Multi-channel fund management system based on bank intranet one-stop payment

Abstract

The invention discloses a multi-channel fund management system based on bank intranet one-stop payment, and relates to the technical field of data analysis, a sub-virtual account after disconnection recovery is defined as a target sub-virtual account, transaction data in the disconnection period of the sub-virtual account is collected, payment channel distribution and the transaction volume are analyzed, and the payment efficiency is improved. Calculating a payment channel uniformity index and a transaction volume index; extracting historical transaction and reconciliation data between the target sub-virtual account and the total virtual account, and calculating a historical transaction reconciliation abnormal index; acquiring connection state data of the two accounts after disconnection recovery, and analyzing and calculating a connection instability index; comprehensively judging whether an account checking time window needs to be prolonged or not based on the four indexes; after the connection is recovered, the length of the reconciliation time window can be dynamically adjusted according to the actual transaction and the connection state, it is guaranteed that transaction abnormity is found and corrected in time, fund safety and service continuity are guaranteed, occupation of computing resources and cost expenditure are effectively reduced, and fund management efficiency and accuracy are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data analysis, and in particular to a multi-channel fund management system based on one-stop payment of internal bank accounts. Background Art

[0002] With the development of multi-store operations in chain restaurants, retail businesses, and other industries, these companies face challenges in fund management, such as diverse transaction channels, dispersed capital flows, and cumbersome cross-institutional settlements. To improve fund settlement efficiency and centralized financial management, some banks have launched one-stop payment platforms based on internal virtual accounts. These platforms establish a "master virtual account" for businesses and configure "sub-virtual accounts" for each of their stores or business units, enabling real-time fund transfers and unified payment settlements between internal bank accounts. Businesses can use this platform to conduct multi-channel fund collection, payment, accounting, and reconciliation operations, eliminating the need for interbank fund transfers. This significantly reduces settlement costs and the complexity of fund allocation, while improving payment security and financial controllability.

[0003] However, under this one-stop multi-channel fund management architecture, if there is a network interruption or system anomaly between the store and the platform, the transaction data will be temporarily stored in each sub-virtual account, and will be centrally reconciled and re-uploaded after the connection is restored. Fund reconciliation is a key link to ensure accounting accuracy and fund security. Fund reconciliation usually sets a "time window", that is, transaction data within a certain time range is checked and processed; however, how to reasonably determine the size of this time window is an urgent problem that needs to be solved in practical applications. If the time window is set too large, it may lead to a sudden increase in the amount of transaction data involved in the reconciliation, resulting in negative effects such as excessive consumption of computing resources and reduced processing efficiency; conversely, if the window is too small, transaction anomalies may not be discovered and corrected in time, affecting fund security and business continuity. Summary of the Invention

[0004] The purpose of the present invention is to solve the above-mentioned problems and provide a multi-channel fund management system based on one-stop payment of internal bank accounts.

[0005] In a first aspect of the present invention, a multi-channel fund management system based on one-stop payment for internal bank accounts is proposed, the system comprising: Transaction analysis module: This module records the restored sub-virtual account as the target sub-virtual account, collects the transaction data of the target sub-virtual account during the disconnection period, analyzes the payment channels and transaction volumes of the transaction data, and calculates the payment channel uniformity index and transaction volume index. Historical reconciliation module: extracts historical transaction and reconciliation data between the target sub-virtual account and the master virtual account, analyzes the historical transaction and reconciliation data, and calculates the historical transaction reconciliation anomaly index; Connection status module: obtains the connection status data of the target sub-virtual account and the main virtual account after the connection is restored, analyzes the connection status data, and calculates the connection instability index; Management module: Determine whether to increase the reconciliation time window between the target sub-virtual account and the master virtual account based on the payment channel uniformity index, transaction volume index, historical transaction reconciliation anomaly index, and connection instability index, and manage the transaction funds of the target sub-virtual account.

[0006] Optionally, the transaction analysis module includes: The first statistics module: during the period when the target sub-virtual account is disconnected, counts the number of transactions of each payment channel used by it; Transaction share module: For each payment channel, divide the number of transactions during the disconnection period by the total number of transactions across all channels to obtain the transaction share of the payment channel. Payment channel uniformity module: Calculates the overall payment channel uniformity index, which represents the actual degree of dispersion of actual payment channel usage during the period when the target sub-virtual account is disconnected. The calculation formula is: , where is the payment channel uniformity index.

