Data processing method and device, equipment, medium and program product

Abstract

The invention provides a data processing method which can be applied to the technical field of big data. The method comprises the following steps: acquiring real transaction record information between legal clients; based on the real transaction record information, a fund flow directed weighted network between the legal clients is constructed, nodes of the fund flow directed weighted network represent the legal clients, and edges of the fund flow directed weighted network represent the real transaction record information; and determining a target legal person customer based on the fund flow directed weighted network and the network centrality. The invention further provides a data processing device, equipment, a storage medium and a program product.

Description

Technical Field

[0001] The present disclosure relates to the field of big data, and more specifically to a data processing method, apparatus, device, medium, and program product. Background Art

[0002] As a provider of capital, banks need to fully understand their clients' position within the entire supply chain and their relationships with other clients in order to assess their credit and systemic risks. Relevant customer assessment methods are often based on single-dimensional financial data or simple statistical analysis. In an increasingly complex economic environment, the financial status of a single client may be influenced by upstream and downstream clients, and these methods struggle to capture these indirect relationships. This can lead to biased assessment results and hinders the comprehensive reflection of the client's importance within the overall economic system and its potential risks. Summary of the Invention

[0003] In view of the above problems, the present disclosure provides a data processing method, apparatus, device, medium and program product.

[0004] According to a first aspect of the present disclosure, a data processing method is provided, the method comprising:

[0005] Obtain real transaction records between legal person clients;

[0006] Based on the real transaction record information, constructing a directed weighted network of capital flows between the corporate clients, wherein the nodes of the directed weighted network of capital flows represent the corporate clients, and the edges of the directed weighted network of capital flows represent the real transaction record information;

[0007] Target corporate clients are determined based on the directed weighted network of capital flows and network centrality.

[0008] According to an embodiment of the present disclosure, the real transaction record information includes at least initiator customer information, recipient customer information, and transaction amount information. Constructing a directed weighted network of capital flows between the legal person customers based on the real transaction record information includes:

[0009] The corporate client is represented as a node, the directed transaction behavior between the corporate clients is defined as the directed edge between the nodes, and the total transaction amount between the corporate clients is defined as the weight of the directed edge, thereby constructing a directed weighted network of capital flows between the corporate clients;

[0010] The starting node of the directed edge is the initiator's customer information, and the ending node of the directed edge is the receiver's customer information.

[0011] According to an embodiment of the present disclosure, the network centrality includes at least one of in-degree centrality, out-degree centrality, and eigenvector centrality, and determining the target legal person client based on the directed weighted capital flow network and the network centrality includes:

[0012] Based on the directed weighted network of capital flows, a weighted adjacency matrix is ​​determined, wherein the weighted adjacency matrix Row represents legal person customer The capital outflow situation, the weighted adjacency matrix Column represents legal entity customer The capital inflow situation, i and j are both positive integers;

[0013] Determining a first result based on the weighted adjacency matrix and the indegree centrality;

[0014] determining a second result based on the weighted adjacency matrix and the out-degree centrality;

[0015] determining a third result based on the weighted adjacency matrix and the eigenvector centrality;

[0016] A target legal person client is determined according to at least one of the first result, the second result, and the third result.

[0017] According to an embodiment of the present disclosure, determining the first result based on the weighted adjacency matrix and the indegree centrality includes:

[0018] Based on the weighted adjacency matrix, the total capital inflow of the legal person client is represented by the in-degree centrality;

[0019] The first display information and the second display information of the node are used to represent the in-degree centrality, and a transaction capital flow network is constructed;

[0020] The first display information has multiple levels, and the level of the first display information is positively correlated with the importance of the node. The second display information has multiple levels, and the level of the second display information is positively correlated with the total capital inflow of the node.

[0021] According to an embodiment of the present disclosure, determining the second result based on the weighted adjacency matrix and the out-degree centrality includes:

[0022] Based on the weighted adjacency matrix, the out-degree centrality is used to represent the total capital outflow of the legal person client;

[0023] The out-degree centrality is represented by the third display information and the fourth display information of the node, and a transaction capital flow network is constructed;

[0024] The third display information has multiple levels, and the level of the third display information is positively correlated with the importance of the node. The fourth display information has multiple levels, and the level of the fourth display information is positively correlated with the total capital outflow of the node.

