Housing accumulation fund information processing method, system, device, medium and product

Abstract

The invention discloses a housing accumulation fund information processing method, system and device, a medium and a product, and relates to the field of accumulation fund businesses, and the method comprises the steps: obtaining accumulation fund related data; in response to a public accumulation fund service request, the public accumulation fund service request comprises a service type label, the service type label comprises a first label and a second label, the first label and the second label are respectively used for identifying a public accumulation fund extraction service request and a public accumulation fund loan service request, and the public accumulation fund extraction service request and the public accumulation fund loan service request are received based on the service type label. Carrying out classification processing on the public accumulation fund business; when the service type label is the first label, executing accumulation fund extraction condition judgment according to the accumulation fund related data; when the business type label is the second label, executing accumulation fund loan qualification evaluation according to the accumulation fund related data; and executing corresponding public accumulation fund business operation according to the classification processing result. According to the invention, data delay and errors caused by manual operation are avoided.

Description

Technical Field

[0001] The present application relates to the field of provident fund business, and in particular to a housing provident fund information processing method, system, equipment, medium and product. Background Art

[0002] With the continuous advancement of urbanization and modernization, the housing provident fund system came into being, providing solid housing security for the majority of employees. The payment and management of housing provident funds cover a wide range of business scenarios, including employee provident fund deposits, withdrawals, loans and other operations. Provident fund business involves the processing and analysis of a large amount of data, especially in the withdrawal of provident funds, loan applications and other links. The accuracy and efficiency of data analysis directly affect the processing speed and results of the business.

[0003] However, although traditional manual analysis methods meet business needs to a certain extent, they are not only time-consuming but also prone to human errors. Summary of the invention

[0004] The purpose of this application is to provide a housing provident fund information processing method, system, device, medium and product, which can avoid data delays and errors caused by manual operations.

[0005] To achieve the above objectives, this application provides the following solutions: In a first aspect, the present application provides a housing provident fund information processing method, comprising: Obtain provident fund related data; Responding to a provident fund business request, the provident fund business request includes a business type tag, the business type tag includes a first tag and a second tag, the first tag and the second tag are used to identify a provident fund withdrawal business request and a provident fund loan business request, respectively, wherein the provident fund withdrawal business request includes an applied withdrawal amount and a withdrawal type, and the provident fund loan business request includes a loan application amount; Classify and process the provident fund business based on the business type label; When the business type tag is the first tag, performing provident fund withdrawal condition judgment according to the provident fund related data; When the business type label is the second label, performing housing provident fund loan qualification assessment according to the housing provident fund related data; Execute corresponding provident fund business operations according to the classification processing results.

[0006] In a second aspect, the present application provides a housing provident fund information processing system, including: Acquisition module, used to obtain provident fund related data; A response module, used to respond to a provident fund business request, the provident fund business request includes a business type tag, the business type tag includes a first tag and a second tag, the first tag and the second tag are used to identify a provident fund withdrawal business request and a provident fund loan business request, respectively, wherein the provident fund withdrawal business request includes an applied withdrawal amount and a withdrawal type, and the provident fund loan business request includes a loan application amount; A classification module, used for classifying the provident fund business based on the business type label; A judgment module, configured to, when the business type tag is the first tag, perform provident fund withdrawal condition judgment according to the provident fund related data; An evaluation module, configured to perform a housing provident fund loan qualification evaluation according to the housing provident fund related data when the business type label is the second label; An execution module is used to execute corresponding provident fund business operations according to the classification processing results.

[0007] In a third aspect, the present application provides a computer device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of any one of the above-mentioned housing provident fund information processing methods.

[0008] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any one of the housing provident fund information processing methods described above.

[0009] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of any one of the housing provident fund information processing methods described above.

