Financial product quota processing method, device and electronic equipment

Abstract

This application discloses a method, apparatus, and electronic device for processing credit limits of financial products. Relating to the field of fintech, the method includes: responding to a user's transaction request for a target financial product initiated at a branch of a target financial institution; executing a transaction based on the available credit limit of the target financial institution, wherein the target financial institution concurrently executes different transaction behaviors based on concurrency parameters, the concurrency parameters including at least the number of sub-credit limits obtained from the available credit limit and the value of the sub-credit limits; after the transaction behavior is completed, updating the available credit limit of the target credit limit node corresponding to the target financial institution and calculating the popularity parameter value of the target credit limit node; and updating the concurrency parameters of the target credit limit node according to the updated available credit limit and popularity parameter value. This application solves the performance bottleneck problem of wealth management systems caused by high-concurrency transactions of popular credit limits for financial products in related technologies.

Description

Technical Field

[0001] This application relates to the field of distributed systems, and more specifically, to a method, apparatus, and electronic device for processing credit limits for a financial product. Background Technology

[0002] In existing wealth management systems, popular financial products often experience high concurrency transactions during open trading periods. Each transaction requires the allocation and release of credit limit resources, leading to frequent read and write operations on credit limit records. In this situation, multiple transaction requests compete for write locks on the credit limit table, causing lock waiting and system performance degradation, directly impacting user transaction response time and experience.

[0003] Solutions in related technologies include: limiting the number of transaction requests through concurrency control is simple, but it may cause a large number of customers to retry transactions through electronic channels or wait in line at branches, resulting in branch congestion; while database sharding can distribute the pressure, it increases the system construction cost and is not cost-effective for scenarios with non-continuous high concurrency; while using Kafka asynchronous updates can smooth out peaks and valleys, message congestion may occur when the queue consumption speed is lower than the transaction volume increase rate, which cannot meet the real-time requirements of cash-based financial products; while in-memory databases are fast, data is prone to loss and stability is difficult to guarantee.

[0004] There is currently no effective solution to the performance bottleneck of wealth management systems caused by high-concurrency transactions of popular financial products in related technologies. Summary of the Invention

[0005] The main purpose of this application is to provide a method, device, and electronic device for processing the credit limit of financial products, so as to solve the performance bottleneck problem of wealth management system caused by high-concurrency transactions of popular credit limits of financial products in related technologies.

[0006] To achieve the above objectives, according to one aspect of this application, a method for processing credit limits for financial products is provided. The method includes: responding to a transaction request for a target financial product initiated by a user at a branch of a target financial institution; executing a transaction based on the available credit limit of the target financial institution, wherein the target financial institution concurrently executes different transaction behaviors based on concurrency parameters, the concurrency parameters including at least the number of sub-credit limits obtained from the available credit limit and the value of the sub-credit limits; after the transaction behavior is completed, updating the available credit limit of the target credit limit node corresponding to the target financial institution, and calculating the popularity parameter value of the target credit limit node, wherein the total credit limit of the target financial product is allocated hierarchically to the credit limit nodes corresponding to each level of financial institution, and the popularity parameter value represents the frequency of transactions using the credit limit; and updating the concurrency parameters of the target credit limit node according to the updated available credit limit and popularity parameter value of the target credit limit node.

[0007] Optionally, updating the concurrency parameters of the target quota node based on the updated available quota and popularity parameter value of the target quota node includes: updating the number of sub-quota items of the target quota node based on the relationship between the popularity parameter value and the popularity parameter value threshold of the target quota node; and updating the value of the sub-quota based on the updated available quota and the updated number of sub-quota items of the target quota node.

[0008] Optionally, the heat parameter value includes the heat increase rate, which represents the growth rate of transaction frequency. Based on the relationship between the heat parameter value of the target quota node and the heat parameter value threshold, updating the number of sub-quota entries of the target quota node includes: increasing the number of sub-quota entries of the target quota node and resetting the initial heat value of the sub-quota when the heat increase rate is greater than or equal to the upper limit of the heat increase rate; and decreasing the number of sub-quota entries of the target quota node and resetting the initial heat value of the sub-quota when the heat increase rate is less than the upper limit of the heat increase rate.

[0009] Optionally, the popularity parameter value, including the popularity increase rate, is determined by: calculating the sum of the popularity values ​​of all sub-quotas of the available quota of the target financial institution within a preset time period to obtain the total popularity value; and calculating the ratio of the total popularity value to the duration of the preset time period to obtain the popularity increase rate.

[0010] Optionally, the heat parameter value includes a heat value representing the number of transactions. Based on the relationship between the heat parameter value of the target credit node and the heat parameter value threshold, updating the number of sub-credits of the target credit node includes: obtaining the time required for the total heat value of the target credit node to grow from the initial heat value to the heat value limit during a historical period, and obtaining the time threshold; after exceeding the time threshold, if the total heat value of all sub-credits of the target financial institution's available credit does not reach the heat value limit, reducing the number of sub-credits of the target credit node.

[0011] Optionally, before responding to a user's transaction request for a target financial product initiated at a branch of the target financial institution, the method further includes: allocating the total amount of the target financial product to various levels of quota nodes, wherein each level of quota node includes branches of financial institutions at different levels; for each quota node, distributing the available quota of the quota node into multiple sub-quotas to obtain the number of sub-quotas and the value of the sub-quotas, setting the initial popularity value of the sub-quotas, and setting the popularity parameter threshold of the quota node.

[0012] Optionally, responding to a user's transaction request for a target financial product initiated at a branch of the target financial institution includes: querying all sub-limits of the target financial institution's available credit limit to obtain the values ​​of M sub-limits, where M is a positive integer; if the values ​​of the M sub-limits are different, using the sub-limit with the highest value to process and execute the transaction; if the values ​​of the M sub-limits are the same, randomly selecting a sub-limit to process and execute the transaction.