[0025] According to an embodiment of the present disclosure, determining the target legal person client based on at least one of the first result, the second result, and the third result includes:

[0026] Selecting a legal person client that meets a preset condition from the third result;

[0027] Based on the first result and the second result, determining a target legal person customer from the legal person customers that meet the preset conditions; or,

[0028] The legal person customers who meet the preset conditions are regarded as the target legal person customers.

[0029] According to an embodiment of the present disclosure, the real transaction record information includes transaction time, and the method further includes:

[0030] Based on the transaction time, updating the directed weighted network of capital flows according to an annual frequency;

[0031] Each year is regarded as a window period, and at the end of the year, the directed weighted network of capital flows is constructed based on the real transaction record information between corporate clients in the year.

[0032] A second aspect of the present disclosure provides a data processing device, the device comprising:

[0033] The acquisition module is used to obtain real transaction record information between legal person customers;

[0034] a construction module, configured to construct a directed weighted network of capital flows between the corporate clients based on the real transaction record information, wherein the nodes of the directed weighted network of capital flows represent the corporate clients, and the edges of the directed weighted network of capital flows represent the real transaction record information;

[0035] A determination module is used to determine target legal person customers based on the directed weighted network of capital flows and network centrality.

[0036] A third aspect of the present disclosure provides an electronic device, comprising: one or more processors; and a memory for storing one or more computer programs, wherein the one or more processors execute the one or more computer programs to implement the steps of the above method.

[0037] The fourth aspect of the present disclosure further provides a computer-readable storage medium having a computer program or instructions stored thereon, which implements the steps of the above method when the computer program or instructions are executed by a processor.

[0038] The fifth aspect of the present disclosure further provides a computer program product, comprising a computer program or instructions, which implement the steps of the above method when executed by a processor. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The above contents and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0040] Figure 1 Schematically illustrates an application scenario diagram of a data processing method, apparatus, device, medium, and program product according to an embodiment of the present disclosure;

[0041] Figure 2 The following schematically shows a flow chart of a data processing method according to an embodiment of the present disclosure;

[0042] Figure 3 A schematic diagram of a transaction funds flow network according to an embodiment of the present disclosure is schematically shown;

[0043] Figure 4 A block diagram schematically illustrates a structure of a data processing device according to an embodiment of the present disclosure; and

[0044] Figure 5 The block diagram schematically shows an electronic device suitable for implementing the data processing method according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0045] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are merely exemplary and are not intended to limit the scope of the present disclosure. In the detailed description below, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of well-known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0046] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise," "include," etc. used herein indicate the presence of the features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0047] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0048] When expressions such as "at least one of A, B, and C, etc." are used, they should generally be interpreted in accordance with the meaning commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0049] In the technical solutions disclosed herein, all user information (including but not limited to user personal information, user image information, user transaction record information, user device information, such as location information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved are information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data comply with relevant laws, regulations and standards, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0050] In scenarios where personal information is used for automated decision-making, the methods, devices, and systems provided by the embodiments of the present disclosure all provide users with corresponding operation portals for them to choose to agree or reject the automated decision-making results; if the user chooses to reject, the expert decision-making process will be entered. The expression "automated decision-making" here refers to the activity of automatically analyzing and evaluating an individual's behavioral habits, interests and hobbies, or economic, health, credit status, etc. through computer programs and making decisions. The expression "expert decision-making" here refers to the activity of making decisions by people who specialize in a certain field, have specialized experience, knowledge, and skills, and have reached a certain level of professionalism.

[0051] Figure 1 The application scenario diagram of the data processing method according to an embodiment of the present disclosure is schematically shown.

[0052] like Figure 1 As shown, the application scenario 100 according to this embodiment may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104, and a server 105. The network 104 is used as a medium for providing a communication link between the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 105. The network 104 may include various connection types, such as wired or wireless communication links or optical fiber cables.

[0053] A user may use a first terminal device 101, a second terminal device 102, or a third terminal device 103 to interact with a server 105 via a network 104 to receive or send messages, etc. Various communication client applications may be installed on the first terminal device 101, the second terminal device 102, or the third terminal device 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (for example only).

[0054] The first terminal device 101 , the second terminal device 102 , and the third terminal device 103 may be various electronic devices having display screens and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, desktop computers, and the like.

[0055] The server 105 may be a server that provides various services, such as a background management server (for example only) that supports websites browsed by users using the first terminal device 101, the second terminal device 102, and the third terminal device 103. The background management server may analyze and process received data such as user requests, and feed back processing results (e.g., web pages, information, or data obtained or generated based on user requests) to the terminal devices.

