Risk score determination method and device, equipment, medium and product
The method automates risk scoring using preset indicators and weights to enhance accuracy and efficiency, addressing inefficiencies in existing manual methods.
Patent Information
- Application Number
- CN202411296170.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-14
- Publication Date
- 2024-12-27
AI Technical Summary
Existing methods for determining risk scores of users, particularly medium and large organizations, are inefficient and inaccurate due to reliance on manual data collection and judgment, leading to suboptimal risk assessment and avoidance.
A method and device that utilize preset scoring indicators, data, and weights to determine risk scores automatically, using predefined rules and hierarchical weight models to enhance accuracy and efficiency without human intervention.
The method improves the accuracy and efficiency of risk scoring by standardizing the process and reducing the need for manual participation, resulting in more precise risk assessments.
Smart Images
Figure CN119205384A_ABST
Abstract
Description
Technical Field
[0001] The present application belongs to the field of data processing technology, and in particular, relates to a method, device, equipment, medium and product for determining a risk score. Background Art
[0002] At present, the risk scores of users (such as medium and large organizations) are mainly determined through financial data. Determining the risk scores is helpful for risk assessment of users and appropriate risk avoidance.
[0003] Existing scoring methods usually rely on manually collecting users' financial data, sorting it out, and then making manual comprehensive judgments to determine the risk score. This is not only inefficient, but also the risk score obtained is inaccurate. Summary of the invention
[0004] The embodiments of the present application provide a method, apparatus, device, medium and product for determining a risk score. The risk score is determined by using preset scoring rules through preset scoring indicators of target users and scoring data corresponding to the preset scoring indicators. This not only improves efficiency, but also the scoring method for each user is fixed, and no human intervention is required, thereby improving the accuracy of the risk score.
[0005] In a first aspect, an embodiment of the present application provides a method for determining a risk score, comprising:
[0006] Obtaining preset scoring indicators of target users, scoring data corresponding to the preset scoring indicators, and preset weights of the preset scoring indicators;
[0007] Determine the risk score of the preset scoring indicator by using the first preset scoring rule of the preset scoring indicator according to the scoring data;
[0008] Determine the overall risk score of the target user based on the risk score and preset weight.
[0009] In a possible implementation, the first preset scoring rule includes relationship information between a scoring threshold interval of a preset scoring indicator and a preset risk score; according to the scoring data, the risk score of the preset scoring indicator is determined by using the first preset scoring rule of the preset scoring indicator, including:
[0010] Determine that the target risk score corresponding to the target score threshold interval in which the score data of the preset score indicator is located is the risk score of the preset score indicator, the score threshold interval includes the target score threshold interval, and the preset risk score includes the target risk score.
[0011] In a possible embodiment, it also includes:
[0012] In the case where it is detected that the first target scoring indicator in the preset scoring indicator includes multiple sub-preset scoring indicators, according to the scoring data corresponding to each sub-preset scoring indicator, using the second preset scoring rule of each sub-preset scoring indicator, a sub-risk score of each sub-preset scoring indicator is determined;
[0013] Get the preset sub-weight of each sub-preset scoring indicator;
[0014] Determine the risk score of the first target scoring indicator based on the sub-risk scores and preset sub-weights.
[0015] In one possible implementation, obtaining a preset weight of a preset scoring indicator includes:
[0016] Obtaining a relative weight of each second target scoring indicator relative to a third target scoring indicator in the preset scoring indicators, where the second target scoring indicator is any one of the preset scoring indicators, and the third target scoring indicator is a scoring indicator in the preset scoring indicators except the second target scoring indicator;
[0017] The relative weights are input into the hierarchical weight model corresponding to the preset scoring indicators, and the hierarchical weight model is used to generate a judgment matrix corresponding to the relative weights, and a weight vector corresponding to the judgment matrix is generated. The weight vector includes the preset weights of each second target scoring indicator.
[0018] In one possible implementation, after determining the total risk score of the target user according to the risk score and the preset weight, the method further includes:
[0019] Use the preset display template to display the risk score and total risk score of the preset scoring indicators.
[0020] In a possible implementation, obtaining scoring data corresponding to a preset scoring indicator includes:
[0021] Obtain financial information, resource information, rating information and warning information of target users;
[0022] Based on financial information, resource information, rating information and early warning information, the scoring data corresponding to the preset scoring indicators are determined according to the preset calculation rules.
[0023] In a second aspect, an embodiment of the present application provides a device for determining a risk score, including:
[0024] An acquisition module is used to acquire a preset scoring indicator of a target user, scoring data corresponding to the preset scoring indicator, and a preset weight of the preset scoring indicator;
[0025] A determination module, configured to determine a risk score of a preset scoring indicator based on the scoring data and using a first preset scoring rule of the preset scoring indicator;
[0026] The determination module is also used to determine the total risk score of the target user based on the risk score and preset weights.
