CN117853241A - Risk service provider identification method, apparatus, device and storage medium thereof - Google Patents
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Abstract
The embodiment of the application belongs to the technical field of financial science and technology, is applied to a financial industry risk service provider identification scene, and relates to a risk service provider identification method, a device, equipment and a storage medium thereof, wherein the service providers with high risk, medium risk and low risk are determined from service information and credit information according to historical service data of a target service provider, business administration credit rating data and credit investigation data of a target responsible person, so that a target user terminal is facilitated to be assisted in screening out a desired service provider, and particularly when the financial service provider is screened out, the desired service provider can be accurately identified through the risk service provider identification method when the target user terminal performs financial service investment, financial investment loss of a target user is reduced, cheated by unqualified financial service providers is avoided, and regular financial investment service providers are assisted to the greatest extent.
Description
Technical Field
The application relates to the technical field of financial science and technology, and is applied to a risk service provider identification scene in the financial industry, in particular to a risk service provider identification method, a risk service provider identification device, risk service provider identification equipment and a storage medium thereof.
Background
With the rapid development of the internet, various industries seek industry breakthrough points by relying on the internet, and in recent years, the financial industry is expanding online business around the internet. Because the financial industry involves a large amount of traffic and data, the financial products are continuously updated in category as the demand of users for products is continuously increased. Particularly in the field of financial services such as financial investment, financial financing or stock analysis.
Due to the multiple heterogeneity of the financial service providers, supervision difficulty is caused to a certain extent, so that some non-formal financial service providers are unavoidable in the financial service providers, and the trust of investors is fraudulently obtained by adopting illegal means, so that huge benefit loss is caused to the investors. The current risk identification method for financial business mostly takes a financial service provider as a starting point to identify a risk client, but cannot help a target user to reduce financial investment loss and screen out a regular financial investment service provider.
Disclosure of Invention
An objective of the embodiments of the present application is to provide a risk service provider identification method, apparatus, device and storage medium thereof, so as to solve the problem that in the prior art, most of the problems that a financial service provider is taken as a starting point to identify a risk client, but a target user cannot be helped to reduce financial investment loss and screen out a regular financial investment service provider.
In order to solve the above technical problems, the embodiment of the present application provides a risk service provider identification method, which adopts the following technical scheme:
a risk service provider identification method comprising the steps of:
acquiring historical service data of a target service provider, business administration credit rating data and credit investigation data of a target responsible person, wherein the historical service data at least comprises service result state identifiers, and the service result state identifiers comprise service success identifiers and service failure identifiers;
inputting the business management credit rating data and the credit rating data of the target responsible person into a preset first evaluation model, and acquiring and determining the credit information of the target server according to a first output result;
inputting the historical service data into a preset service result classification model, and identifying successful data and failed data of the historical service through the service result classification model;
inputting the data of successful history service, the data of failed history service and the credit information into a preset second evaluation model, and acquiring and determining service information of the target service provider according to a second output result;
Determining the service risk of the target service provider based on the service information and a preset risk identification strategy;
pushing the service risk to a target user terminal for the target user terminal to select a service provider.
Further, the step of obtaining historical service data of the target service provider, credit rating data of the business administration and credit rating data of the target responsible person specifically includes:
receiving the history service data pushed from the service information cache database of the target service provider in an asynchronous receiving mode;
and acquiring the business management credit rating data of the target service provider from a preset authority platform in a query receiving mode, and acquiring credit rating data of a target responsible person.
Further, the step of inputting the business administration credit rating data and the credit investigation data of the target responsible person into a preset first evaluation model, and obtaining and determining the credit information of the target service provider according to a first output result specifically includes:
carrying out numerical conversion on the business management credit rating data and the credit investigation data of the target responsible person according to a preset numerical conversion component to obtain numerical conversion results respectively corresponding to the business management credit rating data and the credit investigation data of the target responsible person;
According to a preset evaluation algorithm in the first evaluation model: c=a×ω 1 +B*ω 2 Obtaining the first output result, wherein a represents a numeric conversion result corresponding to the business administration credit rating data, B represents a numeric conversion result corresponding to the credit rating data of the target responsible person, ω 1 Representing the correspondence of the business administration credit rating dataIs the evaluation weight of omega 2 Representing the evaluation weight corresponding to the credit investigation data of the target responsible person;
and determining the credit information of the target service provider according to the first output result and a preset credit score interval.
