Resource Tracking Method and Related Products

Abstract

This application belongs to the field of computer technology, and particularly relates to a resource tracking method, a resource tracking device, a computer-readable medium, an electronic device, and a computer program product. The method includes: obtaining an associated entity that has a resource flow relationship with the resource to be tracked, where the associated entity includes at least one of a resource inflow entity or a resource outflow entity; counting the resource flow data of the associated entity, and screening one or more flowing resources from the resource flow data that have different resource flow directions from the resource to be tracked; respectively obtaining the time differences when the resource to be tracked generates resource flows with each flowing resource; predicting the flow correlation degree between the resource to be tracked and the flowing resources according to the time differences, and the flow correlation degree has a negative correlation with the time differences; and screening a combination of flowing resources that matches the resource amount of the resource to be tracked according to the flow correlation degree. This application can reduce the difficulty of resource tracking and improve the efficiency of resource tracking.

Description

Technical Field

[0001] This application belongs to the field of computer technology, and particularly relates to a resource tracking method, a resource tracking device, a computer-readable medium, an electronic device, and a computer program product. Background Art

[0002] With the development of computer and network technologies, based on network platforms, it is possible to achieve fast and efficient resource transfer between different business entities, such as the transfer of monetary resources, the trading or exchange of commodity resources, the distribution or collection of data resources, and so on.

[0003] In order to supervise the process and results of resource flow, it is generally necessary to record the resource flow paths in detail. However, since the resource transfer process usually involves the interaction processes of a large number of business entities, the resource transfer data from different sources and destinations are usually mixed together and difficult to distinguish. Therefore, how to efficiently track resources is an urgent problem to be solved at present. Summary of the Invention

[0004] The purpose of this application is to provide a resource tracking method, a resource tracking device, a computer-readable medium, an electronic device, and a computer program product, which can at least overcome the technical problems such as large resource tracking difficulty and low efficiency in the related technologies to a certain extent.

[0005] Other features and advantages of this application will become apparent through the following detailed description, or will be partially learned through the practice of this application.

[0006] According to one aspect of the embodiments of this application, a resource tracking method is provided, and the method includes:

[0007] Obtain associated entities that have a resource flow relationship with the resource to be tracked, where the associated entities include at least one of a resource inflow entity or a resource outflow entity;

[0008] Statistically analyze the resource flow data of the associated entities, and screen one or more flowing resources from the resource flow data that have different resource flow directions from the resource to be tracked;

[0009] Respectively obtain the time differences when the resource to be tracked has a resource flow with each of the flowing resources;

[0010] Predict the flow correlation degree between the resource to be tracked and the flowing resources according to the time differences, and the flow correlation degree has a negative correlation with the time differences;

[0011] Screen a combination of flowing resources that matches the resource amount of the resource to be tracked according to the flow correlation degree.

[0012] According to one aspect of the embodiments of the present application, there is provided a resource tracking device, which includes:

[0013] A main body acquisition module, configured to acquire an associated main body that has a resource flow relationship with the resource to be tracked, where the associated main body includes at least one of a resource inflow main body or a resource outflow main body;

[0014] A data statistics module, configured to count the resource flow data of the associated main body, and screen one or more flowing resources that have different resource flow directions from the resource to be tracked from the resource flow data;

[0015] A time acquisition module, configured to respectively acquire the time difference when the resource to be tracked and each of the flowing resources have a resource flow;

[0016] An association prediction module, configured to predict the flow association degree between the resource to be tracked and the flowing resources according to the time difference, and the flow association degree has a negative correlation with the time difference;

[0017] A resource screening module, configured to screen a combination of flowing resources that matches the resource amount of the resource to be tracked according to the flow association degree.

[0018] According to one aspect of the embodiments of the present application, there is provided a computer-readable medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the resource tracking method in the above technical solution.

[0019] According to one aspect of the embodiments of the present application, there is provided an electronic device, which includes: a processor; and a memory for storing executable instructions of the processor; wherein, the processor is configured to execute the resource tracking method in the above technical solution by executing the executable instructions.

[0020] According to one aspect of the embodiments of the present application, there is provided a computer program product or a computer program, which includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the resource tracking method in the above technical solution.

[0021] In the technical solution provided by the embodiments of the present application, starting from the associated entities that have a resource process relationship with the resource to be traced, by statistically analyzing the resource flow data of the associated entities, the flow association degree between each flowing resource and the resource to be traced can be predicted based on time correlation. Thus, a combination of flowing resources that matches the resource quantity of the resource to be traced can be selected according to the flow association degree. This combination of flowing resources serves as the source of resource flow upstream of the resource to be traced or the destination of resource flow downstream of the resource to be traced. This resource tracing method can automatically mine the transfer path of resources according to time correlation, reduce the difficulty of resource tracing, and improve the efficiency of resource tracing.

[0022] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The drawings herein are incorporated into the specification and form a part of this specification, showing embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0024] Figure 1 Schematically shows an exemplary system architecture block diagram applying the technical solution of the present application.

[0025] Figure 2 Shows a flowchart of the steps of the resource tracing method in an embodiment of the present application.

[0026] Figure 3 Shows a flowchart of the steps of statistically analyzing resource flow data in an embodiment of the present application.

[0027] Figure 4 Shows a data table for summarizing resource flow data in an embodiment of the present application.

[0028] Figure 5 Shows a flowchart of the steps of predicting the flow association degree in an embodiment of the present application.

[0029] Figure 6 Shows a resource flow diagram in an application scenario of the embodiments of the present application.

[0030] Figure 7 Shows the main process of tracking the flow of funds in an application scenario of the embodiments of the present application.

[0031] Figure 8 Schematically shows a structural block diagram of the resource tracing device provided by the embodiments of the present application.

