Business risk data determination method and device, equipment, medium and product

Abstract

The invention discloses a business risk data determination method and device, equipment, a medium and a product. The invention relates to the technical field of data processing. The method comprises the following steps: acquiring resource transfer information associated with a current service, and extracting an index information combination from the resource transfer information; determining an index weight corresponding to each set index identifier according to the index data corresponding to each set index identifier; in the target risk tree, determining a risk path corresponding to the resource transfer information, node risk data of each node in the risk path, a set index identifier corresponding to each node of the target risk tree, an index data interval and the node risk data partially or totally different; and determining service risk data of the current service according to the node risk data corresponding to each node in the risk path and the index weight corresponding to the set index identifier corresponding to each node. According to the technical scheme, the purpose of improving the business risk data determination flexibility can be achieved.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of data processing technology, and in particular, to a method, device, equipment, medium and product for determining business risk data. Background Art

[0002] Existing technologies usually determine business risk data based on a large amount of logical judgment. However, the code programs developed based on a large amount of logical judgment need to be updated when the risk decision at any link changes. This leads to the problem of low data processing flexibility in the existing business risk data determination methods. Summary of the invention

[0003] Embodiments of the present invention provide a method, device, equipment, medium and product for determining business risk data, so as to solve the problem of low data processing flexibility in existing methods for determining business risk data.

[0004] In a first aspect, an embodiment of the present invention provides a method for determining business risk data, including:

[0005] Acquire resource transfer information associated with the current service, and extract an indicator information combination from the resource transfer information, wherein the indicator information combination includes at least two different set indicator identifiers and indicator data corresponding to each of the at least two different set indicator identifiers;

[0006] Determine the indicator weight corresponding to each of the set indicator identifiers according to the indicator data corresponding to each of the set indicator identifiers;

[0007] In the target risk tree, a risk path corresponding to the resource transfer information and node risk data of each node in the risk path are determined, wherein the set indicator identifier and indicator data interval corresponding to each node of the target risk tree are different from part or all of the node risk data;

[0008] The business risk data of the current business is determined according to the node risk data corresponding to each of the nodes in the risk path and the indicator weight corresponding to the set indicator identifier corresponding to each of the nodes.

[0009] In a second aspect, an embodiment of the present invention further provides a risk data determination device, including:

[0010] An information extraction module, used to obtain resource transfer information associated with the current business, and extract an indicator information combination from the resource transfer information, wherein the indicator information combination includes at least two different set indicator identifiers, and indicator data corresponding to each of the at least two different set indicator identifiers;

[0011] An indicator weight module, used to determine the indicator weight corresponding to each of the set indicator identifiers according to the indicator data corresponding to each of the set indicator identifiers;

[0012] A risk path module, used to determine, in a target risk tree, a risk path corresponding to the resource transfer information and node risk data of each node in the risk path, wherein the set indicator identifier and indicator data interval corresponding to each node of the target risk tree are different from part or all of the node risk data;

[0013] The risk data module is used to determine the business risk data of the current business according to the node risk data corresponding to each node in the risk path and the indicator weight corresponding to the set indicator identifier corresponding to each node.

[0014] In a third aspect, an embodiment of the present invention further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for determining business risk data described in any embodiment is implemented.

[0015] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a method for determining business risk data as described in any one of the embodiments of the present invention.

[0016] In a fifth aspect, an embodiment of the present invention further provides a computer program product, including a computer program, which, when executed by a processor, implements a method for determining business risk data as described in any one of the embodiments of the present invention.

[0017] The technical solution of the risk data determination method provided in the embodiment of the present invention determines the indicator weight corresponding to each set indicator identifier according to the indicator data corresponding to each set indicator identifier, so that the determination of the indicator weight corresponding to each set indicator identifier does not rely on the target risk tree, thereby improving the flexibility of the management of the indicator weight corresponding to each set indicator identifier; the target risk tree includes nodes corresponding to each set indicator identifier in the indicator information combination, and each node includes an indicator data interval and node risk data, wherein the configuration of the node risk data of each node is independent of the indicator data corresponding to the corresponding indicator identifier in the indicator information combination, thereby realizing the decoupling of the indicator configuration information and the risk tree configuration information, which helps to improve the flexibility and controllability of the management of the indicator configuration information and the risk tree configuration information, thereby improving the controllability and accuracy of the business risk data determination. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0019] Figure 1 A flowchart of a method for determining business risk data provided by an embodiment of the present invention;

[0020] Figure 2 A schematic diagram of the structure of a target risk tree provided by an embodiment of the present invention;

[0021] Figure 3 Another flow chart of the method for determining business risk data provided by an embodiment of the present invention;

[0022] Figure 4 Another flow chart of the method for determining business risk data provided by an embodiment of the present invention;

[0023] Figure 5A A schematic diagram of the structure of a device for determining business risk data provided by an embodiment of the present invention;

[0024] Figure 5B Another structural diagram of the device for determining business risk data provided by an embodiment of the present invention;

[0025] Figure 5C Another structural diagram of the device for determining business risk data provided by an embodiment of the present invention;

[0026] Figure 5D Another structural diagram of the device for determining business risk data provided by an embodiment of the present invention;

[0027] Figure 5E Another structural diagram of the device for determining business risk data provided by an embodiment of the present invention;

[0028] Figure 6 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0029] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0030] It should be noted that similar numbers and letters represent similar items in the following figures. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance. The acquisition, storage, use, processing, etc. of data in the technical solution of this application comply with the relevant provisions of national laws and regulations. It should be noted that in the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned, and they should be regarded as exemplary. The purpose is only to illustrate the feasibility of the implementation of the technical solution of this application, but it does not mean that the applicant has or must use the relevant content of the solution.

[0031] In order to ensure the resource security of resource holders, it is usually necessary to confirm the risk data of resource transactions before or during resource transfer through risk control methods; if the risk data is high, the risk of the resource transfer business is judged to be high, and the resource holder is advised to perform the resource transfer cautiously or not to perform the resource transfer; conversely, the risk of the resource transfer business is judged to be low, and the resource holder may not be given a risk warning at this time, or may be prompted that the risk of the resource transfer business is low. Therefore, the accuracy of the risk control method is directly related to whether the resource holder can safely transfer resources.

