Financial activity task matching method and device and electronic equipment

Abstract

The invention discloses a financial activity task matching method and device and electronic equipment, and relates to the field of financial science and tech, and the matching method comprises the steps: obtaining preset website coordinate data of all preset websites and coordinate data of all preset clients from a preset spatial database; for each preset website, determining a spatial distance from the preset website to each address coordinate based on the preset website coordinate data and all coordinate data; based on the spatial distance, determining a target customer set of each preset website, and generating an activity strategy for each target customer in the target customer set; and on the basis of a preset allocation algorithm, matching the plurality of financial activity tasks corresponding to the activity strategy with target business personnel of a preset website to obtain a corresponding relationship between the financial activity tasks and the target business personnel. According to the invention, the technical problem of resource waste caused by low financial task allocation accuracy in the prior art is solved.

Description

Technical Field

[0001] This invention relates to the field of financial technology, and more specifically, to a method, apparatus, and electronic device for matching financial activity tasks. Background Technology

[0002] Currently, when conducting financial activities targeting businesses, financial institutions primarily rely on manual, experience-based judgment and generalized activity strategies based on basic business information (size, industry, etc.). However, under this model, account managers must manually match business addresses with the coverage areas of their service outlets, and the allocation of account managers depends on subjective expert assessments. This not only reduces the speed and flexibility of business execution but may also lead to resource misallocation and waste.

[0003] There is currently no effective solution to the above problems. Summary of the Invention

[0004] This invention provides a method, apparatus, and electronic device for matching financial activity tasks, in order to at least solve the technical problem of low accuracy in financial task allocation, which leads to resource waste in related technologies.

[0005] According to one aspect of the embodiments of this application, a method for matching financial activity tasks is provided, comprising: obtaining preset branch coordinate data of all preset branches and coordinate data of all preset customers from a preset spatial database, wherein the preset branches are preset branches of financial institutions pre-built for handling financial activity tasks for customers, and the preset customers are customers pre-registered with the financial institution, and the coordinate data includes: the address coordinates of the preset customers when they register; for each preset branch, determining the spatial distance from the preset branch to each address coordinate based on the preset branch coordinate data and all coordinate data; determining the target customer set of each preset branch based on the spatial distance, and generating an activity strategy for each target customer in the target customer set, wherein the activity strategy corresponds to multiple financial activity tasks; and matching the multiple financial activity tasks corresponding to the activity strategy with the target business personnel of the preset branch based on a preset allocation algorithm to obtain the correspondence between financial activity tasks and target business personnel, wherein each preset branch handles financial activity tasks for each target customer of the preset branch based on the correspondence.

[0006] Furthermore, before obtaining the coordinate data of all preset outlets and the coordinate data of all preset customers from the preset spatial database, the process includes: obtaining the registration address information of multiple preset customers and cleaning the registration address information to obtain cleaned address information; obtaining the registration address information of multiple preset outlets and cleaning the registration address information to obtain cleaned preset outlet address information; converting the cleaned address information into coordinate data based on geocoding technology, and converting the cleaned preset outlet address information into preset outlet coordinate data; and adding the coordinate data and the preset outlet coordinate data to the preset spatial database.

[0007] Furthermore, the step of determining the spatial distance from the preset network point to each address coordinate based on the preset network point coordinate data and all coordinate data includes: using preset spatial indexing technology to filter the coordinate data of multiple preset customers based on the preset network point coordinate data to obtain a target coordinate data set; and determining the spatial distance from the preset network point to each address coordinate based on the preset network point coordinate data and each target coordinate data in the target coordinate data set.

[0008] Furthermore, the step of determining the target customer set for each preset outlet based on spatial distance includes: for each preset outlet, determining a preset distance threshold for spatial distance; comparing the spatial distance with the preset distance threshold, and if the spatial distance is less than the preset distance threshold, determining the preset customer corresponding to the spatial distance as the target customer; and adding the target customer to the target customer set.

[0009] Furthermore, after adding target customers to the target customer set, the process includes: generating a heatmap of the radiation range of the preset outlets based on all preset outlet coordinate data, all target customer coordinate data, and all spatial distances; when a new customer registration is detected, obtaining the new customer's registration address information and converting the registration address information to obtain the new customer's coordinate data, wherein the new customer is a customer other than the target customers in the preset outlet radiation range heatmap; calculating the spatial distance between the new customer's address coordinates and all preset outlets, and updating the preset outlet radiation range heatmap; or, when a change in the coordinate data of preset outlets is detected in the preset spatial database, re-determining the target customer set of the preset outlets, and updating the preset outlet radiation range heatmap.

[0010] Furthermore, based on a preset allocation algorithm, the steps of matching multiple financial activity tasks corresponding to the activity strategy with target business personnel at preset branches to obtain the correspondence between financial activity tasks and target business personnel include: for each preset branch, determining the preset task execution priority for each target customer, and controlling the preset branch to handle the financial activity tasks corresponding to the target customer according to the preset task execution priority, wherein the preset branch includes: multiple business personnel; determining the business needs of each target customer, and matching all financial activity tasks corresponding to the target customer with all business personnel at the preset branch based on the business needs to obtain a matching score; for each target customer, determining an initial set of business personnel based on all matching scores; using the preset allocation algorithm, matching all financial activity tasks corresponding to each target customer with all initial business personnel in the initial set of business personnel to obtain a matching result, wherein the matching result is used to indicate the correspondence between financial activity tasks and target business personnel.

[0011] Furthermore, the step of determining the preset task execution priority for each target customer includes: determining the industry category to which the target customer belongs, and determining the preset adjustment coefficient for the target customer based on the industry category; determining the route length from the preset outlet to the address coordinates of the target customer; and determining the preset task execution priority based on the preset adjustment coefficient and the route length.

[0012] Furthermore, after matching multiple financial activity tasks corresponding to the activity strategy with target business personnel at preset branches based on a preset allocation algorithm to obtain the correspondence between financial activity tasks and target business personnel, the process also includes: monitoring the current task volume of each target business personnel; obtaining historical task processing data for each target business personnel and calculating the historical average daily task volume of the target business personnel based on the historical task processing data; calculating the task saturation value based on the current task volume and the historical average daily task volume, wherein the task saturation value corresponds to a task control level, and the task control level corresponds to a task control strategy; and processing the financial activity tasks based on the task control strategy.