[0010] According to the specific embodiments provided in this application, this application discloses the following technical effects: The present application provides a housing provident fund information processing method, system, device, medium and product, which obtains provident fund related data; responds to provident fund business requests, the provident fund business requests contain business type tags, the business type tags contain first tags and second tags, the first tags and second tags are used to identify provident fund withdrawal business requests and provident fund loan business requests respectively, and classifies provident fund business based on business type tags; when the business type tag is the first tag, perform provident fund withdrawal condition judgment according to provident fund related data; when the business type tag is the second tag, perform provident fund loan qualification assessment according to provident fund related data; perform corresponding provident fund business operations according to the classification processing results. This method reduces manual intervention and avoids data delays and errors caused by manual operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0012] Figure 1 This is an application environment diagram of a housing provident fund information processing method in one embodiment of the present application; Figure 2 A flowchart of a housing provident fund information processing method provided in one embodiment of the present application; Figure 3 A schematic diagram of functional modules of a housing provident fund information processing system provided in one embodiment of the present application; Figure 4 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0013] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0014] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0015] The housing provident fund information processing method provided in the embodiment of the present application can be applied to Figure 1In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be set up separately, or integrated on the server 104, or placed on the cloud or other servers. The terminal 102 can send the provident fund related data to be processed to the server 104. After the server 104 receives the provident fund related data to be processed, the server 104 classifies the provident fund business based on the business type label for the provident fund related data to be processed. The server 104 can feedback the obtained provident fund withdrawal condition judgment and provident fund loan qualification evaluation results to the terminal 102. In addition, in some embodiments, the housing provident fund information processing method can also be implemented by the server 104 or the terminal 102 alone, such as the terminal 102 can directly process the provident fund related data to be processed, or the server 104 can obtain the provident fund related data to be processed from the data storage system and process the provident fund related data to be processed.

[0016] The terminal 102 may be, but is not limited to, various desktop computers, laptop computers, smart phones, tablet computers, IoT devices, and portable wearable devices. The IoT devices may be smart speakers, smart TVs, smart air conditioners, smart vehicle-mounted devices, etc. The portable wearable devices may be smart watches, smart bracelets, head-mounted devices, etc. The server 104 may be implemented as an independent server or a server cluster consisting of multiple servers, or may be a cloud server.

[0017] In an exemplary embodiment, Figure 2 As shown, a housing provident fund information processing method is provided. The method is executed by a computer device, and can be executed by a computer device such as a terminal or a server alone, or by a terminal and a server together. In the embodiment of the present application, the method is applied to Figure 1 The server 104 in the example is used as an example to illustrate the method, which includes the following steps 201 to 206. Among them: Step 201, obtaining provident fund related data.

[0018] Wherein, step 201 includes the following sub-steps: A1. Acquire user provident fund payment data based on the first data interface between the housing provident fund information processing system and the bank system.

[0019] Specifically, based on the first data interface between the housing provident fund information processing system and the bank system, relevant data information about provident fund deposits can be obtained. This data interface, as the key to connecting the provident fund information processing system and the bank system, ensures the efficiency and accuracy of data transmission. Through this interface, the provident fund deposits of employees can be obtained in real time, including detailed information such as the deposit amount, deposit time, and deposit unit, and this information can be used to check and verify the deposit records to ensure the normal operation and management of the provident fund. In addition, this data interface also provides the bank system with real-time updated provident fund deposit data, so that the bank can handle related business operations in a timely manner, such as loan approval, account inquiry, etc.

[0020] It is understandable that the monthly provident fund payment information of employees is remitted by their units through banks. This process involves docking with banks to collect the monthly provident fund payment records of employees. These records include the amount of monthly payment, the specific time of payment, and the balance of the account. The payment amount refers to the actual amount of provident fund paid by employees each month. This amount will be recorded separately according to the part borne by the unit and the individual. This can clearly reflect the contribution of the unit and the individual to the provident fund. The payment time refers to the specific date of each provident fund remittance. By recording the date, it can ensure accurate tracking and monitoring of the monthly payment. The account balance refers to the balance in the employee's provident fund account. The bank will push this information regularly to facilitate real-time monitoring of the account status and ensure that the employee has a clear understanding of his or her account balance. In the process of bank data collection, encryption protocols are used to ensure the security and integrity of data during transmission. This encryption measure can effectively prevent data from being illegally intercepted or tampered with during transmission, thereby protecting the privacy and financial security of employees. Through real-time connection with banks, employees' provident fund payment information can be updated quickly to ensure that the data every month is synchronized and accurate, so that employees and units can keep abreast of the latest provident fund payment situation.

[0021] A2. Obtaining user income data based on the second data interface between the housing provident fund information processing system and the tax system.