[0056] It should be noted that the data processing method provided in the embodiments of the present disclosure can generally be executed by the server 105. Accordingly, the data processing device provided in the embodiments of the present disclosure can generally be set in the server 105. The data processing method provided in the embodiments of the present disclosure can also be executed by a server or server cluster that is different from the server 105 and can communicate with the first terminal device 101, the second terminal device 102, the third terminal device 103 and / or the server 105. Accordingly, the data processing device provided in the embodiments of the present disclosure can also be set in a server or server cluster that is different from the server 105 and can communicate with the first terminal device 101, the second terminal device 102, the third terminal device 103 and / or the server 105.

[0057] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is merely illustrative. Any number of terminal devices, networks and servers may be provided as required.

[0058] The following will be based on Figure 1 The scene described by Figure 2~Figure 3 The data processing method according to the embodiment of the present disclosure is described in detail.

[0059] Figure 2 The flowchart of the data processing method according to the embodiment of the present disclosure is schematically shown.

[0060] like Figure 2 As shown, the data processing method of this embodiment includes operations S210 to S230.

[0061] In operation S210, real transaction record information between legal person customers is obtained.

[0062] According to embodiments of the present disclosure, prior to obtaining actual transaction records between legal entities, user consent or authorization may be obtained. For example, prior to operation S210, a request may be issued to the legal entity to obtain the actual transaction records between the legal entity. If the legal entity consents or authorizes obtaining the actual transaction records, operation S220 is executed.

[0063] In the embodiments of the present disclosure, a corresponding operation portal can be provided for the user to choose to agree or reject the automated decision result. That is, before the construction of a directed weighted network of capital flows for processing / decision-making based on the real transaction records between legal person clients is carried out, an instruction to agree or reject the processing / decision-making based on the user's input through the corresponding operation portal can be obtained. If the user agrees to the processing / decision-making, the construction of a directed weighted network of capital flows for processing / decision-making based on the real transaction records between legal person clients is carried out, i.e., step S230 is executed. If the user rejects the processing / decision-making, the expert decision-making process is entered.

[0064] According to the embodiments of the present disclosure, corporate clients may refer to organizations such as enterprises, institutions, social groups, etc. that have legal person status. As the main body of economic activities, they will conduct various transactions with other corporate clients.

[0065] According to the embodiments of the present disclosure, real transaction record information can be actual fund transaction data between enterprises stored by banks or financial institutions. Real transaction record information can be a detailed record of actual transaction activities between legal person clients, which may include key data such as transaction time, transaction parties (i.e., which legal person clients participated), transaction amount, and transaction goods or service types.

[0066] In operation S220 , a directed weighted network of fund flows between legal person clients is constructed based on real transaction record information.

[0067] According to embodiments of the present disclosure, a directed weighted capital flow network can be a mathematical model used to describe the relationships between elements in a complex system. In this disclosure, it is used to represent the capital flow relationships between legal entity clients. A directed weighted capital flow network includes features such as nodes, edges, weights, and directions.

[0068] According to the embodiment of the present disclosure, nodes represent basic elements in the network. In this disclosure, each node represents a corporate client. By abstracting corporate clients as nodes, the complex corporate client group can be simplified into an easy-to-analyze network structure.

[0069] According to the embodiment of the present disclosure, an edge can represent the connection relationship between nodes, and an edge represents real transaction record information. That is, if there is a transaction record between two corporate customers, then there is an edge connecting these two nodes (corporate customers) in the network.

[0070] According to the disclosed embodiments, direction means that the edge has directionality, which reflects the direction of capital flow. For example, if legal person client i transfers money to legal person client j, then the edge pointing from node i to node j in the network indicates that the funds flow from i to j.

[0071] According to embodiments of the present disclosure, weighting can be performed by assigning weights to edges. Weights can be determined based on at least one of transaction-related information, such as transaction amount and transaction frequency. The size of the weight reflects the importance or intensity of the transaction. For example, the larger the transaction amount, the greater the corresponding edge weight, helping to more accurately describe the scale and influence of capital flows between corporate clients.

[0072] For example, let corporate client A, corporate client B, and corporate client C be represented as node a, node b, and node c respectively. If corporate client A transfers 1 million to corporate client B, draw an arrow from node a to node b, and the weight of the arrow is 100.