[0013] According to another aspect of the embodiments of this application, a matching device for financial activity tasks is also provided, comprising: a first acquisition unit, configured to acquire preset branch coordinate data of all preset branches and coordinate data of all preset customers from a preset spatial database, wherein the preset branches are preset branches of financial institutions pre-built for handling financial activity tasks for customers, and the preset customers are customers pre-registered with the financial institution, and the coordinate data includes: the address coordinates of the preset customers when they register; a first determination unit, configured to determine the spatial distance from each preset branch to each address coordinate based on the preset branch coordinate data and all coordinate data; a second determination unit, configured to determine the target customer set of each preset branch based on the spatial distance, and generate an activity strategy for each target customer in the target customer set, wherein the activity strategy corresponds to multiple financial activity tasks; and a first matching unit, configured to match the multiple financial activity tasks corresponding to the activity strategy with the target business personnel of the preset branches based on a preset allocation algorithm to obtain the correspondence between the financial activity tasks and the target business personnel, wherein each preset branch handles financial activity tasks for each target customer of the preset branch based on the correspondence.

[0014] Furthermore, the matching device for financial activity tasks includes: a first acquisition module, used to acquire the registration address information of multiple preset customers before acquiring the preset branch coordinate data of all preset branches and the coordinate data of all preset customers from the preset spatial database, and to clean the registration address information to obtain cleaned address information; a second acquisition module, used to acquire the preset branch registration address information of multiple preset branches, and to clean the preset branch registration address information to obtain cleaned preset branch address information; a first conversion module, used to convert the cleaned address information into coordinate data based on geocoding technology, and to convert the cleaned preset branch address information into preset branch coordinate data; and a first addition module, used to add the coordinate data and the preset branch coordinate data into the preset spatial database.

[0015] Furthermore, the first determining unit includes: a first filtering module, used to filter the coordinate data of multiple preset customers based on preset network point coordinate data and using preset spatial indexing technology to obtain a target coordinate data set; and a first determining module, used to determine the spatial distance from the preset network point to each address coordinate based on the preset network point coordinate data and each target coordinate data in the target coordinate data set.

[0016] Furthermore, the second determining unit includes: a second determining module, used to determine a preset distance threshold for spatial distance for each preset outlet; a first comparison module, used to compare the spatial distance with the preset distance threshold, and if the spatial distance is less than the preset distance threshold, to determine the preset customer corresponding to the spatial distance as the target customer; and a second adding module, used to add the target customer to the target customer set.

[0017] Furthermore, the matching device for financial activity tasks also includes: a first generation module, used to generate a heat map of the radiation range of preset outlets based on all preset outlet coordinate data, all target customer coordinate data, and all spatial distances after adding target customers to the target customer set; a third acquisition module, used to acquire the registration address information of the new customer when a new customer registration is detected, and to convert the registration address information to obtain the coordinate data of the new customer, wherein the new customer is a customer other than the target customer in the preset outlet radiation range heat map; a first update module, used to calculate the spatial distance between the address coordinates of the new customer and all preset outlets, and to update the preset outlet radiation range heat map; and a second update module, used to redetermine the target customer set of the preset outlets and update the preset outlet radiation range heat map when a change in the coordinate data of the preset outlets in the preset spatial database is detected.

[0018] Further, the first matching unit includes: a third determining module, used to determine the preset task execution priority for each target customer for each preset branch, and control the preset branch to handle the financial activity tasks corresponding to the target customer according to the preset task execution priority, wherein the preset branch includes: multiple business personnel; a fourth determining module, used to determine the business needs of each target customer, and match all financial activity tasks corresponding to the target customer with all business personnel of the preset branch based on the business needs to obtain a matching score; a fifth determining module, used to determine an initial set of business personnel for each target customer based on all matching scores; and a first matching module, used to match all financial activity tasks corresponding to each target customer with all initial business personnel in the initial set of business personnel using a preset allocation algorithm to obtain a matching result, wherein the matching result is used to indicate the correspondence between financial activity tasks and target business personnel.

[0019] Furthermore, the third determining module includes: a first determining submodule, used to determine the industry category to which the target customer belongs, and based on the industry category, to determine the preset adjustment coefficient of the target customer; a second determining submodule, used to determine the route length from the preset outlet to the address coordinates of the target customer; and a third determining submodule, used to determine the preset task execution priority based on the preset adjustment coefficient and the route length.

[0020] Furthermore, the matching device for financial activity tasks also includes: a first monitoring module, used to match multiple financial activity tasks corresponding to the activity strategy with target business personnel of a preset branch based on a preset allocation algorithm, and after obtaining the correspondence between financial activity tasks and target business personnel, monitor the current task volume of each target business personnel; a first calculation module, used to acquire historical task processing data of each target business personnel, and calculate the historical average daily task processing volume of the target business personnel based on the historical task processing data; a second calculation module, used to calculate a task saturation value based on the current task volume and the historical average daily task processing volume, wherein the task saturation value corresponds to a task control level, and the task control level corresponds to a task control strategy; and a first processing module, used to process the financial activity tasks based on the task control strategy.

[0021] According to another aspect of the embodiments of this application, a computer program product is also provided, including a non-volatile computer-readable storage medium storing a computer program, which, when executed by a processor, implements the matching method for any of the above-mentioned financial activity tasks.

[0022] According to another aspect of the embodiments of this application, an electronic device is also provided, including one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement the matching method for any of the above-described financial activity tasks.

[0023] In this invention, the coordinate data of all preset outlets and the coordinate data of all preset customers are obtained from a preset spatial database. For each preset outlet, the spatial distance from the preset outlet to each address coordinate is determined based on the preset outlet coordinate data and all coordinate data. Based on the spatial distance, the target customer set of each preset outlet is determined, and an activity strategy for each target customer in the target customer set is generated. Based on a preset allocation algorithm, multiple financial activity tasks corresponding to the activity strategy are matched with the target business personnel of the preset outlet to obtain the correspondence between financial activity tasks and target business personnel. This solves the technical problem of low accuracy in financial task allocation and resource waste in related technologies.

[0024] In this invention, the preset branches are pre-built branches of financial institutions used to handle financial activities for customers. The preset customers are customers pre-registered with the financial institution. First, the preset branch coordinate data and the coordinate data of all preset customers can be obtained from the preset spatial database. For each preset branch, based on the preset branch coordinate data and all coordinate data, spatial calculation technology is used to calculate the spatial distance between the preset branch and the address coordinates of all customers one by one. Then, based on the spatial distance, the customer group (i.e., the target customer set) of each preset branch is selected, and an activity strategy is generated for each target customer in the target customer set. This activity strategy corresponds to multiple financial activity tasks. Then, based on the preset allocation algorithm, the multiple financial activity tasks corresponding to the activity strategy are matched with the target business personnel of the preset branch to obtain the correspondence between financial activity tasks and target business personnel. Based on the correspondence, financial activity tasks are handled for each target customer of the preset branch. This not only improves the accuracy of customer reach and thus efficiently serves the target customers, but also accurately allocates financial tasks to business personnel, thereby achieving the technical effect of improving resource utilization. Attached Figure Description

[0025] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this invention, illustrate exemplary embodiments of the invention and are used to explain the invention, but do not constitute an undue limitation of the invention. In the drawings:

[0026] Figure 1 A hardware structure block diagram of a computer terminal (or mobile device) for implementing a matching method for financial activity tasks is shown.