[0032] Figure 9 A block diagram of a computer system of an electronic device suitable for implementing the embodiments of the present application is schematically shown. Detailed implementation manners

[0033] Example embodiments will now be described more fully with reference to the accompanying drawings. However, the example embodiments can be implemented in various forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this application will be more complete and comprehensive, and will fully convey the concept of the example embodiments to those skilled in the art.

[0034] In addition, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of the embodiments of the present application. However, those skilled in the art will realize that the technical solutions of the present application can be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. can be used. In other cases, well-known methods, devices, implementations, or operations are not shown or described in detail to avoid obscuring aspects of the present application.

[0035] The block diagrams shown in the accompanying drawings are only functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor devices and / or microcontroller devices.

[0036] The flowcharts shown in the accompanying drawings are only illustrative and do not necessarily include all the contents and operations / steps, nor are they necessarily executed in the described order. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to the actual situation.

[0037] In the specific implementation manners of the present application, data related to user information, transaction records, payment records, resource transfer records, etc. are involved. When the various embodiments of the present application are applied to specific products or technologies, user permission or consent needs to be obtained, and the collection, use, and processing of the relevant data need to comply with the relevant laws, regulations, and standards of the relevant countries and regions.

[0038] Figure 1 A schematic block diagram of an exemplary system architecture applying the technical solution of the present application is shown.

[0039] Such as Figure 1As shown, the system architecture 100 may include a terminal device 110, a network 120, and a server 130. The terminal device 110 may include various electronic devices such as a smart phone, a tablet computer, a laptop computer, and a desktop computer. The server 130 may be an independent physical server, or a server cluster or a distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The network 120 may be a communication medium of various connection types capable of providing a communication link between the terminal device 110 and the server 130. For example, it may be a wired communication link or a wireless communication link.

[0040] According to implementation requirements, the system architecture in the embodiments of the present application may have any number of terminal devices, networks, and servers. For example, the server 130 may be a server group composed of multiple server devices. In addition, the technical solutions provided in the embodiments of the present application may be applied to the terminal device 110, or may be applied to the server 130, or may be jointly implemented by the terminal device 110 and the server 130. The present application does not make special limitations on this.

[0041] For example, a user may perform a resource transfer operation through a client application installed on the terminal device 110. For example, the user may execute various types of resource transfer operations such as the transfer of currency resources, the transaction or replacement of commodity resources, and the distribution or collection of data resources through various software applications such as a payment application, a social application, and a financial application. The relevant transfer data generated during the resource transfer process may be uploaded to the server 130 with the user's permission, so that the server 130 can store, record, and analyze the relevant transfer data of different users, thereby better providing resource transfer services for users.

[0042] Taking the capital transfer as an example, the main body capital flow tracking in the related art mainly determines the capital flow direction of the user main body based on the objects of the total capital flowing out of the user main body for a period of time and the capital amount distribution of each object. Similarly, the capital upstream of the user main body can also be found through the capital inflow distribution of the capital inflow objects of the user main body for a period of time. However, when there are multiple capital uses in the upstream and downstream of the user main body, one or several risky capital transactions are easily mixed in other normal transactions, resulting in the inability to accurately locate the source and destination of the risky transaction funds. Moreover, in this case, since the risky capital flow is dispersed by other capital flows, it is often difficult to perform multi-level capital flow analysis on it.

[0043] Using the technical solution provided in the embodiments of the present application, it is possible to find the previous or next capital flow with the highest correlation with the capital based on the time when the risky capital occurs, making the capital source and destination more focused, and facilitating the gradual and accurate expansion of the entire capital flow source and destination when there are multi-level capital relationships.

[0044] For ease of understanding, the following implementations are mainly described using the application scenario of capital flow as an example, but the implementations in this application can be applied to various types of resource flow scenarios, and this application is not limited to this.

[0045] The following is a detailed description of the technical solutions such as the resource tracking method, resource tracking device, computer-readable medium, electronic device, and computer program product provided by the present application in conjunction with specific implementation methods.

[0046] Figure 2 A flowchart of a resource tracking method in one embodiment of the present application is shown. The resource tracking method can be performed by Figure 1 The process may be executed by the terminal device shown, or may be executed by a server, or may be executed jointly by the terminal device and the server.

[0047] like Figure 2 As shown, the resource tracking method in the embodiment of the present application may mainly include the following steps S210 to S250.

[0048] Step S210: Acquire an associated subject that has a resource flow relationship with the resource to be tracked, where the associated subject includes at least one of a resource inflow subject and a resource outflow subject;

[0049] Step S220: Counting resource flow data of the associated subject, and screening one or more flow resources having a different resource flow direction from the resource to be tracked from the resource flow data;

[0050] Step S230: respectively obtaining the time difference between the resource to be tracked and each flow resource generating the resource flow;

[0051] Step S240: predicting the flow correlation between the resource to be tracked and the flow resource according to the time difference, where the flow correlation is negatively correlated with the time difference;

[0052] Step S250: screening flow resource combinations that match the resource quantities of the resources to be tracked according to the flow correlation.

[0053] In the resource tracking method provided in the embodiment of the present application, starting from the associated subject that has a resource flow relationship with the resource to be tracked, by counting the resource flow data of the associated subject, the flow correlation between each flow resource and the resource to be tracked can be predicted based on time correlation, so that a flow resource combination that matches the resource amount of the resource to be tracked can be screened out according to the flow correlation, and the flow resource combination serves as the resource flow source located upstream of the resource to be tracked or the resource flow destination located downstream of the resource to be tracked. The resource tracking method can automatically mine the flow path of resources according to time correlation, reduce the difficulty of resource tracking, and improve the efficiency of resource tracking.