[0032] In summary, the embodiments of the present invention provide a method for determining business risk data to improve the accuracy of risk control results for resource transfer business, and ensure that resource holders can safely complete resource transfer without being overly conservative.

[0033] Figure 1 This is a flow chart of a method for determining business risk data provided by an embodiment of the present invention. This embodiment can be applied to situations where risk data of a resource transfer business to be, occurring, or already occurred is determined. The method can be executed by a risk data determination device, which can be implemented in the form of hardware and / or software, and can be configured in a processor of an electronic device. Figure 1 As shown, the method includes:

[0034] S110, obtaining resource transfer information associated with the current business, and extracting an indicator information combination from the resource transfer information, wherein the indicator information combination includes at least two different set indicator identifiers, and indicator data corresponding to each of the at least two different set indicator identifiers.

[0035] In one embodiment, the current business may be a loan business, a bill business, a trade financing business, or the like.

[0036] Resource transfer information can be understood as information about the transfer of resource ownership from one party to another, such as transaction information, where resources can be physical items or virtual items, such as currency.

[0037] In one embodiment, extracting the indicator information combination from the resource transfer information is accomplished by the following steps:

[0038] Step a1: determine the target service type identifier according to the resource transfer information.

[0039] The business type identifier is used to indicate the business type of the current business. For example, the first business type identifier corresponds to the loan business, the second business type identifier corresponds to the bill business, and the third business type identifier corresponds to the trade financing business.

[0040] Exemplarily, if the resource transfer information includes a loan identifier, the loan identifier is used as the target business type identifier.

[0041] Exemplarily, the resource transfer information includes a ticket identifier, and the ticket identifier is used as the target service type identifier.

[0042] Step a2: Determine the target setting indicator combination corresponding to the target business type identifier according to the correspondence relationship between the pre-created business type identifier and the setting indicator combination.

[0043] A setting indicator combination corresponding to each business type is created in advance, and the setting indicator combination corresponding to each business type includes at least two setting indicator identifiers.

[0044] After the target business type identifier is determined, the setting indicator combination corresponding to the target business type identifier is determined based on the correspondence between the pre-created business type identifier and the setting indicator combination, and the setting indicator combination is used as the target setting indicator combination corresponding to the target business type identifier.

[0045] Step a3: extracting the indicator data corresponding to each setting indicator identifier in the target setting indicator combination from the resource transfer information.

[0046] Exemplarily, the target setting indicator combination includes an initial resource holder, a resource transfer object, and a resource transfer amount. After the target setting indicator combination is determined, the initial resource holder identifier, the resource transfer object identifier, and the resource transfer amount are extracted from the resource transfer information. The initial resource holder identifier may be an account identifier of the initial resource holder, and the resource transfer object identifier may be an account identifier of the resource transfer object.

[0047] S120: Determine the indicator weight corresponding to each set indicator identifier according to the indicator data corresponding to each set indicator identifier.

[0048] In one embodiment, for each set indicator identifier, a correspondence between an indicator data interval and an indicator weight is created. In this way, after the indicator data corresponding to any set indicator identifier is determined, the indicator weight corresponding to the indicator data interval where the set indicator data is located is used as the indicator weight corresponding to the set indicator identifier. This embodiment can quickly determine the indicator weight corresponding to the indicator data corresponding to each indicator identifier.

[0049] S130. In the target risk tree, determine the risk path corresponding to the resource transfer information and the node risk data of each node in the risk path. The set indicator identifier and indicator data interval corresponding to each node of the target risk tree are partially or completely different from the node risk data.

[0050] The target risk tree includes a root node, a leaf node, and an intermediate node connecting the root node and the leaf node. Each node is provided with a set indicator identifier, an indicator data interval, and a node risk data.

[0051] The target risk tree is a risk tree corresponding to the business type of the current business. In one embodiment, the target risk tree is determined by the following steps: determining the business type identifier of the current business; and taking the risk tree corresponding to the business type identifier of the current business in the risk tree combination as the target risk tree. By pre-creating a corresponding risk tree for each business type, the matching degree between the risk tree and the business is improved, thereby improving the accuracy of determining the business risk data. This embodiment is suitable for each business type corresponding to only one risk tree, and in the indicator configuration information, only one indicator data interval is set for the indicator identifier corresponding to the root node of the risk tree.

[0052] In one embodiment, the target setting indicator identifier in the indicator information combination is determined, and the root node of the target risk tree is configured to be associated with the indicator corresponding to the target setting indicator identifier; a target risk tree that meets the risk tree conditions is selected from the risk tree combination, and the indicator identifier associated with the root node of the target risk tree is the target setting indicator identifier, and the indicator data interval corresponding to the root node includes the indicator data corresponding to the target setting indicator identifier. This embodiment is suitable for the case where the risk tree combination includes at least two associated risk trees, and the business types corresponding to the at least two associated risk trees are the same as the business type of the current business, but the indicator data intervals corresponding to the root nodes of different associated risk trees are different. This embodiment helps to improve the correlation between the target risk tree and the actual business type, thereby improving the matching degree between the target risk tree and the current business.

[0053] In one embodiment, the node risk data includes node weights and node scores; in the target risk tree, at least two child nodes connected to the same parent node have different node weights, and / or at least two child nodes connected to the same parent node have different node scores.

[0054] Exemplarily, there are three child nodes under the first parent node, namely the first child node, the second child node and the third child node, and all three correspond to the resource transfer amount. Among them, the first child node corresponds to the first indicator data interval, the node weight is 1, and the node score is 1; the second child node corresponds to the second indicator data interval, the node weight is 1, and the node score is 2; the third child node corresponds to the third indicator data interval, the node weight is 1, and the node score is 3.

[0055] Exemplarily, there are two child nodes under the first parent node, namely the first child node and the second child node, and both correspond to the remaining amount of resources. The first child node corresponds to the first indicator data interval, the node weight is 1, and the node score is 1; the second child node corresponds to the second indicator data interval, the node weight is 2, and the node score is 1.

[0056] Exemplarily, there are two child nodes under the first parent node, namely the first child node and the second child node, and both correspond to the number of resource transfers. The first child node corresponds to the first indicator data interval, the node weight is 1, and the node score is 1; the second child node corresponds to the second indicator data interval, the node weight is 1.2, and the node score is 1.5.