Further, the step of inputting the history service data into a preset service result classification model, and identifying the data of successful history service and the data of failed history service through the service result classification model specifically includes:
the service result state identification corresponding to each piece of service data in the historical service data is identified through a preset service result state identification component in the service result classification model, and an identification result is obtained;
generating service data subsets respectively corresponding to the service success identification and the service failure identification according to the identification result;
And outputting the service data subsets corresponding to the service success identification and the service failure identification respectively as classification results from the service result classification model.
Further, the step of inputting the data of successful history service, the data of failed history service and the credit information into a preset second evaluation model, and obtaining and determining the service information of the target service provider according to a second output result specifically includes:
calculating the proportion relation between the data of the successful history service and the data of the failed history service by adopting a proportion calculation component in the second evaluation model to obtain the success-failure ratio of the history service;
distributing a confidence level for the historical service success-failure ratio according to the credit information and a preset confidence level, wherein the preset confidence level is preset according to different credit information;
taking the confidence level corresponding to the historical service success-failure ratio and the historical service success-failure ratio as the second output result;
judging the authenticity of the historical service data of the target service provider according to the confidence level and a preset confidence level threshold;
and taking the authenticity of the historical service data and the success-failure ratio of the historical service as the service information of the target service provider.
Further, the step of determining the service risk of the target service provider based on the service information and a preset risk identification policy specifically includes:
identifying the authenticity of the historical service data and the success-failure ratio of the historical service corresponding to the service information;
if the authenticity of the history service is false, the service risk of the target service provider is a high risk;
judging whether the historical service success-failure ratio meets a preset service success-failure ratio threshold value or not;
if the authenticity of the historical service is true and the historical service success-failure ratio does not meet the service success-failure ratio threshold, the service risk of the target service provider is a moderate risk;
and if the historical service authenticity is true and the historical service success-failure ratio meets the service success-failure ratio threshold, the service risk of the target service provider is low risk.
Further, before executing the step of pushing the service risk to a target user terminal for the target user terminal to select a service provider, the method further includes:
the communication modes of all service providers are sent to the target user terminal in advance;
the step of pushing the service risk to a target user terminal for the target user terminal to select a service provider specifically includes:
Receiving communication modes of all service providers and service risks of all service providers through the target user terminal;
screening expected service providers and unexpected service providers from all service providers according to the service risk and preset risk screening conditions;
after the step of pushing the service risk to the target user terminal for the target user terminal to select a service provider is performed, the method further includes:
acquiring communication modes of all unexpected service providers;
and setting the communication modes of all the unexpected service providers as intercepted communication modes by adopting a Spring Boot risk interception component.
In order to solve the above technical problems, the embodiments of the present application further provide a risk service provider identification device, which adopts the following technical scheme:
a risk facilitator identification device comprising:
the system comprises a target data acquisition module, a service management module and a service management module, wherein the target data acquisition module is used for acquiring historical service data of a target service provider, business management credit rating data and credit investigation data of a target responsible person, the historical service data at least comprises a service result state identifier, and the service result state identifier comprises a service success identifier and a service failure identifier;
The credit information determining module is used for inputting the business administration credit rating data and the credit investigation data of the target responsible person into a preset first evaluation model, and obtaining and determining the credit information of the target service provider according to a first output result;
the historical service data classification module is used for inputting the historical service data into a preset service result classification model, and identifying data of successful historical service and data of failed historical service through the service result classification model;
the service information determining module is used for inputting the data of successful history service, the data of failed history service and the credit information into a preset second evaluation model, and obtaining and determining the service information of the target service provider according to a second output result;
the service risk determining module is used for determining the service risk of the target service provider based on the service information and a preset risk identification strategy;
and the service risk pushing module is used for pushing the service risk to a target user terminal for the target user terminal to select a service provider.
In order to solve the above technical problems, the embodiments of the present application further provide a computer device, which adopts the following technical schemes:
A computer device comprising a memory having stored therein computer readable instructions which when executed by a processor implement the steps of the risk facilitator identification method described above.
In order to solve the above technical problems, embodiments of the present application further provide a computer readable storage medium, which adopts the following technical solutions:
a computer readable storage medium having stored thereon computer readable instructions which when executed by a processor perform the steps of the risk facilitator identification method as described above.