[0013] To achieve the above objectives, according to another aspect of this application, a credit limit processing device for financial products is provided. The device includes: a transaction module, configured to respond to a user's transaction request for a target financial product initiated at a branch of a target financial institution, and execute the transaction based on the available credit limit of the target financial institution, wherein the target financial institution concurrently executes different transaction behaviors based on concurrency parameters, the concurrency parameters including at least the number of sub-credit limits obtained from the available credit limit and the value of the sub-credit limits; a popularity parameter calculation module, configured to update the available credit limit of the target credit limit node corresponding to the target financial institution after the transaction behavior is completed, and calculate the popularity parameter value of the target credit limit node, wherein the total credit limit of the target financial product is allocated hierarchically to the credit limit nodes corresponding to each level of financial institution, and the popularity parameter value represents the frequency of transactions using the credit limit; and a concurrency parameter update module, configured to update the concurrency parameters of the target credit limit node according to the updated available credit limit and the popularity parameter value of the target credit limit node.

[0014] To achieve the above objectives, according to another aspect of this application, a computer program product is provided. The product includes: a non-volatile computer-readable storage medium storing a computer program, which, when executed by a processor, implements a method for processing the credit limit of a financial product.

[0015] To achieve the above objectives, according to another aspect of this application, an electronic device is provided. The device includes: a memory storing a computer program, and a processor configured to execute a method for processing the credit limit of a financial product through the computer program.

[0016] In this embodiment, in response to a user's transaction request for a target financial product initiated at a branch of a target financial institution, the transaction is executed based on the available credit limit of the target financial institution. The target financial institution concurrently executes different transaction behaviors based on concurrency parameters, which include at least the number of sub-credit limits distributed from the available credit limit and the value of each sub-credit limit. After the transaction is completed, the available credit limit of the target credit limit node corresponding to the target financial institution is updated, and the popularity parameter value of the target credit limit node is calculated. The total credit limit of the target financial product is allocated hierarchically to the credit limit nodes corresponding to each level of financial institution, and the popularity parameter value represents the frequency of transactions using the credit limit. The concurrency parameters of the target credit limit node are updated based on the updated available credit limit and popularity parameter value. By distributing a single credit limit into multiple sub-credit limits and dynamically adjusting the number of sub-credit limits, the purpose of reducing lock waiting and financial system performance pressure during concurrent operations is achieved. This results in improved system response speed and optimized user transaction experience in high-concurrency transaction scenarios, thereby solving the performance bottleneck problem of financial systems caused by high-concurrency transactions of popular credit limits for financial products in related technologies. Attached Figure Description

[0017] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0018] Figure 1 This is a hardware structure block diagram of a computer terminal used to implement a method for processing the credit limit of financial products.

[0019] Figure 2 This is a flowchart of a method for processing the credit limit of a financial product according to an embodiment of this application;

[0020] Figure 3 This is a flowchart illustrating the summary of regional node quotas provided in the embodiments of this application;

[0021] Figure 4 This is a schematic diagram of the quota node tree provided according to the embodiments of this application;

[0022] Figure 5 This is a schematic diagram of a credit limit processing device for financial products provided according to an embodiment of this application;

[0023] Figure 6 This is a structural block diagram of an electronic device according to an embodiment of this application. Detailed Implementation

[0024] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0025] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0026] It should be noted that the information collected in this application (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for display, data used for analysis, etc.) are information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of this data all comply with relevant laws, regulations, and standards, necessary confidentiality measures have been taken, and they do not violate public order and good morals. Corresponding access points are provided for users to choose to authorize or refuse. For example, interfaces are set up between this system and relevant users or organizations, providing users with corresponding access points to choose to agree to or refuse automated decision-making results; if the user chooses to refuse, the process proceeds to the expert decision-making stage.

[0027] Example 1

[0028] According to an embodiment of this application, a method embodiment for processing the credit limit of a financial product is also provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0029] The method embodiment provided in Embodiment 1 of this application can be executed on a mobile terminal, computer terminal, or similar computing device. Figure 1 This is a hardware structure block diagram of a computer terminal used to implement a method for processing credit limits for financial products. For example... Figure 1 As shown, computer terminal 10 may include one or more ( Figure 1 (Illustrated as 102a, 102b, ..., 102n) Processor 102 (processor 102 may include, but is not limited to, a microprocessor (MCU, Microcontroller Unit) or a programmable gate array (FPGA, Field-Programmable Gate Array), etc.), memory 104 for storing data, and transmission device 106 for communication functions. In addition, it may include: a display, input / output interface (I / O interface), universal serial bus (USB) port (which may be included as one of the ports of a BUS bus), network interface, power supply, and / or camera. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, computer terminal 10 may also include... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0030] It should be noted that the aforementioned one or more processors 102 and / or other data processing circuits are generally referred to herein as "data processing circuits". These data processing circuits may be embodied, in whole or in part, in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuits may be a single, independent processing module, or may be integrated, in whole or in part, into any other element within the computer terminal 10 (or mobile device). As involved in the embodiments of this application, the data processing circuits serve as a processor control mechanism (e.g., selection of a variable resistor termination path connected to an interface).

[0031] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the credit limit processing method for financial products in this embodiment. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, thereby realizing the aforementioned credit limit processing method for financial products. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the computer terminal 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0032] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of the computer terminal 10. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0033] The display may be, for example, a touchscreen liquid crystal display (LCD), which allows the user to interact with the user interface of the computer terminal 10 (or mobile device).

[0034] Under the aforementioned operating environment, this application provides the following: Figure 2 The method for handling credit limits for the financial products shown. Figure 2 This is a flowchart of a method for processing the credit limit of a financial product according to an embodiment of this application.

[0035] Step S201: Respond to the transaction request for the target financial product initiated by the user at the branch of the target financial institution, and execute the transaction behavior based on the available credit limit of the target financial institution. The target financial institution concurrently executes different transaction behaviors based on concurrency parameters, which include at least the number of sub-credit limits obtained from the available credit limit and the value of the sub-credit limits.

