A real-time monitoring method and system for bank funds flow based on enterprises

Abstract

The present application relates to the field of financial information technology, in particular to a method and system for real-time monitoring of bank fund flows based on an enterprise, comprising the following steps: upon receiving a text message sent by a bank, verifying whether the text message conforms to a preset format; when the format verification passes, extracting the arrangement order of key information from the text message; based on the arrangement order, matching the corresponding parsing template to extract key information; performing logical judgment on the key information: encrypting the judged key information based on an encryption protocol, and storing it in a bank transaction database to generate a unique transaction number; synchronizing the encrypted key information to the enterprise ERP system and updating it to a transaction record in a pending verification state; triggering a hierarchical push service to send a notification message to the corresponding user end; recording a full-process operation log and generating a feedback report. The present application has the effect of quickly and accurately extracting real-time fund flow information from a large amount of data.

Description

Technical Field

[0001] The present application relates to the field of financial information technology, and in particular to a method and system for real-time monitoring of bank fund flows based on an enterprise. Background Art

[0002] Currently, businesses generally use SMS alerts provided by banks in conjunction with ERP systems to monitor bank cash flows. This method relies on receiving SMS messages from banks notifying them of fund changes and then uploading this information to the ERP system, enabling monitoring of fund flows. Some businesses also utilize real-time communication tools such as DingTalk or WeChat Work to provide instant notifications of fund changes.

[0003] Although this method improves the real-time performance of fund monitoring to a certain extent, it still has some shortcomings. The shortcoming is that it cannot quickly and accurately extract real-time fund flow information from a large amount of data. Therefore, it needs to be improved. Summary of the Invention

[0004] In order to solve the above technical problems, the present application provides a method and system for real-time monitoring of bank funds flow based on an enterprise.

[0005] The first object of the invention of this application is achieved through the following technical solutions.

[0006] A method for real-time monitoring of bank funds flow based on an enterprise comprises the following steps:

[0007] When receiving a text message from the bank, verify whether the text message conforms to the preset format;

[0008] When the format verification passes, extracting the arrangement order of key information from the SMS;

[0009] Based on the arrangement order, matching the corresponding parsing template to extract key information;

[0010] Perform logical judgment on the key information:

[0011] The judged key information is encrypted based on the encryption protocol and stored in the bank's transaction database to generate a unique transaction number;

[0012] Synchronize the encrypted key information to the enterprise ERP system and update it as a flow record in a status to be verified;

[0013] Based on the amount in the transaction record and the enterprise role permission rules, the hierarchical push service is triggered and the notification message is sent to the corresponding user end;

[0014] Record the entire operation log and generate a feedback report, which includes the operation time, operation content, and operator identity information.

[0015] In a preferred embodiment, when receiving a text message sent by the bank, the step of verifying whether the text message conforms to a preset format includes the following steps:

[0016] Based on the dynamic regular expression library, match whether the SMS header contains the bank identifier;

[0017] Based on the block parsing algorithm, determine whether the text message contains complete structured fields, including transaction date, transaction object, and transaction amount;

[0018] When the SMS header does not include a bank identifier or the SMS body does not include a complete structured field, storing the SMS and marking it as an "abnormal" state;

[0019] Based on the "abnormal" status SMS, match the failure cause and corresponding handling suggestions from the preset failure cause model;

[0020] The reasons for failure include format error and missing content;

[0021] The corresponding processing suggestions include the bank resending the SMS in the correct format and contacting the transaction party to supplement the missing information;

[0022] Generate a failure cause report and send it to relevant personnel. The failure cause report includes the failure cause and handling suggestions.

[0023] In a preferred embodiment, when the format verification is passed, the step of extracting the arrangement order of key information from the text message includes the following steps:

[0024] Based on different bank identifiers, matching corresponding preset rules;

[0025] Based on natural language processing models and preset rules, it identifies the order of key information in text messages.