[0073] In operation S230 , target legal person clients are determined based on the directed weighted capital flow network and network centrality.

[0074] According to embodiments of the present disclosure, network centrality can be a series of metrics used to measure the importance of nodes in a network. Different network centrality metrics reflect the status and role of nodes in the network from different perspectives. For example, network centrality metrics can include degree centrality, closeness centrality, betweenness centrality, in-degree centrality, out-degree centrality, and eigenvector centrality.

[0075] According to the embodiments of the present disclosure, transaction data between corporate clients are used to construct a directed weighted network of corporate client funds flow, and target corporate clients in the network are identified through important nodes in the directed weighted network of funds flow. Risk management strategies can be formulated in advance for these clients to avoid large losses, such as setting up an early warning mechanism for key client funds outflow and adjusting the credit limit of key clients.

[0076] In some embodiments of the present disclosure, the real transaction record information includes at least the initiator's customer information, the recipient's customer information, the transaction amount information, and the transaction time information, as shown in Table 1.

[0077] Table 1

[0078] Initiator Guest Editor Receiving party's code Total transaction amount Trading Hours 000014928 000014748 ¥200000.00 2024 000014657 000014928 ¥100000.00 2024 000014748 000014389 ¥180000.00 2024 000014678 000014399 ¥500000.00 2024

[0079] According to the embodiment of the present disclosure, a corporate customer can be represented as a node, the directed transaction behavior between corporate customers is defined as the directed edge between the nodes, and the total transaction amount information between corporate customers is defined as the weight of the directed edge, so as to construct a directed weighted network of capital flow between corporate customers, in which the starting node of the directed edge is the initiator customer information, and the ending node of the directed edge is the recipient customer information.

[0080] In some embodiments of the present disclosure, the transaction amounts between corporate clients typically exhibit the following characteristics: (1) the transaction amounts range widely, potentially with significant variability (e.g., from a few thousand yuan to several million yuan); and (2) the transaction amount data distribution is highly skewed, potentially with extreme values. Therefore, to improve the accuracy of subsequent analysis, the total transaction amounts between corporate clients can be preprocessed to convert data of different ranges or dimensions to the same scale, thereby eliminating interference caused by data dimensions and highlighting the relative strength of transaction relationships between corporate clients.

[0081] According to the disclosed embodiments, the total transaction volume between corporate clients can be logarithmized to obtain the digitized total transaction volume. This logarithmized total transaction volume can then be used to measure the overall level of client funds flow. The actual transaction records between corporate clients after data preprocessing are shown in Table 2.

[0082] Table 2

[0083] Initiator Guest Editor Receiving party's code Total level of capital flows Trading Hours 000014928 000014748 12.21 2024 000014657 000014928 11.51 2024 000014748 000014389 12.10 2024 000014678 000014399 13.12 2024

[0084] According to the embodiment of the present disclosure, the directed weighted network of capital flow can be defined as .in, Represents node element information in the network, i.e., bank corporate customers; Indicates the number of nodes in the network, that is, the number of legal person customers; Represents the directed edge feature information in the network, represent arrive Directed trading behavior, Represents a directed edge The weight, weight It is constructed based on the total transaction amount of the customer. The larger the total transaction amount, the greater the weight of the directed edge, which represents the higher importance of the transaction behavior between customers in the capital flow network.

[0085] According to the disclosed embodiments, a directed weighted capital flow network can be updated annually based on transaction time. Each year is treated as a window period, and at the end of each year, a directed weighted capital flow network is constructed based on actual transaction records between corporate clients that occurred within the year. This improves the stability of the directed weighted capital flow network over shorter timescales and its dynamics over longer timescales.

[0086] In some embodiments, assuming the current window period is According to the network topology, the current legal person customers The weighted adjacency matrix is:

[0087] Formula 1

[0088] In the above formula 1, the weighted adjacency matrix Indicates window period The total liquidity of funds between corporate customers of a bank. Legal person customers during the representative window period To corporate clients The total flow of funds. Rows represent customers The outgoing edge, Columns represent customers The entry edge.

[0089] In some embodiments, network centrality includes at least one of indegree centrality, outdegree centrality, and eigenvector centrality. Indegree centrality is the number of connections a node receives from other nodes. In a directed network, a node's indegree is the number of edges pointing to the node. Outdegree centrality is the number of connections a node sends to other nodes. In a directed network, a node's outdegree is the number of edges emanating from the node. Eigenvector centrality combines the number of connections a node has and the importance of other nodes connected to it.