Compared with the prior art, the embodiment of the application has the following main beneficial effects:
according to the risk service provider identification method, historical service data of a target service provider, business administration credit rating data and credit investigation data of a target responsible person are obtained; determining the credit information of the target service provider according to the business administration credit rating data and the credit investigation data of the target responsible person; identifying data of successful history service and data of failed history service; determining service information of a target service provider according to the data of the successful history service, the data of the failed history service and the credit information; determining the service risk of a target service provider; pushing the service risk to a target user terminal for the target user terminal to select a service provider. The service providers with high risk, medium risk and low risk are determined from the service information and the credit information according to the historical service data of the target service providers, the business management credit rating data and the credit information of the target responsible person, so that the target user terminal is facilitated to screen out the expected service providers, particularly when the financial service providers are screened out, the expected service providers can be accurately identified by the risk service provider identification method when the financial service providers are invested in the target user terminal, the financial investment loss of the target user is reduced, the situation that the target user is cheated by the unqualified financial service providers is avoided, and the target user is helped to select the regular financial investment service providers as much as possible.
Drawings
For a clearer description of the solution in the present application, a brief description will be given below of the drawings that are needed in the description of the embodiments of the present application, it being obvious that the drawings in the following description are some embodiments of the present application, and that other drawings may be obtained from these drawings without inventive effort for a person of ordinary skill in the art.
FIG. 1 is an exemplary system architecture diagram in which the present application may be applied;
FIG. 2 is a flow chart of one embodiment of a risk service identification method according to the present application;
FIG. 3 is a flow chart of one embodiment of step 201 of FIG. 2;
FIG. 4 is a flow chart of one embodiment of step 202 of FIG. 2;
FIG. 5 is a flow chart of one embodiment of step 203 shown in FIG. 2;
FIG. 6 is a flow chart of one embodiment of step 204 shown in FIG. 2;
FIG. 7 is a flow chart of one embodiment of step 205 of FIG. 2;
FIG. 8 is a schematic diagram of an embodiment of a risk service identification device according to the present application;
FIG. 9 is a schematic structural diagram of one embodiment of a computer device according to the present application.
Detailed Description
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs; the terminology used in the description of the applications herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "comprising" and "having" and any variations thereof in the description and claims of the present application and in the description of the figures above are intended to cover non-exclusive inclusions. The terms first, second and the like in the description and in the claims or in the above-described figures, are used for distinguishing between different objects and not necessarily for describing a sequential or chronological order.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the present application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
In order to better understand the technical solutions of the present application, the following description will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings.
As shown in fig. 1, a system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is used as a medium to provide communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.
The user may interact with the server 105 via the network 104 using the terminal devices 101, 102, 103 to receive or send messages or the like. Various communication client applications, such as a web browser application, a shopping class application, a search class application, an instant messaging tool, a mailbox client, social platform software, etc., may be installed on the terminal devices 101, 102, 103.
The terminal devices 101, 102, 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smartphones, tablet computers, electronic book readers, MP3 players (Moving Picture ExpertsGroup Audio Layer III, dynamic video expert compression standard audio plane 3), MP4 (Moving PictureExperts Group Audio Layer IV, dynamic video expert compression standard audio plane 4) players, laptop and desktop computers, and the like.
The server 105 may be a server providing various services, such as a background server providing support for pages displayed on the terminal devices 101, 102, 103.
It should be noted that, the risk service provider identification method provided in the embodiments of the present application is generally executed by a server/terminal device, and accordingly, the risk service provider identification apparatus is generally disposed in the server/terminal device.
It should be understood that the number of terminal devices, networks and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
With continued reference to fig. 2, a flow chart of one embodiment of a risk service identification method according to the present application is shown. The risk service provider identification method comprises the following steps:
step 201, obtaining historical service data of a target service provider, credit rating data of an industrial and commercial management and credit rating data of a target responsible person, wherein the historical service data at least comprises service result state identifiers, and the service result state identifiers comprise service success identifiers and service failure identifiers.
In this embodiment, the target service provider is a financial service provider, such as a financial investment service provider, a financial management service provider, a stock analysis service provider, etc.
With continued reference to fig. 3, fig. 3 is a flow chart of one embodiment of step 201 of fig. 2, comprising:
step 301, receiving the history service data pushed from the service information cache database of the target service provider in an asynchronous receiving manner;
in this embodiment, the step of receiving, by an asynchronous receiving manner, the history service data pushed from the service information cache database of the target service provider specifically includes: and pushing the history service data to a target receiving end according to a preset message pushing component by taking the service information cache database as a data pushing end, wherein the message pushing component comprises a distributed architecture message pushing component based on Kafka.