[0026] The key information includes amount information, time information, and transaction party information.

[0027] In a preferred embodiment, the step of extracting key information by matching the corresponding parsing template based on the arrangement order includes the following steps:

[0028] Based on the arrangement order, matching the corresponding parsing template, and performing structured parsing on the text message;

[0029] When a combination of numbers and currency units is parsed, the amount information is extracted based on the parsing template positioning;

[0030] When the format of the date and time is parsed, the time information is extracted based on the parsing template positioning;

[0031] When the preset transaction party name and the preset transaction party account number are parsed, the transaction party information is extracted based on the positioning of the parsing template.

[0032] In a preferred embodiment, the step of performing logical judgment on the key information includes the steps of:

[0033] Compare the extracted amount information with pre-set risk thresholds at different levels;

[0034] Based on the matching result, determine whether the amount information is greater than a preset threshold. If the amount information is greater than the first preset threshold, mark it as a high-risk transaction;

[0035] Based on time series analysis, repeated transaction behavior is identified. When the transaction frequency is greater than the second preset threshold, repeated transaction behavior occurs:

[0036] When a transaction is marked as high-risk and there are repeated transactions, the transaction will be marked as abnormal and the abnormality handling process will be initiated;

[0037] The exception handling process includes manual review, contacting relevant parties for confirmation, and taking preset risk control measures.

[0038] In a preferred embodiment, the step of triggering the hierarchical push service based on the amount value in the transaction record and the enterprise role authority rules to send the notification message to the corresponding user terminal includes the following steps:

[0039] Based on the preset amount threshold, transactions are divided into multiple levels, and different levels are associated with different message receiving roles;

[0040] When push fails, retries are performed based on the exponential backoff algorithm and are transferred to the dead letter queue after the maximum number of retries is reached.

[0041] The second object of the present invention is achieved through the following technical solutions:

[0042] The first module: when receiving a text message sent by the bank, verify whether the text message conforms to the preset format;

[0043] The second module: when the format verification is passed, extract the arrangement order of key information from the text message;

[0044] The third module: based on the arrangement order, matching the corresponding parsing template and extracting key information;

[0045] Module 4: Perform logical judgment on the key information:

[0046] The fifth module: encrypts the key information after judgment based on the encryption protocol, stores it in the bank's transaction database, and generates a unique transaction number;

[0047] Module 6: Synchronize the encrypted key information to the enterprise ERP system and update it as a flow record in a state to be verified;

[0048] Module 7: Based on the amount in the transaction record and the enterprise role permission rules, trigger the hierarchical push service and send the notification message to the corresponding user end;

[0049] Module 8: Record the entire process operation log and generate a feedback report, which includes the operation time, operation content, and operator identity information.

[0050] The third objective of this application is achieved through the following technical solutions:

[0051] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the above-mentioned method for real-time monitoring of bank funds flow based on an enterprise are implemented.

[0052] The fourth objective of this application is achieved through the following technical solutions:

[0053] A computer-readable storage medium stores a computer program, wherein the computer program, when executed by a processor, implements the steps of the above-mentioned method for real-time monitoring of bank funds flow based on an enterprise.

[0054] In summary, this application includes at least one of the following beneficial technical effects:

[0055] Utilizing advanced technology, the system receives, intelligently analyzes, rigorously evaluates, securely stores, and efficiently pushes SMS messages sent by banks in real time, enabling comprehensive and accurate monitoring of capital flows. Specifically, the system first verifies the format of incoming SMS messages to ensure data validity. Once verified, it automatically extracts key information from the SMS using natural language processing technology and matches the information to corresponding parsing templates based on its order, ensuring accurate information extraction. The system then performs logical analysis on the extracted key information to ensure data accuracy and rationality. To ensure data security, the system encrypts the identified key information using an encryption protocol and stores it in the bank's transaction database, generating a unique transaction number for data traceability. The encrypted information is synchronized with the enterprise ERP system and updated as a transaction record in a pending verification state, facilitating subsequent verification and processing. Furthermore, the system intelligently triggers a tiered push service based on the amount in the transaction record and enterprise role permissions, delivering notifications precisely to the relevant users and ensuring that critical information reaches the right personnel in a timely manner. Finally, the system logs the entire operation process and generates a detailed feedback report, including operation time, content, and operator identity information, providing strong support for subsequent audits and problem tracking. Through this series of efficient and intelligent operations, this embodiment achieves real-time monitoring of corporate bank fund flows, effectively improving the efficiency and accuracy of fund management while ensuring data security and traceability. This approach not only simplifies the fund monitoring process but also enhances the company's risk prevention and control capabilities, providing strong support for its stable operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 This is a flowchart of an implementation of an embodiment of a method for real-time monitoring of bank funds flow based on an enterprise in the present application;

[0057] Figure 2 This is a flowchart of an implementation of step S10 in an embodiment of a method for real-time monitoring of bank funds flow based on an enterprise of the present application;

[0058] Figure 3 This is a flowchart for implementing step S20 in an embodiment of a method for real-time monitoring of bank funds flow for an enterprise according to the present application;

[0059] Figure 4 This is a flowchart of an implementation of step S30 in an embodiment of a method for real-time monitoring of bank funds flow based on an enterprise of the present application;

[0060] Figure 5 This is a flowchart of an implementation of step S40 in an embodiment of a method for real-time monitoring of bank funds flow based on an enterprise of the present application;

[0061] Figure 6 This is a flowchart of an implementation of step S70 in an embodiment of a method for real-time monitoring of bank funds flow based on an enterprise of the present application;

[0062] Figure 7 This is a principle block diagram of a computer device of the present application. DETAILED DESCRIPTION

[0063] The following is combined with Figure 1-7 This application is described in further detail.

[0064] In one embodiment, if Figure 1 As shown, the present application discloses a method for real-time monitoring of bank funds flow based on an enterprise, which specifically includes the following steps:

[0065] S10: When receiving a text message sent by the bank, verify whether the text message conforms to a preset format;

[0066] S20: When the format verification passes, extract the arrangement order of key information from the text message;

[0067] S30: Based on the arrangement order, matching the corresponding parsing template to extract key information;

[0068] S40: Perform logical judgment on the key information:

[0069] S50: Encrypt the determined key information based on the encryption protocol and store it in the bank's transaction database to generate a unique transaction number;

[0070] S60: Synchronize the encrypted key information to the enterprise ERP system and update it as a flow record in a pending verification state;

[0071] S70: Based on the amount in the transaction record and the enterprise role authority rules, trigger the hierarchical push service and send the notification message to the corresponding user terminal;

[0072] S80: Record the entire process operation log and generate a feedback report, which includes the operation time, operation content, and operator identity information.

[0073] In this embodiment, advanced technologies are utilized to receive, intelligently analyze, rigorously analyze, securely store, and efficiently push SMS messages sent by banks in real time, thereby achieving comprehensive and accurate monitoring of capital flows. Specifically, the system first verifies the format of received SMS messages to ensure data validity. Once verified, the system automatically extracts key information from the SMS using natural language processing technology and matches the information to corresponding parsing templates based on its order, ensuring accurate information extraction. The system then performs logical analysis on the extracted key information to ensure data accuracy and rationality. To ensure data security, the system encrypts the identified key information using an encryption protocol and stores it in the bank's transaction database, generating a unique transaction number for data traceability. The encrypted information is synchronized with the enterprise ERP system and updated as a transaction record in a pending verification state, facilitating subsequent verification and processing. Furthermore, the system intelligently triggers a tiered push service based on the amount in the transaction record and enterprise role permission rules, accurately delivering notification messages to relevant users and ensuring that critical information is promptly communicated to the relevant personnel. Finally, the system logs the entire operation process and generates a detailed feedback report, including operation time, content, and operator identity information, providing strong support for subsequent audits and problem tracking. Through this series of efficient and intelligent operations, this embodiment achieves real-time monitoring of corporate bank fund flows, effectively improving the efficiency and accuracy of fund management while ensuring data security and traceability. This approach not only simplifies the fund monitoring process but also enhances the company's risk prevention and control capabilities, providing strong support for its stable operations.

