Intelligent invoice state monitoring and exception handling method, system, medium and equipment

Abstract

The invention provides an intelligent invoice state monitoring and exception handling method and system, a medium and equipment, and the method comprises the steps: a docking and collection step: carrying out the docking of a development interface and an enterprise system, and collecting invoice information; a cleaning and storing step: processing the invoice information and storing the invoice information in a database; a rule setting step: setting a monitoring rule; a checking processing step: comparing the invoice information with the monitoring rule to obtain an identification result; a monitoring notification step: on the basis of multi-dimensional monitoring, when an exception is found, notifying relevant personnel of exception condition information; an intelligent processing step: after the abnormal condition information is received, automatically executing corresponding processing measures according to the decision tree model; and a report analysis step: obtaining an abnormal trend by adopting a big data analysis tool Apache Spark. By constructing the intelligent invoice state monitoring system, automatic data acquisition, intelligent state monitoring and exception handling are realized, the monitoring efficiency is improved, manual intervention is reduced, and reliable support is provided for factoring business.

Description

Technical Field

[0001] The present invention relates to the technical field of electronic invoice tax analysis, and in particular to an intelligent invoice status monitoring and exception handling method, system, medium and equipment. Background Art

[0002] In today's business environment, factoring business, as an important financial service, plays a key role in promoting corporate capital flow and reducing risks. In factoring business, monitoring of invoice status is crucial, which is directly related to the smooth progress of business and effective control of risks.

[0003] At present, there are many problems in the traditional invoice status monitoring process. First, a large amount of manual intervention and inspection is the norm. Staff need to manually collect invoice information from various data sources, including internal enterprise systems and other factoring, insurance and other systems. This process is not only time-consuming and labor-intensive, but also prone to human errors. At the same time, the availability of manual invoice status inspection is inefficient and difficult to meet the needs of the rapid development of modern business.

[0004] Secondly, the existing monitoring methods lack flexibility. Different users often have different needs in factoring business. However, the current monitoring system is difficult to flexibly adjust according to the specific needs of users and cannot provide personalized monitoring services.

[0005] In addition, traditional monitoring methods are also insufficient in terms of exception handling. When an invoice status is abnormal, it is often not possible to detect and notify relevant personnel in a timely manner, resulting in delayed problem handling and increased business risks. Moreover, in the process of exception handling, there is a lack of intelligent means, and most of them rely on manual judgment and processing, which is not only inefficient, but may also lead to inaccurate processing results due to human factors.

[0006] With the continuous expansion of the scale of business and the increasing complexity of the business environment, the traditional invoice status monitoring method can no longer meet the actual needs. The prior art patent CN202310857086.9 discloses an invoice monitoring processing method, device, computer equipment and storage medium, which includes: updating the monitoring rules in the channel monitoring rule table according to the monitoring rules in the monitoring list; updating the monitoring rules in the monitoring table according to the monitoring rules in the monitoring list; receiving the monitoring return code corresponding to each invoice information sent by the third-party agency, and entering at least one monitoring return code into the monitoring table; sending the monitoring return code in the monitoring table to the third-party agency, receiving the invoice status sent by the third-party agency, and generating risk information according to the invoice status; obtaining the invoice information corresponding to the monitoring return code from the monitoring table, obtaining the terminal number corresponding to the invoice information from the channel monitoring rule table, and sending the risk information to the channel end corresponding to the channel number. The patent focuses on the management of the monitoring list, the updating of monitoring rules and the generation of risk information. The structure is relatively linear, emphasizing the interaction with third-party agencies, lacking a detailed description of data cleaning and storage, intelligent processing after monitoring, and big data analysis.

[0007] To sum up, enterprises urgently need a more efficient, accurate and flexible intelligent invoice status monitoring and exception handling method and system. Summary of the invention

[0008] In view of the defects in the prior art, the purpose of the present invention is to provide an intelligent invoice status monitoring and exception handling method, system, medium and equipment.

