System and method for automatically generating bond management report

Abstract

The invention is suitable for the technical field of Internet, and provides a bond management report automatic generation system and method. In the embodiment of the invention, the system collects the bond initial data from the bond target data source, preprocesses the bond initial data, generates the bond target data matched with the data analysis model, and analyzes the bond target data through the pre-trained data analysis model, thereby automatically obtaining the bond research report. And after the bond research report is audited and passes, the bond research report is published and shared. According to the system, the bond report is automatically generated, the information processing accuracy and efficiency are improved, and the quality of the enterprise bond report is improved.

Description

Technical Field

[0001] The present application relates to the field of Internet technology, and in particular to a system and method for automatically generating a bond management report. Background Art

[0002] In the actual operation of corporate bond issuance and bond management by large comprehensive groups, with the continuous development of the bond market, investors' demand for bond information is growing. The bond issuance business of large enterprises involves a large amount of data and information processing, which requires efficient and accurate analysis tools to support decision-making; bond issuance involves a large amount of data collection, collation and analysis. The traditional manual processing method is not only inefficient, but also prone to errors. Summary of the invention

[0003] In view of this, the present application provides a bond management report automatic generation system and method to achieve the following effects: improving report generation efficiency, improving report quality, reducing labor costs, enhancing risk control capabilities, etc.

[0004] The first aspect of the present application provides a bond management report automatic generation system, the system comprising a data integration and acquisition module, a report template management module, an intelligent analysis and report generation module, a report review and release module, and a permission management and security module;

[0005] The data integration and collection module is used to collect initial bond data from the bond target data source, pre-process the initial bond data, and generate bond target data, wherein the pre-processing includes data cleaning, data integration, and data conversion;

[0006] The report template management module is used to provide a template processing page, display multiple report templates through the template processing page, and determine the template selected or customized by the user on the template processing page as the target template;

[0007] The intelligent analysis and report generation module is used to perform in-depth analysis on the bond target data through a machine learning algorithm and a trained data analysis model, generate analysis results of the bond target data, and generate a bond research report based on the analysis results and the target template;

[0008] The report review and release module is used to review the bond research report and, when the review is passed, release or share the bond research report in a format selected by the user;

[0009] The permission management and security module is used to determine several different levels of permissions and set corresponding permissions for the user according to the user's user information, so that when each user logs in, he or she can obtain corresponding functions through different permissions to protect the security of user data and the bond research report.

[0010] Optionally, the system further includes a timed task module;

[0011] The timed task and reminder module is used to set a timed task through a timer. When the collection time set by the timer is reached, the data integration and collection module collects data for processing to generate second bond target data, and then the intelligent analysis and report generation module generates a bond research report corresponding to the second bond target data;

[0012] Update the collection time on the timer, and when the updated collection time is reached, execute again the steps of collecting data, generating the corresponding bond research report, and sending the report completion notification.

[0013] Optionally, the in-depth analysis of the bond target data by using a machine learning algorithm and a trained data analysis model to generate analysis results of the bond target data includes:

[0014] Dividing the bond target data into a training set, a validation set, and a test set;

[0015] Training a pre-built data analysis model using the training set data, and adjusting parameters of the data analysis model;

[0016] Then, the validation set is used to evaluate the performance of the data analysis model. After the best data analysis model is selected, the best data analysis model is tested using the test set, and after the test passes, the best data analysis model is determined as the trained data analysis model;

[0017] The bond target data is input into the trained data analysis model to generate corresponding analysis results.

[0018] Optionally, the system further includes a field configuration module;

[0019] The field configuration module is used to provide the user with field adjustment options for the bond research report, allowing the user to add or delete fields in the bond research report according to the field adjustment options, wherein the field adjustment options include adding, modifying, moving and deleting.

[0020] Optionally, the system further includes a multi-person collaboration and editing module;

[0021] The multi-person collaboration and editing module is used to store the bond research report edited by several users through distributed caching technology.

[0022] Optionally, the scheduled task module also includes a reminder module;

[0023] The reminder module is used to monitor in real time whether the bond initial data of the bond target data source is updated. When an update is determined, the updated bond initial data is collected, and the updated bond initial data is analyzed, and risk warnings and response suggestions are determined according to the analysis results, and the risk warnings and response suggestions are sent to the target user;

[0024] The reminder module is also used to send a report completion notification to the target user of the bond research report after the report generation module generates the bond research report.