And 302, acquiring the business management credit rating data of the target service provider and the credit rating data of the target responsible person from a preset authority platform in a query receiving mode.
In this embodiment, the step of obtaining, by a query receiving manner, the business administration credit rating data of the target service provider and the credit investigation data of the target responsible person from a preset authority platform specifically includes: taking the distinguishing identification information of the target service provider as a first query field, and acquiring the business management credit rating data of the target service provider from a first authority platform, wherein the distinguishing identification information of the target service provider comprises a social unified credit code of the target service provider, and the first authority platform comprises a business information management platform; and taking the distinguishing identification information of the target responsible person as a second query field, and acquiring credit investigation data of the target responsible person from a second authority platform, wherein the distinguishing identification information of the target responsible person comprises identification card number information of the target responsible person, and the second authority platform comprises a bank credit investigation system.
By acquiring historical service data of the target service provider, business management credit rating data and credit investigation data of the target responsible person, the target user terminal is facilitated to be assisted to screen out expected service providers, and the target user terminal is assisted to screen out financial service providers which do not accord with relevant financial service qualification, so that when the target user terminal selects a financial service provider, financial loss of the target user is reduced from a service source as much as possible, such as financial investment deception risk is reduced, and financial financing deception risk is reduced.
Step 202, inputting the business management credit rating data and the credit rating data of the target responsible person into a preset first evaluation model, and obtaining and determining the credit information of the target service provider according to a first output result.
With continued reference to FIG. 4, FIG. 4 is a flow chart of one embodiment of step 202 of FIG. 2, including:
step 401, performing numeric conversion on the business management credit rating data and the credit investigation data of the target responsible person according to a preset numeric conversion component to obtain numeric conversion results respectively corresponding to the business management credit rating data and the credit investigation data of the target responsible person;
Specifically, for example, the industrial and commercial management credit rating data includes a plurality of rating indexes, each rating index corresponds to a corresponding rating weight value, a numeric conversion result corresponding to the industrial and commercial management credit rating data is obtained through an accumulation and summation mode, and similarly, the credit investigation data of the target responsible person also includes a plurality of credit investigation indexes, each credit investigation index corresponds to a corresponding index weight value, and a numeric conversion result corresponding to the credit investigation data of the target responsible person is obtained through an accumulation and summation mode.
Step 402, according to an evaluation algorithm preset in the first evaluation model: c=a×ω 1 +β*ω 2 Obtaining the first output result, wherein a represents a numeric conversion result corresponding to the business administration credit rating data, B represents a numeric conversion result corresponding to the credit rating data of the target responsible person, ω 1 Representing the evaluation weight omega corresponding to the business management credit rating data 2 Representing the evaluation weight corresponding to the credit investigation data of the target responsible person;
step 403, determining the credit information of the target service provider according to the first output result and a preset credit value interval.
Specifically, the first output result obtained through the preset evaluation algorithm in the first evaluation model is numeric data, a credit score interval of a target number is preset, the credit score interval to which the first output result belongs is identified according to the first output result and the preset credit score interval, and the credit score interval to which the first output result belongs is used as the credit information of the target server.
And 203, inputting the historical service data into a preset service result classification model, and identifying successful data and failed data of the historical service through the service result classification model.
With continued reference to fig. 5, fig. 5 is a flow chart of one embodiment of step 203 shown in fig. 2, comprising:
step 501, identifying service result state identifiers corresponding to each piece of service data in the historical service data through a preset service result state identifier identification component in the service result classification model, and obtaining an identification result;
step 502, generating service data subsets corresponding to the service success identifier and the service failure identifier respectively according to the identification result;
And step 503, outputting the service data subsets corresponding to the service success identifier and the service failure identifier respectively from the service result classification model as classification results.
And identifying service result state identifiers corresponding to each piece of service data in the historical service data through a preset service result state identifier identification component in the service result classification model, so that successful service data and failed service data in the historical service data can be conveniently identified according to the service result state identifiers.
And 204, inputting the data of successful history service, the data of failed history service and the credit information into a preset second evaluation model, and acquiring and determining the service information of the target service provider according to a second output result.