[0074] Figure 2 , step S10, comprising the steps of:

[0075] S101: Based on the dynamic regular expression library, match whether the SMS header includes a bank identifier;

[0076] S102: Based on a block parsing algorithm, determine whether the text of the SMS message includes complete structured fields, where the complete structured fields include transaction date, transaction object, and transaction amount;

[0077] S103: When the SMS header does not include the bank identifier or the SMS body does not include a complete structured field, the SMS is stored and marked as an "abnormal" state;

[0078] S104: Based on the "abnormal" status SMS, match the failure cause and corresponding processing suggestions from the preset failure cause model;

[0079] S105: The failure reasons include format error and content missing;

[0080] S106: The corresponding processing suggestions include the bank resending the SMS in the correct format and contacting the transaction counterpart to supplement the missing information;

[0081] S107: Generate a failure cause report and send it to relevant personnel. The failure cause report includes the failure cause and handling suggestions.

[0082] In this embodiment, step S10 utilizes an advanced dynamic regular expression library and block parsing algorithm to ensure the accuracy and reliability of bank fund flow monitoring. First, the system uses the dynamic regular expression library to match SMS headers to identify bank identifiers, a critical step in verifying the legitimacy of the SMS source. Next, the block parsing algorithm performs a structural analysis of the SMS body, checking for complete structured fields such as the transaction date, transaction party, and transaction amount. This ensures that each SMS message contains the necessary information for subsequent processing. If the SMS header lacks a bank identifier or the body is incomplete, the system stores these messages and marks them as "abnormal" to distinguish between normal and abnormal data. For messages in this "abnormal" state, the system matches the specific failure reason, such as formatting errors or missing content, to a pre-defined failure cause model and provides appropriate action suggestions, such as requiring the bank to resend the message in the correct format or contacting the transaction party to provide the missing information. Furthermore, the system generates a detailed failure report, including the failure reason and action suggestions, and sends it to the relevant personnel for prompt corrective action. This mechanism not only improves the accuracy and efficiency of data processing but also enhances the system's self-correction capabilities and user-friendliness. Overall, the S10 process effectively ensures the accuracy and integrity of bank funds flow monitoring data through a series of intelligent and automated processes, providing a solid foundation for subsequent monitoring and analysis. Furthermore, by providing timely feedback and processing of abnormal data, it improves the overall reliability of the system and user satisfaction, providing strong technical support for corporate funds management.

[0083] Figure 3 , step S20, comprising the steps of:

[0084] S201: Matching corresponding preset rules based on different bank identifiers;

[0085] S202: Based on the natural language processing model and preset rules, identify the order of key information in the text message;

[0086] S203: The key information includes amount information, time information, and transaction party information.

[0087] In this embodiment, the natural language processing model's ability to understand the semantics and analyze the structure of text messages, combined with the guidance of preset rules for specific information formats, enables rapid positioning and accurate extraction of key information. Effectively, step S20 not only greatly improves the accuracy and efficiency of information extraction, but also significantly reduces manual intervention and operational errors, providing reliable and complete data support for subsequent fund flow monitoring and analysis. Overall, the implementation of step S20 makes the entire monitoring system more intelligent, automated, and efficient, providing strong technical support for enterprises to monitor bank fund flows in real time, and effectively improving their fund management capabilities and risk control levels.