[0025] A second aspect of the present application provides a method for automatically generating a bond management report, the method comprising:

[0026] Collecting initial bond data from a bond target data source, preprocessing the initial bond data, and generating bond target data, wherein the preprocessing includes data cleaning, data integration, and data conversion;

[0027] Displaying a template processing page to the user, displaying multiple report templates through the template processing page, and determining the template selected or customized by the user on the template processing page as the target template;

[0028] Conducting in-depth analysis of the bond target data through machine learning algorithms and trained data analysis models, generating analysis results of the bond target data, and generating a bond research report based on the analysis results and the target template;

[0029] The bond research report is reviewed, and when the review is passed, the bond research report is published or shared in a format selected by the user.

[0030] Optionally, the method further includes:

[0031] A timer is used to set a timed task. When the collection time set by the timer is reached, the data integration and collection module is used to collect data for processing to generate second bond target data, and then the intelligent analysis and report generation module is used to generate a bond research report corresponding to the second bond target data;

[0032] Update the collection time on the timer, and when the updated collection time is reached, execute again the steps of collecting data, generating the corresponding bond research report, and sending the report completion notification.

[0033] Optionally, the in-depth analysis of the bond target data by using a machine learning algorithm and a trained data analysis model to generate analysis results of the bond target data includes:

[0034] Dividing the bond target data into a training set, a validation set, and a test set;

[0035] Training a pre-built data analysis model using the training set data, and adjusting parameters of the data analysis model;

[0036] Then, the validation set is used to evaluate the performance of the data analysis model. After the best data analysis model is selected, the best data analysis model is tested using the test set, and after the test passes, the best data analysis model is determined as the trained data analysis model;

[0037] The bond target data is input into the trained data analysis model to generate corresponding analysis results.

[0038] Optionally, monitor in real time whether the bond initial data of the bond target data source is updated, and when it is determined to be updated, collect the updated bond initial data, analyze the updated bond initial data, determine risk warnings and response suggestions based on the analysis results, and send the risk warnings and response suggestions to the target user;

[0039] And after generating the bond research report, a report completion notification is sent to the target user of the bond research report.

[0040] In the embodiment provided by the present application, after the system collects the initial bond data from the bond target data source, it pre-processes it, generates the bond target data matched by the data analysis model, and then analyzes the bond target data through the pre-trained data analysis model, thereby automatically obtaining a bond research report, and after the bond research report is reviewed and approved, it is published and shared. The following technical effects are achieved through this embodiment:

[0041] 1. Improve report generation efficiency: By automatically generating reports, the time for report preparation is greatly shortened, allowing companies to obtain market information and make decisions faster.

[0042] 2. Improve report quality: The system uses advanced data analysis technology and algorithms to conduct in-depth mining and analysis of bond data to generate more accurate and comprehensive reports.

[0043] 3. Reduce labor costs: Traditional report preparation requires a lot of manual operations, while the automatic generation system can greatly reduce manpower input and reduce the company's operating costs.

[0044] 4. Enhance risk control capabilities: The system can monitor and analyze market changes in real time, provide companies with timely risk warnings and response suggestions, and help companies better control risks.

[0045] 5. Support decision-making: High-quality bond research reports can provide strong support for a company's bond issuance decisions and help the company formulate a more scientific and reasonable bond issuance strategy. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 A system module diagram provided for an embodiment of the present application;

[0047] Figure 2 A flow chart of the method provided in the embodiment of the present application;

[0048] Figure 3 A schematic diagram of the internal structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0049] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0050] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms of "a", "said" and "the" used in this application and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0051] It should be understood that although the terms first, second, third, etc. may be used in the present application to describe various information, these information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0052] The present application provides a bond management report automatic generation system to assist enterprises in improving the quality of bond research reports.

[0053] The technical solution of the present application is described in detail with specific embodiments below. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0054] like Figure 1As shown, this is a module diagram of a bond management report automatic generation system provided by the present application, the system includes a data integration and collection module, a report template management module, an intelligent analysis and report generation module, a report review and release module, and an authority management and security module.