[0054] The following will separately elaborate on each method step of the resource tracking method in the above embodiments in detail.

[0055] In step S210, obtain the associated entities that have a resource flow relationship with the resource to be tracked. The associated entities include at least one of the resource inflow entity or the resource outflow entity.

[0056] The resource to be tracked refers to one resource or a combination of multiple resources for which the source or destination of the resource flow needs to be tracked. For example, when funds are transferred among multiple user entities, the initial source or the final destination of a sum of money can be obtained through tracking.

[0057] The resource flow relationship includes two types: the resource inflow relationship and the resource outflow relationship. For example, when user A receives the resource to be tracked transferred by other users, user A is the resource inflow entity relative to the resource to be tracked. When user A transfers the resource to be tracked to other users, user A is the resource outflow entity relative to the resource to be tracked.

[0058] In the embodiments of the present application, different types of associated entities can be selected according to the tracking requirements of the resource. Taking the resource to be tracked transferred from user A to user B as an example; when it is necessary to track the source of the resource, the resource outflow entity can be selected as the associated entity, that is, user A is selected as the associated entity; when it is necessary to track the destination of the resource, the resource inflow entity can be selected as the associated entity, that is, user B is selected as the associated entity.

[0059] In an embodiment of the present application, two types of associated entities, namely the resource inflow entity and the resource outflow entity, can be selected simultaneously, so that the source tracking and destination tracking of the resource to be tracked can be carried out respectively.

[0060] Step S220: Statistically analyze the resource flow data of the associated entities, and screen out one or more flowing resources with different resource flow directions from the resource flow data for the resource to be tracked.

[0061] Figure 3 Shows the step flow chart of statistically analyzing the resource flow data in an embodiment of the present application. As Figure 3 shown, on the basis of the above embodiments, statistically analyzing the resource flow data of the associated entities in step S220 may include the following steps S310 to S330.

[0062] Step S310: Obtain the flow time when the resource to be tracked generates a resource flow.

[0063] The flow time includes at least one of the resource outflow time or the resource inflow time. For example, when there is a resource inflow relationship between the resource to be tracked and the associated entity, the resource to be tracked flows into the associated entity, and the corresponding flow time of the resource flow is the resource inflow time of the resource to be tracked; for another example, when there is a resource outflow relationship between the resource to be tracked and the associated entity, the resource to be tracked flows out of the associated entity, and the corresponding flow time of the resource flow is the resource outflow time of the resource to be tracked.

[0064] Step S320: Obtain the statistical time range related to the flow time of the resource to be tracked.

[0065] In an embodiment of the present application, a statistical time range with the flow time of the resource to be tracked as the intermediate node can be obtained. For example, a time starting point is selected at a first time distance before the flow time of the resource to be tracked, and a time ending point is selected at a second time distance after the flow time of the resource to be tracked. The range delimited by the time starting point and the time ending point is used as the statistical time range. Among them, the first time distance can be the same as or different from the second time distance.

[0066] In an embodiment of the present application, different statistical time ranges can be determined according to the resource flow direction. In the embodiment of the present application, the resource flow direction of the resource to be tracked generating the resource flow is obtained. The resource flow direction includes flowing into the associated entity or flowing out of the associated entity; when the resource flow direction is flowing into the associated entity, a statistical time range with the flow time of the resource to be tracked as the time starting point is obtained; when the resource flow direction is flowing out of the associated entity, a statistical time range with the flow time of the resource to be tracked as the time ending point is obtained.

[0067] Step S330: Statistically analyze the resource flow data of the associated entity generating the resource flow within the statistical time range.

[0068] In an embodiment of the present application, the resource flow data includes detailed data related to the resource flow. Figure 4 Shows a data table for summarizing resource flow data in an embodiment of the present application. As Figure 4As shown, the resource flow data includes: a transaction number for uniquely identifying a resource transfer transaction, the transaction time of the resource transfer transaction (i.e., the flow time of the resource), the outflow party ID of the resource outflow entity related to the resource transfer transaction, the inflow party ID of the resource inflow entity, and the amount of the resource transfer transaction (i.e., the resource quantity). For example, the resource transfer transaction with the transaction number XXXX001 is a resource transfer transaction generated at 17:36:12 on October 14, 2021. The resource outflow entity of this transaction is IDXXX01, the resource inflow entity of this transaction is IDXXX05, and the resource quantity of the transaction is 23. This transaction indicates that user IDXXX01 transferred 23 resources to user IDXXX05 at the above time point.

[0069] Step S230: Obtain the time differences between the resource to be traced and each flowing resource when the resource flows are generated, respectively.

[0070] In an embodiment of the present application, the flowing time when the resource to be traced and each flowing resource generate resource flows can be obtained first, and at the same time, the time unit for counting the time difference can be obtained, and then the time differences between the resource to be traced and each flowing resource when the resource flows are generated are calculated based on this time unit. For example, if the time unit is "day", the time difference can be calculated by the number of days between the flowing times; if the time unit is "hour", the time difference can be calculated by the number of hours between the flowing times.

[0071] Step S240: Predict the flow correlation degree between the resource to be traced and the flowing resource according to the time difference, and the flow correlation degree has a negative correlation with the time difference.

[0072] In an embodiment of the present application, the flow correlation degree can be directly determined according to the time difference. When the time difference between the resource to be traced and the flowing resource is larger, the flow correlation degree between the two is lower; when the time difference between the resource to be traced and the flowing resource is smaller, the flow correlation degree between the two is higher. The embodiment of the present application is applicable to a transaction scenario with a high degree of dispersion of the main bodies of resource transfer. In this scenario, there may be a situation where resources flow in or out dispersedly, resulting in a relatively large difference in the resource quantity between resource inflow and resource outflow, but the tightness feature in the transaction time is relatively obvious. In this case, the time difference can be directly used to calculate the flow correlation degree.