[0022] Specifically, in the provident fund information processing system, the employee's wage income data can be obtained through the second data interface between the tax system. This interface can extract the employee's monthly wage income information from the tax system in real time, thereby providing accurate data support for the calculation of the provident fund contribution ratio and loan amount. It ensures the timeliness and accuracy of the employee's wage income data, and then accurately calculates the provident fund base that the employee should pay, and evaluates their repayment ability when taking out a loan.

[0023] A3. Obtaining the user's social security payment data based on the third data interface between the housing provident fund information processing system and the social security system.

[0024] Specifically, in the provident fund information processing system, the social security payment data of employees can be obtained through the third data interface between the social security system and the social security system. This interface can extract the social security payment records of employees from the social security system in real time to ensure the qualification review of employees when withdrawing provident funds or applying for loans. In this way, the timeliness and accuracy of employees' social security payment data can be ensured, and then the social security payment situation of employees can be accurately evaluated so as to make reasonable decisions in the processing of provident fund information. Data such as employees' salary income and social security payment situation are obtained from the tax and social security systems to calculate the employee's deposit ratio and loan amount. The monthly salary income of employees is obtained through the tax system to calculate the base of employees' provident fund payment and determine the repayment ability when taking loans. The payment records of employees are obtained from the social security system to ensure the qualification review of employees when withdrawing provident funds or applying for loans. The data collection in this process is realized through the API interface, and the system can call the relevant information of the tax and social security systems on demand to ensure the timeliness and accuracy of the data.

[0025] A4. Acquire the user's house purchase data based on the fourth data interface between the provident fund information processing system and the real estate management system.

[0026] Specifically, house purchase data is obtained through the fourth data interface between the provident fund information processing system and the real estate management system. The house purchase information of employees is extracted from the real estate management system to determine the employee's loan and withdrawal qualifications. This information includes key data such as the purchase contract, the type of real estate, and the time and amount of the purchase. In this way, the employee's house purchase behavior can be verified and ensured to comply with relevant policy regulations. In addition, it is also necessary to collect the specific types of real estate, such as commercial housing, second-hand housing, etc., in order to facilitate the subsequent qualification review of provident fund withdrawal or loan. At the same time, it is also crucial to collect the purchase time and purchase price of the house, because this information will be used to evaluate the amount of provident fund withdrawal and loan approval standards for employees.

[0027] A5. User provident fund payment data, user income data, user social security payment data and user housing purchase data constitute provident fund related data.

[0028] Specifically, in order to ensure that the provident fund information processing system can exchange data efficiently and securely with the banking system, tax system, social security system and real estate management system, it is necessary to define the URL path for the detailed specifications of the first data interface between the provident fund information processing system and the banking system, the second data interface between the provident fund information processing system and the tax system, the third data interface between the provident fund information processing system and the social security system, and the fourth data interface between the provident fund information processing system and the real estate management system for data exchange to ensure that the request can be accurately sent to the target system. HTTP methods such as GET, POST, etc. are used to determine the acquisition and submission of data. In addition, the format of the request parameters also needs to be clear. Common formats include JSON and XML, which help to standardize the transmission and parsing of data. In order to ensure the security of data exchange, authentication methods such as OAuth, API keys, tokens, etc. need to be used to ensure that only authorized users can access sensitive data and prevent the risk of unauthorized access and data leakage. Send the HTTP request to the API endpoint of the corresponding system, carrying the necessary authentication information and query parameters. These parameters include user authentication information, specific content of the request, etc. After receiving the response from the corresponding system, the provident fund information processing system needs to parse the returned data, extract useful information, and store it in the local system for subsequent processing and use.

[0029] Through the connection of the above data sources, the real-time update of employee provident fund information is realized. This process avoids errors and delays in manual input, and improves the accuracy and timeliness of data. It also reduces the number of employees who repeatedly submit paper materials when withdrawing provident funds or applying for loans, simplifies procedures, and improves processing efficiency. Staff no longer need to spend a lot of time and energy on tedious paper material preparation, thereby improving overall job satisfaction and work efficiency.

[0030] In one implementation, preprocessing the provident fund related data includes the following sub-steps: B1. Clean the provident fund related data.