[0055] The functions of each module are described below:

[0056] 1. Data integration and collection module. This module is used to collect initial bond data from bond target data sources, which can be market data platforms, corporate announcements, news reports, etc. When collecting data, different strategies can be customized for collection according to different market needs. For example, when a company needs an analysis report related to bond policies within a certain time period, such as between 1990 and 2024, the strategy customized when collecting data can include time intervals and keywords.

[0057] After the collection is completed, the collected initial bond data is preprocessed, including:

[0058] Data cleaning, identifying and processing missing values, removing duplicate records, and correcting inconsistent or erroneous data.

[0059] Data integration, merging initial bond data from different sources and resolving conflicts between data sources.

[0060] And data conversion, normalize, standardize or encode the initial bond data and convert it into a format suitable for data analysis model analysis.

[0061] After processing, bond target data suitable for data analysis models can be obtained.

[0062] 2. Report template management module. This module is used to manage the templates of bond research reports.

[0063] This module provides a template processing page to users through the client or APP. The page provides users with multiple designed templates and multiple template components, so that users can directly select a template as the target template, or modify the provided template and select the modified template as the target template. After the system receives the target template submitted by the user, it will subsequently generate a bond research report in the format of the target template.

[0064] 3. Intelligent analysis and report generation module. This module is used to perform in-depth analysis on the bond target data through machine learning algorithms and trained data analysis models, generate analysis results of the bond target data, and generate a bond research report based on the analysis results and the target template.

[0065] The specific method is as follows: first, the bond target data is divided into training set, validation set and test set;

[0066] Training a pre-built data analysis model using the training set data, and adjusting parameters of the data analysis model;

[0067] Then, the validation set is used to evaluate the performance of the data analysis model. After the best data analysis model is selected, the best data analysis model is tested using the test set, and after the test passes, the best data analysis model is determined as the trained data analysis model;

[0068] The bond target data is input into the trained data analysis model to generate corresponding analysis results.

[0069] After adding the analysis results to the target template, you can get the corresponding bond research report.

[0070] 4. Report review and release module. This module is used to review the bond research report, such as format review or sensitive word review, etc.

[0071] Taking the sensitive word review as an example, a sensitive word database can be built in advance, and the bond research report can be compared with each word in the sensitive word database. When there is no matching word, it is determined that the review is passed.

[0072] After the review is passed, the bond research report will be published or shared in the format selected by the user, such as PDF, WORD, etc.

[0073] 5. The authority management and security module is used to determine several different levels of authority and set corresponding authority for the user according to the user's user information, so that when each user logs in, he or she can obtain corresponding functions through different authorities to protect the security of user data and the bond research report.

[0074] In this module, after the system determines the different levels of permissions, it is necessary to configure users for each permission. The user can be created in this system, or the system can be connected to the internal system of the enterprise to obtain the user information of the internal system of the enterprise. Then different permissions are set for each user based on the user information.

[0075] So far, completed Figure 1 System module description shown.

[0076] In the embodiment of the present application, after the system collects the initial bond data from the bond target data source, it pre-processes it, generates the bond target data matching the data analysis model, and then analyzes the bond target data through the pre-trained data analysis model, thereby automatically obtaining a bond research report, and after the bond research report is reviewed and approved, it is published and shared. The system realizes the automatic generation of bond reports, improves the accuracy and efficiency of information processing, and improves the quality of corporate bond reports.

[0077] In another embodiment, the above system further includes a timed task module;

[0078] The timed task and reminder module is used to set a timed task through a timer. When the collection time set by the timer is reached, the data integration and collection module collects data for processing to generate second bond target data, and then the intelligent analysis and report generation module generates a bond research report corresponding to the second bond target data;

[0079] Update the collection time on the timer, and when the updated collection time is reached, execute again the steps of collecting data, generating the corresponding bond research report, and sending the report completion notification.

[0080] By setting the collection time through a timer and updating the collection time regularly, it is possible to automatically generate a bond research report according to a fixed period.

[0081] In another embodiment, the timed task module further includes a reminder module;

[0082] The reminder module is used to monitor in real time whether the bond initial data of the bond target data source is updated. When an update is determined, the updated bond initial data is collected, and the updated bond initial data is analyzed, and risk warnings and response suggestions are determined according to the analysis results, and the risk warnings and response suggestions are sent to the target user;

[0083] This enables real-time monitoring and analysis of market changes, providing companies with timely risk warnings and response suggestions, and helping companies better control risks.