[0027] Figure 2 This is a flowchart of a matching method for financial activity tasks according to Embodiment 1 of this application;

[0028] Figure 3 This is a schematic diagram of an optional matching device for financial activity tasks according to an embodiment of this application;

[0029] Figure 4 This is a structural block diagram of an electronic device according to an embodiment of this application. Detailed Implementation

[0030] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0031] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention 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 the invention 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 a 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.

[0032] It should be noted that all related information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, and displayed data) collected and involved in this invention 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 comply with the relevant laws, regulations, and standards of the relevant regions, necessary confidentiality measures have been taken, and it does not violate public order and good morals. Corresponding operation entry points are provided for users to choose to authorize or refuse. For example, this system has an interface with relevant users or organizations. Before obtaining relevant information, a request to obtain the information needs to be sent to the aforementioned user or organization through the interface, and the relevant information is obtained only after receiving consent from the aforementioned user or organization.

[0033] In this invention, by integrating the data processing capabilities of the data platform (including data standardization and cleaning, efficient geocoding conversion, and construction of a detailed spatial database) with spatial distance calculation technology (calculating the geographical distance between enterprises and financial institution branches), the reach to customers is improved. Furthermore, through an automated task allocation mechanism, accurate matching of financial activity tasks is achieved, reducing the time cost of manual matching. In addition, through a real-time update and dynamic optimization mechanism, geographical information and customer status are continuously tracked and updated, improving the response rate.

[0034] The present invention will now be described in detail with reference to various embodiments.

[0035] Example 1

[0036] According to an embodiment of this application, an embodiment of a matching method for financial activity tasks 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. Also, 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.

[0037] 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 A hardware block diagram of a computer terminal (or mobile device) for implementing a matching method for financial activity tasks is shown. Figure 1 As shown, computer terminal 10 (or mobile device) may include one or more ( Figure 1 The processor 102 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.), a memory 104 for storing data, and a transmission device 106 for communication functions may also be included. In addition, it may include: a display, a keyboard, a cursor control device, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of a BUS bus), a network interface, a power supply, and / or a camera, wherein the network interface can be connected to wired and / or wireless networks. 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.

[0038] 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).

[0039] 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 matching method for financial activity tasks 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 matching method for financial activity tasks. 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.

[0040] 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.

[0041] The display may be, for example, a touchscreen liquid crystal display (LCD) that allows the user to interact with the user interface of the computer terminal 10 (or mobile device).

[0042] Under the aforementioned operating environment, this application provides the following: Figure 2 The matching method for financial activity tasks is shown. Figure 2 This is a flowchart of the matching method for financial activity tasks according to Embodiment 1 of this application, as follows: Figure 2 As shown, the method includes the following steps:

[0043] Step S201: Obtain the coordinate data of all preset branches and the coordinate data of all preset customers from the preset spatial database. The preset branches are preset branches of financial institutions that are pre-built and used to handle financial activities for customers. The preset customers are customers who have registered with the financial institution in advance. The coordinate data includes the address coordinates of the preset customers when they register.

[0044] In this embodiment of the invention, the coordinate data of all preset outlets (i.e., the latitude and longitude coordinates of the financial institution outlets) and the coordinate data of all preset customers (customers who have registered with the financial institution in advance, such as enterprises) are obtained from the preset spatial database (a pre-established database, including all preset outlet coordinate data and preset customer coordinate data).

[0045] Step S202: For each preset network point, based on the preset network point coordinate data and all coordinate data, determine the spatial distance from the preset network point to each address coordinate.

[0046] In this embodiment of the invention, based on the preset network point coordinate data and all coordinate data, the spatial distance from each preset network point to the address coordinates of all preset customers is calculated one by one. For example, the spatial distance can be calculated using the Haversine formula (used to calculate the spherical distance between two points on the Earth's surface).

[0047] Alternatively, for non-high-precision scenarios, spatial distances can be calculated using planar approximation formulas (such as the Pythagorean theorem) to improve calculation speed.

[0048] Step S203: Based on spatial distance, determine the target customer set for each preset branch and generate an activity strategy for each target customer in the target customer set. The activity strategy corresponds to multiple financial activity tasks.

[0049] In this embodiment of the invention, spatial distance can be used to determine the coverage area of ​​a service point and potential target customers (i.e., the target customer set for each preset service point). For example, for a service point A, the distance between it and all customers such as Company B and Company C can be calculated to determine which customers are within its 3-kilometer radius. Then, an activity strategy is generated for each target customer in the target customer set. The activity strategy corresponds to multiple financial activity tasks, which may include, but are not limited to, financial consulting, providing customized credit solutions, and conducting door-to-door services.

[0050] Step S204: Based on the preset allocation algorithm, match multiple financial activity tasks corresponding to the activity strategy with the target business personnel of the preset outlets to obtain the correspondence between financial activity tasks and target business personnel. Each preset outlet handles financial activity tasks for each target customer of the preset outlet based on the correspondence.

[0051] In this embodiment of the invention, a preset allocation algorithm, such as a genetic algorithm, is used to assign financial activity tasks related to the activity strategy to the most suitable target business personnel (such as account managers), thereby obtaining the correspondence between financial activity tasks and target business personnel (such as a manufacturing account manager handling financial activity tasks related to manufacturing enterprises).

[0052] Optionally, intelligent grouping of target customers can also be achieved based on the K-means algorithm (a clustering algorithm). First, all target customers within a 2-kilometer radius of the same cluster center can be filtered out. The financial activity tasks corresponding to target customers in the same cluster center are packaged and processed to generate access paths. When handling financial activity tasks, business personnel can prioritize target customers located near the same cluster center, shorten travel time, and improve task processing efficiency.

[0053] In summary, firstly, the coordinates of all preset branches and customers are obtained from a preset spatial database. Then, using calculation methods such as the Haversine formula, the spatial distance from each preset branch to the preset customer address coordinates is evaluated to determine the target customer set. Based on the spatial distance and customer attributes, a customized activity strategy is generated for each target customer. This activity strategy corresponds to multiple financial activity tasks. Next, based on a preset allocation algorithm, the activity tasks are accurately matched with the target business personnel at the preset branches, improving the work efficiency of account managers, achieving optimized resource allocation, and thus solving the technical problem of low accuracy in financial task allocation leading to resource waste in related technologies.

[0054] To accurately obtain the preset spatial database, the matching method for financial activity tasks provided in Embodiment 1 of this application obtains the registration address information of multiple preset customers and cleans the registration address information to obtain cleaned address information; obtains the preset branch registration address information of multiple preset branches and cleans the preset branch registration address information to obtain cleaned preset branch address information; based on geocoding technology, the cleaned address information is converted into coordinate data, and the cleaned preset branch address information is converted into preset branch coordinate data; the coordinate data and the preset branch coordinate data are added to the preset spatial database.