[0057] In one embodiment, in the target risk tree, the target child node under the first target parent node and the target child node under the second target parent node have different node weights and / or different node scores; wherein, the first target parent node and the second target child node are at the same level of the target risk tree and correspond to the same set indicator identifier, and the target child node under the first target parent node and the target child node under the second target parent node correspond to the same set indicator identifier.

[0058] Specifically, Figure 2As shown, node 1 and node 2 are two target parent nodes, node 3, node 4, node 5, node 6 and node 7 are child nodes of node 1; node 8, node 9, node 10, node 11 and node 12 are all child nodes of node 2. Among them, the node weights of nodes 3-7 are all 1, the score of node 3 is 1, the score of node 4 is 2, the score of node 5 is 3, the score of node 6 is 4, and the score of node 7 is 5. The node weights of nodes 8-9 are all 1.2, the score of node 8 is 1, the score of node 9 is 2, the score of node 10 is 3, the score of node 11 is 4, and the score of node 12 is 5. Obviously, in this figure, the node weights of different child nodes connected to the same parent node and corresponding to the same indicator data interval are different, and the node scores are the same. For example, node 3 and node 8 both hit the first-level interval, that is, corresponding to the first indicator data interval, and the scores of both are 1, the weight of node 8 is 1, and the weight of node 8 is 1.2. It should be noted that the associated index 004, the associated index 002 and the associated index 001 in the figure should be understood as: associated with the index marked as 004, associated with the index marked as 002 and associated with the index marked as 001; the first level is the abbreviation of the first level interval (the first indicator data interval). It can be understood that the attached Figure 2 The risk tree in is the target risk tree corresponding to the first-level interval.

[0059] It can be understood that the risk path in this embodiment includes at least two nodes, and the setting indicator identifiers corresponding to the at least two nodes correspond one-to-one to the at least two different setting indicator identifiers. At the same time, the indicator data corresponding to each of the at least two different setting indicator identifiers is within the indicator data interval corresponding to the corresponding node.

[0060] After the indicator information combination is determined, all the set indicator identifiers in the indicator information combination are sorted to obtain the sorting result; the arrangement order of each set indicator identifier in the sorting result is consistent with the hierarchical order of the nodes corresponding to each set indicator identifier in the target risk tree; the nodes corresponding to each set indicator identifier in the sorting result in the target risk tree are determined in sequence. Specifically, for the first set indicator identifier in the sorting result, the node (generally the root node) corresponding to the first set indicator identifier is determined in the target risk tree, and the node is used as the latest node; for other set indicator identifiers in the sorting result, taking the Nth set indicator identifier as an example, the target node is queried in the lower node of the latest node of the target risk tree, and the data interval corresponding to the target node includes the indicator data corresponding to the Nth set indicator identifier, and the target node is used as the node corresponding to the Nth set indicator identifier. And so on, the nodes corresponding to all the set indicator identifiers in the indicator information combination in the target risk tree are determined.

[0061] Since the arrangement order of each set indicator identifier in the sorting result is consistent with the hierarchical order of the nodes corresponding to each set indicator identifier in the target risk tree, the selected nodes in the target risk tree can be connected into a broken line, which is the risk path.

[0062] S140: Determine business risk data of the current business according to the node risk data corresponding to each node in the risk path and the indicator weight corresponding to the set indicator identifier corresponding to each node.

[0063] In one embodiment, the product of the node risk data corresponding to each node in the risk path and the indicator weight corresponding to the set indicator identifier corresponding to each node is used as the target node risk data of each node; then the sum of the target node risk data corresponding to all nodes in the risk path is used as the business risk data of the current business. Optionally, the node risk data in this embodiment is configured as a modifiable item. The user can modify the node risk data of the node corresponding to any set indicator identifier in the target risk tree according to actual conditions. This embodiment can quickly and accurately determine the business risk data of the current business.

[0064] In one embodiment, the node risk data includes node weights and node scores, and the node weights and node scores are independent of each other, that is, the two do not affect each other. Accordingly, the business risk data of the current business is determined based on the node weights, node scores of each of the nodes in the risk path, and the indicator weights of the set indicators corresponding to each of the nodes. In this embodiment, since the node weights and node scores are independent of each other, the user can adjust the node weights and / or node scores as needed, thereby improving the flexibility of modifying the node risk-related data and the convenience of maintaining the target risk tree.

[0065] In one embodiment, the target risk data of each node is determined according to the node weight, node score and the indicator weight of the set indicator corresponding to each node in the risk path; the sum of the target risk data of all nodes in the risk path is used as the business risk data of the current business. This embodiment achieves the technical effect of accurately quantifying the risk level of each node in the current business process, and then determining the risk data of the current business based on the risk level of each node, thereby improving the accuracy of determining the risk data of the current business.

[0066] like Figure 2As shown, the indicator information combination includes three set indicator identifiers, namely 004, 002 and 001. The three set indicator identifiers in the indicator information combination and the indicator data corresponding to the three set indicator identifiers are matched with each node in the target risk data. It is found that 004 is associated with the root node 9 (node ​​0) of the target risk tree, 002 is associated with the node 002 of the target risk tree; 001 is associated with the node 10 of the target risk tree. Therefore, the broken line corresponding to node 0, node 2 and node 9 is the risk path.

[0067] Set the indicator weight corresponding to the indicator data of 004 ​​in the indicator information combination to 1; the indicator weight corresponding to the indicator data of 002 is 1; the indicator weight corresponding to the indicator data of 001 is 0.872; then in this risk path, the target risk data corresponding to node 0 is: 1×1×4=4; the target risk data corresponding to node 2 is: 1×1×2=2; the sub-risk data corresponding to node 10 is: 0.872×1.2×2=3.1392. The current business risk data is: 4+2+3.1392=9.1392.

[0068] In one embodiment, after the current business risk data is determined, the current business risk data is displayed in a visualization interface, or, if the current business risk data meets the risk notification conditions, the current business risk data is displayed in a visualization interface, or the current business risk data is notified to the user in a set manner. Timely notification of the current business risk data allows the user to obtain the risk level of the current business in a timely manner and take corresponding measures based on the risk level.