[0036] For example, when a customer initiates a transaction at a branch of a target financial institution, the financial institution accepts the transaction request and responds, and the response may be to execute the corresponding transaction behavior according to the transaction type.

[0037] Specifically, transaction behavior can include purchasing and redeeming target financial products; concurrency parameters refer to the set of relevant parameters used to control concurrent transactions when the target financial institution processes transaction behavior. These parameters are directly related to how the target financial institution allocates resources, processes transaction requests, and optimizes the number and value of sub-quota under high concurrency conditions.

[0038] The number of sub-quotas refers to the number of sub-quotas corresponding to each quota node after the quota node is distributed into multiple sub-quotas. The number of sub-quotas determines the upper limit of concurrent transactions supported by the quota node.

[0039] The value of a sub-quota refers to the specific amount of each sub-quota. When the value of a sub-quota is greater than or equal to the value of the target financial product, the transaction can be executed directly; when the value of a sub-quota is less than the value of the target financial product, the quota node and its sub-quotas are called from the superior level.

[0040] Step S202: After the transaction is completed, update the available quota of the target quota node corresponding to the target financial institution and calculate the heat parameter value of the target quota node. The total quota of the target financial product is allocated to the quota nodes corresponding to each level of financial institution. The heat parameter value represents the frequency of using the quota for transactions.

[0041] Specifically, updating the available credit limit includes: when the transaction is to purchase a target financial product, the amount purchased will be deducted from the original available credit limit; when the transaction is to redeem a target financial product, the amount redeemed will be added to the original available credit limit.

[0042] The popularity parameter value characterizes the frequency of use of the target quota node when processing transaction requests, reflecting the level of transaction activity. The popularity parameter value can include the popularity increase rate, which represents the growth rate of transaction volume, and the popularity value of the transaction volume. Based on these parameter values, the number and value of sub-quotas can be dynamically adjusted to optimize the resource allocation of the target quota node.

[0043] Step S203: Update the concurrency parameters of the target quota node according to the updated available quota and popularity parameter values ​​of the target quota node.

[0044] Specifically, after each transaction is completed, the concurrency parameters are adjusted by reassessing the current state of the target quota node. The concurrency parameters are a set of key parameters used to control the processing of transaction requests, mainly involving the configuration of the target quota node and its sub-quotas, such as the number and value of sub-quotas.

[0045] In this embodiment, in response to a user's transaction request for a target financial product initiated at a branch of a target financial institution, the transaction is executed based on the available credit limit of the target financial institution. The target financial institution concurrently executes different transaction behaviors based on concurrency parameters, which include at least the number of sub-credit limits distributed from the available credit limit and the value of each sub-credit limit. After the transaction is completed, the available credit limit of the target credit limit node corresponding to the target financial institution is updated, and the popularity parameter value of the target credit limit node is calculated. The total credit limit of the target financial product is allocated hierarchically to the credit limit nodes corresponding to each level of financial institution, and the popularity parameter value represents the frequency of transactions using the credit limit. The concurrency parameters of the target credit limit node are updated based on the updated available credit limit and popularity parameter value. By distributing a single credit limit into multiple sub-credit limits and dynamically adjusting the number of sub-credit limits, the purpose of reducing lock waiting and financial system performance pressure during concurrent operations is achieved. This results in improved system response speed and optimized user transaction experience in high-concurrency transaction scenarios, thereby solving the performance bottleneck problem of financial systems caused by high-concurrency transactions of popular credit limits for financial products in related technologies.

[0046] In order to dynamically adjust the resource allocation of the target quota node according to the transaction load, optionally, in the quota processing method of financial products provided in this application embodiment, updating the concurrency parameters of the target quota node according to the updated available quota and popularity parameter value of the target quota node includes: updating the number of sub-quota of the target quota node according to the relationship between the popularity parameter value and the popularity parameter value threshold of the target quota node; and updating the value of the sub-quota according to the updated available quota and the updated number of sub-quota of the target quota node.

[0047] Specifically, the heat parameter threshold is a preset reference value used to assess the transaction activity level of the target quota node, and to determine whether the current concurrency parameters need to be adjusted. The heat parameter threshold can include: upper limit of heat value, which represents the preset maximum value of the heat value of the target quota node. When the heat value reaches or approaches the upper limit, it indicates that the transaction activity level is high; upper limit and lower limit of heat increase rate, which represent the preset maximum and minimum values ​​of the heat value growth rate within a preset time period, reflecting the speed at which the transaction frequency increases.

[0048] Updating the number of sub-quotas within the target quota node is to adjust the number of transactions the target financial institution can process simultaneously. Increasing the number of sub-quotas allows the target financial institution to support more concurrent transactions; decreasing the number avoids waste caused by excessive resource dispersion.

[0049] The total credit limit Q is obtained by adding the values ​​of all sub-credit limits within a credit limit node.

[0050]

[0051] Where n is the number of sub-quota entries, k is a positive integer increasing from 1 to n, and Q k It is the value of the kth sub-quota.

[0052] The value of a sub-quota can be calculated by dividing the updated available quota by the number of updated sub-quotas. The value of each sub-quota can be evenly distributed during the update.

[0053] This application embodiment updates the number of sub-quota entries based on the relationship between the heat parameter value and the threshold, and recalculates the value of each sub-quota, thereby optimizing the concurrent processing capability of the quota node.

[0054] To adjust the number of sub-quota entries of the target quota node to adapt to real-time transaction needs, optionally, in the quota processing method for financial products provided in this application embodiment, the heat parameter value includes the heat increase rate, which characterizes the growth rate of transaction frequency. Updating the number of sub-quota entries of the target quota node based on the relationship between the heat parameter value of the target quota node and a heat parameter value threshold includes: increasing the number of sub-quota entries of the target quota node and resetting the initial heat value of the sub-quota when the heat increase rate is greater than or equal to the upper limit of the heat increase rate; and decreasing the number of sub-quota entries of the target quota node and resetting the initial heat value of the sub-quota when the heat increase rate is less than the upper limit of the heat increase rate.