[0073] In some other transaction scenarios, the time difference of the flowing time and the resource quantity can be used simultaneously to calculate the flow correlation degree, thereby improving the accuracy and reliability of the calculation of the flow correlation degree.

[0074] Figure 5 Shows the step flowchart for predicting the flow correlation degree in an embodiment of the present application. As Figure 5As shown, based on the above embodiments, step S240 may further include steps S510 to S540 as follows.

[0075] Step S510: Determine a flow time correlation parameter representing the time difference degree of resource flow according to the time difference and a preset time adjustment coefficient.

[0076] In an embodiment of the present application, taking the time adjustment coefficient as an exponent, perform a power operation on the absolute value of the time difference to obtain a flow time correlation parameter representing the time difference degree of resource flow.

[0077] Step S520: Obtain the resource amounts of the resource to be traced and each flowing resource respectively.

[0078] Step S530: Determine a resource amount correlation parameter representing the resource amount similarity of resource flow according to the resource amounts.

[0079] In an embodiment of the present application, obtain the sum value and difference value of the resource amounts of the resource to be traced and the flowing resource; determine a resource amount correlation parameter representing the resource amount similarity of resource flow according to the sum value of the resource amounts, the difference value of the resource amounts, and a preset resource amount adjustment coefficient.

[0080] In an embodiment of the present application, the resource amount correlation parameter has a positive correlation with the sum value of the resource amounts and a negative correlation with the absolute value of the difference value of the resource amounts. The larger the absolute value of the difference value of the resource amounts, the lower the similarity of the two resources in terms of resource amount. In the embodiments of the present application, by introducing the sum value of the resource amounts, the influence of the net resource amount on the similarity can be reduced, and the usability of the resource amount correlation parameter can be improved.

[0081] In an embodiment of the present application, the method for determining the resource amount correlation parameter may include: performing a summation operation on the absolute value of the difference value of the resource amounts and a preset resource amount adjustment coefficient to obtain a coefficient sum value, and the resource amount adjustment coefficient is a positive number; performing a quotient operation on the sum value of the resource amounts and the coefficient sum value to obtain a coefficient ratio; performing a logarithmic operation on the coefficient ratio to obtain a resource amount correlation parameter representing the resource amount similarity of resource flow.

[0082] Step S540: Predict the flow correlation degree between the resource to be traced and the flowing resource according to the flow time correlation parameter and the resource amount correlation parameter; the flow correlation degree has a negative correlation with the flow time correlation parameter and a positive correlation with the resource amount correlation parameter.

[0083] The flow time correlation parameter is used to represent the time difference degree between two resources. The larger the time difference degree, the lower the flow correlation degree; the resource amount correlation parameter is used to represent the resource amount similarity between two resources. The larger the resource amount similarity, the higher the flow correlation degree.

[0084] Based on the above steps S510 to S540, the correlation degree between resources can be predicted from two dimensions of time and resource quantity, with relatively high prediction accuracy and reliability.

[0085] In step S250, according to the flow correlation degree, a combination of flowing resources that matches the resource quantity of the resource to be traced is screened.

[0086] In an embodiment of the present application, the method for screening a combination of flowing resources may include: sorting the flowing resources according to the flow correlation degree to obtain a flowing resource sequence; sequentially selecting one or more flowing resources from the flowing resource sequence in descending order of the flow correlation degree to form a combination of flowing resources until the total resource quantity of the combination of flowing resources is greater than or equal to the resource quantity of the resource to be traced.

[0087] For example, each flowing resource is sequentially arranged in descending order of the flow correlation degree in the flowing resource sequence; first, the first flowing resource ranked first is selected, and the numerical relationship between the resource quantity N1 of this flowing resource and the resource quantity N0 of the resource to be traced is compared.

[0088] If the resource quantity N1 of the first flowing resource is greater than or equal to the resource quantity N0 of the resource to be traced, it can be determined that the first flowing resource is used as the combination of flowing resources that matches the resource quantity of the resource to be traced.

[0089] If the resource quantity N1 of the first flowing resource is less than the resource quantity N0 of the resource to be traced, the second flowing resource ranked second can be continuously added to the combination of flowing resources.

[0090] The resource quantity of the second flowing resource is N2. At this time, the total resource quantity of the combination of flowing resources is N1 + N2. If the total resource quantity N1 + N2 is greater than or equal to the resource quantity N0 of the resource to be traced, it can be determined that the first flowing resource and the second flowing resource form the combination of flowing resources that matches the resource quantity of the resource to be traced.

[0091] If the total resource quantity N1 + N2 is less than the resource quantity N0 of the resource to be traced, the third flowing resource ranked third can be continuously added to the combination of flowing resources, and after updating the total resource quantity of the combination of flowing resources, it is compared with the resource quantity of the resource to be traced again. And so on, until the total resource quantity of the combination of flowing resources is greater than or equal to the resource quantity of the resource to be traced.

[0092] In one embodiment of the present application, after screening the mobile resource combinations that match the resource quantity of the resource to be traced according to the mobile correlation degree, the associated entities that generate resource flow relationships with each mobile resource in the mobile resource combination can be obtained, and the mobile resource combinations corresponding to the associated entities can be iteratively obtained until the mobile edge nodes of the resource to be traced are obtained. The mobile edge nodes include at least one of the resource flow start point or the resource flow end point. By using the iterative method, other resources with a high correlation degree with the resource to be traced can be found step by step, and finally the resource flow start point or the resource flow end point of the resource to be traced can be determined. Therefore, a complete resource flow path can be obtained.