[0069] In one embodiment, for each business type corresponding to the set indicator combination, the indicator configuration information corresponding to each set indicator identifier is pre-created. After the indicator configuration information corresponding to each set indicator identifier is created, the user can modify the indicator configuration information of any indicator according to actual needs. Optionally, in response to the set indicator combination selection operation, the corresponding set indicator combination is displayed; in response to the modification operation of the indicator configuration information corresponding to any set indicator identifier in the set indicator combination, the corresponding modification operation is performed on the indicator configuration information corresponding to the set indicator identifier to update the indicator configuration information corresponding to the set indicator identifier.

[0070] Exemplarily, the first resource provider provides target resources to the first resource demander from time to time. When the social evaluation data of the resource demander is average, its indicator data is the first data; as the business of the first resource demander expands, products are upgraded, etc., its social evaluation data is getting better and better, so its indicator data can be modified accordingly, for example, modified to the second data, and the second data is higher than the first data. This embodiment makes the indicator configuration information corresponding to each indicator identifier independent of the risk tree, which improves the flexibility of maintaining the indicator configuration information corresponding to each indicator identifier.

[0071] In one embodiment, the node risk data and the index data interval corresponding to each node in the risk tree are configured as modifiable items. Optionally, the node weight, node score and the index data interval corresponding to each node in the risk tree are configured as modifiable items. The user can complete the modification of the target risk tree through the following steps according to actual needs: In response to the modification operation on the target risk tree, perform the corresponding modification operation on the target risk tree to update the target risk tree.

[0072] Exemplarily, in response to a modification operation on the target risk tree node N, the node weight, node score and indicator data interval of node N are displayed in the interactive interface; and the three items are all configured as modifiable items; the user modifies the node weight, node score and part or all of the data in the indicator data interval according to actual needs; in response to the confirmation operation, the current node weight, current node score and current indicator data interval of node N are saved as the modified node weight, node peak value and indicator data interval of node N. This embodiment provides a feasible way to determine the node weight, node score and indicator data interval of each node in the risk tree, which improves the convenience of risk tree maintenance. At the same time, decoupling the indicator configuration information from the risk tree can improve the controllability and flexibility of business risk data determination.

[0073] The technical solution of the risk data determination method provided in the embodiment of the present invention determines the indicator weight corresponding to each set indicator identifier according to the indicator data corresponding to each set indicator identifier, so that the determination of the indicator weight corresponding to each set indicator identifier does not rely on the target risk tree, thereby improving the flexibility of the management of the indicator weight corresponding to each set indicator identifier; the target risk tree includes nodes corresponding to each set indicator identifier in the indicator information combination, and each node includes an indicator data interval and node risk data, wherein the configuration of the node risk data of each node is independent of the indicator data corresponding to the corresponding indicator identifier in the indicator information combination, thereby realizing the decoupling of the indicator configuration information and the risk tree configuration information, which helps to improve the flexibility and controllability of the management of the indicator configuration information and the risk tree configuration information, thereby improving the controllability and accuracy of the business risk data determination.

[0074] Figure 3 Another flow chart of the risk data determination method provided by an embodiment of the present invention. This embodiment is used to refine the "determining the indicator weight corresponding to each set indicator identifier according to the indicator data corresponding to each set indicator identifier" in the above embodiment. Figure 3 As shown, the method includes:

[0075] S210. Obtain resource transfer information associated with the current business, and extract an indicator information combination from the resource transfer information, where the indicator information combination includes at least two different set indicator identifiers, and indicator data corresponding to each of the at least two different set indicator identifiers.

[0076] S2201. Determine the indicator data interval corresponding to the indicator data corresponding to each set indicator identifier and the reference weight corresponding to the indicator data interval.

[0077] In this embodiment, a set of indicator configuration information is set for each set indicator identifier, and the indicator configuration information includes at least two indicator data intervals corresponding to the set indicator identifier and reference weights corresponding to the at least two indicator data intervals, wherein the reference weight can also be understood as an initial weight.

[0078] It should be noted that the determination method of the indicator data interval of different set indicator identifiers is different. In one embodiment, a business will involve two types of indicators, namely resource transfer related indicators and non-resource transfer related indicators. Resource transfer related indicators include resource transfer amount, remaining resource amount, number of resource transfers, etc. In this implementation, the indicators whose corresponding indicator data will change with the progress of resource transfer are called resource transfer related indicators. Non-resource transfer indicators include account creation location, resource transfer object, etc. In this embodiment, the indicators whose corresponding indicator data will not change with the progress of resource transfer are called non-resource transfer related indicators. The indicator data corresponding to the non-resource transfer related indicators are determined based on the social evaluation data of the existing non-resource related indicators.

[0079] Taking the account creation location as an example, the social evaluation data is the regional economic security evaluation data. For example, if the account creation location is a first-tier city, the corresponding indicator data is 75; if the account creation location is a fourth-tier city, the corresponding indicator data is 90. Among them, the first indicator data interval corresponding to the account creation location is 50-100.

[0080] Taking the resource transfer object as an example, the social evaluation data is the financial security evaluation data of the account holder. For example, if the resource transfer object is a bank, the corresponding index data of the resource transfer object is 25, if the resource transfer object is a leading enterprise, the corresponding index data of the resource transfer object is 30, and if the resource transfer object is an enterprise held by a dishonest person, the corresponding index data of the resource transfer object is 45. Among them, the first index data corresponding to the resource transfer object is in the range of 0-50.

[0081] In one embodiment, the configuration information corresponding to each set indicator identifier also includes a deviation operator corresponding to each indicator data interval, so when determining the indicator data interval corresponding to the indicator data corresponding to each set indicator identifier and the reference weight corresponding to the indicator data interval, the deviation operator corresponding to the indicator data interval is also determined. The deviation operator can be selected as a plus sign or a minus sign.

[0082] S2202: Determine the indicator weight corresponding to each set indicator identifier according to the indicator data corresponding to each set indicator identifier, the indicator data interval corresponding to the indicator data, and the reference weight corresponding to the indicator data interval.