[0031] Specifically, use data processing tools (such as the Python pandas library) to find records with the same identifier (such as ID number, employee number, etc.). Delete or merge duplicate records to retain the latest or most complete information. For missing values ​​that may exist in certain fields, fill reasonable values ​​according to business rules (such as using the average, median, or specific value), or choose to delete records with missing values. Correct obviously incorrect data entries, such as incorrect date format, negative amounts, etc.

[0032] B2. Format the provident fund related data after data cleaning.

[0033] Specifically, convert all date fields into a unified format (such as YYYY-MM-DD) and unify the monetary amount fields into the same unit (such as yuan). Verify the consistency of data, for example, compare the employee's salary income with the provident fund contribution amount to check whether there is an unreasonable contribution ratio or amount. For data from different sources, establish a field mapping table to ensure that the key field names and meanings of all data sources are consistent. Convert unstructured data (such as text descriptions) to structured data (such as classification labels) for subsequent processing. By preprocessing the data, the consistency and accuracy of the data are ensured.

[0034] Step 202, responding to a provident fund business request, the provident fund business request includes a business type tag, the business type tag includes a first tag and a second tag, the first tag and the second tag are respectively used to identify a provident fund withdrawal business request and a provident fund loan business request, wherein the provident fund withdrawal business request includes an applied withdrawal amount and a withdrawal type, and the provident fund loan business request includes a loan application amount.

[0035] Specifically, when a user sends a provident fund business request to the provident fund information processing system, the request can be divided into two categories: one is a provident fund withdrawal business request, and the other is a provident fund loan business request. Provident fund withdrawal business requests involve users applying to the provident fund management center to withdraw part or all of the provident fund balance in their personal accounts under certain conditions. Provident fund loan business requests refer to employees applying to the provident fund management center to use the provident fund balance in their personal accounts for loans when they need to buy a house, rent a house, repay a loan, etc., in order to obtain loan funds at a lower interest rate. Both types of business requests need to be submitted and processed through the provident fund information processing system.

[0036] It is understandable that when making a request for provident fund withdrawal, it is necessary to provide the employee's personal information, such as ID number, name, etc.; the reason for withdrawal, such as house purchase, renovation, loan repayment, etc.; relevant supporting materials, such as house purchase contract, medical expense invoice, etc.; and the withdrawal amount. Construct the request message according to the API document or business process guide of the provident fund information processing system. The message should contain the above information that needs to be prepared. Make sure that the request message conforms to the prescribed format, such as JSON or XML. If authentication is required, add authentication information such as API key, OAuth token, etc. Use an HTTP client, such as the curl command, Postman tool, or HTTP library in a programming language, to send a POST request to the specified API endpoint. When sending a request, you need to ensure that the correct HTTP method is used, usually the POST method, and ensure that the URL address of the request is correct. At the same time, you also need to check whether the content of the request header and request body meets the requirements of the provident fund management center. If the response information indicates that the request is successful, record the relevant processing results and information. If the response information indicates that the request failed, make corresponding adjustments based on the returned error code and error message.

[0037] Step 203: Classify and process the provident fund business based on the business type label.

[0038] Step 204, when the business type tag is the first tag, the provident fund withdrawal condition judgment is performed according to the provident fund related data.

[0039] Wherein, step 204 includes the following sub-steps: C1. Based on the user's provident fund payment data, obtain the provident fund payment years, provident fund payment amount and account balance; C2. If the provident fund payment period is greater than or equal to the preset payment period, and the payment ratio of the provident fund payment amount is greater than or equal to the preset payment ratio, a provident fund withdrawal plan is generated based on the withdrawal type, application withdrawal amount, payment amount and account balance, and the provident fund withdrawal plan includes the actual withdrawal amount; Specifically, the withdrawal types include but are not limited to house purchase and medical treatment, and the provident fund withdrawal plan includes the withdrawal amount, withdrawal method, withdrawal time and possible restrictions. The plan will be submitted to the Provident Fund Management Center for review. If the Provident Fund Management Center approves the withdrawal plan, the system will automatically execute the withdrawal operation and update the user's provident fund account balance. If the Provident Fund Management Center rejects the withdrawal plan, the system will notify the user of the reason for the rejection and provide the option to modify the plan. Users can adjust the withdrawal amount or choose other withdrawal methods based on feedback, and then resubmit the withdrawal application. The entire process will ensure compliance with relevant laws and regulations and the regulations of the Provident Fund Management Center, while providing users with a convenient and transparent service experience.