With continued reference to FIG. 6, FIG. 6 is a flow chart of one embodiment of step 204 shown in FIG. 2, comprising:
step 601, calculating a proportion relation between the data of successful history service and the data of failed history service by adopting a proportion calculation component in the second evaluation model, and obtaining a success-failure ratio of the history service;
step 602, allocating a confidence level for the historical service success-failure ratio according to the credit information and a preset confidence level, wherein the preset confidence level is preset according to different credit information;
Step 603, taking the confidence level corresponding to the success-failure ratio of the historical service and the success-failure ratio of the historical service as the second output result;
step 604, determining the authenticity of the historical service data of the target service provider according to the confidence level and a preset confidence level threshold;
and step 605, taking the authenticity of the historical service data and the success-failure ratio of the historical service as the service information of the target service provider.
And determining service information of the target service provider by combining the data of the successful history service, the data of the failed history service and the credit information, and combining the service provider data of multiple dimensions, so that the financial service provider screening is conveniently and accurately carried out for the target user terminal to provide data support.
Step 205, determining the service risk of the target service provider based on the service information and a preset risk identification policy.
With continued reference to fig. 7, fig. 7 is a flow chart of one embodiment of step 205 shown in fig. 2, comprising:
step 701, identifying the authenticity of the historical service data and the success-failure ratio of the historical service corresponding to the service information;
step 702, if the authenticity of the history service is false, the service risk of the target service provider is a high risk;
Step 703, judging whether the historical service success-failure ratio meets a preset service success-failure ratio threshold;
step 704, if the authenticity of the history service is true and the success-failure ratio of the history service does not meet the threshold of the success-failure ratio of the service, the service risk of the target service provider is a moderate risk;
step 705, if the historical service authenticity is true and the historical service success-failure ratio meets the service success-failure ratio threshold, the service risk of the target service provider is a low risk.
In this embodiment, the historical service success-failure ratio meets the service cost ratio threshold, that is, the historical service success-failure ratio is greater than the service cost ratio threshold, and the historical service success-failure ratio does not meet the service success-failure ratio threshold, that is, the historical service success-failure ratio is less than or equal to the service cost ratio threshold, where the historical service success-failure ratio, that is, the ratio of data items for which the historical service is successful to data items for which the historical service is failed.
Step 206, pushing the service risk to a target user terminal for the target user terminal to select a service provider.
In this embodiment, before the step of pushing the service risk to the target ue for the target ue to select a service provider is performed, the method further includes: the communication modes of all service providers are sent to the target user terminal in advance;
In this embodiment, the step of pushing the service risk to a target user terminal for the target user terminal to perform service provider selection specifically includes: receiving communication modes of all service providers and service risks of all service providers through the target user terminal; screening expected service providers and unexpected service providers from all service providers according to the service risk and preset risk screening conditions;
specifically, the preset risk screening conditions include screening out high-risk service providers as the undesired service providers, and reserving medium-risk service providers and low-risk service providers as desired service providers; the preset risk screening conditions further comprise screening out service providers with medium risks and high risks as the undesired service providers, and reserving service providers with low risks as desired service providers. The specific risk screening conditions can be freely set by the target user terminal in combination with financial business risk scenes.
In this embodiment, after the step of pushing the service risk to the target ue for the target ue to select a service provider is performed, the method further includes: acquiring communication modes of all unexpected service providers; and setting the communication modes of all the unexpected service providers as intercepted communication modes by adopting a Spring Boot risk interception component.
By adopting the Spring Boot risk interception component to set the communication modes of all the non-expected service providers as intercepted communication modes, the information messages or call requests sent by all the non-expected service providers are intercepted at the first time.
The service providers with high risk, medium risk and low risk are determined from the service information and the credit information according to the historical service data of the target service providers, the business management credit rating data and the credit information of the target responsible person, so that the target user terminal is facilitated to screen out the expected service providers, particularly when the financial service providers are screened out, the expected service providers can be accurately identified by the risk service provider identification method when the financial service providers are invested in the target user terminal, the financial investment loss of the target user is reduced, the situation that the target user is cheated by the unqualified financial service providers is avoided, and the target user is helped to select the regular financial investment service providers as much as possible.