[0055] Specifically, when the rate of increase in popularity is greater than or equal to the upper limit of the rate of increase in popularity, it indicates that the transaction frequency is increasing too fast and the existing number of sub-quota transactions is insufficient to support the current concurrent transaction demand. Therefore, it is necessary to increase the number of sub-quota transactions to alleviate the concurrent pressure. When the rate of increase in popularity is lower than the upper limit, it indicates that the current number of sub-quota transactions is too large and there is redundancy in resource allocation. In this case, reducing the number of sub-quota transactions will save resource consumption.

[0056] For example, if a node's total popularity value T reaches its upper limit M within the time interval t0-t1, calculate the node's popularity increase rate:

[0057] r = M / (t1-t0);

[0058] Where r is the rate of increase in popularity, and t0-t1 is the time it takes for the total popularity value T of a node to reach the upper limit M of that node's popularity value.

[0059] It should be noted that resetting the initial popularity value of a sub-quota ensures that the new sub-quota popularity value starts counting from zero, avoiding impact on subsequent monitoring of popularity parameter values ​​and adjustments to the number of sub-quota entries; after resetting, record the time t = t1 when the regional quota last reached the hotspot limit, and the time T required to last reach the limit. m = t - t0.

[0060] When the rate of increase in popularity is between the upper and lower limits of the rate of increase in popularity, it indicates that the number of sub-quotas n just meets the concurrency requirements and no adjustment is needed. Record the time t = t1 when the regional quota most recently reached the upper limit of popularity, and the time Tm required to most recently reach the upper limit is t - t0.

[0061] If the monitored quota node fails to reach the hotspot limit M at time t2, and the time Tm required to reach the limit last time has exceeded the limit (i.e., t2-t < Tm and T < M), it indicates that the node has been allocated too many sub-quotas n, resulting in wasted capacity in the financial management system. The number of sub-quotas is adjusted to n-1, and one less sub-quota is reallocated without resetting the sub-quota hotspot value. The sub-quota hotspot value is not reset because the quota node has not reached the hotspot limit M, and there is no need to record the time until the quota node reaches the hotspot limit M, at which point the time is recorded.

[0062] This application embodiment updates the number of sub-quota entries based on the rate of increase in popularity and resets the initial popularity value of the sub-quota, thereby increasing the number of concurrent processing operations and avoiding lock waiting issues in high-concurrency scenarios.

[0063] To obtain accurate heat index parameter values ​​and heat index growth rates, optionally, in the credit limit processing method for financial products provided in this application embodiment, the heat index parameter values, including the heat index growth rate, are determined by: calculating the sum of the heat index values ​​of all sub-credit limits of the available credit limit of the target financial institution within a preset time period to obtain the total heat index value; and calculating the ratio of the total heat index value to the duration of the preset time period to obtain the heat index growth rate.

[0064] The formula for the total heat value T:

[0065]

[0066] Where n is the number of sub-quota entries, k is a positive integer increasing from 1 to n, and R k It is the popularity value of the kth sub-quota.

[0067] Specifically, the preset time period refers to a fixed time range used in the embodiment to calculate the transaction activity level of the target quota node. It is a pre-set time length for monitoring the heat parameter value, such as the past month. The higher the rate of increase in heat, the higher the hot spot in the region.

[0068] This application embodiment achieves the effect of quantifying the level of trading activity by obtaining the total popularity value and then calculating the rate of increase in popularity.

[0069] To determine and adjust the number of sub-quota entries based on a time threshold and total popularity value, optionally, in the quota processing method for financial products provided in this application embodiment, the popularity parameter value includes a popularity value representing the number of transactions. Updating the number of sub-quota entries for the target quota node based on the relationship between the popularity parameter value and the popularity parameter value threshold includes: obtaining the time required for the total popularity value of the target quota node to increase from the initial popularity value to the upper limit of the popularity value over a historical period, thus obtaining the time threshold; and after exceeding the time threshold, if the total popularity value of all sub-quota entries of the available quota of the target financial institution has not reached the upper limit of the popularity value, reducing the number of sub-quota entries for the target quota node.

[0070] Specifically, the upper limit of the heat value refers to the maximum preset value that the total heat value of the target quota node can reach, which is used to characterize the maximum level of transaction activity that the node can withstand within a certain period of time. When the total heat value reaches the upper limit of the heat value within the time threshold, it means that the transaction activity of the node has exceeded the carrying capacity of the financial system; when the total heat value does not reach the upper limit of the heat value, it means that the transaction activity of the node is within the carrying capacity of the financial system.

[0071] The upper limit of the heat value is set to provide a quantitative threshold for monitoring and adjusting the allocation of sub-quotas, ensuring that the system runs stably in high-concurrency scenarios and avoiding the consumption of resources beyond the quota nodes.

[0072] In one optional implementation, customers A and B, in the same region G and at the same time, trade the same financial product through mobile banking. Customer A purchases 10,000 yuan worth of wealth management products, and customer B purchases 20,000 yuan worth. Customer C, in a different region Z, redeems 5,000 yuan worth of wealth management products at the same time. The process is as follows:

[0073] The default sub-quota number of entries rule is set as shown in Table 1 below:

[0074] Table 1

[0075] Total available quota range for nodes Number of scattered lines n 0≤x＜10000 1 10000≤x＜50000 2 50000≤x 3

[0076] The quota is divided into regional quotas from the head office quota, and an upper limit for the heat value and an upper and lower limit for the heat increase rate are set for each node, as shown in Table 2:

[0077]

[0078] Each quota node is distributed to sub-quotas according to the sub-quota number rules (Table 1), as shown in Tables 3.1, 3.2, and 3.3:

[0079] Table 3.1

[0080] node Sub-quota Popularity value Head Office Node Sub-Quota 1 5000 0

[0081] Table 3.2

[0082] node Sub-quota Popularity value G region node 1 23333 0 G region node 2 23333 0 G region node 3 23334 0

[0083] Table 3.3

[0084] node Sub-quota Popularity value Z region node 1 12500 0 Z region node 2 12500 0

[0085] Figure 3 This is a flowchart of the regional node quota aggregation provided in the embodiments of this application. After the quota is initialized, the financial management system receives a transaction request and executes the steps of "sub-quota record update" and "sub-quota summary query". The transaction process is as follows: Figure 3 As shown, each transaction is assigned a quota node based on the transaction region, uses the sub-quota under the quota node of the region, and is finally aggregated into the quota node of the region.