[0007] Optionally, the transaction analysis module further includes: The second statistical module: divide the target sub-virtual account disconnection time period into Sub-time periods of equal length, and count the number of transactions in each sub-time period , where For the Number of transactions in each sub-time period; Transaction density change module: Calculates the absolute difference in the number of transactions between two adjacent sub-time periods and calculates the transaction density change rate; the calculation formula is: ,in, The value range is ; Calculation module: Calculate the range of density change rate Deviation from the median ; Volume Index Module: Based on the range of density change rate Deviation from the median Calculate the trading volume index. The formula is: Where, is the trading volume index.

[0008] Optionally, the historical reconciliation module includes: Sliding Window Module: Set a basic sliding window width and slide it by step size within the historical reconciliation transaction period to generate multiple sliding windows; Sequence module: counts the number of abnormal transactions in each sliding window to form a sliding window sequence; Abnormal Window Density Module: Sets an abnormality judgment threshold. When the number of abnormal transactions within a sliding window is not less than the judgment threshold, the corresponding sliding window is determined to be an abnormal window. The proportion of all abnormal windows in the sliding window set is calculated and defined as the abnormal window density. Window segment length module: detects continuous abnormal window segments in the sliding window sequence and counts the length of the longest continuous abnormal window segment; Historical transaction reconciliation anomaly index module: Multiply the anomaly window density by the length of the longest continuous anomaly window segment to obtain the historical transaction reconciliation anomaly index.

[0009] Optionally, the connection status module includes: Connection status value module: within the preset detection period after the target sub-virtual account is disconnected and restored, the connection status is sampled at fixed time intervals and recorded to form a connection status value sequence. Each sampled value in the connection status sequence represents whether the connection is normal or disconnected. When the connection is normal, the corresponding value of the connection status is 1, and when the connection is disconnected, the corresponding value of the connection status is 0. Recording module: traverses the connection state value sequence, merges consecutive sampling points with the same connection state value into several continuous state segments, and records the state type and the number of continuous sampling points of each state segment; Judgment module: sets a minimum stable duration threshold and determines that the state segment with the number of continuous sampling points less than the threshold is an unstable segment; Connection instability index module: counts the number of unstable segments and the total number of all status segments, and calculates the ratio of the number of unstable segments to the total number of status segments as the connection instability index.

[0010] Optionally, the management module includes: Evaluation module: Normalizes the payment channel average index, transaction volume index, historical transaction reconciliation anomaly index, and connection instability index, mapping them to a range of 0-1. Then, it performs a weighted summation of the normalized payment channel average index, transaction volume index, historical transaction reconciliation anomaly index, and connection instability index to obtain the window increase evaluation index. Comparison module: compares the window increase evaluation index with the preset window increase evaluation index threshold, and determines whether to increase the length of the reconciliation time window between the target sub-virtual account and the master virtual account based on the comparison result, and manages the transaction funds of the target sub-virtual account.

[0011] Optionally, the comparison module includes: The first comparison management module: If the window increase evaluation index is not less than the preset window increase evaluation index threshold, the target sub-virtual account and the master virtual account are disconnected for a period of time as the basic reconciliation time window, the length of the basic reconciliation time window is increased, and the target sub-virtual account and the master virtual account are reconciled according to the increased length of the reconciliation time window to manage transaction funds; Second comparison management module: If the window increase evaluation index is less than the preset window increase evaluation index threshold, there is no need to increase the length of the reconciliation time window between the target sub-virtual account and the total virtual account. The reconciliation between the target sub-virtual account and the total virtual account is directly performed according to the basic reconciliation time window to manage the transaction funds.

[0012] Beneficial effects of the present invention: The present invention proposes a multi-channel fund management system based on one-stop payment of internal bank accounts. The multi-channel fund management system records the sub-virtual account after the disconnection is restored as the target sub-virtual account, collects its transaction data during the disconnection period, analyzes the payment channel and transaction volume, and calculates the payment channel uniformity index and transaction volume index; extracts the historical transaction and reconciliation data between the target sub-virtual account and the total virtual account, and calculates the historical transaction reconciliation anomaly index; obtains the connection status data of the two accounts after the disconnection is restored, and analyzes and calculates the connection instability index; finally, based on these four indexes, it is comprehensively judged whether the reconciliation time window needs to be extended, thereby effectively managing and controlling the risks of the transaction funds of the target sub-virtual account; in this way, when the connection between the target sub-virtual account and the total virtual account is restored, the size of the reconciliation time window can be reasonably set according to the actual situation, thereby minimizing computing resources and reducing computing costs as much as possible while ensuring that transaction anomalies can be discovered and corrected in time and without affecting fund security and business continuity. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The present invention will be further described below with reference to the accompanying drawings.