[0083] In one embodiment, the reference weight corresponds to the starting value of the indicator data interval. If the indicator data corresponding to the set indicator identifier is equal to the starting value of the indicator data interval, the reference weight is used as the indicator weight corresponding to the indicator data corresponding to the set indicator identifier. If the indicator data corresponding to the set indicator identifier is in the middle of the indicator data interval, the product of the reference weight and 150% is used as the indicator weight corresponding to the indicator data corresponding to the set indicator identifier; if the indicator data corresponding to the set indicator identifier is 40, and the indicator data interval is [0, 50), the product of the reference weight and (1+40 / 50) is used as the indicator weight corresponding to the indicator data corresponding to the set indicator identifier.

[0084] In one embodiment, the difference between the indicator data corresponding to each of the setting indicator identifiers and the center value of the indicator data interval corresponding to each of the setting indicator identifiers is used as the indicator deviation value corresponding to each of the setting indicator identifiers; the indicator weight corresponding to each of the setting indicator identifiers is determined based on the indicator deviation value corresponding to each of the setting indicator identifiers, the deviation operator and the benchmark weight.

[0085] Specifically, the deviation operator is a plus sign or a minus sign; the difference between the indicator data corresponding to each of the setting indicator identifiers and the center value of the indicator data interval corresponding to each of the setting indicator identifiers is used as the indicator deviation value corresponding to each of the setting indicator identifiers; the sum of the indicator deviation value corresponding to each of the setting indicator identifiers and the benchmark weight is used as the indicator weight corresponding to each of the setting indicator identifiers; or, the difference between the indicator deviation value corresponding to each of the setting indicator identifiers and the benchmark weight is used as the indicator weight corresponding to each of the setting indicator identifiers.

[0086] For example, if the remaining amount of resources in a certain account is 96, the secondary configuration item of the indicator is hit, that is, the corresponding second indicator data interval, the center value of the second indicator data interval is 75, the deviation operator is "+", and the deviation value is (96-75) / 75=0.28; the indicator weight is: 1+0.28=1.28. If the remaining amount of resources in a certain account is 12 yuan, the primary configuration item of the indicator is hit, that is, the first indicator data interval is hit, the center value of the first indicator data interval is 25, the deviation operator is "+", so the deviation value is (12-25) / 25=-0.52; the indicator weight is: 1+(-0.52)=0.48.

[0087] S230. In the target risk tree, determine the risk path corresponding to the resource transfer information and the node risk data of each node in the risk path. The set indicator identifier and indicator data interval corresponding to each node of the target risk tree are partially or completely different from the node risk data.

[0088] S240: Determine business risk data of the current business according to the node risk data corresponding to each node in the risk path and the indicator weight corresponding to the set indicator identifier corresponding to each node.

[0089] The technical solution provided by the embodiment of the present invention, since the indicator weight is determined based on the indicator data corresponding to the set indicator identifier, the indicator data interval corresponding to the indicator data, and the benchmark weight corresponding to the indicator data interval, and the maintenance of the indicator data interval and the benchmark weight does not depend on the target risk tree, this allows the user to adjust the indicator weight of the indicator data by modifying the indicator data interval or the benchmark weight, thereby improving the controllability and accuracy of the indicator weight determination, and at the same time improving the convenience of maintaining the configuration information corresponding to the set indicator.

[0090] Figure 4 Another flow chart of the method for determining business risk data provided by an embodiment of the present invention. This embodiment adds a business risk level determination step based on the previous embodiment. Figure 4 As shown, the method includes:

[0091] S310, obtaining resource transfer information associated with the current business, and extracting an indicator information combination from the resource transfer information, wherein the indicator information combination includes at least two different set indicator identifiers, and indicator data corresponding to each of the at least two different set indicator identifiers.

[0092] S320: Determine the indicator weight corresponding to each set indicator identifier according to the indicator data corresponding to each set indicator identifier.

[0093] S330. In the target risk tree, determine the risk path corresponding to the resource transfer information and the node risk data of each node in the risk path. The set indicator identifier and indicator data interval corresponding to each node of the target risk tree are partially or completely different from the node risk data.

[0094] S340: Determine business risk data of the current business according to the node risk data corresponding to each node in the risk path and the indicator weight corresponding to the set indicator identifier corresponding to each node.

[0095] S350: Determine a risk data range corresponding to the business risk data of the current business, and use the set business risk level corresponding to the risk data range as the business risk level of the current business.

[0096] This embodiment pre-creates at least two risk data ranges and business risk levels corresponding to the at least two risk data ranges. After determining the business risk data of the current business, the risk data range corresponding to the business risk data of the current business is determined, and the set business risk level corresponding to the risk data range is used as the business risk level of the current business. The business risk level allows users to quickly determine the risk level of the current business.

[0097] Exemplarily, the first risk data range (less than or equal to 20) corresponds to the first business risk level; the second risk data range (greater than 20 and less than or equal to 40) corresponds to the second business risk level; the third risk data range (greater than 40 and less than or equal to 60) corresponds to the third business risk level; and the fourth risk data range (greater than 60) corresponds to the fourth business risk level.

[0098] S360, displays the business risk level of the current business in a visual interface.

[0099] In one embodiment, the business risk level is directly displayed in the visual interface, such as level one, level two, etc. This embodiment allows users to quickly determine the risk level of the current business.

[0100] In one embodiment, risk indicators corresponding to the business risk levels are displayed in the visualization interface. For example, yellow indicator information corresponding to level 1 risk, orange indicator information corresponding to level 2 risk, and red indicator information corresponding to level 3 risk. This embodiment allows users to quickly determine the risk level of the current business.

[0101] In one embodiment, while displaying the business risk level of the current business, the target risk data of each node in the risk path is also displayed. Optionally, when the business risk level of the current business meets the prompt condition, while displaying the business risk level of the current business, the target risk data of each node in the risk path is also displayed. Among them, the prompt condition is that the business risk level is greater than or equal to level three. In this way, when the business risk level of the current business is high, the user can quickly determine the risk level of each node in the business execution process, thereby quickly locking the target node, wherein the target node is a node whose target risk data is greater than or equal to the set risk threshold, providing the user with a risk point determination speed.

[0102] The technical solution of the risk data determination method provided by the embodiment of the present invention improves the speed at which users obtain the degree of business risk by displaying the business risk level in a visual interface, making it easier for users to take necessary risk prevention measures at the first time.