[0040] For example, if the withdrawal type is to buy a house, the withdrawal amount will be determined based on the purchase contract amount, the down payment ratio, and the user's existing provident fund balance. The system will give priority to the user's existing provident fund balance to reduce the user's cash expenditure. If the purchase contract amount exceeds the user's provident fund balance, the system will calculate the additional cash portion that needs to be paid and prompt the user to prepare the corresponding funds. In addition, the system will evaluate the user's repayment ability based on the user's deposit record and account balance, and give reasonable repayment plan suggestions. When the user chooses the withdrawal method, the system will provide a variety of withdrawal methods for the user to choose, including one-time withdrawal, installment withdrawal, etc., to meet the actual needs of different users.

[0041] C3. Otherwise, the provident fund withdrawal plan is rejected and the first prompt message is sent.

[0042] Step 205: when the business type tag is the second tag, perform housing provident fund loan qualification assessment according to the housing provident fund related data.

[0043] Wherein, step 205 includes the following sub-steps: D1. Based on user income data, obtain user salary income; D2. If the provident fund payment period is greater than or equal to the preset payment period, and the payment ratio of the provident fund payment amount is greater than or equal to the preset payment ratio, a provident fund loan plan is generated based on the user's salary income and loan application amount. The provident fund loan plan includes the actual provident fund loan amount.

[0044] D3. Otherwise, the provident fund loan plan is rejected and a second prompt message is sent.

[0045] Specifically, based on the user's housing fund payment data, obtain the housing fund payment years, housing fund payment amount and account balance, and based on the user's income data, obtain the user's salary income. Check the user's housing fund payment record to ensure that the payment time meets the minimum loan term requirements (such as continuous payment for 12 months), and confirm whether the user has interrupted the payment, and exclude records that do not meet the requirements. Verify the user's salary income level to ensure that he has sufficient income to bear the loan repayment responsibility. Assess the user's job stability and understand whether his income is stable and reliable. According to the payment and income situation, determine whether the employee meets the basic qualifications for applying for a housing fund loan. Obtain the employee's current balance from the housing fund account. Calculate the proportion of the employee's housing fund payment based on the employee's monthly income to determine the income portion that can be used for the loan. Combine the employee's income, debt situation and other factors to assess their future repayment ability. Calculate the maximum loan amount based on the employee's housing fund account balance, income level and repayment ability. Ensure that the calculated loan amount complies with the provisions of the housing fund loan policy and can meet the actual needs of the employee. Check the employee's existing debts, including but not limited to credit card arrears, other loans, etc. Calculate the employee's total debt ratio based on their total income and total existing debt to assess their overall debt level. Recommend a reasonable repayment period based on the employee's monthly income and the proposed loan amount. Ensure that the recommended repayment period does not cause the employee's monthly repayment amount to exceed their ability to bear. If the initial assessment shows that the employee's repayment ability is insufficient, adjust the loan term or recommend reducing the loan amount to reduce repayment pressure.

[0046] Step 206, executing corresponding provident fund business operations according to the classification processing results.

[0047] It is understandable that after the loan application is approved, the system will generate the corresponding loan contract document. At this point, users will have the opportunity to conveniently view and sign this contract through the online platform. In order to meet the needs of different users, the platform provides a variety of contract templates for users to choose from, which vary according to the type and amount of the loan. Each template pre-sets specific terms and conditions, such as loan amount, interest rate, repayment period and other relevant details. After the user selects the appropriate contract template, the system will automatically fill the user's personal information and detailed information in the loan application into the selected template to ensure the accuracy of the contract content. After the contract is generated, users can easily sign it online. In order to ensure the legality and validity of the contract, the platform supports electronic signature technology. After carefully reading and confirming that the content of the contract is correct, the user signs electronically, eliminating the cumbersome processing process of traditional paper documents. After completing the electronic signature, the relevant information of the contract will be synchronized to the bank system and regulatory authorities to ensure that all relevant parties can obtain the latest contract information in a timely manner. This move not only improves work efficiency, but also speeds up the subsequent process of loan issuance, allowing users to obtain the required financial support more quickly.

[0048] In one achievable manner, the provident fund information processing method further includes the following steps: E1. Regularly monitor provident fund payment records.