[0014] Figure 1 The framework diagram of a multi-channel fund management system based on one-stop payment for internal bank accounts. DETAILED DESCRIPTION

[0015] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0016] The embodiment of the present invention provides a multi-channel fund management system based on one-stop payment of internal bank accounts. Figure 1 , Figure 1 This is a framework diagram of a multi-channel funds management system based on one-stop payment for internal bank accounts provided by an embodiment of the present invention. The system includes: Transaction analysis module: This module records the restored sub-virtual account as the target sub-virtual account, collects the transaction data of the target sub-virtual account during the disconnection period, analyzes the payment channels and transaction volumes of the transaction data, and calculates the payment channel uniformity index and transaction volume index. Historical reconciliation module: extracts historical transaction and reconciliation data between the target sub-virtual account and the master virtual account, analyzes the historical transaction and reconciliation data, and calculates the historical transaction reconciliation anomaly index; Connection status module: obtains the connection status data of the target sub-virtual account and the main virtual account after the connection is restored, analyzes the connection status data, and calculates the connection instability index; Management module: Determine whether to increase the reconciliation time window between the target sub-virtual account and the master virtual account based on the payment channel uniformity index, transaction volume index, historical transaction reconciliation anomaly index, and connection instability index, and manage the transaction funds of the target sub-virtual account.

[0017] According to a multi-channel fund management system based on one-stop payment of internal bank accounts provided by an embodiment of the present invention, through the above-mentioned method, when the connection between the target sub-virtual account and the master virtual account is restored, the size of the reconciliation time window can be reasonably set according to the actual situation, thereby minimizing computing resources and reducing computing costs as much as possible while ensuring that transaction anomalies can be discovered and corrected in a timely manner without affecting fund security and business continuity.

[0018] In one embodiment, the transaction analysis module collects transaction data of the target sub-virtual account during the disconnection period, analyzes the payment channels and transaction volumes of the transaction data, and calculates a payment channel average index and a transaction volume index; In one implementation, the transaction analysis module includes: The first statistical module: During the period when the target sub-virtual account is disconnected, the number of transactions of each payment channel used by it is counted, recorded as , indicating the Number of transactions per payment channel; Transaction share module: For each payment channel, the number of transactions during the disconnection period is divided by the total number of transactions across all channels to obtain the transaction share of the payment channel. The calculation formula is: , where For the The proportion of transactions by payment channel; Payment channel uniformity module: Calculates the overall payment channel uniformity index, which represents the actual degree of dispersion of actual payment channel usage during the period when the target sub-virtual account is disconnected. The calculation formula is: , where is the payment channel uniformity index.

[0019] It should be noted that the payment channel uniformity index refers to an indicator that measures the degree of balance in the use distribution of different payment channels of the target sub-virtual account during a specific time period, such as the period of disconnection. Its numerical range is usually between (0,1]. When the uniformity index is closer to 1, it means that the sub-account is used more evenly across multiple payment channels, that is, the proportion of transactions in each channel is closer; when the index is close to 0, it means that the payment behavior of the account is highly concentrated in a few channels, and the channel usage distribution is extremely unbalanced. In the actual one-stop payment platform for internal bank accounts, the payment channel uniformity index not only reflects the degree of dispersion of store transaction behavior, but also implies the redundancy and difficulty of review of transaction data. When the payment channel uniformity index is low, that is, one or a few payment channels undertake the vast majority of transactions, the transaction flows of these high-frequency channels need to be more intensively and finely proofread during reconciliation, especially after the disconnection is restored. , there is a higher probability of anomalies such as transaction backlogs, duplicate submissions, and misordered transactions. Furthermore, due to the high concentration and volume of transactions in these channels, any reconciliation discrepancies can lead to the need for retransmission and correction of large-scale transactions within a single channel, creating a processing bottleneck. Therefore, when the payment channel uniformity index is low, to ensure the integrity and accuracy of the reconciliation process and the matching quality of transaction logs, the reconciliation time window between the target sub-virtual account and the master virtual account should be proactively expanded—in other words, the time range covered by the reconciliation data should be lengthened. This will cover more potential delayed or backlogged transactions, effectively reducing the risk of missed or incorrect transactions. Furthermore, a larger time window facilitates the implementation of more cross-verification and fault-tolerance mechanisms, thereby improving the resilience and data consistency of the entire reconciliation process. Simply put, the more concentrated the payment activity, the greater the complexity and risk of reconciliation, and the greater the need for compensatory controls with a wider tolerance interval in the time dimension.