[0093] In one embodiment of the present application, after obtaining the mobile edge nodes of the resource to be traced, the proportion of the resource quantity of each mobile resource in the mobile resource combination in the resource to be traced can be sequentially counted in descending order of the mobile correlation degree; then, taking the associated entity as a node and the resource quantity proportion as an edge, a resource flow diagram of the resource to be traced can be drawn. Based on the resource flow diagram, the complete resource flow path of the resource to be traced can be intuitively seen, and the proportion of the resource quantity in each flow link can be compared. Therefore, important resource transfer nodes can be quickly screened out.

[0094] Figure 6 The resource flow diagram in an application scenario of an embodiment of the present application is shown. As Figure 6 shown, a certain sum or several sums of funds transferred from user B to user A are the resources to be traced. By executing the above embodiments of the present application, the flow situation after the funds reach user A can be automatically mined. For example, 61% of the funds are transferred to user C, 30% of the funds are transferred to user E, and the other 9% of the funds are transferred to user D. On this basis, iterative operations are respectively performed on the funds flowing into user C and user D, that is, the resource flow path mining is continued. After iterative calculation, it is found that among the 61% of the funds flowing to user C, 59% continue to flow to user E, and at the same time, user E transfers all 89% of the aggregated funds to user F. It can be seen that user F is the largest beneficiary of this sum of funds, while user C and user D obtain a small amount of income from the fund transfer.

[0095] Figure 7 The main process of fund transfer tracking in an application scenario of an embodiment of the present application is shown. As Figure 7 shown, this process mainly includes the following steps S701 to S705.

[0096] Step S701: Collect transaction data and perform data cleaning on the transaction data.

[0097] After collecting the transaction detail data of all users, it can be obtained after data cleaning as Figure 4Summary data table of the resource flow data shown, including transaction time, transaction amount, and multiple other data.

[0098] Step S702: Calculate the transaction correlation degree between each incoming fund and each outgoing fund.

[0099] (1) Calculate the flow time correlation parameter t for representing the time difference degree of resource flow:

[0100] t = |T out - T in | k

[0101] Where, T in is the transaction time when the funds flow into the current entity, T out is the transaction time when the funds flow out of the current entity, and k is the time adjustment coefficient.

[0102] The flow time correlation parameter is a parameter that has a positive correlation with the time difference in days between two transactions. The greater the time difference in days between the two transactions, the greater the flow time correlation parameter, and the smaller the correlation between the two transactions. k is the time adjustment coefficient used to adjust the weight of the time parameter in the correlation degree calculation. The greater k is, the greater the flow time correlation parameter corresponding to the change in unit time.

[0103] Generally speaking, if it is limited that the outflow time of the associated transaction is later than the inflow time, that is, only considering the scenario where T out - T in is greater than 0, then the process of taking the absolute value of the time difference can also be omitted in the above formula.

[0104] In addition, in some risk analysis scenarios, there may be a situation where funds are transferred out first, and then transferred in through other channels to make up for an outgoing fund. In this scenario, it can be considered not to enforce the restriction on the front and back of the fund entry and exit time. Even if the outgoing funds are before the incoming funds, the time correlation can be calculated through the absolute value of the time difference, and then the subsequent steps can be carried out.

[0105] (2) Calculate the resource quantity correlation parameter m for representing the resource quantity similarity of resource flow:

[0106]

[0107] Where, m1 and m2 are the resource quantities of two resources in the incoming transaction and the outgoing transaction respectively, and δ is a resource quantity adjustment coefficient with a value greater than 0.

[0108] When the amounts of the two transactions are the same, the resource quantity correlation parameter m can obtain the maximum value:

[0109]

[0110] When there is a significant difference between two amounts, for example, when m1 is significantly greater than m2, the resource volume correlation parameter m can approximately obtain the minimum value (approximately equal to 0):

[0111]

[0112] The larger the resource volume correlation parameter m, the greater the correlation between the amounts of the two funds.

[0113] (3) Calculate the flow correlation degree s of the two funds:

[0114]

[0115] The flow correlation degree in this application scenario is the ratio of the resource volume correlation parameter m to the flow time correlation parameter t. That is, the larger the time correlation parameter of the two funds and the smaller the resource volume correlation parameter, the smaller the overall flow correlation degree of the two funds; conversely, the larger the flow correlation degree of the two funds.

[0116] Step S703: Aggregate and calculate the transaction flow direction.

[0117] (1) Sort all transactions corresponding to a certain transaction according to the flow correlation degree.

[0118] For example, in order to calculate the flow direction of 100,000 yuan of funds flowing in at 10 o'clock in the morning of a certain day for a certain user A, first calculate the flow correlation degree between all outflow transactions after this transaction time and this transaction. Then, sort the calculated flow correlation degrees of transactions within a subsequent period of time. The higher the flow correlation degree, the higher the ranking.

[0119] (2) Calculate the fund outflow direction

[0120] After sorting, select the funds flowing out to user B with the highest flow correlation degree, and judge whether its amount covers the amount of this 100,000 yuan of funds. If the funds flowing out to user B are greater than or equal to 100,000 yuan, then take 100% of this 100,000 yuan of inflowing funds and flow out to user B.

[0121] If the transaction with the highest flow correlation degree fails to cover all the inflowing funds, for example, a transaction of 80,000 yuan flowing out to user C has the highest flow correlation degree with this 100,000 yuan of inflowing funds, but its amount is only 80,000 yuan and fails to cover the 100,000 yuan of inflowing funds. At this time, the transaction flowing into user D with the second-highest flow correlation degree can be further selected, and so on. If the amount of the second one is greater than 20,000 yuan, then at this time, it can be determined that the outflow situation of this 100,000 yuan of inflowing funds is that 80% of the funds flow from user A to user C, and the remaining 20% of the funds flow from user A to user D.

