an instant payment system to realize the arrival of subsidy funds, and automatically triggers the payment process after the application is approved;

[0022] The system provides real-time payment monitoring function. All payment data is encrypted through the SSL protocol during transmission. When users perform cashing operations, they use passwords plus SMS verification codes and face recognition authentication to establish a risk monitoring mechanism to monitor and warn of the fund disbursement process in real time.

[0023] A talent subsidy claiming and redeeming device, comprising: at least one memory and at least one processor;

[0024] The at least one memory is used to store a machine-readable program;

[0025] The at least one processor is used to call the machine-readable program to execute a method for applying for and cashing in talent subsidies.

[0026] Compared with the prior art, the talent subsidy claiming and cashing method and device of the present invention has the following outstanding beneficial effects:

[0027] The present invention improves accuracy and efficiency, and uses big data analysis and comparison technology to accurately determine the applicant's qualifications and subsidy amount, avoiding errors and omissions that may occur during manual review. At the same time, it greatly improves the efficiency of application.

[0028] Applicants no longer need to worry about preparing cumbersome paper materials, and can handle the entire process online, greatly shortening the application cycle. In addition, the system automatically performs data comparison and condition judgment, reducing the workload of manual review and making the review process faster and more efficient.

[0029] Applicants no longer need to go to multiple departments and submit a large amount of paper materials. They can complete the entire application process by submitting the application through the online platform, which greatly simplifies the process and improves the applicant's satisfaction and convenience.

[0030] In addition to reducing the workload of manual review, the system has further improved overall efficiency by optimizing data processing and review processes. The system can process a large amount of application data in real time and quickly give review results, so that subsidy funds can be distributed to applicants more quickly to meet their actual needs.

[0031] The system ensures fairness and transparency in the issuance of subsidies through data sharing and public disclosure mechanisms. Applicant information and review results can be shared in real time between departments, avoiding information silos and duplicate reviews.

[0032] At the same time, the system also supports the public disclosure of the review results, allowing the public and all sectors of society to supervise the entire application process, effectively preventing violations such as repeated applications and false claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0034] Attached Figure 1 It is a flowchart of the method of applying for and cashing in talent subsidies. DETAILED DESCRIPTION

[0035] In order to enable those skilled in the art to better understand the solution of the present invention, the present invention is further described in detail below in conjunction with specific implementation methods. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] A best embodiment is given below:

[0037] like Figure 1 As shown, a talent subsidy claim and cashing method in this embodiment, first, the user management module verifies the user identity and manages the authority of the applicant, the reviewer and the manager, and the data collection module exchanges data with the external system through the standard API interface to realize the automatic collection of user information;

[0038] Then, the data analysis module conducts in-depth analysis of the user data collected by the data collection module, and the subsidy matching module clarifies the subsidy objects, conditions, amounts and application process information;

[0039] Finally, the claim processing module automates the claim process and data verification, and the fund cashing module establishes an instant payment system to realize the receipt of subsidy funds.

[0040] Among them, the user management module is responsible for user identity verification and permission management of applicants, reviewers, managers, etc. Applicants need to register an account in the system, fill in basic information (such as name, ID number, contact information, etc.), and submit it to the system. The system verifies the user's identity by comparing the information submitted by the user with the preset verification rules or information in the database. Verification methods include password verification, mobile phone verification code verification, email verification, and facial recognition. The system assigns a set of basic permissions to each role, allowing users to modify their basic information (such as contact information, password, etc.) while restricting the modification of sensitive information. Record user login time, IP address, login results and other information for security audits and anomaly detection. Manage user account status (such as activation, freezing, deregistration, etc.) to respond to various situations and enhance security.

[0041] The data collection module exchanges data with external systems (including but not limited to social security systems, education department databases, real estate registration systems, marriage registration authorities and tax departments, etc.) through standard API interfaces to achieve automatic collection of user information. The collected information includes but is not limited to social security payment records, academic degree certificates, real estate holdings, marital status and tax information, etc., to meet the needs of enterprises or individual users for comprehensive information verification, risk assessment or personalized services.

[0042] The data analysis module uses machine learning algorithms such as gradient boosting trees and neural networks to build an evaluation model based on historical data and expert knowledge, conducts in-depth analysis of user data collected by the data collection module, and extracts key features from the preprocessed data according to the specific requirements of the subsidy policy, such as age, educational level, work experience, income level, tax status, property status, marital status, etc., and performs necessary feature conversion and selection to reduce human errors and biases, ensuring that subsidy resources can be accurately allocated to qualified talents.

[0043] The subsidy matching module clarifies key information such as subsidy recipients, conditions, amounts, and application procedures. Based on a multi-stage processing flow, the subsidy matching algorithm first conducts a preliminary screening and quickly excludes subsidy policies that do not meet the conditions based on the basic conditions of the applicant.

[0044] Furthermore, the algorithm uses fuzzy matching technology to handle edge cases. For example, when the applicant's conditions are close to policy requirements but not completely in line with them, the algorithm can provide approximate matching suggestions. By continuously collecting feedback on matching results, the matching strategy is continuously optimized using reinforcement learning to adapt to the ever-changing policy environment. The algorithm can handle the superposition effect of multiple policies to ensure that applicants can obtain the maximum possible total subsidy amount.

[0045] The claim processing module automates the claim process, reduces manual intervention, improves review efficiency, and automates data verification. After the applicant submits the claim form, the system automatically performs data integrity and consistency verification to ensure that all required information has been filled in and is in the correct format.