[0020] In one implementation, the transaction analysis module further includes: The second statistical module: divide the target sub-virtual account disconnection time period into Sub-time periods of equal length, and count the number of transactions in each sub-time period , where For the Number of transactions in each sub-time period; Transaction density change module: Calculates the absolute difference in the number of transactions between two adjacent sub-time periods and calculates the transaction density change rate; the calculation formula is: ,in, The value range is ; Calculation module: Calculate the range of density change rate Deviation from the median , the calculation formula is: , , where is the median of the density change rate; Volume Index Module: Based on the range of density change rate Deviation from the median Calculate the trading volume index. The formula is: Where, is the trading volume index.

[0021] It should be noted that the trading volume index is a comprehensive indicator used to measure the target sub-virtual account's trading activity and its fluctuations during the disconnection period. It reflects the intensity and volatility of the account's trading behavior over a short period of time. It not only focuses on the total volume of transactions, but also captures phenomena such as "dramatic changes" and "concentrated bursts" in trading behavior over time. When transaction density fluctuates dramatically between adjacent time periods, or when the number of transactions surges within certain sub-time periods, the trading volume index will show a large value, indicating that the account engaged in high-frequency, highly concentrated, or even irregular trading behavior during the disconnection period. A higher trading volume index indicates that the system must process not only a large amount of transaction data during reconciliation, but also an uneven distribution and significant fluctuations. This can easily lead to missed transactions, misaligned accounts, and incomplete data coverage. This is particularly true in scenarios where bank payment systems require transaction-by-transaction matching, significantly increasing the system's computational pressure and data consistency risks. If a conventional reconciliation window is still used in this situation, it may not cover all valid transaction records, resulting in some transactions not being included in the reconciliation scope in a timely manner, increasing the risk of reconciliation failures or delays. Therefore, when the trading volume index is high, the reconciliation time window between the target sub-virtual account and the total virtual account should be appropriately increased to extend the reconciliation coverage in the time dimension and provide the system with more sufficient reconciliation time and data processing space to ensure the integrity of capital flow, the accuracy of account reconciliation, and the stability and security of overall capital management.

[0022] In one embodiment, the historical reconciliation module extracts historical transaction and reconciliation data between the target sub-virtual account and the master virtual account, analyzes the historical transaction and reconciliation data, and calculates a historical transaction reconciliation anomaly index; In one implementation, the historical reconciliation module includes: Sliding Window Module: Set a basic sliding window width and slide it by step size within the historical reconciliation transaction period to generate multiple sliding windows; Sequence module: counts the number of abnormal transactions in each sliding window to form a sliding window sequence; Abnormal Window Density Module: Sets an abnormality judgment threshold. When the number of abnormal transactions within a sliding window is not less than the judgment threshold, the corresponding sliding window is determined to be an abnormal window. The proportion of all abnormal windows in the sliding window set is calculated and defined as the abnormal window density. Window segment length module: detects continuous abnormal window segments in the sliding window sequence and counts the length of the longest continuous abnormal window segment; Historical transaction reconciliation anomaly index module: Multiply the anomaly window density by the length of the longest continuous anomaly window segment to obtain the historical transaction reconciliation anomaly index.

[0023] It should be noted that the Historical Transaction Reconciliation Anomaly Index is a composite indicator used to measure the concentration and continuity of reconciliation anomalies between the target sub-virtual account and the master virtual account in historical transactions. This index reflects two risk characteristics: first, the anomaly window density quantifies the overall proportion of anomaly windows within the historical sliding window sequence, indicating the prevalence of anomalies. Second, the length of the longest consecutive anomaly window segment measures the consistency of anomalies, reflecting whether anomalies occur frequently over a certain period of time. A higher Historical Transaction Reconciliation Anomaly Index indicates not only frequent anomalies but also a concentrated, continuous pattern. This often indicates systemic risk, batch errors, or serious desynchronization of accounts. After the reconciliation system is restored, historical transactions must be reviewed and verified using a time window to ensure accounting accuracy and completeness. If the Historical Anomaly Index is high and a smaller reconciliation time window is still used, some anomalies may not be included in the comparison in a timely manner, creating the risk of "missed" or "incorrect" accounts. Furthermore, a smaller window may lead to frequent and repeated comparisons, wasting resources and limiting effectiveness. Therefore, when the anomaly index is high, the reconciliation time window should be appropriately expanded to cover more historical transaction intervals and suspicious anomalies, thereby improving the effectiveness of reconciliation and the system's fault tolerance.