[0055] In this embodiment of the invention, multiple preset customer registration address information (i.e., the address provided by the customer during registration) can be obtained from the internal database of a financial institution or an external platform. The registration address information is then cleaned to obtain cleaned address information. At the same time, multiple preset branch registration address information, i.e., the address of the financial institution's branch when it was constructed, is also required. The preset branch registration address information is then cleaned to obtain cleaned preset branch address information. By standardizing the address format and removing invalid or duplicate data, the accuracy of subsequent geocoding is ensured.

[0056] In this embodiment of the invention, based on geocoding technology, the cleaning address information is converted into coordinate data (represented in the form of latitude and longitude). For example, the customer address of No. 1, C Road, B District, City A is converted into latitude and longitude coordinates (39.904989, 116.455265) through geocoding technology. At the same time, the cleaning preset network address information is converted into preset network coordinate data, and the coordinate data and the preset network coordinate data are added to the preset spatial database.

[0057] In order to accurately determine the spatial distance from the preset branch to each address coordinate, in the matching method for financial activity tasks provided in Embodiment 1 of this application, based on the preset branch coordinate data, a preset spatial indexing technique is used to filter the coordinate data of multiple preset customers to obtain a target coordinate data set; based on the preset branch coordinate data and each target coordinate data in the target coordinate data set, the spatial distance from the preset branch to each address coordinate is determined.

[0058] In this embodiment of the invention, by integrating preset spatial indexing technologies, such as R-Tree (a hierarchical index data structure for spatial data structures) or Geohash (a technology for encoding geographic location information into short strings), the process of filtering coordinate data for multiple preset customers is optimized. Spatial indexing technology can reduce the direct comparison of large amounts of data when performing spatial queries by dividing or encoding geographic coordinates, thereby improving search efficiency. In this way, customer coordinate data (i.e., target coordinate data set) related to a specific preset location can be quickly located in a large preset spatial database. For example, for a preset location N1, if its coverage rule is set to a radius of 3 kilometers, the preset spatial indexing technology can be used to filter out all customer coordinate data within a 3-kilometer radius of N1, forming a target coordinate data set. Then, based on the preset location coordinate data and each target coordinate data in the target coordinate data set, the spatial distance from the preset location to each address coordinate is determined using the Haversine formula equidistant calculation method.

[0059] In order to accurately obtain the target customer set, in the matching method for financial activity tasks provided in Embodiment 1 of this application, for each preset branch, a preset distance threshold is determined; the spatial distance is compared with the preset distance threshold, and if the spatial distance is less than the preset distance threshold, the preset customer corresponding to the spatial distance is determined as the target customer; the target customer is added to the target customer set.

[0060] In this embodiment of the invention, for each preset network point, a preset distance threshold for spatial distance needs to be set first (the threshold can be set based on different strategies, such as expanding the service range to 5 kilometers for strategic customers (such as large enterprises with more than 500 employees), while other customers can be set to within 3 kilometers). The spatial distance is then compared with the preset distance threshold. If the spatial distance is less than the preset distance threshold, the preset customer corresponding to the spatial distance is identified as the target customer, and the target customer is added to the target customer set.

[0061] Optionally, the distance between each preset outlet can also be determined. If the distance between preset outlets is small (i.e. there is a dense area of ​​outlets), for each preset outlet, the customer closest to that preset outlet can be identified as the target customer of that outlet.

[0062] To improve the accuracy of the preset branch coverage heatmap, in the financial activity task matching method provided in Embodiment 1 of this application, a preset branch coverage heatmap is generated based on all preset branch coordinate data, all target customer coordinate data, and all spatial distances. When a new customer registration is detected, the new customer's registration address information is obtained and converted to obtain the new customer's coordinate data. The new customer is a customer other than the target customers in the preset branch coverage heatmap. The spatial distance between the new customer's address coordinates and all preset branches is calculated, and the preset branch coverage heatmap is updated. Alternatively, when a change in the preset branch coordinate data is detected in the preset spatial database, the target customer set for the preset branches is redefined, and the preset branch coverage heatmap is updated.

[0063] In this embodiment of the invention, a heat map of the radiation range of the preset outlets is generated based on all preset outlet coordinate data, all target customer coordinate data and all spatial distances (i.e., a circular coverage area with a dynamic radius is drawn with the outlet as the center, which intuitively shows the service radiation range of the outlet). The heat map shows the distribution of customer density in the coverage area of ​​each outlet in a visual way. The color depth or the size of the color spot can reflect the number or value of customers.

[0064] For example, by calculating the coordinates of all target customers within the coverage area of ​​the preset outlet N1 and the spatial distance between them, a heat map of the radiation range of N1 can be generated. For example, the area within 3 kilometers around N1 is represented by dark red to indicate densely populated areas (i.e., areas with a large number of businesses), while the area beyond 5 kilometers is represented by light blue to indicate sparsely populated areas.

[0065] In this embodiment of the invention, the map area can be divided into uniform grid units (e.g., 100m × 100m), and the customer coverage rate within the grid (i.e., the proportion of financial institution customers to the total number of enterprises) can be calculated. Grids with high coverage rates will have lower transparency (close to opaque) on the heat map, indicating that these areas have been widely covered by the financial institution, while areas with low coverage rates will have higher transparency (close to transparent), and enterprises in these areas may require more development and attention. The relationship between enterprise location and branch coverage can be updated in real time.

[0066] Optionally, a layer overlay function can be set to enhance the visualization of the location and service area of ​​the service points. By adding Icon Markers (a type of graphic element used to identify specific locations or points of interest) to the preset service point radiation range heat map, the location of each service point is clearly marked. Detailed information about the service points can be obtained simply by clicking the icon, improving the convenience of information retrieval.

[0067] In this embodiment of the invention, when a new customer registration is detected, the new customer's registration address information is obtained, and the registration address information is converted using geocoding technology to obtain the new customer's coordinate data. The spatial distance between the new customer's address coordinates and all preset network points is calculated, and the heat map of the preset network point radiation range is updated (e.g., adjusting the color gradient of the preset network point radiation range heat map to reflect the change in customer distribution within the coverage area after the new customer joins). Alternatively, data change events are captured through database triggers or message queues. When a change in the coordinate data of preset network points is detected in the preset spatial database, only the grids or network points associated with the changed data are locally recalculated (i.e., the spatial distance between the coordinate data of all target customers and the changed preset network points is recalculated, and the target customer set of the preset network points is redefined), and the heat map of the preset network point radiation range is updated. This flexibly adapts to changes in network point locations and maintains the real-time accuracy of the heat map.