[0046] The system conducts preliminary screening of applications based on preset rules, excludes applications that are obviously not in compliance with subsidy policies, and reduces the workload of subsequent audits. The audit tasks are intelligently allocated based on the auditors’ expertise and current workload to ensure a balanced distribution of audit work.

[0047] For qualified and undisputed applications, the system can automatically approve them and enter the fund cashing process, reducing manual intervention. When there are doubts or the application does not meet the standards, the system can automatically mark it and transfer it to professional reviewers for in-depth review.

[0048] After the review is completed, the system automatically sends the applicant a notification of the review result, including the reason for approval or rejection. The system records the detailed process and results of each review to facilitate future audits and reviews. It provides an appeal channel for rejected applicants and supports the review process to ensure the fairness of the review. It monitors the efficiency of the review process, including key indicators such as average review time and review pass rate, to continuously optimize the review process.

[0049] The fund cashing module cooperates with major banks or payment institutions to establish an instant payment system to realize the arrival of subsidy funds in seconds. After the application is approved, the system automatically triggers the payment process without human intervention, and realizes rapid payment. It supports multiple payment methods, including bank transfers, e-wallets, mobile payments, etc., to meet the needs of different applicants.

[0050] The system provides real-time payment monitoring function to ensure that every payment can be tracked and confirmed. All payment data is encrypted through SSL protocol during transmission. When users cash out, they need to use multi-factor authentication such as password plus SMS verification code and face recognition. A risk monitoring mechanism is established to monitor and warn the fund disbursement process in real time, and to promptly identify and handle potential risks.

[0051] Based on the above method, a talent subsidy claiming and redeeming device in this embodiment includes: at least one memory and at least one processor;

[0052] The at least one memory is used to store a machine-readable program;

[0053] The at least one processor is used to call the machine-readable program to execute a method for applying for and cashing in talent subsidies.

[0054] The above-mentioned specific implementations are only specific cases of the present invention. The patent protection scope of the present invention includes but is not limited to the above-mentioned specific implementations. Any technical solutions that comply with the claims of the present invention and any appropriate changes or substitutions made by ordinary technicians in the relevant technical field shall fall within the patent protection scope of the present invention.

[0055] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for applying for and cashing talent allowances, characterized in that: First, the user management module verifies the user identity and manages the permissions of applicants, reviewers, and managers. The data collection module exchanges data with external systems through standard API interfaces to achieve automated collection of user information. Then, the data analysis module conducts in-depth analysis of the user data collected by the data collection module, and the subsidy matching module clarifies the subsidy objects, conditions, amounts and application process information; Finally, the claim processing module automates the claim process and data verification, and the fund cashing module establishes an instant payment system to realize the receipt of subsidy funds.

2. A method for applying for and cashing talent allowances according to claim 1, characterized in that: In the user management module, the applicant needs to register an account in the system, fill in basic information, and submit it to the system. The system verifies the user's identity by comparing the information submitted by the user with the preset verification rules or information in the database; The system assigns a set of basic permissions to each role, allowing users to modify basic information while restricting modifications to sensitive information and recording users' login time, IP address, and login result information.

3. A method for applying for and cashing talent allowances according to claim 2, characterized in that: The data collection module exchanges data with external systems through a standard API interface to achieve automated collection of user information. The collected information includes but is not limited to social security payment records, academic degree certificates, property holdings, marital status and tax information, meeting the needs of enterprises or individual users for comprehensive information verification, risk assessment or personalized services.

4. A method for applying for and cashing talent allowances according to claim 3, characterized in that: The data analysis module uses gradient boosting trees and neural network machine learning algorithms to build an evaluation model based on historical data and expert knowledge, conducts in-depth analysis of user data collected by the data acquisition module, extracts key features from the preprocessed data according to the specific requirements of the subsidy, and performs necessary feature conversion and selection.

5. A method for applying for and cashing talent allowances according to claim 4, characterized in that: The subsidy matching module first performs a preliminary screening to quickly exclude subsidies that do not meet the conditions based on the applicant's basic conditions. Furthermore, the algorithm uses fuzzy matching technology to handle edge cases of conditions, and continuously optimizes the matching strategy using reinforcement learning by continuously collecting feedback on matching results.

6. A method for applying for and cashing talent allowances according to claim 5, characterized in that: After the applicant submits the application form, the system automatically performs data integrity and consistency checks, preliminarily screens the applications according to preset rules, excludes applications that are obviously not eligible for subsidies, and intelligently allocates review tasks based on the reviewer's expertise and current workload; For qualified and undisputed applications, they will be automatically approved and enter the fund redemption process; When an application is questionable or does not meet the standards, it will be automatically flagged and transferred to professional reviewers for in-depth review; After the review is completed, the review result notification will be automatically sent to the applicant, recording the detailed process and results of each review, providing an appeal channel for rejected applicants, and supporting the review process.

7. A method for applying for and cashing talent allowances according to claim 6, characterized in that: The fund cashing module establishes an instant payment system to realize the arrival of subsidy funds. After the application is approved, the payment process is automatically triggered; The system provides real-time payment monitoring function. All payment data is encrypted through the SSL protocol during transmission. When users perform cashing operations, they use passwords plus SMS verification codes and face recognition authentication to establish a risk monitoring mechanism to monitor and warn of the fund disbursement process in real time.

8. A talent subsidy claiming and redemption device, characterized in that: include: at least one memory and at least one processor; The at least one memory is used to store a machine-readable program; The at least one processor is configured to call the machine-readable program to execute the method according to any one of claims 1 to 7.

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