[0024] In one embodiment, the connection status module: obtains connection status data of the target sub-virtual account and the master virtual account after the connection is restored, analyzes the connection status data, and calculates a connection instability index; In one implementation, the connection status module includes: Connection status value module: within the preset detection period after the target sub-virtual account is disconnected and restored, the connection status is sampled at fixed time intervals and recorded to form a connection status value sequence. Each sampled value in the connection status sequence indicates whether the connection is normal or disconnected. When the connection is normal, the corresponding value of the connection status is 1, and when the connection is disconnected, the corresponding value of the connection status is 0. Recording module: traverses the connection state value sequence, merges the sampling points with the same consecutive connection state value into several continuous state segments, and records the state type and the number of continuous sampling points of each state segment; Judgment module: sets a minimum stable duration threshold and determines that the state segment with the number of continuous sampling points less than the threshold is an unstable segment; Connection instability index module: counts the number of unstable segments and the total number of all status segments, and calculates the ratio of the number of unstable segments to the total number of status segments as the connection instability index; It should be noted that the connection instability index reflects the frequency of fluctuations and the difference in stability between the connection status between the target sub-virtual account and the master virtual account. A high index indicates frequent switching of the connection status during the monitoring period, with multiple disconnections and restorations occurring within a short period of time, resulting in a lack of continuity and stability in the overall connection status. These frequent and brief connection interruptions increase the uncertainty and risk of omissions in transaction data transmission. Some transactions may not be uploaded to the master virtual account in a timely or complete manner, thereby affecting the accuracy and completeness of reconciliation data. Therefore, to fully cover these transaction data omissions and anomalies caused by connection fluctuations, it is necessary to appropriately extend the reconciliation time window between the target sub-virtual account and the master virtual account. By expanding the time window, transaction information during periods of disconnection and restoration, as well as periods of frequent connection fluctuations, can be more comprehensively collected and reconciled, effectively reducing data omissions and reconciliation errors caused by unstable connections, and ensuring accurate and reliable fund management and accounting.

[0025] In one embodiment, the management module determines whether to increase the reconciliation time window between the target sub-virtual account and the master virtual account based on the payment channel uniformity index, the transaction volume index, the historical transaction reconciliation anomaly index, and the connection instability index, and manages the transaction funds of the target sub-virtual account. In one implementation, the management module includes: Evaluation module: Normalize the payment channel average index, transaction volume index, historical transaction reconciliation anomaly index, and connection instability index, map them to a value range of 0-1, and perform weighted summation of the normalized payment channel average index, transaction volume index, historical transaction reconciliation anomaly index, and connection instability index to obtain the window increase evaluation index. The calculation formula for the window increase evaluation index is: , where Add an evaluation index to the window, They are the normalized transaction volume index, historical transaction reconciliation anomaly index, connection instability index and payment channel uniformity index.

[0026] Comparison module: compares the window increase evaluation index with the preset window increase evaluation index threshold, and determines whether to increase the length of the reconciliation time window between the target sub-virtual account and the master virtual account based on the comparison result, and manages the transaction funds of the target sub-virtual account.

[0027] It should be noted that commonly used normalization methods include Min-Max normalization and Z-Score standardization. The specific selection depends on the actual situation and is not limited or elaborated on. In addition, under normal circumstances, the weight values ​​of the normalized transaction volume index, historical transaction reconciliation anomaly index, connection instability index and payment channel uniformity index are the same, and the sum of the weights is 1.

[0028] In one implementation, the comparison module includes: The first comparison management module: If the window increase evaluation index is not less than the preset window increase evaluation index threshold, the target sub-virtual account and the master virtual account are disconnected for a period of time as the basic reconciliation time window, the length of the basic reconciliation time window is increased, and the target sub-virtual account and the master virtual account are reconciled according to the increased length of the reconciliation time window to manage transaction funds; Second comparison management module: If the window increase evaluation index is less than the preset window increase evaluation index threshold, there is no need to increase the length of the reconciliation time window between the target sub-virtual account and the total virtual account. The reconciliation between the target sub-virtual account and the total virtual account is directly performed according to the basic reconciliation time window to manage the transaction funds.