[0049] The above step E1 includes the following sub-steps: E11. Obtain user provident fund payment data based on the first data API interface between the provident fund information processing system and the bank system. Format the obtained user provident fund payment data to ensure a unified data format; E12. Create a Kafka topic for provident fund payment records in Kafka (distributed stream processing platform). This topic is used to transmit user provident fund payment data. E13. Configure the producer in Kafka. The producer is used to transmit the collected user provident fund payment data to the corresponding Kafka topic; E2. Identify abnormal situations based on provident fund payment records.

[0050] The above step E2 includes the following sub-steps: E21. Build Apache Flink (stream processing framework) based on Kafka.

[0051] E22. Set the minimum amount of a single deposit as the first threshold, the number of deposits required each month as the second threshold, the maximum difference between consecutive deposit amounts as the third threshold, and the maximum number of consecutive days of non-payment as the fourth threshold.

[0052] For example, the minimum deposit amount is 500 yuan; the number of deposits to be made per month is 1; the maximum number of consecutive days of non-payment is 7 days; the difference between two consecutive deposit amounts shall not exceed 1,000 yuan.

[0053] E23. The first condition is that the single deposit amount is less than the first threshold, the second condition is that the number of monthly deposits is less than the second threshold, the third condition is that the maximum difference between multiple deposit amounts is greater than the third threshold, and the fourth condition is that the maximum consecutive number of non-payment days is greater than the fourth threshold. As long as at least one of the above-mentioned first condition, second condition, third condition and fourth condition is met, an abnormal situation is determined.

[0054] E3. Generate early warning information based on abnormal situations.

[0055] Specifically, regularly monitor employees' provident fund payment records to ensure that each employee's payment status is Keep a constant eye on the data to track and record employees' contributions in real time. Based on the provident fund contribution records, identify possible anomalies, which may include abnormal contribution amounts, abnormal contribution times, or abnormal contribution frequencies. Set specific thresholds so that the system can automatically identify these anomalies. If an abnormal situation occurs, the system will immediately generate an early warning message and send it to relevant managers for manual review. The early warning message can be sent via email, SMS, or internal system messages to ensure that relevant personnel can receive it in time and take appropriate measures.

[0056] When using Kafka for data processing, you first need to create one or more topics for provident fund payment records. These topics can be divided according to different business scenarios or record types to better manage and process data. For example, you can create a topic specifically for storing personal payment records, and another topic for corporate payment records, so that the data is more orderly. After the data flows into Kafka, it needs to be converted and cleaned, and the original message format needs to be parsed to ensure that the data is in the correct format. In addition, invalid data, such as records with incorrect formats or incomplete records, needs to be filtered out to ensure data quality.

[0057] In one achievable manner, the provident fund information processing method further includes the following steps: F1. Obtain historical payment records from the provident fund management system. The historical payment records include the user's unique identifier (user ID), payment amount, and payment date.

[0058] F2. Extract feature data from historical deposit records to form a feature data set. The feature data includes the user's deposit amount, the most recent deposit date, the number of consecutive days of non-payment, etc.

[0059] F3. Use support vector machine algorithm for data analysis.

[0060] Specifically, the feature data set is divided into a training set and a test set. Usually, the training set accounts for 80% of the total data volume, while the test set accounts for 20%. Use the training set data to train the selected model and adjust the model's parameters. After the training is completed, use the test set data to evaluate the performance of the model.

[0061] F4. Input real-time data into the trained support vector machine model to identify potential abnormal patterns. When the model detects abnormal behavior, the system will automatically generate early warning information and send it to relevant personnel in a timely manner. Managers can take quick measures to prevent potential risks and losses and improve the efficiency of provident fund management.