[0103] Figure 5A Schematic diagram of the structure of the business risk data determination device provided by the embodiment of the present invention. Figure 5A As shown, the device comprises:

[0104] An information extraction module 41 is used to obtain resource transfer information associated with the current business, and extract an indicator information combination from the resource transfer information, wherein the indicator information combination includes at least two different set indicator identifiers, and indicator data corresponding to each of the at least two different set indicator identifiers;

[0105] An indicator weight module 42, configured to determine an indicator weight corresponding to each of the set indicator identifiers according to the indicator data corresponding to each of the set indicator identifiers;

[0106] A risk path module 43 is used to determine, in a target risk tree, a risk path corresponding to the resource transfer information and node risk data of each node in the risk path, wherein the set indicator identifier and indicator data interval corresponding to each node of the target risk tree are different from part or all of the node risk data;

[0107] The risk data module 44 is used to determine the business risk data of the current business according to the node risk data corresponding to each node in the risk path and the indicator weight corresponding to the set indicator identifier corresponding to each node.

[0108] Alternatively, if Figure 5B As shown, the device further includes a risk tree determination module 450, and the risk data determination module 450 includes:

[0109] Type unit, used to determine the business type identifier of the current business;

[0110] The risk tree unit is used to use the risk tree corresponding to the business type identifier of the current business in the risk tree combination as the target risk tree.

[0111] Optionally, the risk tree unit is used to:

[0112] Determine a target setting indicator identifier in the indicator information combination, and the root node of the target risk tree is configured to associate an indicator corresponding to the target setting indicator identifier;

[0113] A target risk tree that meets the risk tree conditions is selected from the risk tree combination, the indicator identifier associated with the root node of the target risk tree is the target setting indicator identifier, and the indicator data interval corresponding to the root node includes the indicator data corresponding to the target setting indicator identifier.

[0114] Optionally, the risk path includes at least two nodes, and the setting indicator identifiers corresponding to the at least two nodes correspond one-to-one to the at least two different setting indicator identifiers. At the same time, the indicator data corresponding to each of the at least two different setting indicator identifiers is within the indicator data interval corresponding to the corresponding node.

[0115] Optionally, the information extraction module 410 is used to:

[0116] Determine a target service type identifier according to the resource transfer information;

[0117] Determine a target setting indicator combination corresponding to the target business type identifier according to a correspondence relationship between a pre-created business type identifier and a setting indicator combination;

[0118] Extracting the indicator data corresponding to each setting indicator identifier in the target setting indicator combination from the resource transfer information;

[0119] Each setting indicator identifier in the target setting indicator combination and the indicator data corresponding to each setting indicator identifier are used as an indicator information combination.

[0120] Optionally, the indicator weight module 420 includes:

[0121] The first unit is used to determine the index data interval corresponding to the index data corresponding to each of the set index identifiers and the reference weight corresponding to the index data interval;

[0122] The second unit is used to determine the indicator weight corresponding to each of the set indicator identifiers according to the indicator data corresponding to each of the set indicator identifiers, the indicator data interval corresponding to the indicator data, and the reference weight corresponding to the indicator data interval.

[0123] Optionally, the first unit is further configured to:

[0124] Determine a deviation operator corresponding to the indicator data interval;

[0125] The second unit is specifically used for:

[0126] The difference between the indicator data corresponding to each of the set indicator identifiers and the central value of the indicator data interval corresponding to each of the set indicator identifiers is used as the indicator deviation value corresponding to each of the set indicator identifiers;

[0127] The indicator weight corresponding to each of the set indicator identifiers is determined according to the indicator deviation value corresponding to each of the set indicator identifiers, the deviation operator and the reference weight.

[0128] Optionally, the deviation operator is a plus sign or a minus sign;

[0129] The second unit is specifically used for:

[0130] The sum of the indicator deviation value corresponding to each of the set indicator identifiers and the reference weight is used as the indicator weight corresponding to each of the set indicator identifiers; or

[0131] The difference between the indicator deviation value corresponding to each of the setting indicator identifiers and the reference weight is used as the indicator weight corresponding to each of the setting indicator identifiers.

[0132] Optionally, the node risk data includes node weight and node score; the risk data module is specifically used to:

[0133] Determine the target risk data corresponding to each of the nodes according to the node weights and node scores corresponding to each of the nodes in the risk path and the indicator weights corresponding to the set indicator identifiers corresponding to each of the nodes;

[0134] The sum of the target risk data corresponding to all the nodes in the risk path is used as the business risk data of the current business.

[0135] Alternatively, if Figure 5C As shown, the device further includes a display module 460, and the display module 460 includes:

[0136] Determine a risk data range corresponding to the business risk data of the current business, and use a set business risk level corresponding to the risk data range as the business risk level of the current business;

[0137] The business risk level of the current business is displayed in a visual interface.

[0138] Alternatively, if Figure 5D As shown, the device further includes a first configuration modification module 401, and the first configuration modification module 401 is used to:

[0139] In response to the setting indicator combination selection operation, displaying the corresponding setting indicator combination;

[0140] In response to a modification operation on the indicator configuration information corresponding to any setting indicator identifier in the setting indicator combination, a corresponding modification operation is performed on the indicator configuration information corresponding to the setting indicator identifier to update the indicator configuration information corresponding to the setting indicator identifier.

[0141] Alternatively, if Figure 5E As shown, the apparatus further includes a second configuration modification module 402, and the second configuration modification module 402 is used to:

[0142] In response to a modification operation on the target risk tree, a corresponding modification operation is performed on the target risk tree to update the target risk tree.

[0143] Optionally, in the target risk data, at least two child nodes connected to the same parent node have different node weights, and / or at least two child nodes connected to the same parent node have different node scores.

[0144] Optionally, in the target risk tree, the target child node under the first target parent node and the target child node under the second target parent node have different node weights and / or different node scores;

[0145] Among them, the first target parent node and the second target child node are at the same level of the target risk tree and correspond to the same setting indicator identifier, and the target child node under the first target parent node and the target child node under the second target parent node correspond to the same setting indicator identifier.

[0146] Optionally, different child nodes connected to the same parent node and corresponding to the same indicator data interval have different node weights and the same node scores.