[0029] It should be noted that the four indicators—the payment channel uniformity index, transaction volume index, historical transaction reconciliation anomaly index, and connection instability index—are first converted to a numerical value between 0 and 1, a process called normalization. This ensures comparability across indicators. Next, each indicator is assigned a weight based on its importance. The weighted values ​​are then summed to produce a composite score, called the "window expansion assessment index." This index reflects the complexity and risk level of reconciliation between the target sub-virtual account and the master virtual account. This composite score is then compared against a pre-set threshold. If the score is above or equal to the threshold, it indicates that transactions during the disconnection period were more complex, with more anomalies or risks. Therefore, the reconciliation window should be increased. This means that transaction data over a longer period of time should be reviewed during reconciliation to ensure that no omissions are missed, thereby improving reconciliation accuracy and fund management security. Conversely, if the score is below the threshold, indicating a relatively stable trading environment and lower risk, the reconciliation window can be maintained at the default base length to avoid unnecessary resource waste. The benefit of dynamically adjusting the reconciliation time window is that it ensures accurate verification of funds and transaction data, preventing important transactions from being missed due to a too-short time window, while also avoiding the excessive consumption of computing resources and reduced efficiency caused by an overly long time window. For example, if a store experiences a disconnection with a uniform distribution of transaction channels but high transaction volume and unstable connection, the reconciliation time window will be automatically extended to cover more transaction data and prevent omissions. Meanwhile, if another store maintains a stable connection with minimal anomalies, it will use only the standard time window, improving reconciliation efficiency and conserving resources. This ensures both fund security and operational efficiency.

[0030] It should be noted that the specific length of the increased basic reconciliation time window depends on actual circumstances and is not specified or elaborated upon here. For example, a store within a chain enterprise was disconnected from the main virtual account for two hours due to a network failure. After the disconnection was restored, the window increase assessment index was calculated to be 0.85 based on the normalized payment channel uniformity index, transaction volume index, historical transaction reconciliation anomaly index, and connection instability index, with a preset threshold of 0.8. Because the assessment index is not less than the threshold, the basic reconciliation time window is appropriately extended based on the two-hour disconnection period, for example, by 30 minutes, to a reconciliation window of 2 hours and 30 minutes. This allows for a more comprehensive verification of transaction data during and before and after the disconnection, ensuring that no missed or undetected funds are present, thereby improving reconciliation accuracy and the security of fund management. Conversely, if another store's disconnection lasts only 30 minutes, the calculated window increase evaluation index is 0.5, which is below the threshold of 0.8. The basic 30-minute reconciliation window is then used for reconciliation, without extending the window. This ensures reconciliation efficiency while avoiding unnecessary consumption of computing resources. This dynamic adjustment of the reconciliation window ensures both secure and reliable fund management and efficient and economical management.

[0031] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and should not be considered to limit the scope of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A multi-channel fund management system based on one-stop payment for internal bank accounts, characterized in that: The system comprises: Transaction analysis module: This module records the restored sub-virtual account as the target sub-virtual account, collects the transaction data of the target sub-virtual account during the disconnection period, analyzes the payment channels and transaction volumes of the transaction data, and calculates the payment channel uniformity index and transaction volume index. Historical reconciliation module: extracts historical transaction and reconciliation data between the target sub-virtual account and the master virtual account, analyzes the historical transaction and reconciliation data, and calculates the historical transaction reconciliation anomaly index; Connection status module: obtains the connection status data of the target sub-virtual account and the main virtual account after the connection is restored, analyzes the connection status data, and calculates the connection instability index; Management module: Determine whether to increase the reconciliation time window between the target sub-virtual account and the master virtual account based on the payment channel uniformity index, transaction volume index, historical transaction reconciliation anomaly index, and connection instability index, and manage the transaction funds of the target sub-virtual account.