[0122] Step S704: Iteratively calculate the fund transfer situation of the next level.

[0123] In the above step S702, the inflow entity and outflow entity of a certain fund flow at the next level or the previous level are calculated. In order to trace the ultimate source or ultimate flow of the fund, it is necessary to iteratively calculate the above steps and continue to calculate the subsequent funds and users with the highest correlation after the 100,000 yuan flowing into A flows to other users. When it comes to situations outside the fund transfer system, such as fund withdrawal, recharge, etc., the corresponding flow edge can be determined and the resource tracking can be stopped.

[0124] Step S705: Aggregate multiple funds.

[0125] When not tracking a single transaction but multiple transactions of a certain entity or multiple entities over a period of time, for the result of the above step S703, the sources or flows of multiple funds can be aggregated to obtain the cumulative overall fund flow situation.

[0126] Through the technical solution provided by the embodiments of the present application, it is possible to accurately trace the source and destination of each fund, and there will be no problem that the tracking of the fund flow is dispersed due to a large number of other types of transactions of some entities within the statistical data time, resulting in the situation that the further follow-up of the fund trend cannot be carried out. At the front-end interaction level, the fund flow automatic analysis technology implemented by this method can greatly improve the risk fund analysis efficiency of the auditors and reduce the fund flow analysis time by more than 60%.

[0127] It should be noted that although the steps of the method in the present application are described in a specific order in the drawings, this does not require or imply that these steps must be executed in this specific order, or that all the steps shown must be executed to achieve the desired result. Additionally or alternatively, some steps can be omitted, multiple steps can be combined into one step for execution, and / or one step can be decomposed into multiple steps for execution, etc.

[0128] The following introduces the device embodiments of the present application, which can be used to execute the resource tracking method in the above embodiments of the present application. Figure 8 Schematically shows the structural block diagram of the resource tracking device provided by the embodiments of the present application. As Figure 8 shown, the resource tracking device 800 mainly may include:

[0129] The entity acquisition module 810 is configured to acquire an associated entity having a resource flow relationship with the resource to be tracked, and the associated entity includes at least one of a resource inflow entity or a resource outflow entity;

[0130] A data statistics module 820, configured to count the resource flow data of the associated entity, and screen one or more flowing resources with different resource flow directions from the resource flow data compared with the resource to be traced;

[0131] A time acquisition module 830, configured to respectively obtain the time differences when the resource to be traced and each of the flowing resources generate resource flows;

[0132] An association prediction module 840, configured to predict the flow association degree between the resource to be traced and the flowing resource according to the time difference, and the flow association degree has a negative correlation with the time difference;

[0133] A resource screening module 850, configured to screen a combination of flowing resources that matches the resource amount of the resource to be traced according to the flow association degree.

[0134] In an embodiment of the present application, based on the above embodiments, the association prediction module 840 may further include:

[0135] A time parameter determination module 841, configured to determine a flow time association parameter for representing the time difference degree of resource flow according to the time difference and a preset time adjustment coefficient;

[0136] A resource amount acquisition module 842, configured to respectively obtain the resource amounts of the resource to be traced and each of the flowing resources;

[0137] A resource amount parameter determination module 843, configured to determine a resource amount association parameter for representing the resource amount similarity of resource flow according to the resource amount;

[0138] A flow association degree determination module 844, configured to predict the flow association degree between the resource to be traced and the flowing resource according to the flow time association parameter and the resource amount association parameter; the flow association degree has a negative correlation with the flow time association parameter and a positive correlation with the resource amount association parameter.

[0139] In an embodiment of the present application, based on the above embodiments, the time parameter determination module 841 may be further configured to: take the time adjustment coefficient as an exponent, perform a power operation on the absolute value of the time difference, and obtain a flow time association parameter for representing the time difference degree of resource flow.

[0140] In one embodiment of the present application, based on the above embodiments, the resource quantity parameter determination module 843 may be further configured to: obtain the resource quantity sum value and the resource quantity difference value of the to-be-tracked resource and the flowing resource; determine a resource quantity correlation parameter for representing the resource quantity similarity of resource flow according to the resource quantity sum value, the resource quantity difference value, and a preset resource quantity adjustment coefficient.

[0141] In one embodiment of the present application, based on the above embodiments, the resource quantity correlation parameter has a positive correlation with the resource quantity sum value and a negative correlation with the absolute value of the resource quantity difference value.

[0142] In one embodiment of the present application, based on the above embodiments, the resource quantity parameter determination module 843 may be further configured to: perform a summation operation on the absolute value of the resource quantity difference value and a preset resource quantity adjustment coefficient to obtain a coefficient sum value, where the resource quantity adjustment coefficient is a positive number; perform a division operation on the resource quantity sum value and the coefficient sum value to obtain a coefficient ratio; perform a logarithmic operation on the coefficient ratio to obtain a resource quantity correlation parameter for representing the resource quantity similarity of resource flow.

[0143] In one embodiment of the present application, based on the above embodiments, the data statistics module 820 may further include:

[0144] A flow time acquisition module 821, configured to acquire the flow time when the to-be-tracked resource generates resource flow;

[0145] A time range acquisition module 822, configured to acquire a statistical time range related to the flow time of the to-be-tracked resource;

[0146] A flow data statistics module 823, configured to statistically analyze the resource flow data generated by the associated entity within the statistical time range.

[0147] In one embodiment of the present application, based on the above embodiments, the time range acquisition module 822 may be further configured to: acquire a statistical time range with the flow time of the to-be-tracked resource as the intermediate node.