[0086] The changes in sub-quota parameters are shown in Table 4 (Customers A and B purchase 10,000 and 20,000 yuan of wealth management products in region G, respectively, resulting in a deduction of 10,000 and 20,000 yuan from their sub-quotas G1 and G2, respectively), and Table 5 (Customer C redeems 5,000 yuan of wealth management products in region Z, resulting in an increase of 5,000 yuan in their sub-quota Z1).

[0087] Table 4

[0088]

[0089]

[0090] Table 5

[0091] node Sub-quota Popularity value Z region node 1 17500 1 Z region node 2 12500 0

[0092] According to Tables 4 and 5, after the transaction is completed, the total available credit in region G is 13333 + 3333 + 23334 = 40000, and the total available credit in region Z is 17500 + 12500 = 30000. The total popularity value of region G is 2, and the total popularity value of region Z is 1.

[0093] After customers A and B complete their transactions, the total popularity value of region G reaches 2, which is the set maximum popularity value. Assuming the total transaction time of A and B is 1 second, the popularity increase rate is 2 / s, which also reaches the maximum increase rate. At this point, the background monitoring process determines that the number of sub-quotas in region G is no longer sufficient to meet the current concurrency requirements, and redistributes the quotas of node G, distributing them into 4 sub-quotas as shown in Table 6:

[0094] Table 6

[0095] node Sub-quota Popularity value G region node 1 10000 0 G region node 2 10000 0 G region node 3 10000 0 G region node 3 10000 0

[0096] Assuming customer C's transaction time is 1 second, the popularity of region Z reaches its maximum, with a popularity increase rate of 1 / s, which is less than the lower limit of the popularity increase rate of region Z (2 / s). At this time, the background monitoring process determines that the number of sub-quotas in region Z is too large, resulting in performance overkill. Therefore, it reduces the number of sub-quotas, and the redistributed sub-quotas are shown in Table 7.

[0097] Table 7

[0098] node Sub-quota Popularity value Z region node 1 30000 0

[0099] This application embodiment determines whether to reduce the number of sub-quota entries after the time threshold is exceeded, based on whether the current total popularity value has reached the upper limit. This achieves the effect of recovering excess sub-quota when the transaction frequency is low and reducing system resource consumption.

[0100] To allocate reasonable quota and sub-quota parameters before a transaction begins, optionally, in the quota processing method for financial products provided in this application embodiment, before responding to a user's transaction request for the target financial product initiated at a branch of the target financial institution, the method further includes: allocating the total quota of the target financial product to quota nodes at various levels, wherein the quota nodes at various levels include branches of financial institutions at different levels; for each quota node, distributing the available quota of the quota node into multiple sub-quotas to obtain the number of sub-quotas and the value of the sub-quotas, setting the initial popularity value of the sub-quotas, and setting the popularity parameter threshold of the quota node.

[0101] Specifically, the various levels of quota nodes can include head office quota nodes, regional quota nodes, and branch quota nodes.

[0102] Figure 4 This is a schematic diagram of the quota node tree provided according to the embodiments of this application, such as... Figure 4As shown, the head office quota is divided into multiple regional quotas, and each region is further divided into multiple branch quotas. Each quota record is defined as a quota node. From the head office node to the regional nodes, and then to the branch nodes, all quota nodes form a quota tree. Each quota node is then distributed into n sub-quotas, with a sub-quota value of Qn. Each quota node is given an upper limit M for its popularity value, an upper limit N for its popularity increase rate, and a lower limit P for its popularity increase rate. The initial popularity value Rn of each sub-quota is 0.

[0103] This application embodiment achieves the effect of laying the foundation for transaction load distribution and real-time dynamic adjustment by allocating quota nodes at each level and further distributing the quota of each node into multiple sub-quotas and setting various sub-quota parameters.

[0104] To balance the sub-quota values ​​during transaction execution, optionally, in the quota processing method for financial products provided in this application embodiment, responding to a user's transaction request for a target financial product initiated at a branch of the target financial institution includes: querying all sub-quotas of the target financial institution's available quota to obtain the values ​​of M sub-quotas, where M is a positive integer; if the values ​​of the M sub-quotas are different, using the sub-quota with the highest value to process and execute the transaction; if the values ​​of the M sub-quotas are the same, randomly selecting a sub-quota to process and execute the transaction.

[0105] Specifically, when the sub-quota values ​​are different, the sub-quota with the highest value is selected for the transaction. This minimizes the value difference between this sub-quota and other sub-quotas, thereby balancing the values ​​of each sub-quota.

[0106] When the values ​​of sub-quotas are the same, randomly selecting one of the sub-quotas to execute the transaction can avoid the excessive concentration of sub-quotas due to fixed order selection, which would affect the balance of values ​​of each sub-quota.

[0107] This application embodiment achieves the effect of balancing the use of sub-quotas and avoiding excessive consumption of popular sub-quotas by querying all sub-quotas of the target financial institution and using the sub-quotas to execute transactions according to the selection rules.

[0108] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0109] Example 2

[0110] This application also provides a credit limit processing device for financial products. It should be noted that the credit limit processing device for financial products in this application can be used to execute the credit limit processing method for financial products provided in this application. The following describes the credit limit processing device for financial products provided in this application.

[0111] According to an embodiment of this application, an apparatus for implementing the above-described method for processing credit limits of financial products is also provided. Figure 5 This is a schematic diagram of a credit limit processing device for financial products provided according to embodiments of this application, such as... Figure 5 As shown, the device includes:

[0112] Transaction module 501 is used to respond to transaction requests for target financial products initiated by users at the branches of the target financial institution and to execute transaction behavior based on the available credit of the target financial institution. The target financial institution concurrently executes different transaction behaviors based on concurrency parameters, which include at least the number of sub-credits obtained from the available credit and the value of the sub-credits.