[0090] Accordingly, a first result can be determined based on the weighted adjacency matrix and in-degree centrality. A second result can be determined based on the weighted adjacency matrix and out-degree centrality. A third result can be determined based on the weighted adjacency matrix and eigenvector centrality. A target corporate client can be determined based on at least one of the first, second, and third results.

[0091] According to the disclosed embodiment, for node i, its in-degree centrality is equal to the sum of the weights of all edges pointing to node i. The calculated in-degree centrality scores of all nodes can be organized into a list or vector form as a first result, reflecting the ranking of the node's ability to receive funding or attention in the network.

[0092] According to the disclosed embodiments, each row of the weighted adjacency matrix can be traversed. For node i, all non-zero elements in that row (i.e., the weights of the edges originating from node i) are summed to obtain the out-degree centrality of node i. The out-degree centrality scores of all nodes can be organized into a list or vector form as a second result, reflecting the ranking of each legal entity client's ability to export funds within the network.

[0093] Figure 3 A schematic diagram of a transaction funds flow network according to an embodiment of the present disclosure is schematically shown.

[0094] like Figure 3 As shown, in this embodiment, based on the weighted adjacency matrix, the total capital inflow of corporate clients is represented by in-degree centrality, and the first display information and second display information of the node are used to represent the in-degree centrality to construct a transaction capital flow network.

[0095] In the weighted adjacency matrix In the adjacency matrix, the capital flow between customers is directional. The i-th row of the adjacency matrix represents the capital outflow of customer i, and the j-th column of the adjacency matrix represents the capital inflow of customer i. Therefore, the overall level of capital inflow of legal person customer i can be expressed by in-degree centrality ( ), specifically as follows:

[0096] Formula 2

[0097] The first display information has multiple levels, and the level of the first display information is positively correlated with the importance of the node. The second display information has multiple levels, and the level of the second display information is positively correlated with the total capital inflow of the node.

[0098] For example, the first piece of information is the size of the node, and the second piece is its color. In-degree centrality is characterized by both node size and color. Larger nodes and darker colors indicate a higher importance within the network during the current window. The higher the level of capital inflow received by the corporate client it represents, the more likely it is to be a target corporate client.

[0099] In some embodiments, the out-degree centrality can be used to represent the total capital outflow of legal person clients based on the weighted adjacency matrix. The overall level of capital outflow can be expressed by the out-degree centrality ( ) is expressed as follows. The specific formula is as follows:

[0100] Formula 3

[0101] The degree centrality is represented by the third display information and the fourth display information of the node, and a transaction capital flow network is constructed, wherein the third display information has multiple levels, and the level of the third display information is positively correlated with the importance of the node; the fourth display information has multiple levels, and the level of the fourth display information is positively correlated with the total capital outflow of the node.

[0102] It can be understood that constructing a transaction capital flow network based on out-degree centrality is similar to constructing a transaction capital flow network based on in-degree centrality, and will not be repeated here.

[0103] In some embodiments, the third result is determined based on the weighted adjacency matrix and eigenvector centrality, which can take into account both direct and indirect capital flows between corporate clients. This not only depicts the direct relationship between corporate clients, but also takes into account the indirect relationship between corporate clients, thereby more accurately identifying nodes with significant influence, that is, target corporate clients. Eigenvector centrality is introduced to measure the target corporate clients in the network, and its specific calculation formula is as follows:

[0104] Formula 4

[0105] In formula 4, is the weighted adjacency matrix The maximum eigenvalue of is the maximum eigenvalue The corresponding eigenvector. The eigenvector centrality of customer i is recorded as , which is the eigenvector Since eigenvector centrality can be used to measure the indirect importance of the influence of corporate client i on the capital flow network through its important "friends", the eigenvector centrality index can be used to identify "leverage-type" key clients who influence capital flows through indirect connection networks, that is, target corporate clients.

[0106] The calculated eigenvector centrality scores can be organized into a list or vector form as the third result. Taking into account the importance of the node's own connections and neighboring nodes, the comprehensive influence of each legal entity client in the network is ranked.

[0107] According to an embodiment of the present disclosure, corporate clients that meet preset conditions can be selected from the third result and designated as target corporate clients. For example, the eigenvector centrality scores of each corporate client can be sorted, and clients that meet the preset sorting order can be selected as target corporate clients. For example, the eigenvector centrality scores of each corporate client can be compared with a preset threshold, and clients whose eigenvector centrality scores exceed the preset threshold can be selected as target corporate clients.