[0027] In a possible implementation, the first preset scoring rule includes relationship information between a scoring threshold interval of a preset scoring indicator and a preset risk score; the determination module is specifically used to:
[0028] Determine that the target risk score corresponding to the target score threshold interval in which the score data of the preset score indicator is located is the risk score of the preset score indicator, the score threshold interval includes the target score threshold interval, and the preset risk score includes the target risk score.
[0029] In a possible embodiment, it also includes:
[0030] The determination module is further configured to determine the sub-risk score of each sub-preset scoring indicator according to the scoring data corresponding to each sub-preset scoring indicator and using the second preset scoring rule of each sub-preset scoring indicator when it is detected that the first target scoring indicator in the preset scoring indicator includes multiple sub-preset scoring indicators;
[0031] The acquisition module is also used to obtain the preset sub-weight of each sub-preset scoring indicator;
[0032] The determination module is also used to determine the risk score of the first target scoring indicator based on the sub-risk scores and preset sub-weights.
[0033] In one possible implementation, the acquisition module is specifically used for:
[0034] Obtaining a relative weight of each second target scoring indicator relative to a third target scoring indicator in the preset scoring indicators, where the second target scoring indicator is any one of the preset scoring indicators, and the third target scoring indicator is a scoring indicator in the preset scoring indicators except the second target scoring indicator;
[0035] The relative weights are input into the hierarchical weight model corresponding to the preset scoring indicators, and the hierarchical weight model is used to generate a judgment matrix corresponding to the relative weights, and a weight vector corresponding to the judgment matrix is generated. The weight vector includes the preset weights of each second target scoring indicator.
[0036] In a possible embodiment, the device further includes:
[0037] The display module is used to display the risk score and the total risk score of the preset scoring indicator using a preset display template after determining the total risk score of the target user according to the risk score and the preset weight.
[0038] In a possible implementation, the acquisition module is specifically used for:
[0039] Obtain financial information, resource information, rating information and warning information of target users;
[0040] Based on financial information, resource information, rating information and early warning information, the scoring data corresponding to the preset scoring indicators are determined according to the preset calculation rules.
[0041] In a third aspect, an embodiment of the present application provides an electronic device, the device comprising:
[0042] a processor and a memory storing computer program instructions;
[0043] When the processor executes the computer program instructions, any one of the above risk score determination methods is implemented.
[0044] In a fourth aspect, an embodiment of the present application provides a computer storage medium, on which computer program instructions are stored. When the computer program instructions are executed by a processor, any of the above-mentioned methods for determining a risk score is implemented.
[0045] In a fifth aspect, an embodiment of the present application provides a computer program product, characterized in that when the instructions in the computer program product are executed by a processor of an electronic device, the electronic device is enabled to execute any of the above-mentioned risk score determination methods.
[0046] The method, device, equipment, medium and product for determining the risk score of the embodiment of the present application include: obtaining the preset scoring index of the target user, the scoring data corresponding to the preset scoring index and the preset weight of the preset scoring index; according to the scoring data, using the first preset scoring rule of the preset scoring index, determining the risk score of the preset scoring index; according to the risk score and the preset weight, determining the total risk score of the target user. In this way, by using the preset scoring index of the target user and the scoring data and weight corresponding to the preset scoring index, and using the preset scoring rules to determine the risk score, not only the efficiency is improved, but also the scoring method of each user is fixed, no manual participation is required, and the accuracy of the risk score is improved. BRIEF DESCRIPTION OF THE DRAWINGS
[0047] In order to more clearly illustrate the technical solution of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.
[0048] Figure 1 is a flowchart of a method for determining a risk score provided by an embodiment of the present application;
[0049] Figure 2 is a flowchart of a method for determining a risk score provided by another embodiment of the present application;
[0050] Figure 3 is a flowchart of a method for determining a risk score provided by another embodiment of the present application;
[0051] Figure 4 is a flowchart of a method for determining a risk score provided in yet another embodiment of the present application;
[0052] Figure 5 is a schematic diagram of the structure of a device for determining a risk score provided in yet another embodiment of the present application;
[0053] Figure 6 It is a structural diagram of an electronic device provided in yet another embodiment of the present application. DETAILED DESCRIPTION
[0054] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is only to provide a better understanding of the present application by illustrating the examples of the present application.
[0055] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "include..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.
[0056] It should be noted that the acquisition, storage, use and processing of data in the embodiments of the present application are in compliance with the relevant provisions of national laws and regulations.