[0009] According to the present invention, an intelligent invoice status monitoring and exception handling method is provided, comprising the following steps:

[0010] Connect with the collection steps, develop interfaces to connect with the enterprise system, and collect invoice information;

[0011] Cleaning and storing step, processing the invoice information, and storing the processed invoice information in the database;

[0012] Rule setting step: set monitoring rules according to business needs;

[0013] Check the processing steps, monitor the invoice status in real time, compare the invoice information with the monitoring rules, and obtain the identification results;

[0014] Monitoring and notification steps: Based on multi-dimensional monitoring, when an abnormality is found, the abnormal situation information will be notified to relevant personnel;

[0015] Intelligent processing steps, after receiving abnormal situation information, automatically execute corresponding processing measures according to the decision tree model;

[0016] In the analysis and reporting step, the big data analysis tool Apache Spark is used to perform real-time analysis on the recognition results and abnormal situation information to obtain abnormal trends.

[0017] Preferably, in the docking and collection step, a RESTful API interface is developed to connect with the data of the enterprise system, and during the data transmission process, the invoice information is transmitted in JSON format.

[0018] Preferably, in the cleaning and storage step, the collected invoice information is cleaned to remove duplicate, erroneous or incomplete invoice information, and the cleaned invoice information is stored in a MySQL database.

[0019] Preferably, in the rule setting step, the monitoring rules include: invoice issuance time, amount range, status change and post-trigger warning related rules.

[0020] Preferably, the checking and processing step extracts the invoice information from the database according to the set timing rules, compares the invoice information with the monitoring rules through an intelligent algorithm, and obtains an identification result, which includes availability and validity.

[0021] Preferably, in the monitoring notification step, the monitoring rules are read from the database, and then the invoice amount, invoice status, and transaction frequency are obtained from the database to determine whether the invoice data complies with the rules. If an abnormality is found, the abnormal situation information is notified to relevant personnel via email, SMS, or APP push.

[0022] Preferably, in the intelligent processing step, corresponding processing measures are automatically executed according to the received abnormal situation information and the decision tree model. The processing measures include: suspending financing, initiating an investigation, reducing the financing amount, and performing manual intervention or adjustment if a situation that the system cannot automatically handle is encountered.

[0023] The present invention also provides an intelligent invoice status monitoring and exception handling system, comprising:

[0024] Docking collection module: develop an interface to connect with the enterprise system to collect invoice information;

[0025] Cleaning storage module: processes the invoice information and stores the processed invoice information in the database;

[0026] Rule setting module: set monitoring rules according to business needs;

[0027] Verification and processing module: monitor the invoice status in real time, compare the invoice information with the monitoring rules, and obtain the identification results;

[0028] Monitoring and notification module: Based on multi-dimensional monitoring, when an abnormality is found, the abnormal situation information will be notified to relevant personnel;

[0029] Intelligent processing module: After receiving abnormal situation information, it automatically executes corresponding processing measures according to the decision tree model;

[0030] Analysis and reporting module: Using the big data analysis tool Apache Spark, the recognition results and abnormal situation information are analyzed in real time to obtain abnormal trends.

[0031] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the above-mentioned intelligent invoice status monitoring and exception handling method.

[0032] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, the steps of the above-mentioned intelligent invoice status monitoring and exception handling method are implemented.

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] The present invention realizes real-time monitoring and processing of invoice status through intelligent technology, and it includes a docking acquisition module, a cleaning storage module, a rule setting module, a verification processing module, a monitoring notification module, an intelligent processing module and an analysis report module. Through the collaborative work of these modules, the present invention can automatically obtain invoice data from different data sources, clean and store them, set flexible monitoring rules according to user needs, monitor the invoice status in real time, discover abnormalities in time and notify relevant personnel, and can also handle abnormalities through intelligent means or manual intervention, and provide data analysis reports for business decisions, improve monitoring efficiency, reduce manual intervention, and provide reliable support for factoring business. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0036] Figure 1 This is a flow chart of an intelligent invoice status monitoring and exception handling method in an embodiment of the present invention;

[0037] Figure 2 The following is an architecture diagram of an intelligent invoice status monitoring and exception handling system in an embodiment of the present invention. DETAILED DESCRIPTION

[0038] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0039] The present invention realizes automatic data collection, intelligent status monitoring and exception handling by constructing an intelligent invoice status monitoring system, which significantly improves monitoring efficiency, reduces manual intervention and provides reliable support for factoring business.