[0108] According to embodiments of the present disclosure, different weights can be assigned to the first, second, and third results, respectively, and then a comprehensive score for each corporate client can be calculated. For example, let the weight of the first result be w1, the weight of the second result be w2, and the weight of the third result be w3 (w1+w2+w3=1). For corporate client i, its comprehensive score Si = w1Cin(i)+w2Cout(i)+w3xi. All corporate clients are ranked based on their comprehensive scores, and those with the highest comprehensive scores are selected as target corporate clients. This approach can more comprehensively consider the importance of nodes in different aspects and improve the accuracy of target corporate client identification.

[0109] Based on the above data processing method, the present disclosure also provides a data processing device. Figure 4 The device is described in detail.

[0110] Figure 4 The structural block diagram of the data processing device according to an embodiment of the present disclosure is schematically shown.

[0111] like Figure 4 As shown, the data processing device 400 of this embodiment includes an acquisition module 410 , a construction module 420 and a determination module 430 .

[0112] The acquisition module 410 is used to obtain the real transaction record information between legal person customers. In one embodiment, the acquisition module 410 can be used to perform the operation S210 described above, which will not be repeated here.

[0113] Construction module 420 is used to construct a directed weighted network of capital flows between corporate clients based on real transaction records. The nodes of the directed weighted network represent corporate clients, and the edges of the directed weighted network represent real transaction records. In one embodiment, construction module 420 can be used to perform operation S220 described above, and will not be further described here.

[0114] The determination module 430 is used to determine the target legal person client based on the directed weighted capital flow network and the network centrality. In one embodiment, the determination module 430 can be used to perform the operation S230 described above, which will not be repeated here.

[0115] According to an embodiment of the present disclosure, real transaction record information includes at least initiator customer information, recipient customer information and transaction total amount information. Based on the real transaction record information, a directed weighted network of capital flow between corporate customers is constructed, including: representing the corporate customer as a node, defining the directed transaction behavior between corporate customers as directed edges between nodes, and defining the transaction total amount information between corporate customers as the weight of the directed edge, and constructing a directed weighted network of capital flow between corporate customers; wherein the starting node of the directed edge is the initiator customer information, and the ending node of the directed edge is the recipient customer information.

[0116] According to an embodiment of the present disclosure, network centrality includes at least one of in-degree centrality, out-degree centrality, and eigenvector centrality. Based on the directed weighted network of capital flow and the network centrality, determining the target legal person client includes: determining a weighted adjacency matrix based on the directed weighted network of capital flow, and the weighted adjacency matrix is Row represents legal person customer The capital outflow situation of the weighted adjacency matrix Column represents legal entity customer The capital inflow situation of , i and j are both positive integers; based on the weighted adjacency matrix and in-degree centrality, the first result is determined; based on the weighted adjacency matrix and out-degree centrality, the second result is determined; based on the weighted adjacency matrix and eigenvector centrality, the third result is determined;

[0117] A target legal person client is determined based on at least one of the first result, the second result, and the third result.

[0118] According to an embodiment of the present disclosure, based on the weighted adjacency matrix and indegree centrality, determining the first result includes: based on the weighted adjacency matrix, using indegree centrality to represent the total capital inflow of corporate clients; using the first display information and the second display information of the node to represent the indegree centrality, and constructing a transaction capital flow network; wherein the first display information has multiple levels, and the level of the first display information is positively correlated with the importance of the node, and the second display information has multiple levels, and the level of the second display information is positively correlated with the total capital inflow of the node.

[0119] According to an embodiment of the present disclosure, based on the weighted adjacency matrix and out-degree centrality, determining the second result includes: based on the weighted adjacency matrix, using out-degree centrality to represent the total capital outflow of corporate clients; using the third display information and fourth display information of the node to represent the out-degree centrality, and constructing a transaction capital flow network; wherein the third display information has multiple levels, and the level of the third display information is positively correlated with the importance of the node; the fourth display information has multiple levels, and the level of the fourth display information is positively correlated with the total capital outflow of the node.

[0120] According to an embodiment of the present disclosure, determining the target corporate client based on at least one of the first result, the second result, and the third result includes: selecting a corporate client that meets a preset condition from the third result; determining the target corporate client from the corporate clients that meet the preset condition based on the first result and the second result; or, using the corporate client that meets the preset condition as the target corporate client.