[0148] In one embodiment of the present application, based on the above embodiments, the time range acquisition module 822 may be further configured to: acquire the resource flow direction of the to-be-tracked resource when generating resource flow, where the resource flow direction includes flowing into the associated entity or flowing out of the associated entity; when the resource flow direction is flowing into the associated entity, acquire a statistical time range with the flow time of the to-be-tracked resource as the time starting point; when the resource flow direction is flowing out of the associated entity, acquire a statistical time range with the flow time of the to-be-tracked resource as the time ending point.

[0149] In one embodiment of the present application, based on the above embodiments, the resource screening module 850 may further include:

[0150] A resource sorting module 851, configured to sort the flowing resources according to the flow correlation degree to obtain a flowing resource sequence;

[0151] A resource combination module 852, configured to sequentially select one or more flowing resources from the flowing resource sequence to form a flowing resource combination in the order of the flow correlation degree from high to low until the total amount of resources in the flowing resource combination is greater than or equal to the amount of resources of the resource to be traced.

[0152] In one embodiment of the present application, based on the above embodiments, the resource tracing device 800 may further include: an iteration module, configured to obtain an associated entity that has a resource flow relationship with each flowing resource in the flowing resource combination, and iteratively obtain a flowing resource combination corresponding to the associated entity until a flowing edge node of the resource to be traced is obtained, where the flowing edge node includes at least one of a resource flow start point or a resource flow end point.

[0153] In one embodiment of the present application, based on the above embodiments, the resource tracing device 800 may further include: a proportion statistics module, configured to sequentially count the proportion of the resource amount of each flowing resource in the flowing resource combination in the resource to be traced in the order of the flow correlation degree from high to low; a flow diagram drawing module, configured to draw a resource flow diagram of the resource to be traced with the associated entity as a node and the resource amount proportion as an edge.

[0154] The specific details of the resource tracing device provided in the embodiments of the present application have been described in detail in the corresponding method embodiments, and will not be repeated here.

[0155] Figure 9 Schematically shows a computer system block diagram of an electronic device for implementing the embodiments of the present application.

[0156] It should be noted that Figure 9 The computer system 900 of the electronic device shown is only an example and should not bring any limitation to the functions and usage scopes of the embodiments of the present application.

[0157] Such as Figure 9As shown, computer system 900 includes a central processing unit 901 (CPU), which can perform various appropriate actions and processes according to programs stored in read-only memory 902 (ROM) or programs loaded from storage section 908 into random access memory 903 (RAM). In random access memory 903, various programs and data required for system operation are also stored. The central processing unit 901, read-only memory 902, and random access memory 903 are connected to each other via bus 904. Input / output interface 905 (Input / Output interface, i.e., I / O interface) is also connected to bus 904.

[0158] The following components are connected to input / output interface 905: input section 906 including a keyboard, a mouse, etc.; output section 907 including, for example, a cathode ray tube (CRT), a liquid crystal display (LCD), etc. and a speaker, etc.; storage section 908 including a hard disk, etc.; and communication section 909 including a network interface card such as a local area network card, a modem, etc. Communication section 909 performs communication processing via a network such as the Internet. Drive 910 is also connected to input / output interface 905 as needed. A removable medium 911, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on drive 910 as needed so that a computer program read from it can be installed into storage section 908 as needed.

[0159] In particular, according to an embodiment of the present application, the processes described in each method flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product that includes a computer program carried on a computer-readable medium, and the computer program includes program code for performing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network via communication section 909, and / or installed from removable medium 911. When the computer program is executed by central processing unit 901, various functions defined in the system of the present application are executed.

[0160] It should be noted that the computer-readable medium shown in the embodiments of the present application can be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, the computer-readable storage medium can be any tangible medium that contains or stores a program, and this program can be used by or in combination with an instruction execution system, apparatus, or device. In the present application, a computer-readable signal medium can include a data signal propagated in a baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, and this computer-readable medium can send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0161] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagram can represent a module, a program segment, or a part of code, and the above module, program segment, or 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 blocks may occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram or flowchart, as well as the combination of blocks in the block diagram or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0162] It should be noted that although several modules or units of the device for action execution are mentioned in the above detailed description, such division is not mandatory. In fact, according to the embodiments of the present application, the features and functions of the two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0163] Through the description of the above embodiments, those skilled in the art can easily understand that the example embodiments described herein can be implemented by software or by a combination of software and necessary hardware. Therefore, the technical solutions according to the embodiments of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on the network, and includes several instructions to enable a computing device (such as a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiments of the present application.

[0164] After considering the specification and practicing the invention disclosed herein, those skilled in the art will readily conceive of other embodiments of the present application. The present application is intended to cover any variations, uses, or adaptations of the present application, which follow the general principles of the present application and include known common knowledge or conventional technical means in the technical field not disclosed in the present application.

[0165] It should be understood that the present application is not limited to the exact structures already described and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present application is only limited by the appended claims.

Claims

1. A resource tracking method, characterized in that, Including: Obtain associated entities that have a resource flow relationship with the resource to be traced, where the associated entities include at least one of a resource inflow entity or a resource outflow entity; Statistically analyze the resource flow data of the associated entities, and screen one or more flowing resources from the resource flow data that have different resource flow directions from the resource to be traced; Respectively obtain the time differences when the resource to be traced has a resource flow with each of the flowing resources; Predict the flow association degree between the resource to be traced and the flowing resources according to the time differences, and the flow association degree has a negative correlation with the time differences; Screen a combination of flowing resources that matches the resource quantity of the resource to be traced according to the flow association degree.