[0057] At present, the risk scores of users (such as medium and large organizations) are mainly determined through financial data. Determining risk scores is conducive to risk assessment of users and appropriate risk avoidance, such as risk assessment after resource replacement.
[0058] Existing scoring methods usually rely on manually collecting users' financial data, sorting it out, and then making manual comprehensive judgments to determine the risk score. This is not only inefficient, but also the risk score obtained is inaccurate.
[0059] In order to solve the problems of the prior art, the embodiments of the present application provide a method, device, equipment, medium and product for determining a risk score. The method for determining a risk score provided in the embodiments of the present application determines the risk score by using a unified scoring standard through the preset scoring indicators of the target user and the scoring data corresponding to the preset scoring indicators, which not only improves efficiency, but also fixes the scoring method for each user, thereby improving the accuracy of the risk score.
[0060] The following first introduces the method for determining the risk score provided in the embodiment of the present application. Figure 1 As shown, the method for determining the risk score provided in the embodiment of the present application includes the following steps.
[0061] S110: Obtain preset scoring indicators of the target user, scoring data corresponding to the preset scoring indicators, and preset weights of the preset scoring indicators.
[0062] Here, the target user can be an individual or an organization. For example, the organization is a medium or large enterprise or institution. The preset scoring indicators and the preset weights of the preset scoring indicators are set in advance.
[0063] In some embodiments, the preset scoring indicators may include but are not limited to operating capability indicators, resource change indicators, resource replacement quantity indicators, rating indicators, personnel change indicators, RAD (risk warning platform) warning indicators, etc.
[0064] In some embodiments, the preset scoring indicators of the target user and the scoring data corresponding to the preset scoring indicators can be read from a database.
[0065] S120: Determine a risk score of a preset scoring indicator according to the scoring data and using a first preset scoring rule of the preset scoring indicator.
[0066] Here, the first preset scoring rule is set in advance.
[0067] In some embodiments, the first preset scoring rule includes a correspondence between scoring data and risk scores. For each preset scoring indicator, at least one preset scoring rule corresponds; for a preset scoring indicator corresponding to multiple preset scoring rules, multiple risk scores can be obtained according to the scoring data. The first preset scoring rule also includes a preset selection rule for the multiple risk scores. Using the preset selection rule, a risk score is selected from the multiple risk scores, and the final risk score is the risk score of the preset scoring indicator.
[0068] S130: Determine the total risk score of the target user according to the risk score and the preset weight.
[0069] In some embodiments, for each preset scoring indicator, the product of its risk score and the preset weight is calculated, and all the obtained values are summed to obtain the total risk score of the target user, that is, the risk scores of the preset scoring indicators are weighted (preset weights) and summed to obtain the total risk score of the target user.
[0070] In some embodiments, for each preset scoring indicator, the product of its risk score and the preset weight is calculated, and all the obtained values are averaged to obtain the total risk score of the target user, that is, the risk scores of the preset scoring indicators are weighted (preset weights) and averaged to obtain the total risk score of the target user.
[0071] In this way, the risk score is determined by using the preset scoring indicators of the target users and the scoring data and weights corresponding to the preset scoring indicators, using the preset scoring rules. This not only improves efficiency, but also the scoring method for each user is fixed, without the need for human participation, thereby improving the accuracy of the risk score.
[0072] Based on this, in some embodiments, the first preset scoring rule includes relationship information between the scoring threshold interval of the preset scoring indicator and the preset risk score; Figure 2 As shown, the above S120 may specifically include:
[0073] S121. Determine that a target risk score corresponding to a target score threshold interval in which the score data of a preset score indicator is located is a risk score of the preset score indicator, the score threshold interval includes the target score threshold interval, and the preset risk score includes the target risk score.
[0074] Here, for a preset scoring indicator that does not include a sub-preset scoring indicator, the preset scoring indicator includes at least one scoring item, and the first preset scoring rule is specifically the relationship information between the scoring threshold interval of the scoring item of the preset scoring indicator and the preset risk score. The scoring threshold interval of the scoring item is at least one, which is set in advance.
[0075] It can be understood that when the scoring threshold interval of the target scoring item of the preset scoring indicator is one, if the scoring data does not fall within the interval, it can be understood that the risk score of the target scoring item of the preset scoring indicator is 0.
[0076] In some embodiments, when there are multiple scoring threshold intervals for the target scoring items of the preset scoring indicators, the relationship information between the scoring threshold intervals of the preset scoring indicators and the preset risk scores includes the relationship information between the scoring threshold intervals of the target scoring items of the preset scoring indicators and the multiple preset risk scores, as well as the selection rule information of the preset risk scores from the multiple preset risk scores.