[0084] The reminder module is also used to send a report completion notification to the target user of the bond research report after the report generation module generates the bond research report.

[0085] In another embodiment, the above system further includes a field configuration module;

[0086] The field configuration module is used to provide the user with field adjustment options for the bond research report, allowing the user to add or delete fields in the bond research report according to the field adjustment options, wherein the field adjustment options include adding, modifying, moving and deleting.

[0087] Since different companies have different focuses, through this module, each corporate user can adjust the fields in the bond research report according to their own needs, making the generated bond research report more practical.

[0088] In another embodiment, the above system further includes a multi-person collaboration and editing module;

[0089] The multi-person collaboration and editing module is used to store the bond research report edited by several users through distributed caching technology.

[0090] This module uses distributed caching technology to improve access speed, reduce latency, maintain data consistency, and ensure data accuracy when multiple people collaborate.

[0091] like Figure 2 As shown, the present application also provides a method for automatically generating a bond management report, the method comprising:

[0092] S201, collecting initial bond data from a bond target data source, preprocessing the initial bond data, and generating bond target data, wherein the preprocessing includes data cleaning, data integration, and data conversion;

[0093] S202, displaying a template processing page to the user, displaying multiple report templates through the template processing page, and determining the template selected or customized by the user on the template processing page as a target template;

[0094] S203, performing in-depth analysis on the bond target data through a machine learning algorithm and a trained data analysis model, generating analysis results of the bond target data, and generating a bond research report based on the analysis results and the target template;

[0095] S204, reviewing the bond research report, and when the review is passed, publishing or sharing the bond research report in a format selected by the user.

[0096] In another embodiment, the method further comprises:

[0097] Setting a timed task through a timer, when the collection time set by the timer is reached, collecting data through the data integration and collection module to generate second bond target data, and then generating a bond research report corresponding to the second bond target data through the intelligent analysis and report generation module;

[0098] Update the collection time on the timer, and when the updated collection time is reached, execute again the steps of collecting data, generating the corresponding bond research report, and sending the report completion notification.

[0099] In another embodiment, the in-depth analysis of the bond target data by using a machine learning algorithm and a trained data analysis model to generate the analysis results of the bond target data includes:

[0100] Dividing the bond target data into a training set, a validation set, and a test set;

[0101] Training a pre-built data analysis model using the training set data, and adjusting parameters of the data analysis model;

[0102] Then, the validation set is used to evaluate the performance of the data analysis model. After the best data analysis model is selected, the best data analysis model is tested using the test set, and after the test passes, the best data analysis model is determined as the trained data analysis model;

[0103] The bond target data is input into the trained data analysis model to generate corresponding analysis results.

[0104] In another embodiment, the method further comprises:

[0105] Monitor in real time whether the initial bond data of the bond target data source is updated. When an update is determined, collect the updated initial bond data, analyze the updated initial bond data, determine risk warnings and response suggestions based on the analysis results, and send the risk warnings and response suggestions to the target user;

[0106] And after generating the bond research report, a report completion notification is sent to the target user of the bond research report.

[0107] The above-mentioned embodiment of the present invention provides a system for automatically generating a bond management report, and based on the system provides a method for automatically generating a bond management report. Through the above-mentioned system and method, the automatic generation of bond reports is realized, the accuracy and efficiency of information processing are improved, and the quality of corporate bond reports is improved.

[0108] This embodiment also discloses a computer device, such as Figure 3As shown, the computer device includes a processor and a memory, wherein the memory stores at least one instruction, and the at least one instruction is loaded and executed by the processor to implement any of the above-mentioned methods for automatically generating a bond management report.

[0109] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A bond management report automatic generation system, characterized in that: The system includes a data integration and acquisition module, a report template management module, an intelligent analysis and report generation module, a report review and release module, and a rights management and security module; The data integration and collection module is used to collect initial bond data from the bond target data source, pre-process the initial bond data, and generate bond target data, wherein the pre-processing includes data cleaning, data integration, and data conversion; The report template management module is used to provide a template processing page, display multiple report templates through the template processing page, and determine the template selected or customized by the user on the template processing page as the target template; The intelligent analysis and report generation module is used to perform in-depth analysis on the bond target data through a machine learning algorithm and a trained data analysis model, generate analysis results of the bond target data, and generate a bond research report based on the analysis results and the target template; The report review and release module is used to review the bond research report and, when the review is passed, release or share the bond research report in a format selected by the user; The permission management and security module is used to determine several different levels of permissions and set corresponding permissions for the user according to the user's user information, so that when each user logs in, he or she can obtain corresponding functions through different permissions to protect the security of user data and the bond research report.