[0062] In order to provide convenient online services, a unified operation platform can be established. This platform will integrate all provident fund-related functions, including account management, withdrawal applications, loan applications, etc. Through this platform, users can operate anytime and anywhere, without being restricted by time and place. In order to ensure that users can use the platform conveniently, it supports multiple terminal access, including mobile terminals. In this way, users can access their provident fund accounts through their most commonly used devices, whether at home, in the office or outside. The operation platform can perform account management, withdrawal applications and loan applications. Users can query account balances, deposit records and other information. Provident fund withdrawal applications can be submitted online and the application progress can be checked. Provident fund loan applications can be submitted online and the application progress can be checked. The platform adopts a unified interface to ensure that users have a consistent operation experience on different terminals. All functional modules should be laid out through intuitive menus and buttons, so that employees can quickly find the required services and reduce learning costs. Users can view the current status of their applications through the operation platform, such as "submitted", "under review", "approved", etc., to ensure that users can see the processing status of their applications at a glance. When the application status changes, users will be notified via SMS or APP push notifications, so that they can be informed of the application progress at the first time. When applying for provident fund withdrawal or loan, users can fill in the electronic form online and fill in the relevant content according to the information provided by the user, reducing the trouble of repeated input. The platform directly uploads the required supporting documents (such as identity proof, income proof, etc.), supports multiple file formats, and is convenient for employees to quickly upload using mobile phones or computers.

[0063] Based on the same inventive concept, the present application embodiment also provides a method for realizing the above-mentioned Provident fund information processing system of provident fund information processing method. The implementation scheme for solving the problem provided by the system is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more provident fund information processing system embodiments provided below can refer to the limitations on the provident fund information processing method above, and will not be repeated here.

[0064] In an exemplary embodiment, Figure 3 As shown, a housing provident fund information processing method is provided. System, including: The acquisition module 310 is used to acquire provident fund related data; A response module 320 is used to respond to a provident fund business request, wherein the provident fund business request includes a business type tag, wherein the business type tag includes a first tag and a second tag, wherein the first tag and the second tag are used to identify a provident fund withdrawal business request and a provident fund loan business request, respectively, wherein the provident fund withdrawal business request includes an applied withdrawal amount and a withdrawal type, and the provident fund loan business request includes an applied loan amount; A classification module 330, configured to classify the provident fund business based on the business type label; A judgment module 340, configured to, when the business type tag is the first tag, perform a judgment on a housing fund withdrawal condition according to the housing fund related data; An evaluation module 350, configured to perform a housing provident fund loan qualification evaluation according to the housing provident fund related data when the business type tag is the second tag; The execution module 360 ​​is used to execute corresponding provident fund business operations according to the classification processing results.

[0065] As an optional implementation, the acquisition module 310 is specifically configured to: Acquiring housing provident fund payment data based on a first data interface between the housing provident fund information processing system and a bank system; Acquiring wage income data based on a second data interface between the provident fund information processing system and the tax system; Acquiring social security payment data based on a third data interface between the provident fund information processing system and the social security system; Acquiring housing purchase data based on a fourth data interface between the provident fund information processing system and the real estate management system; The provident fund payment data, salary income data, social security payment data and house purchase data constitute the provident fund related data.

[0066] As an optional implementation, the provident fund information processing system further includes: Preprocessing the provident fund related data; The pretreatment method comprises: Clean the provident fund related data; Format the provident fund related data after data cleaning.

[0067] As an optional implementation, the determination module 340 is specifically configured to: Based on the user's provident fund payment data, obtain the provident fund payment years, provident fund payment amount and account balance; If the provident fund payment period is greater than or equal to the preset payment period, and the payment ratio of the provident fund payment amount is greater than or equal to the preset payment ratio, a provident fund withdrawal plan is generated according to the withdrawal type, the applied withdrawal amount, the payment amount and the account balance, and the provident fund withdrawal plan includes the actual withdrawal amount; Otherwise, the provident fund withdrawal plan will be rejected and a prompt message will be sent.

[0068] As an optional implementation, the evaluation module 350 is specifically configured to: Based on the user income data, obtaining the user's salary income; If the provident fund payment period is greater than or equal to the preset payment period, and the payment ratio of the provident fund payment amount is greater than or equal to the preset payment ratio, a provident fund loan plan is generated based on the user's salary income and the loan application amount, and the provident fund loan plan includes the actual provident fund loan amount.

[0069] As an optional implementation, the provident fund information processing system further includes: Regularly monitor employees' provident fund payment records; Identify abnormal situations based on the provident fund payment records; If the abnormal situation occurs, a warning message is generated.

[0070] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 4As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store provident fund related data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a provident fund information processing method is implemented.