[0121] According to an embodiment of the present disclosure, the real transaction record information includes the transaction time, and the device 400 also includes: an update module for updating the directed weighted network of capital flow based on the transaction time according to the annual frequency; a construction module for taking each year as a window period and constructing the directed weighted network of capital flow at the end of the year based on the real transaction record information between corporate customers within the year.

[0122] According to embodiments of the present disclosure, any multiple modules among acquisition module 410, construction module 420, and determination module 430 may be combined into a single module, or any one of these modules may be split into multiple modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of other modules and implemented in a single module. According to embodiments of the present disclosure, at least one of acquisition module 410, construction module 420, and determination module 430 may be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application-specific integrated circuit (ASIC), or may be implemented in hardware or firmware through any other reasonable means of circuit integration or packaging, or may be implemented in any one of software, hardware, and firmware, or any appropriate combination of these. Alternatively, at least one of acquisition module 410, construction module 420, and determination module 430 may be at least partially implemented as a computer program module that, when executed, performs the corresponding functionality.

[0123] Figure 5 Schematically shows a block diagram of an electronic device suitable for implementing a data processing method according to an embodiment of the present disclosure. Figure 5As shown, the electronic device 500 according to an embodiment of the present disclosure includes a processor 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage unit 508 into a random access memory (RAM) 503. The processor 501 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 501 may also include onboard memory for caching purposes. The processor 501 may include a single processing unit or multiple processing units for performing different actions of the method flow according to the embodiment of the present disclosure.

[0124] Various programs and data required for the operation of the electronic device 500 are stored in the RAM 503. The processor 501, ROM 502, and RAM 503 are connected to each other via a bus 504. The processor 501 executes the various operations of the method flow according to the embodiment of the present disclosure by executing the programs in the ROM 502 and / or RAM 503. It should be noted that the programs may also be stored in one or more memories other than the ROM 502 and RAM 503. The processor 501 may also execute the various operations of the method flow according to the embodiment of the present disclosure by executing the programs stored in the one or more memories.

[0125] According to an embodiment of the present disclosure, electronic device 500 may further include an input / output (I / O) interface 505, which is also connected to bus 504. Electronic device 500 may also include one or more of the following components connected to I / O interface 505: an input section 506 including a keyboard, mouse, etc.; an output section 507 including devices such as a cathode ray tube (CRT), liquid crystal display (LCD), and speakers; a storage section 508 including a hard disk; and a communication section 509 including a network interface card such as a LAN card or modem. Communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to I / O interface 505 as needed. Removable media 511, such as a magnetic disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed in drive 510 as needed, so that computer programs read from the removable media can be installed into storage section 508 as needed.

[0126] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments, or may exist independently and not be incorporated into the device / apparatus / system. The computer-readable storage medium carries one or more programs, and when executed, implements the method according to the embodiments of the present disclosure.

[0127] According to an embodiment of the present disclosure, a computer-readable storage medium may be a non-volatile computer-readable storage medium, and may include, for example, but not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to an embodiment of the present disclosure, a computer-readable storage medium may include the ROM 502 and / or RAM 503 described above, and / or one or more memories other than ROM 502 and RAM 503.

[0128] The embodiments of the present disclosure also include a computer program product, which includes a computer program containing program code for executing the method shown in the flowchart. When the computer program product is run in a computer system, the program code is used to enable the computer system to implement the data processing method provided by the embodiments of the present disclosure.

[0129] The computer program executes the above functions defined in the system / device of the embodiment of the present disclosure when the computer program is executed by the processor 501. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0130] In one embodiment, the computer program may be stored on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may be transmitted and distributed in the form of a signal on a network medium, downloaded and installed via the communication portion 509, and / or installed from a removable medium 511. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to wireless, wired, or any suitable combination thereof.

[0131] In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 509, and / or installed from a removable medium 511. When the computer program is executed by the processor 501, the above-described functions defined in the system of the embodiment of the present disclosure are performed. According to the embodiment of the present disclosure, the systems, devices, means, modules, units, etc. described above can be implemented by computer program modules.

[0132] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computer programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C" or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect via the Internet).