[0068] Optionally, full data synchronization calculation and updates can be performed at fixed times each day to ensure the accuracy of baseline data, and the heatmap can be updated incrementally every 30 minutes to balance real-time performance and system load.

[0069] Optionally, to improve computing speed, the map area can be divided into pieces, and different map area pieces can be assigned to different computing nodes for parallel computing.

[0070] To accurately determine the correspondence between financial activity tasks and target business personnel, the financial activity task matching method provided in Embodiment 1 of this application involves: for each preset branch, determining the preset task execution priority for each target customer, and controlling the preset branch to handle the financial activity tasks corresponding to the target customer based on the preset task execution priority. The preset branch includes multiple business personnel. The business needs of each target customer are determined, and based on these needs, all financial activity tasks corresponding to the target customer are matched with all business personnel at the preset branch to obtain a matching score. For each target customer, an initial set of business personnel is determined based on all matching scores. A preset allocation algorithm is used to match all financial activity tasks corresponding to each target customer with all initial business personnel in the initial set of business personnel to obtain a matching result. The matching result indicates the correspondence between the financial activity tasks and the target business personnel.

[0071] In this embodiment of the invention, for each preset branch, the preset task execution priority of each target customer can be determined based on the route length between the preset branch and the target customer and the industry to which the target customer belongs. Based on the preset task execution priority, the preset branch is controlled to handle the financial activity tasks corresponding to the target customer. For example, the business personnel of the preset branch will give priority to serving enterprises within 3 kilometers of the branch.

[0072] In this embodiment of the invention, the business needs of each target customer (such as loan needs, wealth management needs, etc.) are determined. Based on the business needs, all financial activity tasks corresponding to the target customer are matched with all business personnel of a preset branch (for example, the customer's business needs and the business personnel's professional abilities can be numerically and vectorized respectively, and the cosine similarity between the customer's demand vector and the business personnel's professional ability vector can be calculated to measure the matching degree between the customer and the business personnel). A matching score is obtained. For each target customer, an initial set of business personnel is determined based on all matching scores (for example, if the matching score is greater than or equal to 0.7, a matching flag is triggered, and the business personnel corresponding to the matching score are added to the initial set of business personnel). Then, a preset allocation algorithm (such as a genetic algorithm) is used to match all financial activity tasks corresponding to each target customer with all initial business personnel in the initial set of business personnel to obtain the correspondence between financial activity tasks and target business personnel.

[0073] Optionally, the system can also track the onboarding time of sales personnel, and automatically match strategic clients with sales personnel who have been with the company for a longer period.

[0074] Optionally, the allocation of financial activity tasks and target business personnel can be recalculated periodically.

[0075] In order to accurately determine the execution priority of the preset task, in the matching method for financial activity tasks provided in Embodiment 1 of this application, the industry category to which the target customer belongs is determined, and based on the industry category, a preset adjustment coefficient for the target customer is determined; the route length from the preset branch to the address coordinates of the target customer is determined; and the execution priority of the preset task is determined based on the preset adjustment coefficient and the route length.

[0076] In this embodiment of the invention, the target customer's industry code, main business description, etc., can be analyzed to classify them into their respective industry categories, and a preset adjustment coefficient (e.g., based on the industry category) can be determined for the target customer. ,manufacturing =0.3, service industry =0.5), determine the route length from the preset outlet to the target customer's address coordinates, and based on the preset adjustment coefficient and route length (L), determine the preset task execution priority (i.e., P, By dynamically adjusting task priorities based on industry characteristics and route length, service resources can be precisely allocated.

[0077] To accurately process financial activity tasks, the matching method for financial activity tasks provided in Embodiment 1 of this application monitors the current task volume of each target business personnel; obtains historical task processing data for each target business personnel, and calculates the historical average daily task volume of the target business personnel based on the historical task processing data; calculates a task saturation value based on the current task volume and the historical average daily task volume, wherein the task saturation value corresponds to a task control level, and the task control level corresponds to a task control strategy; and processes the financial activity tasks based on the task control strategy.

[0078] In this embodiment of the invention, the current workload of each target business personnel can be continuously monitored to dynamically assess their work status, prevent task overload, and acquire historical task processing data for each target business personnel (including the number, type, and completion time of tasks completed over a period of time, reflecting the business personnel's work efficiency and task processing capabilities). Based on the historical task processing data, the historical average daily task processing volume of the target business personnel is calculated. Then, based on the current task volume and the historical average daily task processing volume, a task saturation value (i.e., current task volume / historical average daily task processing volume, reflecting the degree of matching between the business personnel's current workload and their normal processing capabilities) is calculated. According to the task saturation value, it can be mapped to the corresponding task control level. The task control level corresponds to a specific task control strategy, and the financial activity tasks are processed based on the task control strategy. For example, when the saturation value exceeds 0.9, a high-intensity work state is entered, and task restriction measures can be taken to reduce the allocation of new activity tasks to avoid overload; when the saturation value is between 0.76 and 0.9, a collaboration mechanism is activated; when the saturation value is less than 0.75, activity tasks are allocated normally.

[0079] Optionally, customers can be stratified by spatial relationship. For example, customers ≤1 km from the service point (walkable, high-frequency service target) are classified as Class A customers, customers 1-3 km away (covered by electric vehicles, key maintenance target) are classified as Class B customers, and customers 3-5 km away (requires targeted expansion and supporting transportation solutions) are classified as Class C customers.

[0080] An emergency task priority mechanism can also be set up. This requires first assessing the urgency of the task, the economic benefits of completing it, and the timeliness of completion. For example, priority P1 = 0.4 × customer level + 0.3 × urgency + 0.2 × expected revenue + 0.1 × timeliness coefficient. When P is greater than 0.8, a red alert is triggered, and the task is automatically assigned to a sales representative.

[0081] Optionally, by collecting real-time data on account managers' activity trajectories, task completion rates, and customer feedback, and combining this with deep learning models to analyze task completion effectiveness (such as conversion rates and response times), inefficient processes can be automatically identified and optimization strategies can be triggered (such as prioritizing high-conversion-rate customers), updating the customer tagging system, and adjusting the task allocation algorithm, thereby continuously improving the accuracy of activity tasks and resource utilization.

[0082] The financial activity task matching method provided in this application embodiment can ensure real-time adjustment of the branch coverage area by constructing geocoding, spatial database, and rapid response when new customers register and branch locations change. Based on distance attenuation and industry adjustment coefficient, it can dynamically calculate task execution priority. In addition, it can also use intelligent matching of financial activity tasks and business personnel. By monitoring task volume and historical processing data, it can calculate task saturation and implement control strategies, optimize service processes, improve the work efficiency of business personnel and customer satisfaction, accurately reach target customers, efficiently allocate service resources, and improve resource utilization efficiency.

[0083] 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.