[0040] Embodiment 1:

[0041] Figure 1 The present invention is a flowchart of an intelligent invoice status monitoring and exception handling method in an embodiment of the present invention.

[0042] like Figure 1 As shown, this embodiment provides an intelligent invoice status monitoring and exception handling method, including the following steps:

[0043] Connect with the collection steps, develop an interface to connect with the enterprise system, and collect invoice information.

[0044] Specifically, by developing a RESTful API interface, data is connected to the enterprise system, and invoice information is transmitted in JSON format during data transmission.

[0045] Enterprise systems include factoring platforms of different banks, enterprise resource planning systems (ERP), financial systems and other factoring, insurance and other related systems.

[0046] Cleaning and storing step, processing the invoice information, and storing the processed invoice information in the database;

[0047] Specifically, the collected invoice information is cleaned to remove duplicate, erroneous or incomplete invoice information, and the cleaned invoice information is stored in a MySQL database.

[0048] Rule setting step: Set monitoring rules according to business needs.

[0049] Specifically, the monitoring rules include: invoice issuance time, amount range, status change and post-trigger warning related rules.

[0050] Check the processing steps, monitor the invoice status in real time, compare the invoice information with the monitoring rules, and obtain the identification results.

[0051] Specifically, according to the set timing rules, invoice information is extracted from the database, and the invoice information is compared with the monitoring rules through an intelligent algorithm to obtain a recognition result, which includes availability and effectiveness.

[0052] More specifically, the intelligent algorithm includes: extracting key features and analyzing them using machine learning models, evaluating availability and effectiveness according to monitoring rules, assigning feature weights, and finally marking the invoice as "available", "invalid", "abnormal", and recording the reasons.

[0053] The monitoring and notification step is based on multi-dimensional monitoring. When an abnormality is found, the abnormal situation information will be notified to the relevant personnel.

[0054] Specifically, the monitoring rules are read from the database, and then the invoice amount, invoice status, and transaction frequency are obtained from the database to determine whether the invoice data complies with the rules. If an abnormality is found, the abnormal situation information is notified to relevant personnel via email, SMS, or APP push.

[0055] Intelligent processing steps, after receiving abnormal situation information, automatically execute corresponding processing measures according to the decision tree model.

[0056] Specifically, according to the received abnormal situation information and decision tree model, corresponding processing measures are automatically executed, including: suspending financing, initiating investigation, reducing the financing amount, and if the system cannot handle the situation automatically, manual intervention or adjustment will be carried out.

[0057] Specifically, automatically executing corresponding processing measures includes: identifying abnormal features, such as invoice amount exceeding the set range, invoice status being "invalid" or "abnormal", abnormal transaction frequency, etc. The identified abnormal features are input into the decision tree model. The model judges layer by layer according to the preset rules and conditions, determines the processing path for each abnormal situation, and finally outputs the corresponding processing measures.

[0058] In the analysis and reporting step, the big data analysis tool Apache Spark is used to analyze the recognition results and abnormal situation information in real time to obtain the abnormal trends of each project or enterprise.

[0059] Embodiment 2:

[0060] Figure 2 The following is an architecture diagram of an intelligent invoice status monitoring and exception handling system in an embodiment of the present invention.

[0061] like Figure 2 As shown, this embodiment provides an intelligent invoice status monitoring and exception handling system, including:

[0062] Docking collection module: develop an interface to connect with the enterprise system to collect invoice information;

[0063] Cleaning storage module: processes the invoice information and stores the processed invoice information in the database;

[0064] Rule setting module: set monitoring rules according to business needs;

[0065] Verification and processing module: monitor the invoice status in real time, compare the invoice information with the monitoring rules, and obtain the identification results;

[0066] Monitoring and notification module: Based on multi-dimensional monitoring, when an abnormality is found, the abnormal situation information will be notified to relevant personnel;

[0067] Intelligent processing module: After receiving abnormal situation information, it automatically executes corresponding processing measures according to the decision tree model;

[0068] Analysis and reporting module: Using the big data analysis tool Apache Spark, the recognition results and abnormal situation information are analyzed in real time to obtain abnormal trends.