[0113] The heat parameter calculation module 502 is used to update the available quota of the target quota node corresponding to the target financial institution after the transaction is completed, and to calculate the heat parameter value of the target quota node. The total quota of the target financial product is allocated to the quota nodes corresponding to each level of financial institutions, and the heat parameter value represents the frequency of using the quota for transactions.

[0114] The concurrent parameter update module 503 is used to update the concurrent parameters of the target quota node based on the updated available quota and popularity parameter values ​​of the target quota node.

[0115] In this embodiment, in response to a user's transaction request for a target financial product initiated at a branch of a target financial institution, the transaction is executed based on the available credit limit of the target financial institution. The target financial institution concurrently executes different transaction behaviors based on concurrency parameters, which include at least the number of sub-credit limits distributed from the available credit limit and the value of each sub-credit limit. After the transaction is completed, the available credit limit of the target credit limit node corresponding to the target financial institution is updated, and the popularity parameter value of the target credit limit node is calculated. The total credit limit of the target financial product is allocated hierarchically to the credit limit nodes corresponding to each level of financial institution, and the popularity parameter value represents the frequency of transactions using the credit limit. The concurrency parameters of the target credit limit node are updated based on the updated available credit limit and popularity parameter value. By distributing a single credit limit into multiple sub-credit limits and dynamically adjusting the number of sub-credit limits, the purpose of reducing lock waiting and financial system performance pressure during concurrent operations is achieved. This results in improved system response speed and optimized user transaction experience in high-concurrency transaction scenarios, thereby solving the performance bottleneck problem of financial systems caused by high-concurrency transactions of popular credit limits for financial products in related technologies.

[0116] It should be noted that the transaction module 501, the popularity parameter calculation module 502, and the concurrent parameter update module 503 mentioned above correspond to steps S201 to S203 in Embodiment 1. The three modules and their corresponding steps implement the same instances and application scenarios, but are not limited to the content disclosed in Embodiment 1. It should be noted that the above modules or units can be hardware or software components stored in memory (e.g., memory 104) and processed by one or more processors (e.g., processors 102a, 102b, ..., 102n). The above modules can also be part of a device and run in the computer terminal 10 provided in Embodiment 1.

[0117] Optionally, in the credit limit processing device for financial products provided in this application embodiment, the concurrent parameter update module 503 includes: a sub-credit limit number update module, used to update the number of sub-credit limits of the target credit limit node according to the relationship between the heat parameter value and the heat parameter value threshold of the target credit limit node; and a sub-credit limit value update module, used to update the value of the sub-credit limit according to the updated available credit limit of the target credit limit node and the updated number of sub-credit limits.

[0118] Optionally, in the credit limit processing device for financial products provided in this application embodiment, the sub-credit limit update module includes a sub-credit limit increase module, which is used to increase the number of sub-credit limits of the target credit limit node and reset the initial popularity value of the sub-credit limit when the popularity increase rate is greater than or equal to the upper limit of the popularity increase rate; and a sub-credit limit decrease module, which is used to decrease the number of sub-credit limits of the target credit limit node and reset the initial popularity value of the sub-credit limit when the popularity increase rate is less than the upper limit of the popularity increase rate.

[0119] Optionally, in the credit limit processing device for financial products provided in this application embodiment, the sub-credit limit update module includes a total popularity value calculation module, which is used to calculate the sum of the popularity values ​​of all sub-credit limits of the available credit limit of the target financial institution within a preset time period to obtain the total popularity value; and a popularity increase rate, which is used to calculate the ratio of the total popularity value to the duration of the preset time period to obtain the popularity increase rate.

[0120] Optionally, in the credit limit processing device for financial products provided in this application embodiment, the sub-credit limit update module includes a time threshold acquisition module, which is used to acquire the time required for the total popularity value of the target credit limit node to increase from the initial popularity value to the upper limit of the popularity value during a historical time period, and obtain the time threshold; and a sub-credit limit reduction sub-module, which is used to reduce the number of sub-credit limits of the target credit limit node if the total popularity value of all sub-credit limits of the available credit limit of the target financial institution has not reached the upper limit of the popularity value after the time threshold is exceeded.

[0121] Optionally, in the credit limit processing device for financial products provided in this application embodiment, the transaction module 501 includes: a credit limit node allocation module, used to allocate the total credit limit of the target financial product to credit limit nodes at each level, wherein the credit limit nodes at each level include branches of financial institutions at different levels; and a sub-credit limit setting module, used to distribute the available credit limit of each credit limit node into multiple sub-credit limits, obtain the number of sub-credit limits and the value of the sub-credit limits, set the initial popularity value of the sub-credit limits, and set the popularity parameter threshold of the credit limit node.

[0122] Optionally, in the credit limit processing device for financial products provided in this application embodiment, the transaction module 501 includes: a sub-credit limit query module, used to query all sub-credit limits of the available credit limit of the target financial institution to obtain the values ​​of M sub-credit limits, where M is a positive integer; a sub-credit limit selection module, used to use the sub-credit limit with the highest value to process and execute the transaction when the values ​​of the M sub-credit limits are different; and a sub-credit limit randomization module, used to randomly select a sub-credit limit to process and execute the transaction when the values ​​of the M sub-credit limits are the same.

[0123] Example 3

[0124] Embodiments of this application may provide an electronic device. Figure 6 This is a structural block diagram of an electronic device according to an embodiment of this application. Figure 6 As shown, the electronic device may include: one or more ( Figure 6 (Only one is shown) processor 602, memory 604, memory controller, and peripheral interface, wherein the peripheral interface is connected to the radio frequency module, audio module and display.