The method comprises the steps of obtaining historical service data of a target service provider, credit rating data of business administration and credit rating data of a target responsible person; determining the credit information of the target service provider according to the business administration credit rating data and the credit investigation data of the target responsible person; identifying data of successful history service and data of failed history service; determining service information of a target service provider according to the data of the successful history service, the data of the failed history service and the credit information; determining the service risk of a target service provider; pushing the service risk to a target user terminal for the target user terminal to select a service provider. The service providers with high risk, medium risk and low risk are determined from the service information and the credit information according to the historical service data of the target service providers, the business management credit rating data and the credit information of the target responsible person, so that the target user terminal is facilitated to screen out the expected service providers, particularly when the financial service providers are screened out, the expected service providers can be accurately identified by the risk service provider identification method when the financial service providers are invested in the target user terminal, the financial investment loss of the target user is reduced, the situation that the target user is cheated by the unqualified financial service providers is avoided, and the target user is helped to select the regular financial investment service providers as much as possible.
The embodiment of the application can acquire and process the related data based on the artificial intelligence technology. Among these, artificial intelligence (Artificial Intelligence, AI) is the theory, method, technique and application system that uses a digital computer or a digital computer-controlled machine to simulate, extend and extend human intelligence, sense the environment, acquire knowledge and use knowledge to obtain optimal results.
Artificial intelligence infrastructure technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, high risk facilitator identification technologies, operation/interaction systems, mechatronics, and the like. The artificial intelligence software technology mainly comprises a computer vision technology, a robot technology, a biological recognition technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and other directions.
In the embodiment of the application, the historical service data of the target service provider, the credit rating data of the business administration and the credit investigation data of the target responsible person are obtained; determining the credit information of the target service provider according to the business administration credit rating data and the credit investigation data of the target responsible person; identifying data of successful history service and data of failed history service; determining service information of a target service provider according to the data of the successful history service, the data of the failed history service and the credit information; determining the service risk of a target service provider; pushing the service risk to a target user terminal for the target user terminal to select a service provider. The service providers with high risk, medium risk and low risk are determined from the service information and the credit information according to the historical service data of the target service providers, the business management credit rating data and the credit information of the target responsible person, so that the target user terminal is facilitated to screen out the expected service providers, particularly when the financial service providers are screened out, the expected service providers can be accurately identified by the risk service provider identification method when the financial service providers are invested in the target user terminal, the financial investment loss of the target user is reduced, the situation that the target user is cheated by the unqualified financial service providers is avoided, and the target user is helped to select the regular financial investment service providers as much as possible.
With further reference to fig. 8, as an implementation of the method shown in fig. 2, the present application provides an embodiment of a risk service provider identification apparatus, where an embodiment of the apparatus corresponds to the embodiment of the method shown in fig. 2, and the apparatus may be specifically applied to various electronic devices.
As shown in fig. 8, the risk service provider identification device 800 according to the present embodiment includes: a target data acquisition module 801, a credit information determination module 802, a historical service data classification module 803, a service information determination module 804, a service risk determination module 805, and a service risk push module 806.
Wherein:
the target data obtaining module 801 is configured to obtain historical service data of a target service provider, credit rating data of an industrial and commercial management, and credit rating data of a target responsible person, where the historical service data at least includes service result status identifiers, and the service result status identifiers include service success identifiers and service failure identifiers;
the credit information determining module 802 is configured to input the business administration credit rating data and the credit rating data of the target responsible person into a preset first evaluation model, and acquire and determine the credit information of the target server according to a first output result;
The historical service data classification module 803 is configured to input the historical service data into a preset service result classification model, and identify data of successful historical service and data of failed historical service through the service result classification model;
the service information determining module 804 is configured to input the data of successful history service, the data of failed history service, and the credit information into a preset second evaluation model, and obtain and determine service information of the target service provider according to a second output result;
a service risk determining module 805, configured to determine a service risk of the target facilitator based on the service information and a preset risk identification policy;
and a service risk pushing module 806, configured to push the service risk to a target user terminal, so that the target user terminal performs service provider selection.
In some embodiments of the present application, the risk service provider identification device 800 further includes a risk communication method interception module, where the risk communication method interception module is configured to obtain communication methods of all undesired service providers; the method is also used for setting the communication modes of all the unexpected service providers as intercepted communication modes by adopting the Spring Boot risk interception component.