[0088] Figure 4 , step S30, comprising the steps of:

[0089] S301: Based on the arrangement order, matching the corresponding parsing template, and performing structured parsing on the text message;

[0090] S302: When a combination of numbers and currency units is parsed, the amount information is extracted based on the parsing template positioning;

[0091] S303: When the date and time format is parsed, locate and extract the time information based on the parsing template;

[0092] S304: When the preset transaction party name and the preset transaction party account are parsed, the transaction party information is extracted based on the positioning of the parsing template.

[0093] In this embodiment, step S30 utilizes structured parsing templates and key information location technology to accurately extract and efficiently process key information from bank text messages. First, the system automatically matches the corresponding parsing templates based on the order of key information identified in step S20. These templates are pre-designed for various possible message formats within text messages, ensuring the accuracy and adaptability of structured parsing. During the parsing process, the system analyzes the text message content item by item using the parsing templates. Upon detecting a combination of numbers and currency units, the system locates and accurately extracts the amount information based on the templates. Similarly, upon identifying text that matches a date and time format, the system immediately locates and extracts the time information. For pre-set transaction party names and account numbers, the system can also quickly locate and extract relevant transaction party information using the templates. The principle behind this step is that, using the pre-set parsing templates as a guide, combined with the recognition of specific message formats, it achieves precise location and efficient extraction of key information from text messages. Effectively, step S30 not only significantly improves information extraction accuracy and processing efficiency, but also significantly reduces manual intervention and operational errors, providing solid and reliable data support for subsequent fund flow monitoring, analysis, and decision-making. Overall, the implementation of step S30 makes the entire monitoring system more intelligent, automated, and efficient, providing strong technical support for enterprises to monitor bank fund flows in real time, and effectively improving the company's fund management capabilities and risk control level.

[0094] Figure 5 , step S40, comprising the steps of:

[0095] S401: Compare the extracted amount information with preset risk thresholds of different levels;

[0096] S402: Based on the matching result, determine whether the amount information is greater than a preset threshold. If the amount information is greater than the first preset threshold, mark it as a high-risk transaction;

[0097] S403: Based on time series analysis, identify repeated transaction behavior. When the transaction frequency is greater than a second preset threshold, there is repeated transaction behavior:

[0098] S404: When a transaction is marked as high-risk and there are repeated transactions, the transaction is marked as abnormal and the abnormality handling process is initiated;

[0099] S405: The exception handling process includes manual review, contacting relevant parties for confirmation, and taking preset risk control measures.

[0100] In this embodiment, step S40 establishes a comprehensive risk monitoring and response mechanism designed to achieve efficient risk control of banking transactions. First, the system compares the extracted amount information with preset risk thresholds of varying levels (S401), using pre-set risk assessment criteria to quickly screen out potentially risky transactions. Based on this, the system further determines whether the amount information exceeds a preset threshold (S402). Transactions exceeding the first preset threshold are marked as high-risk, providing a preliminary risk warning. To more comprehensively identify risks, the system also incorporates time series analysis technology (S403), monitoring transaction frequency to identify repeated transactions. When the transaction frequency exceeds the second preset threshold, the system identifies repeated transactions. This analysis effectively complements the limitations of a single amount threshold. If a transaction is both marked as high-risk and repeated (S404), the system marks it as an abnormal transaction and automatically initiates the abnormality handling process (S405). This process includes manual review, contact with relevant parties for confirmation, and the implementation of pre-set risk control measures, ensuring timely and accurate risk management. Overall, the S40 process significantly improves the accuracy and efficiency of risk monitoring through multi-level, multi-dimensional risk identification and control. This mechanism not only reduces false positives and missed reports, but also provides businesses with a more robust security framework, effectively enhancing their risk control capabilities and capital security management.

[0101] Figure 6 , step S70, comprising the steps of:

[0102] S701: Based on a preset amount threshold, the transaction is divided into multiple levels, and different levels are associated with different message receiving roles;

[0103] S702: When push fails, retry based on the exponential backoff algorithm, and transfer to the dead letter queue after reaching the maximum number of retries.