[0125] The memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the methods and apparatus in the embodiments of this application. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, thereby implementing the above-described methods. The memory may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include memory remotely located relative to the processor, and these remote memories can be connected to the terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0126] The processor can access information and applications stored in memory via a transmission device to perform the following steps: responding to a user's transaction request for a target financial product initiated at a branch of the target financial institution; executing the transaction based on the target financial institution's available credit limit, wherein the target financial institution concurrently executes different transaction behaviors based on concurrency parameters, which at least include the number of sub-credit limits obtained from the available credit limit and the value of the sub-credit limits; after the transaction behavior is completed, updating the available credit limit of the target credit limit node corresponding to the target financial institution, and calculating the heat parameter value of the target credit limit node, wherein the total credit limit of the target financial product is allocated hierarchically to the credit limit nodes corresponding to each level of financial institution, and the heat parameter value represents the frequency of using the credit limit for transactions; updating the concurrency parameters of the target credit limit node according to the updated available credit limit and heat parameter value of the target credit limit node.

[0127] The processor can also call the information and application stored in the memory through the transmission device to perform the following steps: updating the concurrency parameters of the target quota node according to the updated available quota and popularity parameter values ​​of the target quota node, including: updating the number of sub-quota of the target quota node according to the relationship between the popularity parameter value and the popularity parameter value threshold of the target quota node; updating the value of the sub-quota according to the updated available quota and the updated number of sub-quota of the target quota node.

[0128] The processor can also call the information and application stored in the memory through the transmission device to perform the following steps: The heat parameter value includes the heat increase rate, which represents the growth rate of the number of transactions. According to the relationship between the heat parameter value of the target quota node and the heat parameter value threshold, the number of sub-quota entries of the target quota node is updated, including: when the heat increase rate is greater than or equal to the upper limit of the heat increase rate, the number of sub-quota entries of the target quota node is increased and the initial heat value of the sub-quota is reset; when the heat increase rate is less than the upper limit of the heat increase rate, the number of sub-quota entries of the target quota node is decreased and the initial heat value of the sub-quota is reset.

[0129] The processor can also call the information and application stored in the memory through the transmission device to perform the following steps: The heat parameter value, including the heat increase rate, is determined by: calculating the sum of the heat values ​​of all sub-quotas of the available quota of the target financial institution within a preset time period to obtain the total heat value; calculating the ratio of the total heat value to the duration of the preset time period to obtain the heat increase rate.

[0130] The processor can also call the information and application stored in the memory through the transmission device to perform the following steps: The heat parameter value includes a heat value representing the number of transactions. According to the relationship between the heat parameter value of the target quota node and the heat parameter value threshold, the number of sub-quota entries of the target quota node is updated, including: obtaining the time required for the total heat value of the target quota node to grow from the initial heat value to the heat value limit in the historical time period, and obtaining the time threshold; after the time threshold is exceeded, if the total heat value of all sub-quota entries of the available quota of the target financial institution has not reached the heat value limit, the number of sub-quota entries of the target quota node is reduced.

[0131] The processor can also invoke information and applications stored in the memory via a transmission device to perform the following steps: Before responding to a user's transaction request for a target financial product initiated at a branch of the target financial institution, the method further includes: allocating the total amount of the target financial product to various levels of quota nodes, wherein each level of quota node includes branches of financial institutions at different levels; for each quota node, distributing the available quota of the quota node into multiple sub-quotas, obtaining the number of sub-quotas and the value of the sub-quotas, setting the initial popularity value of the sub-quotas, and setting the popularity parameter threshold of the quota node.

[0132] The processor can also access information and applications stored in the memory via a transmission device to perform the following steps: responding to a user's transaction request for a target financial product initiated at a branch of the target financial institution, including: querying all sub-limits of the target financial institution's available credit limit to obtain the values ​​of M sub-limits, where M is a positive integer; if the values ​​of the M sub-limits are different, using the sub-limit with the highest value to process and execute the transaction; if the values ​​of the M sub-limits are the same, randomly selecting a sub-limit to process and execute the transaction.

[0133] In this embodiment, in response to a user's transaction request for a target financial product initiated at a branch of a target financial institution, the transaction is executed based on the available credit limit of the target financial institution. The target financial institution concurrently executes different transaction behaviors based on concurrency parameters, which include at least the number of sub-credit limits distributed from the available credit limit and the value of each sub-credit limit. After the transaction is completed, the available credit limit of the target credit limit node corresponding to the target financial institution is updated, and the popularity parameter value of the target credit limit node is calculated. The total credit limit of the target financial product is allocated hierarchically to the credit limit nodes corresponding to each level of financial institution, and the popularity parameter value represents the frequency of transactions using the credit limit. The concurrency parameters of the target credit limit node are updated based on the updated available credit limit and popularity parameter value. By distributing a single credit limit into multiple sub-credit limits and dynamically adjusting the number of sub-credit limits, the purpose of reducing lock waiting and financial system performance pressure during concurrent operations is achieved. This results in improved system response speed and optimized user transaction experience in high-concurrency transaction scenarios, thereby solving the performance bottleneck problem of financial systems caused by high-concurrency transactions of popular credit limits for financial products in related technologies.

[0134] Those skilled in the art will understand that Figure 6 The structure shown is for illustrative purposes only. Electronic devices can also be smartphones, tablets, handheld computers, mobile internet devices (MIDs), PADs, and other terminal devices. Figure 6 This does not limit the structure of the aforementioned electronic device. For example, electronic devices may also include components that are more... Figure 6 The more or fewer components shown (such as network interfaces, display devices, etc.), or having the same Figure 6 The different configurations shown.

[0135] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing the hardware related to the terminal device. The program can be stored in a computer-readable storage medium, which may include: flash drive, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0136] Example 4

[0137] Embodiments of this application also provide a storage medium. Optionally, in this embodiment, the storage medium can be used to store the program code executed by the credit limit processing method for the financial product provided in Embodiment 1.

[0138] Optionally, in this embodiment, the storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any mobile terminal in a group of mobile terminals.