[0071] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0072] In an exemplary embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0073] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0074] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0075] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0076] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0077] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0078] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0079] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A housing provident fund information processing method, which is implemented by a housing provident fund information processing system, characterized in that: The housing provident fund information processing method comprises: Obtain provident fund related data; Responding to a provident fund business request, the provident fund business request includes a business type tag, the business type tag includes a first tag and a second tag, the first tag and the second tag are used to identify a provident fund withdrawal business request and a provident fund loan business request, respectively, wherein the provident fund withdrawal business request includes an applied withdrawal amount and a withdrawal type, and the provident fund loan business request includes a loan application amount; Classify and process the provident fund business based on the business type label; When the business type tag is the first tag, performing provident fund withdrawal condition judgment based on the provident fund related data; When the business type label is the second label, performing housing provident fund loan qualification assessment based on the housing provident fund related data; Execute corresponding provident fund business operations according to the results of the classification processing.

2. The housing provident fund information processing method according to claim 1, characterized in that: The acquisition of provident fund related data specifically includes: Acquiring user provident fund payment data based on a first data API interface between the provident fund information processing system and the bank system; Acquiring user income data based on a second data API interface between the provident fund information processing system and the tax system; Acquiring user social security payment data based on a third data API interface between the provident fund information processing system and the social security system; Acquiring user housing purchase data based on a fourth data API interface between the provident fund information processing system and the real estate management system; The user's provident fund payment data, the user's income data, the user's social security payment data and the user's house purchase data constitute the provident fund related data.

3. The housing provident fund information processing method according to claim 2, characterized in that: When the business type tag is the first tag, performing provident fund withdrawal condition judgment according to the provident fund related data includes: Based on the user's provident fund payment data, obtain the provident fund payment years, provident fund payment amount and account balance; If the provident fund payment period is greater than or equal to the preset payment period, and the payment ratio of the provident fund payment amount is greater than or equal to the preset payment ratio, a provident fund withdrawal plan is generated according to the withdrawal type, the applied withdrawal amount, the provident fund payment amount and the account balance, and the provident fund withdrawal plan includes the actual withdrawal amount; Otherwise, the provident fund withdrawal plan will be rejected and the first prompt message will be sent.

4. The housing provident fund information processing method according to claim 3, characterized in that: When the business type tag is the second tag, performing housing provident fund loan qualification assessment based on the housing provident fund related data includes: Based on the user income data, obtaining the user's salary income; If the provident fund payment period is greater than or equal to the preset payment period, and the payment ratio of the provident fund payment amount is greater than or equal to the preset payment ratio, a provident fund loan plan is generated according to the user's salary income, the loan application amount and the provident fund payment amount, and the provident fund loan plan includes the actual provident fund loan amount; Otherwise, the provident fund loan plan is rejected and a second prompt message is sent.

5. The housing provident fund information processing method according to claim 1, characterized in that: Before the step of classifying the provident fund business based on the business type label, the housing provident fund information processing method further includes: Preprocessing the provident fund related data; The pretreatment method comprises: Performing data cleaning on the provident fund related data; The provident fund related data after data cleaning is formatted.

6. The housing provident fund information processing method according to claim 1, characterized in that: The housing provident fund information processing method further includes: Regularly monitor provident fund payment records; Identify abnormal situations based on the provident fund payment records; Generate warning information based on the abnormal situation.

7. A housing provident fund information processing system, characterized in that: The housing provident fund information processing system comprises: Acquisition module, used to obtain provident fund related data; A response module, used to respond to a provident fund business request, the provident fund business request includes a business type tag, the business type tag includes a first tag and a second tag, the first tag and the second tag are used to identify a provident fund withdrawal business request and a provident fund loan business request, respectively, wherein the provident fund withdrawal business request includes an applied withdrawal amount and a withdrawal type, and the provident fund loan business request includes a loan application amount; A classification module, used for classifying the provident fund business based on the business type label; A judgment module, configured to, when the business type tag is the first tag, perform provident fund withdrawal condition judgment according to the provident fund related data; An evaluation module, configured to perform a housing provident fund loan qualification evaluation according to the housing provident fund related data when the business type label is the second label; An execution module is used to execute corresponding provident fund business operations according to the classification processing results.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the housing provident fund information processing method described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the housing provident fund information processing method described in any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the housing provident fund information processing method described in any one of claims 1 to 6 are implemented.

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