2. The system according to claim 1, characterized in that The system also includes a timing task module; The timed task and reminder module is used to set a timed task through a timer. When the collection time set by the timer is reached, the data integration and collection module collects data for processing to generate second bond target data, and then the intelligent analysis and report generation module generates a bond research report corresponding to the second bond target data; Update the collection time on the timer, and when the updated collection time is reached, execute again the steps of collecting data, generating the corresponding bond research report, and sending the report completion notification.

3. The system according to claim 1, characterized in that The in-depth analysis of the bond target data by using the machine learning algorithm and the trained data analysis model to generate the analysis results of the bond target data includes: Dividing the bond target data into a training set, a validation set, and a test set; Training a pre-built data analysis model using the training set data, and adjusting parameters of the data analysis model; Then, the validation set is used to evaluate the performance of the data analysis model. After the best data analysis model is selected, the best data analysis model is tested using the test set, and after the test passes, the best data analysis model is determined as the trained data analysis model; The bond target data is input into the trained data analysis model to generate corresponding analysis results.

4. The system according to claim 1, characterized in that The system also includes a field configuration module; The field configuration module is used to provide the user with field adjustment options for the bond research report, allowing the user to add or delete fields in the bond research report according to the field adjustment options, wherein the field adjustment options include adding, modifying, moving and deleting.

5. The system according to claim 1, characterized in that The system also includes a multi-person collaboration and editing module; The multi-person collaboration and editing module is used to store the bond research report edited by several users through distributed caching technology.

6. The system according to claim 2, characterized in that The timing task module also includes a reminder module; The reminder module is used to monitor in real time whether the bond initial data of the bond target data source is updated. When an update is determined, the updated bond initial data is collected, and the updated bond initial data is analyzed, and risk warnings and response suggestions are determined according to the analysis results, and the risk warnings and response suggestions are sent to the target user; The reminder module is also used to send a report completion notification to the target user of the bond research report after the report generation module generates the bond research report.

7. A method for automatically generating a bond management report, characterized in that: The method comprises: Collecting initial bond data from a bond target data source, preprocessing the initial bond data, and generating bond target data, wherein the preprocessing includes data cleaning, data integration, and data conversion; Displaying a template processing page to the user, displaying multiple report templates through the template processing page, and determining the template selected or customized by the user on the template processing page as the target template; Conducting in-depth analysis of the bond target data through machine learning algorithms and trained data analysis models, generating analysis results of the bond target data, and generating a bond research report based on the analysis results and the target template; The bond research report is reviewed, and when the review is passed, the bond research report is published or shared in a format selected by the user.

8. The method according to claim 7, characterized in that The method further comprises: A timer is used to set a timed task. When the collection time set by the timer is reached, the data integration and collection module is used to collect data for processing to generate second bond target data, and then the intelligent analysis and report generation module is used to generate a bond research report corresponding to the second bond target data; Update the collection time on the timer, and when the updated collection time is reached, execute again the steps of collecting data, generating the corresponding bond research report, and sending the report completion notification.

9. The method according to claim 7, characterized in that: The in-depth analysis of the bond target data by using the machine learning algorithm and the trained data analysis model to generate the analysis results of the bond target data includes: Dividing the bond target data into a training set, a validation set, and a test set; Training a pre-built data analysis model using the training set data, and adjusting parameters of the data analysis model; Then, the validation set is used to evaluate the performance of the data analysis model. After the best data analysis model is selected, the best data analysis model is tested using the test set, and after the test passes, the best data analysis model is determined as the trained data analysis model; The bond target data is input into the trained data analysis model to generate corresponding analysis results.

10. The method according to claim 7, characterized in that The method further comprises: Monitor in real time whether the initial bond data of the bond target data source is updated. When an update is determined, collect the updated initial bond data, analyze the updated initial bond data, determine risk warnings and response suggestions based on the analysis results, and send the risk warnings and response suggestions to the target user; And after generating the bond research report, a report completion notification is sent to the target user of the bond research report.

Images