2. A multi-channel fund management system based on one-stop payment for internal bank accounts according to claim 1, characterized in that: The transaction analysis module includes: The first statistics module: during the period when the target sub-virtual account is disconnected, counts the number of transactions of each payment channel used by it; Transaction share module: For each payment channel, divide the number of transactions during the disconnection period by the total number of transactions across all channels to obtain the transaction share of the payment channel. Payment channel uniformity module: Calculates the overall payment channel uniformity index, which represents the actual degree of dispersion of actual payment channel usage during the period when the target sub-virtual account is disconnected. The calculation formula is: , where is the payment channel uniformity index.

3. A multi-channel fund management system based on one-stop payment for internal bank accounts according to claim 2, characterized in that: The transaction analysis module also includes: The second statistical module: divide the target sub-virtual account disconnection time period into Sub-time periods of equal length, and count the number of transactions in each sub-time period , where For the Number of transactions in each sub-time period; Transaction density change module: Calculates the absolute difference in the number of transactions between two adjacent sub-time periods and calculates the transaction density change rate; the calculation formula is: ,in, The value range is ; Calculation module: Calculate the range of density change rate Deviation from the median ; Volume Index Module: Based on the range of density change rate Deviation from the median Calculate the trading volume index. The formula is: Where, is the trading volume index.

4. A multi-channel fund management system based on one-stop payment for internal bank accounts according to claim 1, characterized in that: The historical reconciliation module includes: Sliding Window Module: Set a basic sliding window width and slide it by step size within the historical reconciliation transaction period to generate multiple sliding windows; Sequence module: counts the number of abnormal transactions in each sliding window to form a sliding window sequence; Abnormal Window Density Module: Sets an abnormality judgment threshold. When the number of abnormal transactions within a sliding window is not less than the judgment threshold, the corresponding sliding window is determined to be an abnormal window. The proportion of all abnormal windows in the sliding window set is calculated and defined as the abnormal window density. Window segment length module: detects continuous abnormal window segments in the sliding window sequence and counts the length of the longest continuous abnormal window segment; Historical transaction reconciliation anomaly index module: Multiply the anomaly window density by the length of the longest continuous anomaly window segment to obtain the historical transaction reconciliation anomaly index.

5. A multi-channel fund management system based on one-stop payment for internal bank accounts according to claim 1, characterized in that: The connection status module includes: Connection status value module: within the preset detection period after the target sub-virtual account is disconnected and restored, the connection status is sampled at fixed time intervals and recorded to form a connection status value sequence. Each sampled value in the connection status sequence represents whether the connection is normal or disconnected. When the connection is normal, the corresponding value of the connection status is 1, and when the connection is disconnected, the corresponding value of the connection status is 0. Recording module: traverses the connection state value sequence, merges consecutive sampling points with the same connection state value into several continuous state segments, and records the state type and the number of continuous sampling points of each state segment; Judgment module: sets a minimum stable duration threshold and determines that the state segment with the number of continuous sampling points less than the threshold is an unstable segment; Connection instability index module: counts the number of unstable segments and the total number of all status segments, and calculates the ratio of the number of unstable segments to the total number of status segments as the connection instability index.

6. A multi-channel fund management system based on one-stop payment for internal bank accounts according to claim 1, characterized in that: The management module includes: Evaluation module: Normalizes the payment channel average index, transaction volume index, historical transaction reconciliation anomaly index, and connection instability index, mapping them to a range of 0-1. Then, it performs a weighted summation of the normalized payment channel average index, transaction volume index, historical transaction reconciliation anomaly index, and connection instability index to obtain the window increase evaluation index. Comparison module: compares the window increase evaluation index with the preset window increase evaluation index threshold, and determines whether to increase the length of the reconciliation time window between the target sub-virtual account and the master virtual account based on the comparison result, and manages the transaction funds of the target sub-virtual account.

7. A multi-channel fund management system based on one-stop payment for internal bank accounts according to claim 1, characterized in that: The comparison module includes: The first comparison management module: If the window increase evaluation index is not less than the preset window increase evaluation index threshold, the target sub-virtual account and the master virtual account are disconnected for a period of time as the basic reconciliation time window, the length of the basic reconciliation time window is increased, and the target sub-virtual account and the master virtual account are reconciled according to the increased length of the reconciliation time window to manage transaction funds; Second comparison management module: If the window increase evaluation index is less than the preset window increase evaluation index threshold, there is no need to increase the length of the reconciliation time window between the target sub-virtual account and the total virtual account. The reconciliation between the target sub-virtual account and the total virtual account is directly performed according to the basic reconciliation time window to manage the transaction funds.

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