[0104] In this embodiment, step S70 designs an intelligent message push and processing mechanism. First, the system divides transactions into multiple levels based on preset monetary thresholds (S701), with each level corresponding to a specific message receiving role. This design ensures that transaction information can be accurately and efficiently pushed to the corresponding responsible person based on its importance and urgency, thereby improving the pertinence and efficiency of information processing. During the message push process, when the system faces network fluctuations or temporary failures, an exponential backoff algorithm is used for retry (S702). By gradually increasing the retry interval, this algorithm effectively avoids excessive consumption of system resources due to frequent retries, while also improving the success rate of message push. When the number of retries reaches the preset maximum value, the system transfers the failed message to a dead letter queue. This design ensures the integrity and traceability of the message, providing data support for subsequent troubleshooting and processing. Overall, step S70 achieves high efficiency, reliability, and flexibility in message push through transaction grading, intelligent retry, and a dead letter queue mechanism. This mechanism not only improves the system's ability to operate stably in complex environments, but also provides enterprises with more timely and accurate information notification services, effectively supporting transaction monitoring and decision-making needs.

[0105] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0106] In one embodiment, a real-time monitoring system for bank funds flow based on an enterprise is provided. This real-time monitoring system for bank funds flow based on an enterprise corresponds to the real-time monitoring method for bank funds flow based on an enterprise in the above embodiment. This real-time monitoring system for bank funds flow based on an enterprise includes:

[0107] The first module: when receiving a text message sent by the bank, verify whether the text message conforms to the preset format;

[0108] The second module: when the format verification is passed, extract the arrangement order of key information from the text message;

[0109] The third module: based on the arrangement order, matching the corresponding parsing template and extracting key information;

[0110] Module 4: Perform logical judgment on the key information:

[0111] The fifth module: encrypts the key information after judgment based on the encryption protocol, stores it in the bank's transaction database, and generates a unique transaction number;

[0112] Module 6: Synchronize the encrypted key information to the enterprise ERP system and update it as a flow record in a state to be verified;

[0113] Module 7: Based on the amount in the transaction record and the enterprise role permission rules, trigger the hierarchical push service and send the notification message to the corresponding user end;

[0114] Module 8: Record the entire process operation log and generate a feedback report, which includes the operation time, operation content, and operator identity information.

[0115] Optionally, also include:

[0116] The first matching module: Based on the dynamic regular expression library, matches whether the SMS header contains the bank identifier;

[0117] The first judgment module: Based on the block parsing algorithm, it is determined whether the text of the SMS message includes complete structured fields, including the transaction date, transaction object, and transaction amount;

[0118] A first marking module: when the SMS header does not include a bank identifier or the SMS body does not include a complete structured field, storing the SMS and marking it as an "abnormal" state;

[0119] The second matching module: based on the "abnormal" status SMS, matches the failure cause and corresponding processing suggestions from the preset failure cause model;

[0120] Failure reason module: The failure reasons include format error and content missing;

[0121] Processing suggestion module: The corresponding processing suggestions include the bank resending the SMS with the correct format and contacting the transaction party to supplement the missing information;

[0122] Sending module: Generates a failure cause report and sends it to relevant personnel. The failure cause report includes the failure cause and handling suggestions.

[0123] Optionally, also include:

[0124] The third matching module: matches the corresponding preset rules based on different bank identifiers;

[0125] The first recognition module: Based on the natural language processing model and preset rules, it identifies the order of key information in the text message;

[0126] The first module includes: the key information includes amount information, time information, and transaction party information.

[0127] Optionally, also include:

[0128] The fourth matching module: matches the corresponding parsing template based on the arrangement order and performs structured parsing on the text message;

[0129] The first extraction module: when parsing the combination of numbers and currency units, locates the amount based on the parsing template and extracts the amount information;

[0130] The second day extraction module: when the date and time format is parsed, the time information is extracted based on the parsing template location;

[0131] The third extraction module: when the preset transaction party name and the preset transaction party account are parsed, the transaction party information is extracted based on the parsing template positioning.