[0084] Example 2

[0085] This application also provides a matching device for financial activity tasks. It should be noted that the matching device for financial activity tasks in this application can be used to execute the matching method for financial activity tasks provided in this application. The matching device for financial activity tasks provided in this application will be described below.

[0086] According to an embodiment of this application, an apparatus for implementing the matching method for the above-described financial activity tasks is also provided. Figure 3 This is a schematic diagram of an optional financial activity task matching device according to an embodiment of this application, such as... Figure 3 As shown, the matching device for the financial activity task may include: a first acquisition unit 30, a first determination unit 31, a second determination unit 32, and a first matching unit 33.

[0087] The first acquisition unit 30 is used to acquire the coordinate data of all preset outlets and the coordinate data of all preset customers from the preset spatial database. The preset outlets are preset outlets of financial institutions that are pre-built and used to handle financial activities for customers. The preset customers are customers who have registered with the financial institution in advance. The coordinate data includes the address coordinates of the preset customers when they register.

[0088] The first determining unit 31 is used to determine the spatial distance from the preset network point to each address coordinate based on the preset network point coordinate data and all coordinate data for each preset network point.

[0089] The second determining unit 32 is used to determine the target customer set of each preset branch based on spatial distance, and generate an activity strategy for each target customer in the target customer set, wherein the activity strategy corresponds to multiple financial activity tasks.

[0090] The first matching unit 33 is used to match multiple financial activity tasks corresponding to the activity strategy with the target business personnel of the preset outlets based on the preset allocation algorithm, so as to obtain the correspondence between the financial activity tasks and the target business personnel. Each preset outlet handles financial activity tasks for each target customer of the preset outlet based on the correspondence.

[0091] The financial activity task matching device provided in this application embodiment can obtain the preset network coordinate data of all preset network points and the coordinate data of all preset customers from the preset spatial database through the first acquisition unit 30. For each preset network point, the first determination unit 31 can determine the spatial distance from the preset network point to each address coordinate based on the preset network point coordinate data and all coordinate data. The second determination unit 32 can determine the target customer set of each preset network point based on the spatial distance and generate an activity strategy for each target customer in the target customer set. The first matching unit 33 can match multiple financial activity tasks corresponding to the activity strategy with the target business personnel of the preset network point based on the preset allocation algorithm to obtain the correspondence between financial activity tasks and target business personnel.

[0092] Optionally, the matching device for financial activity tasks includes: a first acquisition module, used to acquire the registration address information of multiple preset customers before acquiring the preset branch coordinate data of all preset branches and the coordinate data of all preset customers from the preset spatial database, and to clean the registration address information to obtain cleaned address information; a second acquisition module, used to acquire the preset branch registration address information of multiple preset branches, and to clean the preset branch registration address information to obtain cleaned preset branch address information; a first conversion module, used to convert the cleaned address information into coordinate data based on geocoding technology, and to convert the cleaned preset branch address information into preset branch coordinate data; and a first addition module, used to add the coordinate data and the preset branch coordinate data into the preset spatial database.

[0093] Optionally, the first determining unit includes: a first filtering module, used to filter the coordinate data of multiple preset customers based on preset network point coordinate data and using preset spatial indexing technology to obtain a target coordinate data set; and a first determining module, used to determine the spatial distance from the preset network point to each address coordinate based on the preset network point coordinate data and each target coordinate data in the target coordinate data set.

[0094] Optionally, the second determining unit includes: a second determining module, used to determine a preset distance threshold for spatial distance for each preset outlet; a first comparison module, used to compare the spatial distance with the preset distance threshold, and if the spatial distance is less than the preset distance threshold, to determine the preset customer corresponding to the spatial distance as the target customer; and a second adding module, used to add the target customer to the target customer set.

[0095] Optionally, the matching device for financial activity tasks further includes: a first generation module, used to generate a heat map of the radiation range of preset outlets based on all preset outlet coordinate data, all target customer coordinate data, and all spatial distances after adding target customers to the target customer set; a third acquisition module, used to acquire the registration address information of the new customer when a new customer registration is detected, and to convert the registration address information to obtain the coordinate data of the new customer, wherein the new customer is a customer other than the target customer in the heat map of the radiation range of preset outlets; a first update module, used to calculate the spatial distance between the address coordinates of the new customer and all preset outlets, and to update the heat map of the radiation range of preset outlets; and a second update module, used to redetermine the target customer set of preset outlets and update the heat map of the radiation range of preset outlets when a change in the coordinate data of preset outlets is detected in the preset spatial database.

[0096] Optionally, the first matching unit includes: a third determining module, used to determine the preset task execution priority for each target customer for each preset branch, and control the preset branch to handle the financial activity tasks corresponding to the target customer according to the preset task execution priority, wherein the preset branch includes: multiple business personnel; a fourth determining module, used to determine the business needs of each target customer, and match all financial activity tasks corresponding to the target customer with all business personnel of the preset branch based on the business needs to obtain a matching score; a fifth determining module, used to determine an initial set of business personnel for each target customer based on all matching scores; and a first matching module, used to match all financial activity tasks corresponding to each target customer with all initial business personnel in the initial set of business personnel using a preset allocation algorithm to obtain a matching result, wherein the matching result is used to indicate the correspondence between financial activity tasks and target business personnel.

[0097] Optionally, the third determining module includes: a first determining submodule, used to determine the industry category to which the target customer belongs, and based on the industry category, determine the preset adjustment coefficient of the target customer; a second determining submodule, used to determine the route length from the preset outlet to the address coordinates of the target customer; and a third determining submodule, used to determine the preset task execution priority based on the preset adjustment coefficient and the route length.

[0098] Optionally, the matching device for financial activity tasks further includes: a first monitoring module, used to match multiple financial activity tasks corresponding to the activity strategy with target business personnel of a preset branch based on a preset allocation algorithm, and after obtaining the correspondence between financial activity tasks and target business personnel, monitor the current task volume of each target business personnel; a first calculation module, used to acquire historical task processing data of each target business personnel, and calculate the historical average daily task processing volume of the target business personnel based on the historical task processing data; a second calculation module, used to calculate a task saturation value based on the current task volume and the historical average daily task processing volume, wherein the task saturation value corresponds to a task control level, and the task control level corresponds to a task control strategy; and a first processing module, used to process the financial activity tasks based on the task control strategy.

[0099] The matching device for the aforementioned financial activity task may also include a processor and a memory. The first acquisition unit 30, the first determination unit 31, the second determination unit 32, the first matching unit 33, etc., are all stored in the memory as program units, and the processor executes the aforementioned program units stored in the memory to realize the corresponding functions.

[0100] The aforementioned processor contains a kernel, which retrieves the corresponding program units from memory. One or more kernels can be configured. By adjusting kernel parameters, a preset allocation algorithm is used to match multiple financial activity tasks corresponding to the activity strategy with target business personnel at preset branches, thus obtaining the correspondence between financial activity tasks and target business personnel.