[0147] The technical solution of the risk data determination device provided in the embodiment of the present invention determines the indicator weight corresponding to each set indicator identifier according to the indicator data corresponding to each set indicator identifier, so that the determination of the indicator weight corresponding to each set indicator identifier does not rely on the target risk tree, thereby improving the flexibility of the management of the indicator weight corresponding to each set indicator identifier; the target risk tree includes nodes corresponding to each set indicator identifier in the indicator information combination, and each node includes an indicator data interval and node risk data, wherein the configuration of the node risk data of each node is independent of the indicator data corresponding to the corresponding indicator identifier in the indicator information combination, thereby realizing the decoupling of the indicator configuration information and the risk tree configuration information, which helps to improve the flexibility and controllability of the management of the indicator configuration information and the risk tree configuration information, thereby improving the controllability and accuracy of the business risk data determination.

[0148] The business risk data determination device provided in the embodiment of the present invention can execute the business risk data determination method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0149] Figure 6 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. Figure 6 A block diagram of an exemplary server 12 suitable for use in implementing embodiments of the present invention is shown. Figure 6 The server 12 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0150] like Figure 6 As shown, the server 12 is in the form of a general purpose computing device. The components of the server 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that connects various system components (including the system memory 28 and the processing unit 16).

[0151] Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. By way of example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0152] The server 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the server 12, including volatile and non-volatile media, removable and non-removable media.

[0153] The system memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The server 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be used to read and write non-removable, non-volatile magnetic media ( Figure 6 not shown, usually called a "hard drive"). Although Figure 6Not shown in the figure, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The system memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present invention.

[0154] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. Program modules 42 generally perform the functions and / or methods of the embodiments described herein.

[0155] The server 12 may also communicate with one or more external devices 14 (e.g., keyboards, pointing devices, displays 24, etc.), may communicate with one or more devices that enable a user to interact with the server 12, and / or may communicate with any device that enables the server 12 to communicate with one or more other computing devices (e.g., network cards, modems, etc.). Such communication may be performed via an input / output (I / O) interface 22. In addition, the server 12 may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter 20. As shown, the network adapter 20 communicates with other modules of the server 12 via a bus 18. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the server 12, including, but not limited to, microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0156] The processing unit 16 executes various functional applications and data processing by running the program stored in the system memory 28, for example, implementing the steps of the business risk data determination method provided in the above embodiment of the present invention, the method comprising:

[0157] Acquire resource transfer information associated with the current service, and extract an indicator information combination from the resource transfer information, wherein the indicator information combination includes at least two different set indicator identifiers and indicator data corresponding to each of the at least two different set indicator identifiers;

[0158] Determine the indicator weight corresponding to each of the set indicator identifiers according to the indicator data corresponding to each of the set indicator identifiers;

[0159] In the target risk tree, a risk path corresponding to the resource transfer information and node risk data of each node in the risk path are determined, wherein the set indicator identifier and indicator data interval corresponding to each node of the target risk tree are partially or completely different from the node risk data;

[0160] The business risk data of the current business is determined according to the node risk data corresponding to each of the nodes in the risk path and the indicator weight corresponding to the set indicator identifier corresponding to each of the nodes.

[0161] Of course, those skilled in the art can understand that the processor can also implement the technical solution of the business risk data determination method provided by any embodiment of the present invention.

[0162] This embodiment provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the steps of the business risk data determination method provided in the above embodiment of the present invention are implemented. The method includes:

[0163] Acquire resource transfer information associated with the current service, and extract an indicator information combination from the resource transfer information, wherein the indicator information combination includes at least two different set indicator identifiers and indicator data corresponding to each of the at least two different set indicator identifiers;

[0164] Determine the indicator weight corresponding to each of the set indicator identifiers according to the indicator data corresponding to each of the set indicator identifiers;

[0165] In the target risk tree, a risk path corresponding to the resource transfer information and node risk data of each node in the risk path are determined, wherein the set indicator identifier and indicator data interval corresponding to each node of the target risk tree are partially or completely different from the node risk data;

[0166] The business risk data of the current business is determined according to the node risk data corresponding to each of the nodes in the risk path and the indicator weight corresponding to the set indicator identifier corresponding to each of the nodes.

[0167] The computer storage medium of the embodiment of the present invention can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to: an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: 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 or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.

[0168] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0169] The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0170] Computer program code for performing the operations of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0171] It should be understood by those skilled in the art that the modules or steps of the present invention described above can be implemented by a general-purpose computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, optionally, they can be implemented by a program code executable by a computer device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0172] An embodiment of the present invention further provides a computer program product, including a computer program, which, when executed by a processor, implements the business risk data determination method provided in any embodiment of the present application.

[0173] In the process of implementation, the computer program product can be written in one or more programming languages ​​or a combination thereof to perform the computer program code of the present invention, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0174] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for determining business risk data, characterized in that: include: Acquire resource transfer information associated with the current service, and extract an indicator information combination from the resource transfer information, wherein the indicator information combination includes at least two different set indicator identifiers and indicator data corresponding to each of the at least two different set indicator identifiers; Determine the indicator weight corresponding to each of the set indicator identifiers according to the indicator data corresponding to each of the set indicator identifiers; In the target risk tree, a risk path corresponding to the resource transfer information and node risk data of each node in the risk path are determined, wherein the set indicator identifier and indicator data interval corresponding to each node of the target risk tree are partially or completely different from the node risk data; The business risk data of the current business is determined according to the node risk data corresponding to each of the nodes in the risk path and the indicator weight corresponding to the set indicator identifier corresponding to each of the nodes.

2. The method according to claim 1, characterized in that Before determining the risk path corresponding to the resource transfer information and the node risk data of each node in the risk path in the target risk tree, the method further includes: Determine the business type identifier of the current business; In the risk tree combination, a risk tree corresponding to the business type identifier of the current business is selected, and the risk tree is used as the target risk tree.

3. The method according to claim 2, characterized in that The step of selecting a risk tree corresponding to the business type identifier of the current business from the risk tree combination and using the risk tree as the target risk tree includes: Determine a target setting indicator identifier in the indicator information combination, and the root node of the target risk tree is configured to associate an indicator corresponding to the target setting indicator identifier; A target risk tree that meets the risk tree conditions is selected from the risk tree combination, the indicator identifier associated with the root node of the target risk tree is the target setting indicator identifier, and the indicator data interval corresponding to the root node includes the indicator data corresponding to the target setting indicator identifier.