[0132] Optionally, also include:

[0133] Comparison module: compares the extracted amount information with the preset risk thresholds of different levels;

[0134] The second judgment module: based on the matching result, determines whether the amount information is greater than the preset threshold. If the amount information is greater than the first preset threshold, it is marked as a high-risk transaction;

[0135] The second identification module: Based on time series analysis, it identifies repeated transaction behaviors. When the transaction frequency is greater than the second preset threshold, there is repeated transaction behavior:

[0136] Second marking module: When a transaction is marked as high-risk and there is repeated transaction behavior, the transaction is marked as abnormal and the abnormality handling process is initiated;

[0137] Exception handling module: The exception handling process includes manual review, contacting relevant parties for confirmation, and taking preset risk control measures.

[0138] Optionally, also include:

[0139] Associated role module: Based on the preset amount threshold, transactions are divided into multiple levels, and different levels are associated with different message receiving roles;

[0140] Dump module: When push fails, retry is performed based on the exponential backoff algorithm, and the message is dumped to the dead letter queue after the maximum number of retries is reached.

[0141] The specific definition of a real-time enterprise-based bank funds flow monitoring system can be found in the definition of a real-time enterprise-based bank funds flow monitoring method described above and will not be further elaborated here. Each module in the aforementioned real-time enterprise-based bank funds flow monitoring system can be implemented in whole or in part through software, hardware, or a combination thereof. Each of these modules can be embedded in or independent of a processor in a computer device in hardware form, or stored in a computer device memory in software form, so that the processor can call and execute the corresponding operations of each module.

[0142] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 7 As shown. The computer device includes a processor, memory, a network interface, and a database connected via a system bus. 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 computer program in the non-volatile storage medium. The database of the computer device is used to store key information. The network interface of the computer device is used to communicate with an external terminal via a network connection. When executed by the processor, the computer program implements a method for real-time monitoring of bank funds flows based on an enterprise.

[0143] In one embodiment, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, a method for real-time monitoring of bank funds flow based on an enterprise is implemented.

[0144] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, a method for real-time monitoring of bank funds flow based on an enterprise is provided.

[0145] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. 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 memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0146] Those skilled in the art will clearly understand that for the sake of convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

Claims

1. A real-time monitoring method for bank funds flow based on an enterprise, characterized in that: Including steps: When receiving a text message from the bank, verify whether the text message conforms to the preset format; Based on the dynamic regular expression library, match whether the SMS header contains the bank identifier; Based on the block parsing algorithm, determine whether the text message contains complete structured fields, including transaction date, transaction object, and transaction amount; When the SMS header does not include a bank identifier or the SMS body does not include a complete structured field, the SMS is stored and marked as an "abnormal" state; Based on the "abnormal" status SMS, match the failure cause and corresponding handling suggestions from the preset failure cause model; The reasons for failure include format error and missing content; The corresponding processing suggestions include the bank resending the SMS in the correct format and contacting the transaction party to supplement the missing information; Generate a failure cause report and send it to relevant personnel. The failure cause report includes the failure cause and handling suggestions. When the format verification passes, extracting the arrangement order of key information from the SMS; Based on the arrangement order, matching the corresponding parsing template to extract key information; Performing logical judgment on the key information; The judged key information is encrypted based on the encryption protocol and stored in the bank's transaction database to generate a unique transaction number; Synchronize the encrypted key information to the enterprise ERP system and update it as a flow record in a status to be verified; Based on the amount in the transaction record and the enterprise role permission rules, the hierarchical push service is triggered and the notification message is sent to the corresponding user end; Record the entire operation log and generate a feedback report, which includes the operation time, operation content, and operator identity information.