[0133] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the above-mentioned module, program segment, or a part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0134] Those skilled in the art will appreciate that the features described in the various embodiments of the present disclosure may be combined and / or coupled in various ways, even if such combinations or couplings are not explicitly described in the present disclosure. In particular, the features described in the various embodiments of the present disclosure may be combined and / or coupled in various ways without departing from the spirit and teachings of the present disclosure. All such combinations and / or couplings fall within the scope of the present disclosure.

Claims

1. A data processing method, characterized in that: The method comprises: Obtain real transaction records between legal person clients; Based on the real transaction record information, constructing a directed weighted network of capital flows between the corporate clients, wherein the nodes of the directed weighted network of capital flows represent the corporate clients, and the edges of the directed weighted network of capital flows represent the real transaction record information; Target corporate clients are determined based on the directed weighted network of capital flows and network centrality.

2. The method according to claim 1, characterized in that The real transaction record information includes at least initiator customer information, recipient customer information, and transaction total information. Constructing a directed weighted network of capital flows between the legal person customers based on the real transaction record information includes: The corporate client is represented as a node, the directed transaction behavior between the corporate clients is defined as the directed edge between the nodes, and the total transaction amount between the corporate clients is defined as the weight of the directed edge, thereby constructing a directed weighted network of capital flows between the corporate clients; The starting node of the directed edge is the initiator's customer information, and the ending node of the directed edge is the receiver's customer information.

3. The method according to claim 1, characterized in that The network centrality includes at least one of in-degree centrality, out-degree centrality, and eigenvector centrality. The determining of target corporate clients based on the directed weighted capital flow network and the network centrality includes: Based on the directed weighted network of capital flows, a weighted adjacency matrix is ​​determined, wherein the weighted adjacency matrix Row represents legal person customer The capital outflow situation, the weighted adjacency matrix Column represents legal entity customer The capital inflow situation, i and j are both positive integers; Determining a first result based on the weighted adjacency matrix and the indegree centrality; determining a second result based on the weighted adjacency matrix and the out-degree centrality; determining a third result based on the weighted adjacency matrix and the eigenvector centrality; A target legal person client is determined according to at least one of the first result, the second result, and the third result.

4. The method according to claim 3, characterized in that The determining a first result based on the weighted adjacency matrix and the indegree centrality includes: Based on the weighted adjacency matrix, the total capital inflow of the legal person client is represented by the in-degree centrality; The first display information and the second display information of the node are used to represent the in-degree centrality, and a transaction capital flow network is constructed; The first display information has multiple levels, and the level of the first display information is positively correlated with the importance of the node. The second display information has multiple levels, and the level of the second display information is positively correlated with the total capital inflow of the node.

5. The method according to claim 3, characterized in that Determining a second result based on the weighted adjacency matrix and the out-degree centrality includes: Based on the weighted adjacency matrix, the out-degree centrality is used to represent the total capital outflow of the legal person client; The out-degree centrality is represented by the third display information and the fourth display information of the node, and a transaction capital flow network is constructed; The third display information has multiple levels, and the level of the third display information is positively correlated with the importance of the node. The fourth display information has multiple levels, and the level of the fourth display information is positively correlated with the total capital outflow of the node.

6. The method according to claim 3, characterized in that Determining the target legal person client according to at least one of the first result, the second result, and the third result includes: Selecting a legal person client that meets a preset condition from the third result; Based on the first result and the second result, determining a target legal person customer from the legal person customers that meet the preset conditions; or, The legal person customers who meet the preset conditions are regarded as the target legal person customers.

7. The method according to claim 1, characterized in that The real transaction record information includes transaction time, and the method further includes: Based on the transaction time, updating the directed weighted network of capital flows according to an annual frequency; Each year is regarded as a window period, and at the end of the year, the directed weighted network of capital flows is constructed based on the real transaction record information between corporate clients in the year.

8. A data processing device, characterized in that: The device comprises: The acquisition module is used to obtain real transaction record information between legal person customers; a construction module, configured to construct a directed weighted network of capital flows between the corporate clients based on the real transaction record information, wherein the nodes of the directed weighted network of capital flows represent the corporate clients, and the edges of the directed weighted network of capital flows represent the real transaction record information; A determination module is used to determine target legal person customers based on the directed weighted network of capital flows and network centrality.

9. An electronic device comprising: one or more processors; a memory for storing one or more computer programs, It is characterized in that the one or more processors execute the one or more computer programs to implement the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program or instruction stored thereon, characterized in that: When the computer program or instruction is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

11. A computer program product comprising a computer program or instructions, characterized in that When the computer program or instruction is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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