[0077] As an example, the preset scoring indicator is a rating indicator, and the rating items included in the rating indicator are self-rating and external rating. The first preset scoring rule is "self-rating is level one, the preset risk score is 1 point; self-rating is level two to level three, the preset risk score is 2 points; external rating is level one, the preset risk score is 1 point; external rating is level two to level three, the preset risk score is 2 points; the selection rule information is to select the higher risk score of self-rating and external rating". Exemplarily, the scoring data corresponding to the rating indicator is self-rating level one and external rating level two, then the risk score corresponding to the rating indicator is 2 points.
[0078] The preset scoring indicators may also include indicators for the number of partners, etc. If the preset scoring indicator is an indicator for the number of partners, and the scoring item for the indicator for the number of partners is the total number of partners, then the first preset scoring rule is "the total number of partners is greater than the first threshold, and the preset risk score is 1 point; the total number of partners is greater than the second threshold, and the preset risk score is 2 points; the total number of partners is greater than the third threshold, and the preset risk score is 3 points; the rule information is selected as a step score, and the highest risk score is selected (that is, the highest score that can be obtained is selected)". Among them, the first threshold, the second threshold and the third threshold are set in advance. For example, the first threshold, the second threshold and the third threshold are 5, 10 and 15, respectively. Exemplarily, the scoring data corresponding to the indicator for the number of partners is that the total number of partners is 12, and the risk score corresponding to the indicator for the number of partners is 2 points.
[0079] In another example, in the financial field, the preset scoring indicators may also include resource replacement quantity indicators, etc. If the preset scoring indicator is a resource replacement quantity indicator, and the scoring items of the resource replacement quantity indicator are the resource replacement organization change time and the resource replacement organization change quantity, then the first preset scoring rule is "the resource replacement organization change time is the continuous reduction of resource replacement organizations within the preset time period, and the preset risk score is 3 points; the resource replacement organization change quantity is the reduction of resource replacement organizations that is not less than the fourth threshold, and the preset risk score is 1 point; the resource replacement organization change quantity is the reduction of resource replacement organizations that is not less than the fifth threshold, and the preset risk score is 2 points; the resource replacement organization change quantity is the reduction of resource replacement organizations that is not less than the sixth threshold, and the preset risk score is 3 points; the selection rule information is a ladder score, the highest risk score is selected, and the higher risk score of the resource replacement organization change time and the resource replacement organization change quantity is selected". Among them, the fourth threshold, the fifth threshold and the sixth threshold are set in advance. For example, the fourth threshold, the fifth threshold and the sixth threshold are 1, 2 and 3 respectively. Exemplarily, the scoring data corresponding to the resource replacement quantity indicator is that the resource replacement organization change time is that the resource replacement organization has not continued to decrease within the preset time period, and the resource replacement organization change quantity is the resource replacement organization reduction amount 1, then the risk score corresponding to the resource replacement quantity indicator is 1. It can be understood that if the resource replacement organization change time is that the resource replacement organization has not continued to decrease within the preset time period, and does not fall within the scoring threshold interval of the "resource replacement organization change time", it can be understood that its corresponding risk score is 0. Select the higher 1 between 0 and 1.
[0080] It should be noted that the rating indicators, partner quantity indicators and resource exchange quantity indicators here are exemplary descriptions, and the specific preset scoring indicators and preset scoring rules are not specifically limited here.
[0081] In this way, by presetting the scoring rules of the scoring indicators, the scoring method for each user is fixed, and no human intervention is required, which improves the accuracy of the risk score.
[0082] Based on this, in some embodiments, such as Figure 3 As shown, the method may also include:
[0083] S210, when it is detected that the first target scoring indicator in the preset scoring indicator includes multiple sub-preset scoring indicators, determine the sub-risk score of each sub-preset scoring indicator according to the scoring data corresponding to each sub-preset scoring indicator and using the second preset scoring rule of each sub-preset scoring indicator;
[0084] S220, obtaining a preset sub-weight of each preset sub-scoring indicator;
[0085] S230: Determine a risk score for the first target scoring indicator according to the sub-risk scores and preset sub-weights.
[0086] Here, the preset sub-weight is set in advance. The sub-preset scoring indicator is the next level evaluation indicator of the preset scoring indicator. The second preset scoring rule is similar to the first preset scoring rule, except that it corresponds to the preset scoring rule of the sub-preset scoring indicator, and the second preset scoring rule is not specifically limited here. The sub-preset scoring indicator includes at least one scoring item.