[0101] The aforementioned memory may include non-permanent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0102] It should be noted that the first acquisition unit 30, the first determination unit 31, the second determination unit 32, and the first matching unit 33 mentioned above correspond to steps S201 to S204 in Embodiment 1. The instances and application scenarios implemented by the above units and the corresponding steps are the same, but are not limited to the content disclosed in Embodiment 1. It should be noted that the above 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 units can also be part of a device and run in the computer terminal 10 provided in Embodiment 1.

[0103] Example 3

[0104] Embodiments of this application may provide a computer terminal, which may be any computer terminal device in a group of computer terminals. Optionally, in this embodiment, the aforementioned computer terminal may also be replaced with a mobile terminal or an electronic device, etc.

[0105] Optionally, in this embodiment, the computer terminal may be located in at least one of a plurality of network devices in a computer network.

[0106] In this embodiment, the computer terminal described above can execute the program code for the following steps in the matching method for financial activity tasks: obtaining the coordinate data of all preset branches and the coordinate data of all preset customers from a preset spatial database. The preset branches are pre-built branches of financial institutions used to handle financial activity tasks for customers. The preset customers are customers pre-registered with the financial institution. The coordinate data includes the address coordinates of the preset customer at the time of registration. For each preset branch, based on the preset branch coordinate data and all coordinate data, the spatial distance from the preset branch to each address coordinate is determined. Based on the spatial distance, a target customer set for each preset branch is determined, and an activity strategy is generated for each target customer in the target customer set. Each activity strategy corresponds to multiple financial activity tasks. Based on a preset allocation algorithm, the multiple financial activity tasks corresponding to the activity strategy are matched with the target business personnel of the preset branch to obtain the correspondence between financial activity tasks and target business personnel. Each preset branch handles financial activity tasks for each target customer based on this correspondence.

[0107] Optionally, the aforementioned computer terminal can execute the program code for the following steps in the matching method for financial activity tasks: obtaining registration address information of multiple preset customers and cleaning the registration address information to obtain cleaned address information; obtaining preset branch registration address information of multiple preset branches and cleaning the preset branch registration address information to obtain cleaned preset branch address information; converting the cleaned address information into coordinate data based on geocoding technology, and converting the cleaned preset branch address information into preset branch coordinate data; adding the coordinate data and preset branch coordinate data to a preset spatial database.

[0108] Optionally, the computer terminal described above can execute the program code for the following steps in the matching method for financial activity tasks: based on preset branch coordinate data, using preset spatial indexing technology, filtering the coordinate data of multiple preset customers to obtain a target coordinate data set; based on the preset branch coordinate data and each target coordinate data in the target coordinate data set, determining the spatial distance from the preset branch to each address coordinate.

[0109] Optionally, the computer terminal described above can execute the program code for the following steps in the matching method for financial activity tasks: for each preset branch, determine a preset distance threshold for spatial distance; compare the spatial distance with the preset distance threshold, and if the spatial distance is less than the preset distance threshold, determine the preset customer corresponding to the spatial distance as the target customer; add the target customer to the target customer set.

[0110] Optionally, the aforementioned computer terminal can execute the program code for the following steps in the matching method for financial activity tasks: generating a heat map of the radiation range of preset outlets based on all preset outlet coordinate data, all target customer coordinate data, and all spatial distances; when a new customer registration is detected, obtaining the new customer's registration address information and converting the registration address information to obtain the new customer's coordinate data, wherein the new customer is a customer other than the target customer in the preset outlet radiation range heat map; calculating the spatial distance between the new customer's address coordinates and all preset outlets, and updating the preset outlet radiation range heat map; or, when a change in the coordinate data of preset outlets is detected in the preset spatial database, re-determining the target customer set of the preset outlets, and updating the preset outlet radiation range heat map.

[0111] Optionally, the aforementioned computer terminal can execute the program code for the following steps in the financial activity task matching method: For each preset branch, determine the preset task execution priority for each target customer, and control the preset branch to handle the financial activity tasks corresponding to the target customer according to the preset task execution priority, wherein the preset branch includes: multiple business personnel; determine the business needs of each target customer, and based on the business needs, match all financial activity tasks corresponding to the target customer with all business personnel of the preset branch to obtain a matching score; for each target customer, determine an initial set of business personnel based on all matching scores; use a preset allocation algorithm to match all financial activity tasks corresponding to each target customer with all initial business personnel in the initial set of business personnel to obtain a matching result, wherein the matching result is used to indicate the correspondence between financial activity tasks and target business personnel.

[0112] Optionally, the computer terminal described above can execute program code for the following steps in the matching method for financial activity tasks: determining the industry category to which the target customer belongs, and determining the preset adjustment coefficient of the target customer based on the industry category; determining the route length from the preset branch to the address coordinates of the target customer; and determining the preset task execution priority based on the preset adjustment coefficient and the route length.

[0113] Optionally, the aforementioned computer terminal can execute program code for the following steps in the method for matching financial activity tasks: monitoring the current task volume of each target business person; obtaining historical task processing data for each target business person, and calculating the historical average daily task volume of the target business person based on the historical task processing data; calculating a task saturation value based on the current task volume and the historical average daily task volume, wherein the task saturation value corresponds to a task control level, and the task control level corresponds to a task control strategy; and processing the financial activity tasks based on the task control strategy.

[0114] Optionally, Figure 4 This is a structural block diagram of an electronic device according to an embodiment of this application. Figure 4 As shown, the electronic device may include: one or more ( Figure 4 (Only one is shown) Processor 402, memory 404, memory controller, and peripheral interface, wherein the peripheral interface is connected to the radio frequency module, audio module and display.

[0115] The memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the matching method and apparatus for financial activity tasks in this embodiment. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, thereby realizing the aforementioned matching method for financial activity tasks. 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.

[0116] The processor can access the information and application programs stored in the memory via the transmission device to execute the steps described above in the matching method for the aforementioned financial activity tasks.

[0117] This application provides a matching scheme for financial activity tasks. By using geocoding technology to convert enterprise addresses into coordinate data, and combining it with a spatial computing engine to calculate the precise spatial distance between enterprises and financial institution branches, a heat map of the coverage relationship between enterprises and branches is formed based on the dynamic rules of the branch's radiation range. Then, using an intelligent allocation algorithm (such as a genetic algorithm), financial activity tasks are intelligently and personally allocated according to the account manager's ability, experience, and service radius. This ensures that each account manager receives a task that best matches their expertise, improving the accuracy and balance of resource allocation. This solves the technical problem of low accuracy in financial task allocation and resource waste in related technologies.

[0118] Those skilled in the art will understand that Figure 4 The structure shown is for illustrative purposes only. Electronic devices can also be terminal devices such as smartphones, tablets, PDAs, and mobile internet devices (MIDs). Figure 4 This does not limit the structure of the aforementioned electronic device. For example, electronic devices may also include components that are more... Figure 4 The more or fewer components shown (such as network interfaces, display devices, etc.), or having the same Figure 4 The different configurations shown.