[0139] This application also provides a computer program product that, when executed on a data processing device, is suitable for performing the steps of a credit limit processing method for financial products.

[0140] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0141] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0142] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0143] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0144] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0145] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0146] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for processing the credit limit of a financial product, characterized in that, Applied to financial management systems, including: In response to a user's transaction request for a target financial product initiated at a branch of the target financial institution, the transaction is executed based on the available credit limit of the target financial institution. The target financial institution concurrently executes different transaction behaviors based on concurrency parameters, which include at least the number of sub-credit limits obtained from the available credit limit and the value of the sub-credit limits. After the transaction is completed, the available quota of the target quota node corresponding to the target financial institution is updated, and the heat parameter value of the target quota node is calculated. The total quota of the target financial product is allocated to the quota nodes corresponding to each level of financial institutions. The heat parameter value represents the frequency of using the quota for transactions. The concurrency parameter of the target quota node is updated based on the updated available quota of the target quota node and the popularity parameter value; The heat index parameter value includes the heat index increase rate, which characterizes the growth rate of transaction frequency. Based on the relationship between the heat index parameter value and the heat index parameter value threshold of the target quota node, updating the number of sub-quota entries for the target quota node includes: When the rate of increase in popularity is greater than or equal to the upper limit of the rate of increase in popularity, the number of sub-quota entries of the target quota node is increased, and the initial popularity value of the sub-quota is reset; When the rate of increase in popularity is less than the upper limit of the rate of increase in popularity, the number of sub-quota entries of the target quota node is reduced, and the initial popularity value of the sub-quota is reset. Before responding to a user's transaction request for a target financial product initiated at a branch of the target financial institution, the method further includes: The total quota of the target financial product is allocated to quota nodes at various levels, wherein the quota nodes at various levels include branches of financial institutions at different levels; For each quota node, the available quota of the quota node is distributed into multiple sub-quotas to obtain the number of sub-quotas and the value of the sub-quotas. The initial popularity value of the sub-quotas is set, and the popularity parameter threshold of the quota node is set.

2. The method for processing the credit limit of financial products according to claim 1, characterized in that, Updating the concurrency parameters of the target quota node based on the updated available quota and the popularity parameter value includes: Based on the relationship between the popularity parameter value and the popularity parameter value threshold of the target quota node, update the number of sub-quota entries of the target quota node; The sub-quota value is updated based on the updated available quota and the number of updated sub-quota entries for the target quota node.

3. The method for processing the credit limit of financial products according to claim 1, characterized in that, The heat parameter value, including the rate of heat increase, is determined in the following way: Calculate the sum of the popularity values ​​of all sub-limits of the available credit limit of the target financial institution within a preset time period to obtain the total popularity value; The ratio of the total heat value to the duration of the preset time period is calculated to obtain the heat increase rate.

4. The method for processing the credit limit of financial products according to claim 1, characterized in that, The heat index parameter value includes a heat index value representing the number of transactions. Based on the relationship between the heat index parameter value and the heat index parameter value threshold of the target quota node, updating the number of sub-quota transactions for the target quota node includes: Obtain the time required for the total popularity value of the target quota node during the historical time period to increase from the initial popularity value to the upper limit of the popularity value, and obtain the time threshold; If, after the time threshold is exceeded, the total popularity value of all sub-quotas of the available quota of the target financial institution does not reach the upper limit of the popularity value, the number of sub-quotas of the target quota node will be reduced.

5. The method for processing the credit limit of financial products according to claim 1, characterized in that, Responding to a user's transaction request for a target financial product initiated at a branch of the target financial institution includes: Query all sub-limits of the available credit limit of the target financial institution to obtain the values ​​of M sub-limits, where M is a positive integer; If the values ​​of the M sub-quotas are different, the transaction will be processed using the sub-quota with the highest value. If the values ​​of the M sub-quotas are the same, a sub-quota is randomly selected to process and execute the transaction.

6. A credit limit processing device for a financial product, characterized in that, Applied to financial management systems, including: The transaction module is used to respond to transaction requests for target financial products initiated by users at the branches of the target financial institution, and to execute transaction behaviors based on the available credit limit of the target financial institution. The target financial institution concurrently executes different transaction behaviors based on concurrency parameters, which include at least the number of sub-credit limits obtained from the available credit limit and the value of the sub-credit limits. The heat parameter calculation module is used to update the available quota of the target quota node corresponding to the target financial institution after the transaction is completed, and to calculate the heat parameter value of the target quota node. The total quota of the target financial product is allocated to the quota nodes corresponding to each level of financial institution. The heat parameter value represents the frequency of using the quota for transactions. The concurrent parameter update module is used to update the concurrent parameters of the target quota node according to the updated available quota of the target quota node and the heat parameter value; The heat index parameter value includes the heat index increase rate, which characterizes the growth rate of transaction frequency. Based on the relationship between the heat index parameter value and the heat index parameter value threshold of the target quota node, updating the number of sub-quota entries for the target quota node includes: When the rate of increase in popularity is greater than or equal to the upper limit of the rate of increase in popularity, the number of sub-quota entries of the target quota node is increased, and the initial popularity value of the sub-quota is reset; When the rate of increase in popularity is less than the upper limit of the rate of increase in popularity, the number of sub-quota entries of the target quota node is reduced, and the initial popularity value of the sub-quota is reset. Before responding to a transaction request for a target financial product initiated by a user at a branch of the target financial institution, the device further includes: The total quota of the target financial product is allocated to quota nodes at various levels, wherein the quota nodes at various levels include branches of financial institutions at different levels; For each quota node, the available quota of the quota node is distributed into multiple sub-quotas to obtain the number of sub-quotas and the value of the sub-quotas. The initial popularity value of the sub-quotas is set, and the popularity parameter threshold of the quota node is set.

7. A computer program product, characterized in that, The method includes a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, implements the credit limit processing method for the financial product according to any one of claims 1 to 5.

8. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to execute the quota processing method for the financial product according to any one of claims 1 to 5 through the computer program.

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