2. The resource tracking method according to claim 1, characterized in that, Predicting the flow association degree between the resource to be traced and the flowing resources according to the time differences includes: Determine a flow time association parameter representing the time difference degree of resource flow according to the time differences and a preset time adjustment coefficient; Respectively obtain the resource quantities of the resource to be traced and each of the flowing resources; Determine a resource quantity association parameter representing the resource quantity similarity of resource flow according to the resource quantities; Predict the flow association degree between the resource to be traced and the flowing resources according to the flow time association parameter and the resource quantity association parameter; the flow association degree has a negative correlation with the flow time association parameter and a positive correlation with the resource quantity association parameter.

3. The resource tracking method according to claim 2, characterized in that, Determining a flow time association parameter representing the time difference degree of resource flow according to the time differences and a preset time adjustment coefficient includes: Taking the absolute value of the time difference as the exponent and performing a power operation to obtain a flow time association parameter representing the time difference degree of resource flow.

4. The resource tracking method according to claim 2, characterized in that, Determining a resource quantity association parameter representing the resource quantity similarity of resource flow according to the resource quantities includes: Obtain the sum value and the difference value of the resource quantities of the resource to be traced and the flowing resources; Determine a resource quantity association parameter representing the resource quantity similarity of resource flow according to the sum value of the resource quantities, the difference value of the resource quantities, and a preset resource quantity adjustment coefficient.

5. The resource tracking method according to claim 4, characterized in that, The resource quantity association parameter has a positive correlation with the sum value of the resource quantities and a negative correlation with the absolute value of the difference value of the resource quantities.

6. The resource tracking method according to claim 4, characterized in that, Determining a resource quantity association parameter representing the resource quantity similarity of resource flow according to the sum value of the resource quantities, the difference value of the resource quantities, and a preset resource quantity adjustment coefficient includes: Performing a summation operation on the absolute value of the difference value of the resource quantities and the preset resource quantity adjustment coefficient to obtain a coefficient sum value, where the resource quantity adjustment coefficient is a positive number; Performing a division operation on the sum value of the resource quantities and the coefficient sum value to obtain a coefficient ratio; Performing a logarithm operation on the coefficient ratio to obtain a resource quantity association parameter representing the resource quantity similarity of resource flow.

7. The resource tracking method according to any one of claims 1 to 6, characterized in that, Statistically analyzing the resource flow data of the associated entities includes: Obtain the flow time when the resource to be traced has a resource flow; Obtain a statistical time range related to the flow time of the resource to be traced; Statistically analyze the resource flow data of the associated entities that have a resource flow within the statistical time range.

8. The resource tracking method according to claim 7, characterized in that, Obtain a statistical time range related to the flow time of the to-be-tracked resource, including: Obtain a statistical time range with the flow time of the to-be-tracked resource as the intermediate node.

9. The resource tracking method according to claim 7, characterized in that, Obtain a statistical time range related to the flow time of the to-be-tracked resource, including: Obtain the resource flow direction of the to-be-tracked resource generating a resource flow, where the resource flow direction includes flowing into the associated entity or flowing out of the associated entity; When the resource flow direction is flowing into the associated entity, obtain a statistical time range with the flow time of the to-be-tracked resource as the time starting point; When the resource flow direction is flowing out of the associated entity, obtain a statistical time range with the flow time of the to-be-tracked resource as the time ending point.

10. The resource tracking method according to any one of claims 1 to 6, characterized in that, Screen a flow resource combination matching the resource quantity of the to-be-tracked resource according to the flow correlation degree, including: Sort the flow resources according to the flow correlation degree to obtain a flow resource sequence; In the order from high to low of the flow correlation degree, sequentially select one or more flow resources from the flow resource sequence to form a flow resource combination until the total resource quantity of the flow resource combination is greater than or equal to the resource quantity of the to-be-tracked resource.

11. The resource tracking method according to claim 10, characterized in that, After screening a flow resource combination matching the resource quantity of the to-be-tracked resource according to the flow correlation degree, the method further includes: Obtain the associated entities having a resource flow relationship with each flow resource in the flow resource combination, and iteratively obtain the flow resource combination corresponding to the associated entity until the flow edge nodes of the to-be-tracked resource are obtained, where the flow edge nodes include at least one of a resource flow starting point or a resource flow ending point.

12. The resource tracking method according to claim 11, characterized in that, After obtaining the flow edge nodes of the to-be-tracked resource, the method further includes: Sequentially count the proportion of the resource quantity of each flow resource in the flow resource combination in the to-be-tracked resource in the order from high to low of the flow correlation degree; Taking the associated entity as a node and the resource quantity proportion as an edge, draw a resource flow diagram of the to-be-tracked resource.

13. A resource tracking device, characterized in that, Including: A main body acquisition module configured to acquire an associated entity having a resource flow relationship with a to-be-tracked resource, where the associated entity includes at least one of a resource inflow entity or a resource outflow entity; A data statistics module configured to statistically analyze the resource flow data of the associated entity and screen one or more flow resources having different resource flow directions from the resource flow data compared with the to-be-tracked resource; A time acquisition module configured to respectively acquire the time difference between the to-be-tracked resource and each flow resource generating a resource flow; An association prediction module configured to predict the flow correlation degree between the to-be-tracked resource and the flow resource according to the time difference, where the flow correlation degree has a negative correlation relationship with the time difference; A resource screening module configured to screen a flow resource combination matching the resource quantity of the to-be-tracked resource according to the flow correlation degree.

14. A computer-readable medium, characterized in that, A computer program is stored on the computer-readable medium, and when the computer program is executed by a processor, it implements the resource tracking method according to any one of claims 1 to 12.

15. An electronic device, characterized in that, Including: A processor; And A memory for storing executable instructions of the processor; Wherein, the processor is configured to cause the electronic device to execute the resource tracking method according to any one of claims 1 to 12 by executing the executable instructions.

16. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the resource tracking method according to any one of claims 1 to 12.

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