2. A method for real-time monitoring of bank funds flow based on an enterprise according to claim 1, characterized in that: The step of extracting the arrangement order of key information from the text message when the format verification passes includes the following steps: Based on different bank identifiers, matching corresponding preset rules; Based on natural language processing models and preset rules, identify the order of key information in text messages; The key information includes amount information, time information, and transaction party information.

3. The method for real-time monitoring of bank funds flow based on an enterprise according to claim 1, characterized in that: The step of matching the corresponding parsing template based on the arrangement order and extracting key information includes the following steps: Based on the arrangement order, matching the corresponding parsing template, and performing structured parsing on the text message; When a combination of numbers and currency units is parsed, the amount information is extracted based on the parsing template positioning; When the format of the date and time is parsed, the time information is extracted based on the parsing template positioning; When the preset transaction party name and the preset transaction party account number are parsed, the transaction party information is extracted based on the positioning of the parsing template.

4. The method for real-time monitoring of bank funds flow based on an enterprise according to claim 1, characterized in that: The step of performing logical judgment on the key information includes the steps of: Compare the extracted amount information with pre-set risk thresholds at different levels; Based on the matching result, determine whether the amount information is greater than a preset threshold. If the amount information is greater than the first preset threshold, mark it as a high-risk transaction; Based on time series analysis, repeated transaction behavior is identified. When the transaction frequency is greater than a second preset threshold, repeated transaction behavior occurs; When a transaction is marked as high-risk and there are repeated transactions, the transaction will be marked as abnormal and the abnormality handling process will be initiated; The exception handling process includes manual review, contacting relevant parties for confirmation, and taking preset risk control measures.

5. The method for real-time monitoring of bank funds flow based on an enterprise according to claim 1, characterized in that: The step of triggering the hierarchical push service based on the amount value in the transaction record and the enterprise role authority rules and sending the notification message to the corresponding user terminal includes the following steps: Based on the preset amount threshold, transactions are divided into multiple levels, and different levels are associated with different message receiving roles; When push fails, retries are performed based on the exponential backoff algorithm and are transferred to the dead letter queue after the maximum number of retries is reached.

6. A real-time monitoring system for bank funds flow based on an enterprise, characterized in that: include: The first module: when receiving a text message sent by the bank, verify whether the text message conforms to the preset format; The first matching module: Based on the dynamic regular expression library, matches whether the SMS header contains the bank identifier; The first judgment module: Based on the block parsing algorithm, it is determined whether the text of the SMS message includes complete structured fields, including the transaction date, transaction object, and transaction amount; A first marking module: when the SMS header does not include a bank identifier or the SMS body does not include a complete structured field, storing the SMS and marking it as an "abnormal" state; The second matching module: based on the "abnormal" status SMS, matches the failure cause and corresponding processing suggestions from the preset failure cause model; Failure reason module: The failure reasons include format error and content missing; Processing suggestion module: The corresponding processing suggestions include the bank resending the SMS with the correct format and contacting the transaction party to supplement the missing information; Sending module: Generates a failure cause report and sends it to relevant personnel. The failure cause report includes the failure cause and handling suggestions; The second module: when the format verification is passed, extract the arrangement order of key information from the text message; The third module: based on the arrangement order, matching the corresponding parsing template and extracting key information; The fourth module: performing logical judgment on the key information; The fifth module: encrypts the key information after judgment based on the encryption protocol, stores it in the bank's transaction database, and generates a unique transaction number; Module 6: Synchronize the encrypted key information to the enterprise ERP system and update it as a flow record in a state to be verified; Module 7: Based on the amount in the transaction record and the enterprise role permission rules, trigger the hierarchical push service and send the notification message to the corresponding user end; Module 8: Record the entire process operation log and generate a feedback report, which includes the operation time, operation content, and operator identity information.

7. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the enterprise-based real-time monitoring method for bank funds flow are implemented as described in any one of claims 1 to 5.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for real-time monitoring of bank funds flow based on an enterprise as described in any one of claims 1 to 5 are implemented.

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