[0119] 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.

[0120] Example 4

[0121] 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 matching method for financial activity tasks provided in Embodiment 1.

[0122] 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.

[0123] This application also provides a computer program product, which, when executed on a data processing device, is a program suitable for performing matching method steps for financial activity tasks.

[0124] 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.

[0125] 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.

[0126] 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.

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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 matching tasks in financial activities, characterized in that, include: The coordinate data of all preset outlets and the coordinate data of all preset customers are obtained from the preset spatial database. The preset outlets are preset outlets of financial institutions that are pre-built and used to handle financial activities for customers. The preset customers are customers who have registered in advance with the financial institution. The coordinate data includes the address coordinates of the preset customers when they register. For each of the preset network points, the spatial distance from the preset network point to each of the address coordinates is determined based on the preset network point coordinate data and all the coordinate data. Based on the spatial distance, a target customer set for each of the preset outlets is determined, and an activity strategy is generated for each target customer in the target customer set, wherein the activity strategy corresponds to multiple financial activity tasks; Based on a preset allocation algorithm, multiple financial activity tasks corresponding to the activity strategy are matched with target business personnel of the preset outlets to obtain the correspondence between the financial activity tasks and the target business personnel. Each preset outlet handles the financial activity task for each target customer of the preset outlet based on the correspondence.

2. The matching method for financial activity tasks according to claim 1, characterized in that, Before retrieving the coordinate data of all preset locations and all preset customers from the preset spatial database, the process also includes: Obtain the registration address information of multiple preset customers, and clean the registration address information to obtain cleaned address information; Obtain the preset network point registration address information of multiple preset network points, and clean the preset network point registration address information to obtain cleaned preset network point address information; Based on geocoding technology, the cleaning address information is converted into the coordinate data, and the cleaning preset site address information is converted into the preset site coordinate data; The coordinate data and the preset network point coordinate data are added to the preset spatial database.

3. The matching method for financial activity tasks according to claim 1, characterized in that, The step of determining the spatial distance from the preset network point to each address coordinate based on the preset network point coordinate data and all the coordinate data includes: Based on the preset network point coordinate data, a preset spatial indexing technique is used to filter the coordinate data of multiple preset customers to obtain a target coordinate data set; Based on the preset network point coordinate data and each target coordinate data in the target coordinate data set, the spatial distance from the preset network point to each address coordinate is determined.

4. The matching method for financial activity tasks according to claim 1, characterized in that, The step of determining the target customer set for each of the preset outlets based on the spatial distance includes: For each of the preset network points, a preset distance threshold for the spatial distance is determined; The spatial distance is compared with the preset distance threshold. If the spatial distance is less than the preset distance threshold, the preset customer corresponding to the spatial distance is identified as the target customer. Add the target customer to the target customer set.

5. The matching method for financial activity tasks according to claim 4, characterized in that, After adding the target customer to the target customer set, the process also includes: Based on all the preset network point coordinate data, all the target customer coordinate data, and all the spatial distances, a heat map of the preset network point radiation range is generated. When a new customer registration is detected, the registration address information of the new customer is obtained and the registration address information is converted to obtain the coordinate data of the new customer. The new customer is a customer other than the target customer in the preset network radiation range heat map. Calculate the spatial distance between the address coordinates of the new customer and all the preset service points, and update the heat map of the radiation range of the preset service points; or, If the coordinate data of the preset network point in the preset spatial database is changed, the target customer set of the preset network point is redefined, and the heat map of the radiation range of the preset network point is updated.

6. The matching method for financial activity tasks according to claim 1, characterized in that, The step of matching multiple financial activity tasks corresponding to the activity strategy with target business personnel of the preset branch based on a preset allocation algorithm to obtain the correspondence between the financial activity tasks and the target business personnel includes: For each of the preset outlets, a preset task execution priority is determined for each of the target customers, and based on the preset task execution priority, the preset outlets are controlled to handle the financial activity tasks corresponding to the target customers. The preset outlets include: multiple business personnel. Determine the business needs of each target customer, and based on the business needs, match all the financial activity tasks corresponding to the target customer with all the business personnel of the preset branch to obtain a matching score; For each target customer, an initial set of sales personnel is determined based on all the matching scores; A preset allocation algorithm is used to match all financial activity tasks corresponding to each target customer with all initial business personnel in the initial business personnel set to obtain a matching result, wherein the matching result is used to indicate the correspondence between the financial activity tasks and the target business personnel.

7. The matching method for financial activity tasks according to claim 6, characterized in that, The steps for determining the preset task execution priority for each target customer include: Determine the industry category to which the target customer belongs, and based on the industry category, determine the preset adjustment coefficient for the target customer; Determine the route length from the preset outlet to the address coordinates of the target customer; The preset task execution priority is determined based on the preset adjustment coefficient and the route length.

8. The matching method for financial activity tasks according to claim 1, characterized in that, After matching multiple financial activity tasks corresponding to the activity strategy with target business personnel of the preset branch based on a preset allocation algorithm to obtain the correspondence between the financial activity tasks and the target business personnel, the method further includes: Monitor the current workload of each of the target business personnel; Obtain historical task processing data for each of the target business personnel, and calculate the historical average daily task processing volume of the target business personnel based on the historical task processing data; Based on the current task volume and the historical average daily task volume, a task saturation value is calculated, wherein the task saturation value corresponds to a task control level, and the task control level corresponds to a task control strategy. The financial activity tasks are processed based on the task control strategy.

9. A matching device for financial activity tasks, characterized in that, include: The first acquisition unit is used to acquire the coordinate data of all preset outlets and the coordinate data of all preset customers from the preset spatial database. The preset outlets are preset outlets of financial institutions that are pre-built and used to handle financial activities for customers. The preset customers are customers who have registered in advance with the financial institution. The coordinate data includes the address coordinates of the preset customers when they register. The first determining unit is used to determine, for each preset network point, the spatial distance from the preset network point to each address coordinate based on the preset network point coordinate data and all the coordinate data; The second determining unit is used to determine the target customer set of each of the preset outlets based on the spatial distance, and generate an activity strategy for each target customer in the target customer set, wherein the activity strategy corresponds to multiple financial activity tasks; The first matching unit is used to match multiple financial activity tasks corresponding to the activity strategy with the target business personnel of the preset outlets based on a preset allocation algorithm, so as to obtain the correspondence between the financial activity tasks and the target business personnel. Each preset outlet handles the financial activity task for each target customer of the preset outlet based on the correspondence.

10. An electronic device, characterized in that, It includes one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement the matching method for financial activity tasks as described in any one of claims 1 to 8.

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