[0069] Embodiment 3:

[0070] This embodiment provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the steps of the above-mentioned intelligent invoice status monitoring and exception handling method are implemented.

[0071] Embodiment 4:

[0072] This embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, the steps of the above-mentioned intelligent invoice status monitoring and exception handling method are implemented.

[0073] Those skilled in the art know that, in addition to realizing the system and its various devices, modules, and units provided by the present invention in a purely computer-readable program code, it is entirely possible to realize the same functions in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a hardware component, and the devices, modules, and units included therein for realizing various functions can also be regarded as structures within the hardware component; the devices, modules, and units for realizing various functions can also be regarded as both software modules for realizing the method and structures within the hardware component.

[0074] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. An intelligent invoice status monitoring and exception handling method, characterized in that: The steps include: Connect with the collection steps, develop interfaces to connect with enterprise systems, and collect invoice information; A cleaning and storage step, processing the invoice information and storing the processed invoice information in a database; Rule setting step: set monitoring rules according to business needs; Check the processing steps, monitor the invoice status in real time, compare the invoice information with the monitoring rules, and obtain the identification results; Monitoring and notification steps: Based on multi-dimensional monitoring, when an abnormality is found, the abnormal situation information will be notified to relevant personnel; An intelligent processing step, after receiving the abnormal situation information, automatically executing corresponding processing measures according to the decision tree model; In the analysis and reporting step, the big data analysis tool Apache Spark is used to perform real-time analysis on the recognition results and the abnormal situation information to obtain abnormal trends.

2. According to claim 1, the intelligent invoice status monitoring and exception handling method is characterized in that: In the docking and collection step, a RESTful API interface is developed to connect with the data of the enterprise system. During the data transmission process, the invoice information is transmitted in JSON format.

3. According to claim 1, the intelligent invoice status monitoring and exception handling method is characterized in that: In the cleaning and storage step, the collected invoice information is cleaned to remove duplicate, erroneous or incomplete invoice information, and the cleaned invoice information is stored in the MySQL database.

4. According to claim 1, the intelligent invoice status monitoring and exception handling method is characterized in that: In the rule setting step, the monitoring rules include: invoice issuance time, amount range, status change and post-trigger warning related rules.

5. According to claim 1, the intelligent invoice status monitoring and exception handling method is characterized in that: The verification processing step extracts invoice information from the database according to the set timing rules, compares the invoice information with the monitoring rules through an intelligent algorithm, and obtains an identification result, which includes availability and validity.

6. The intelligent invoice status monitoring and exception handling method according to claim 1 is characterized in that: In the monitoring notification step, the monitoring rules are read from the database, and then the invoice amount, invoice status, and transaction frequency are obtained from the database to determine whether the invoice data complies with the rules. If an abnormality is found, the abnormal situation information is notified to relevant personnel via email, SMS, or APP push.

7. The intelligent invoice status monitoring and exception handling method according to claim 1 is characterized in that: In the intelligent processing step, corresponding processing measures are automatically executed according to the received abnormal situation information and the decision tree model. The processing measures include: suspending financing, initiating investigation, reducing the financing amount, and performing manual intervention or adjustment if a situation that the system cannot automatically handle is encountered.

8. An intelligent invoice status monitoring and exception handling system, characterized in that: include: Docking collection module: develop an interface to connect with the enterprise system to collect invoice information; Cleaning storage module: processing the invoice information and storing the processed invoice information in a database; Rule setting module: set monitoring rules according to business needs; Verification and processing module: monitors the invoice status in real time, compares the invoice information with the monitoring rules, and obtains the identification result; Monitoring and notification module: Based on multi-dimensional monitoring, when an abnormality is found, the abnormal situation information will be notified to relevant personnel; Intelligent processing module: after receiving the abnormal situation information, automatically execute corresponding processing measures according to the decision tree model; Analysis and reporting module: Apache Spark, a big data analysis tool, is used to perform real-time analysis on the recognition results and the abnormal situation information to obtain abnormal trends.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of an intelligent invoice status monitoring and exception handling method described in any one of claims 1 to 7 are implemented.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the computer program is executed by a processor, the steps of an intelligent invoice status monitoring and exception handling method described in any one of claims 1 to 7 are implemented.

Images