[0087] In some embodiments, for each sub-preset scoring indicator, the product of its sub-risk score and the preset sub-weight is calculated, and all the obtained values are summed to obtain the total risk score of the first target scoring indicator, that is, the weighted sub-risk scores (preset weights) of the sub-preset scoring indicators are summed to obtain the risk score of the first target scoring indicator.
[0088] In some embodiments, for each sub-preset scoring indicator, the product of its sub-risk score and the preset sub-weight is calculated, and all the obtained values are averaged to obtain the total risk score of the first target scoring indicator, that is, the sub-risk scores of the sub-preset scoring indicators are weighted (preset weights) and averaged to obtain the risk score of the first target scoring indicator. In this way, considering more specific evaluation indicators, the preset scoring indicators can also be more refined and more accurately score the target users, thereby improving the accuracy of the risk score.
[0089] Based on this, in some embodiments, in the above S110, obtaining the preset weight of the preset scoring indicator includes:
[0090] Obtaining a relative weight of each second target scoring indicator relative to a third target scoring indicator in the preset scoring indicators, where the second target scoring indicator is any one of the preset scoring indicators, and the third target scoring indicator is a scoring indicator in the preset scoring indicators except the second target scoring indicator;
[0091] The relative weights are input into the hierarchical weight model corresponding to the preset scoring indicators, and the hierarchical weight model is used to generate a judgment matrix corresponding to the relative weights, and a weight vector corresponding to the judgment matrix is generated. The weight vector includes the preset weights of each second target scoring indicator.
[0092] Here, the relative weight of each second objective scoring indicator with respect to the third objective scoring indicator can be obtained through a large number of samples.
[0093] In some embodiments, the hierarchical weight model may be a model constructed using a hierarchical analysis method. The hierarchical weight model is constructed hierarchically using preset scoring indicators, for example, the preset scoring indicators and the sub-preset scoring indicators are different indicator layers. The relative weight of each second target scoring indicator in the preset scoring indicators relative to the third target scoring indicator is input into the hierarchical weight model corresponding to the preset scoring indicator, and a judgment matrix corresponding to the relative weight is generated using the hierarchical weight model, and a weight vector corresponding to the judgment matrix is generated, and the weight vector includes the preset weight of each second target scoring indicator.
[0094] As an example, the judgment matrix is as follows:
[0095]
[0096] Among them, the i-th row and j-th column represent the relative weight of the second target scoring indicator i relative to the third target scoring indicator j, i, j = 1, 2, 3. It can be understood that the judgment matrix is a square matrix, and the number of rows and columns is equal to the number of preset scoring indicators in the same layer. In the judgment matrix, 1 means that the two scoring indicators have the same importance. The i-th row and j-th column are reciprocal to the j-th row and i-th column, which means that if the ratio of the importance of scoring indicator i to scoring indicator j is x ij , then the importance ratio of scoring index j to scoring index i is x ji =1 / x ij .
[0097] In some embodiments, generating a weight vector corresponding to the judgment matrix may specifically include: normalizing the column vectors of the judgment matrix, calculating the row sum and normalizing, determining the eigenvector using the sum method or the root method, and determining the weight vector based on the eigenvector, the weight vector including the weight of each second target scoring indicator relative to the overall target layer, that is, the preset weight of each second target scoring indicator.
[0098] In some embodiments, the judgment matrix is subjected to consistency check. If x ij With x ji They are not reciprocal and cannot pass the consistency check. A prompt message is displayed to remind the staff that the risk score cannot be accurately determined.
[0099] In this way, the constructed hierarchical weight model can determine the weights of the preset scoring indicators, comprehensively consider the relative importance of the preset scoring indicators, and determine the degree of influence of the preset scoring indicators on the overall risk score, thereby improving the accuracy of weight determination and further improving the accuracy of risk scoring.
[0100] In some embodiments, a machine learning model (such as a random forest algorithm) may also be used to determine the importance of preset scoring indicators, and the weights of preset scoring indicators may be determined through model pre-training and adjustment of model parameters.
[0101] Based on this, in some embodiments, such as Figure 4 As shown, after the above S130, the method may further include:
[0102] S140: Using a preset display template, display the risk score and total risk score of the preset scoring indicator.
[0103] Here, the style of the default display template is set in advance.
[0104] Specifically, the risk score and total risk score of the preset scoring indicators are displayed on the data application platform using a preset display template.
[0105] In some embodiments, each user corresponds to a preset display template, which may include user name, number, scoring time period, etc.
[0106] In some embodiments, the ratio of the risk score of each preset scoring indicator to the total risk score is calculated, and the ratio is displayed using a preset display template.