4. The method according to claim 1, characterized in that: The risk path includes at least two nodes, and the setting indicator identifiers corresponding to the at least two nodes correspond one-to-one to the at least two different setting indicator identifiers. At the same time, the indicator data corresponding to each of the at least two different setting indicator identifiers is within the indicator data interval corresponding to the corresponding node.

5. The method according to claim 1, characterized in that The extracting the indicator information combination from the resource transfer information includes: Determine a target service type identifier according to the resource transfer information; Determine a target setting indicator combination corresponding to the target business type identifier according to a correspondence relationship between a pre-created business type identifier and a setting indicator combination; Extracting the indicator data corresponding to each setting indicator identifier in the target setting indicator combination from the resource transfer information; Each setting indicator identifier in the target setting indicator combination and the indicator data corresponding to each setting indicator identifier are used as an indicator information combination.

6. The method according to claim 1, characterized in that The determining the indicator weight corresponding to each of the set indicator identifiers according to the indicator data corresponding to each of the set indicator identifiers includes: Determine the indicator data interval corresponding to the indicator data corresponding to each of the set indicator identifiers and the reference weight corresponding to the indicator data interval; The indicator weight corresponding to each of the set indicator identifiers is determined according to the indicator data corresponding to each of the set indicator identifiers, the indicator data interval corresponding to the indicator data, and the reference weight corresponding to the indicator data interval.

7. The method according to claim 6, characterized in that While determining the indicator data interval corresponding to the indicator data corresponding to each of the set indicator identifiers and the reference weight corresponding to the indicator data interval, the method further includes: Determine a deviation operator corresponding to the indicator data interval; The step of determining the indicator weight corresponding to each of the set indicator identifiers according to the indicator data interval corresponding to the indicator data of each of the set indicator identifiers and the reference weight corresponding to the indicator data interval includes: The difference between the indicator data corresponding to each of the set indicator identifiers and the central value of the indicator data interval corresponding to each of the set indicator identifiers is used as the indicator deviation value corresponding to each of the set indicator identifiers; The indicator weight corresponding to each of the set indicator identifiers is determined according to the indicator deviation value corresponding to each of the set indicator identifiers, the deviation operator and the reference weight.

8. The method according to claim 7, characterized in that The deviation operator is a plus sign or a minus sign; The step of determining the indicator weight corresponding to each of the set indicator identifiers according to the indicator deviation value corresponding to each of the set indicator identifiers, the deviation operator and the reference weight comprises: The sum of the indicator deviation value corresponding to each of the set indicator identifiers and the reference weight is used as the indicator weight corresponding to each of the set indicator identifiers; or The difference between the indicator deviation value corresponding to each of the setting indicator identifiers and the reference weight is used as the indicator weight corresponding to each of the setting indicator identifiers.

9. The method according to claim 1, characterized in that: After determining the business risk data of the current business, the following further includes: Determine a risk data range corresponding to the current business risk data, and use a set business risk level corresponding to the risk data range as the business risk level of the current business; The business risk level of the current business is displayed in a visual interface.

10. The method according to claim 1, characterized in that The node risk data includes node weight and node score; In the target risk tree, at least two child nodes connected to the same parent node have different node weights, and / or at least two child nodes connected to the same parent node have different node scores.

11. The method according to claim 10, characterized in that In the target risk tree, the target child node under the first target parent node and the target child node under the second target parent node have different node weights and / or different node scores; Among them, the first target parent node and the second target child node are at the same level of the target risk tree and correspond to the same setting indicator identifier, and the target child node under the first target parent node and the target child node under the second target parent node correspond to the same setting indicator identifier.

12. The method according to claim 11, characterized in that The node weights of different child nodes connected to the same parent node and corresponding to the same indicator data interval are different, but the node scores are the same.

13. The method according to any one of claims 10 to 12, characterized in that: The node risk data includes a node weight and a node score; the determining the business risk data of the current business according to the node risk data corresponding to each of the nodes in the risk path and the indicator weight corresponding to the set indicator identifier corresponding to each of the nodes includes: Determine the target risk data corresponding to each of the nodes according to the node weights and node scores corresponding to each of the nodes in the risk path and the indicator weights corresponding to the set indicator identifiers corresponding to each of the nodes; The sum of the target risk data corresponding to all the nodes in the risk path is used as the business risk data of the current business.

14. The method according to claim 1, characterized in that Before obtaining the resource transfer information associated with the current service and extracting the indicator information combination from the resource transfer information, the method further includes: In response to the setting indicator combination selection operation, displaying the corresponding setting indicator combination; In response to a modification operation on the indicator configuration information corresponding to any setting indicator identifier in the setting indicator combination, a corresponding modification operation is performed on the indicator configuration information corresponding to the setting indicator identifier to update the indicator configuration information corresponding to the setting indicator identifier.

15. The method according to claim 1, characterized in that Before obtaining the resource transfer information associated with the current service and extracting the indicator information combination from the resource transfer information, the method further includes: In response to a modification operation on the target risk tree, a corresponding modification operation is performed on the target risk tree to update the target risk tree.

16. A risk data determination device, characterized in that: include: An information extraction module, used to obtain resource transfer information associated with the current business, and extract an indicator information combination from the resource transfer information, wherein the indicator information combination includes at least two different set indicator identifiers, and indicator data corresponding to each of the at least two different set indicator identifiers; An indicator weight module, used to determine the indicator weight corresponding to each of the set indicator identifiers according to the indicator data corresponding to each of the set indicator identifiers; A risk path module, used to determine, in a target risk tree, a risk path corresponding to the resource transfer information and node risk data of each node in the risk path, wherein the set indicator identifier and indicator data interval corresponding to each node of the target risk tree are different from part or all of the node risk data; The risk data module is used to determine the business risk data of the current business according to the node risk data corresponding to each node in the risk path and the indicator weight corresponding to the set indicator identifier corresponding to each node.

17. An electronic device, characterized in that: It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the business risk data determination method as described in any one of claims 1 to 15 when executing the computer program.

18. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the business risk data determination method as described in any one of claims 1-15 is implemented.

19. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the computer program implements the business risk data determination method as described in any one of claims 1-15.

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