[0107] In this way, by displaying the risk score and total risk score of the preset scoring indicators, staff can further conduct risk assessment on target users and improve user experience.
[0108] Based on this, in some embodiments, in the above S110, obtaining the scoring data corresponding to the preset scoring indicator includes:
[0109] Obtain financial information, resource information, rating information and warning information of target users;
[0110] Based on financial information, resource information, rating information and early warning information, the scoring data corresponding to the preset scoring indicators are determined according to the preset calculation rules.
[0111] Here, the preset calculation rules are set in advance, including relationship information between financial information, resource information, rating information and warning information and scoring data corresponding to preset scoring indicators.
[0112] In some embodiments, financial information, resource information, rating information and warning information are raw data related to target users. The raw data is processed (such as cleaning, calculation, etc.) using preset calculation rules to ensure the accuracy and completeness of the data and determine the scoring data corresponding to the preset scoring indicators.
[0113] In this way, the scoring data corresponding to the preset scoring indicators can be obtained based on the original data of the target user, and then the risk score of the target user can be performed.
[0114] It should be noted that, before the above S110, the first preset scoring rule and the second preset scoring rule, the preset scoring index, and the scoring data corresponding to the preset scoring index and the calculation scheme of the preset weights are received and stored in the database.
[0115] In the embodiment provided in the present application, when a user's query input for scoring data is received, the scoring data corresponding to the preset scoring indicators are displayed.
[0116] Based on the risk score determination method provided in the above embodiment, the present application also provides a specific implementation of the risk score determination device. Please refer to the following embodiment.
[0117] See also Figure 5 The risk score determination device 300 provided in the embodiment of the present application includes:
[0118] An acquisition module 310 is used to acquire a preset scoring indicator of a target user, scoring data corresponding to the preset scoring indicator, and a preset weight of the preset scoring indicator;
[0119] A determination module 320, configured to determine a risk score of a preset scoring indicator according to the scoring data and using a first preset scoring rule of the preset scoring indicator;
[0120] The determination module 320 is further configured to determine the total risk score of the target user according to the risk score and the preset weight.
[0121] Based on this, in some embodiments, the first preset scoring rule includes relationship information between a scoring threshold interval of a preset scoring indicator and a preset risk score; the determination module 320 can be specifically used to:
[0122] Determine that the target risk score corresponding to the target score threshold interval in which the score data of the preset score indicator is located is the risk score of the preset score indicator, the score threshold interval includes the target score threshold interval, and the preset risk score includes the target risk score.
[0123] Based on this, in some embodiments, the apparatus 300 may further include:
[0124] The determination module 320 is further configured to determine the sub-risk score of each sub-preset scoring indicator according to the scoring data corresponding to each sub-preset scoring indicator and using the second preset scoring rule of each sub-preset scoring indicator when it is detected that the first target scoring indicator in the preset scoring indicator includes multiple sub-preset scoring indicators;
[0125] The acquisition module 310 is further used to obtain the preset sub-weight of each sub-preset scoring indicator;
[0126] The determination module 320 is further configured to determine the risk score of the first target scoring indicator according to the sub-risk scores and the preset sub-weights.
[0127] Based on this, in some embodiments, the acquisition module 310 may be specifically used for:
[0128] Obtaining a relative weight of each second target scoring indicator relative to a third target scoring indicator in the preset scoring indicators, where the second target scoring indicator is any one of the preset scoring indicators, and the third target scoring indicator is a scoring indicator in the preset scoring indicators except the second target scoring indicator;
[0129] The relative weights are input into the hierarchical weight model corresponding to the preset scoring indicators, and the hierarchical weight model is used to generate a judgment matrix corresponding to the relative weights, and a weight vector corresponding to the judgment matrix is generated. The weight vector includes the preset weights of each second target scoring indicator.
[0130] Based on this, in some embodiments, the apparatus 300 may further include:
[0131] The display module is used to display the risk score and the total risk score of the preset scoring indicator using a preset display template after determining the total risk score of the target user according to the risk score and the preset weight.
[0132] Based on this, in some embodiments, the acquisition module 310 may be specifically used for:
[0133] Obtain financial information, resource information, rating information and warning information of target users;
[0134] Based on financial information, resource information, rating information and early warning information, the scoring data corresponding to the preset scoring indicators are determined according to the preset calculation rules.
[0135] The various modules of the risk score determination device provided in the embodiment of the present application can implement the functions of the various steps of the risk score determination method provided above and achieve the corresponding technical effects, which will not be described in detail here for the sake of brevity.
[0136] Based on the same inventive concept, an embodiment of the present application also provides an electronic device.
[0137] Figure 6 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application is shown.
[0138] The electronic device may include a processor 401 and a memory 402 storing computer program instructions.
[0139] Specifically, the processor 401 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.
[0140] Memory 402 may include a large capacity memory for data or instructions. By way of example and not limitation, memory 402 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. In appropriate cases, memory 402 may include a removable or non-removable (or fixed) medium. In appropriate cases, memory 402 may be inside or outside of an integrated gateway disaster recovery device. In a specific embodiment, memory 402 is a non-volatile solid-state memory.
[0141] The memory may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk storage medium device, an optical storage medium device, a flash memory device, an electrical, optical or other physical / tangible memory storage device. Therefore, generally, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., a memory device) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to one aspect of the present disclosure.
[0142] The processor 401 implements any one of the risk score determination methods in the above embodiments by reading and executing computer program instructions stored in the memory 402 .
[0143] In one example, the electronic device may further include a communication interface 403 and a bus 410. Figure 6 As shown, the processor 401, the memory 402, and the communication interface 403 are connected via a bus 410 and communicate with each other.
[0144] The communication interface 403 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.
[0145] The bus 410 includes hardware, software or both, coupling the components of the electronic device to each other. For example, but not limitation, the bus may include an accelerated graphics port (Accelerated Graphics Port, AGP) or other graphics bus, an enhanced industry standard architecture (Extended Industry Standard Architecture, EISA) bus, a front side bus (Front Side Bus, FSB), a hypertransport (Hyper Transport, HT) interconnection, an industry standard architecture (Industry Standard Architecture, ISA) bus, an infinite bandwidth interconnection, a low pin count (Linear Predictive Coding, LPC) bus, a memory bus, a micro channel architecture (MicroChannel Architecture, MCA) bus, a peripheral component interconnect (Peripheral Component Interconnect, PCI) bus, a PCI-Express (Peripheral Component Interconnect-X, PCI-X) bus, a serial advanced technology attachment (Serial Advanced Technology Attachment, SATA) bus, a video electronics standard association local (VESA Local Bus, VLB) bus or other suitable buses or a combination of two or more of these. Where appropriate, the bus 410 may include one or more buses. Although the embodiments of the present application describe and illustrate a specific bus, the present application considers any suitable bus or interconnection. The electronic device can execute the risk score determination method in the embodiments of the present invention, thereby implementing the above-mentioned risk score determination method.
[0146] In addition, in combination with the risk score determination method in the above embodiment, the embodiment of the present application can provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when the computer program instructions are executed by the processor, any one of the risk score determination methods in the above embodiment is implemented.
[0147] The present application also provides a computer program product. When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes each process of implementing any one of the above-mentioned risk score determination method embodiments.
[0148] It should be clear that the present application is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present application.
[0149] The functional blocks shown in the structural block diagram described above can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application-specific integrated circuit (Application Specific Integrated Circuit, ASIC), appropriate firmware, plug-in, function card, etc. When implemented in software, the elements of the present application are programs or code segments used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or communication link by a data signal carried in a carrier. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, read-only memory (Read-Only Memory, ROM), flash memory, erasable read-only memory (Erasable ReadOnly Memory, EROM), floppy disks, compact disc read-only memory (Compact Disc Read-Only Memory, CD-ROM), optical discs, hard disks, optical fiber media, radio frequency (Radio Frequency, RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.
[0150] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiment, or in a different order from the embodiment, or several steps can be performed simultaneously.
[0151] Aspects of the present disclosure are described above with reference to the flowchart and / or block diagram of the method, device (system) and computer program product according to the embodiment of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field programmable logic circuit. It can also be understood that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs a specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.
[0152] The above are only specific implementation methods of the present application. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the protection scope of the present application is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in this application, and these modifications or replacements should be included in the protection scope of this application.
Claims
1. A method for determining a risk score, characterized in that: include: Obtaining a preset scoring indicator of a target user, scoring data corresponding to the preset scoring indicator, and a preset weight of the preset scoring indicator; Determine the risk score of the preset scoring indicator according to the scoring data and using the first preset scoring rule of the preset scoring indicator; The total risk score of the target user is determined according to the risk score and the preset weight.
2. The method for determining a risk score according to claim 1, characterized in that: The first preset scoring rule includes relationship information between the scoring threshold interval of the preset scoring indicator and the preset risk score; Determining the risk score of the preset scoring indicator according to the scoring data and using the first preset scoring rule of the preset scoring indicator includes: Determine that a target risk score corresponding to a target score threshold interval in which the score data of the preset score indicator is located is the risk score of the preset score indicator, the score threshold interval includes the target score threshold interval, and the preset risk score includes the target risk score.
3. The method for determining a risk score according to claim 1, characterized in that: Also includes: In the case where it is detected that the first target scoring indicator in the preset scoring indicator includes multiple sub-preset scoring indicators, according to the scoring data corresponding to each of the sub-preset scoring indicators, using the second preset scoring rule of each of the sub-preset scoring indicators, a sub-risk score of each of the sub-preset scoring indicators is determined; Obtaining the preset sub-weight of each of the sub-preset scoring indicators; A risk score of the first target scoring indicator is determined according to the sub-risk scores and the preset sub-weights.
4. The method for determining a risk score according to claim 1, characterized in that: Obtaining the preset weight of the preset scoring indicator includes: Obtaining a relative weight of each second target scoring indicator in the preset scoring indicators relative to a third target scoring indicator, wherein the second target scoring indicator is any one of the preset scoring indicators, and the third target scoring indicator is a scoring indicator in the preset scoring indicators except the second target scoring indicator; The relative weight is input into the hierarchical weight model corresponding to the preset scoring indicator, and the judgment matrix corresponding to the relative weight is generated using the hierarchical weight model, and a weight vector corresponding to the judgment matrix is generated, wherein the weight vector includes the preset weight of each second target scoring indicator.
5. The method for determining a risk score according to claim 1, characterized in that: After determining the total risk score of the target user according to the risk score and the preset weight, the method further includes: The risk score of the preset scoring indicator and the total risk score are displayed using a preset display template.
6. The method for determining a risk score according to claim 1, characterized in that: Obtaining scoring data corresponding to the preset scoring indicators, including: Obtain financial information, resource information, rating information and warning information of target users; According to the financial information, the resource information, the rating information and the warning information, the scoring data corresponding to the preset scoring indicator is determined according to the preset calculation rules.
7. A device for determining a risk score, characterized in that: include: An acquisition module, used to acquire a preset scoring indicator of a target user, scoring data corresponding to the preset scoring indicator, and a preset weight of the preset scoring indicator; A determination module, configured to determine a risk score of the preset scoring indicator according to the scoring data and using a first preset scoring rule of the preset scoring indicator; The determination module is further used to determine the total risk score of the target user according to the risk score and the preset weight.
8. The risk score determination device according to claim 7, characterized in that: The first preset scoring rule includes relationship information between the scoring threshold interval of the preset scoring indicator and the preset risk score; the determination module is specifically used to: Determine that a target risk score corresponding to a target score threshold interval in which the score data of the preset score indicator is located is the risk score of the preset score indicator, the score threshold interval includes the target score threshold interval, and the preset risk score includes the target risk score.
9. The device for determining a risk score according to claim 7, characterized in that: Also includes: The determination module is further configured to determine the sub-risk score of each of the sub-preset scoring indicators according to the scoring data corresponding to each of the sub-preset scoring indicators and using the second preset scoring rule of each of the sub-preset scoring indicators when it is detected that the first target scoring indicator in the preset scoring indicators includes multiple sub-preset scoring indicators; The acquisition module is further used to acquire the preset sub-weight of each of the sub-preset scoring indicators; The determination module is further configured to determine the risk score of the first target scoring indicator according to the sub-risk score and the preset sub-weight.
10. The risk score determination device according to claim 7, characterized in that: The acquisition module is specifically used for: Obtaining a relative weight of each second target scoring indicator in the preset scoring indicators relative to a third target scoring indicator, wherein the second target scoring indicator is any one of the preset scoring indicators, and the third target scoring indicator is a scoring indicator in the preset scoring indicators except the second target scoring indicator; The relative weight is input into the hierarchical weight model corresponding to the preset scoring indicator, and the judgment matrix corresponding to the relative weight is generated using the hierarchical weight model, and a weight vector corresponding to the judgment matrix is generated, wherein the weight vector includes the preset weight of each second target scoring indicator.
11. The risk score determination device according to claim 7, characterized in that: The device also includes: The display module is used to display the risk score of the preset scoring indicator and the total risk score using a preset display template after determining the total risk score of the target user according to the risk score and the preset weight.
12. The risk score determination device according to claim 7, characterized in that: The acquisition module is specifically used for: Obtain financial information, resource information, rating information and warning information of target users; According to the financial information, the resource information, the rating information and the warning information, the scoring data corresponding to the preset scoring indicator is determined according to the preset calculation rules.
13. An electronic device, characterized in that: The device comprises: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, the method for determining the risk score according to any one of claims 1 to 6 is implemented.
14. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the method for determining a risk score according to any one of claims 1 to 6 is implemented.
15. A computer program product, characterized in that When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device is enabled to perform the method for determining a risk score as described in any one of claims 1 to 6.