The method comprises the steps of obtaining historical service data of a target service provider, credit rating data of business administration and credit rating data of a target responsible person; determining the credit information of the target service provider according to the business administration credit rating data and the credit investigation data of the target responsible person; identifying data of successful history service and data of failed history service; determining service information of a target service provider according to the data of the successful history service, the data of the failed history service and the credit information; determining the service risk of a target service provider; pushing the service risk to a target user terminal for the target user terminal to select a service provider. The service providers with high risk, medium risk and low risk are determined from the service information and the credit information according to the historical service data of the target service providers, the business management credit rating data and the credit information of the target responsible person, so that the target user terminal is facilitated to screen out the expected service providers, particularly when the financial service providers are screened out, the expected service providers can be accurately identified by the risk service provider identification method when the financial service providers are invested in the target user terminal, the financial investment loss of the target user is reduced, the situation that the target user is cheated by the unqualified financial service providers is avoided, and the target user is helped to select the regular financial investment service providers as much as possible.
Those skilled in the art will appreciate that implementing all or part of the above described embodiment methods may be accomplished by computer readable instructions, stored on a computer readable storage medium, that the program when executed may comprise the steps of embodiments of the methods described above. The storage medium may be a nonvolatile storage medium such as a magnetic disk, an optical disk, a Read-Only Memory (ROM), or a random access Memory (Random Access Memory, RAM).
It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited in order and may be performed in other orders, unless explicitly stated herein. Moreover, at least some of the steps in the flowcharts of the figures may include a plurality of sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, the order of their execution not necessarily being sequential, but may be performed in turn or alternately with other steps or at least a portion of the other steps or stages.
In order to solve the technical problems, the embodiment of the application also provides computer equipment. Referring specifically to fig. 9, fig. 9 is a basic structural block diagram of a computer device according to the present embodiment.
The computer device 9 comprises a memory 9a, a processor 9b, a network interface 9c communicatively connected to each other via a system bus. It should be noted that only a computer device 9 having components 9a-9c is shown in the figures, but it should be understood that not all of the illustrated components need be implemented, and that more or fewer components may alternatively be implemented. It will be appreciated by those skilled in the art that the computer device herein is a device capable of automatically performing numerical calculations and/or information processing in accordance with predetermined or stored instructions, the hardware of which includes, but is not limited to, microprocessors, application specific integrated circuits (Application Specific Integrated Circuit, ASICs), programmable gate arrays (fields-Programmable Gate Array, FPGAs), digital processors (Digital Signal Processor, DSPs), embedded devices, etc.
The computer equipment can be a desktop computer, a notebook computer, a palm computer, a cloud server and other computing equipment. The computer equipment can perform man-machine interaction with a user through a keyboard, a mouse, a remote controller, a touch pad or voice control equipment and the like.
The memory 9a includes at least one type of readable storage medium including flash memory, hard disk, multimedia card, card memory (e.g., SD or DX memory, etc.), random Access Memory (RAM), static Random Access Memory (SRAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), programmable Read Only Memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the storage 9a may be an internal storage unit of the computer device 9, such as a hard disk or a memory of the computer device 9. In other embodiments, the memory 9a may also be an external storage device of the computer device 9, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash Card (Flash Card) or the like, which are provided on the computer device 9. Of course, the memory 9a may also comprise both an internal memory unit of the computer device 9 and an external memory device. In this embodiment, the memory 9a is typically used to store an operating system and various application software installed on the computer device 9, such as computer readable instructions of a risk service provider identification method. Further, the memory 9a may be used to temporarily store various types of data that have been output or are to be output.
The processor 9b may be a central processing unit (Central Processing Unit, CPU), controller, microcontroller, microprocessor, or other risk service identification chip in some embodiments. The processor 9b is typically used to control the overall operation of the computer device 9. In this embodiment, the processor 9b is configured to execute computer readable instructions stored in the memory 9a or process data, such as computer readable instructions for executing the risk service provider identification method.
The network interface 9c may comprise a wireless network interface or a wired network interface, which network interface 9c is typically used for establishing a communication connection between the computer device 9 and other electronic devices.
The computer equipment provided by the embodiment belongs to the technical field of financial science and technology, and is applied to a financial industry risk service provider identification scene. The method comprises the steps of obtaining historical service data of a target service provider, credit rating data of business administration and credit rating data of a target responsible person; determining the credit information of the target service provider according to the business administration credit rating data and the credit investigation data of the target responsible person; identifying data of successful history service and data of failed history service; determining service information of a target service provider according to the data of the successful history service, the data of the failed history service and the credit information; determining the service risk of a target service provider; pushing the service risk to a target user terminal for the target user terminal to select a service provider. The service providers with high risk, medium risk and low risk are determined from the service information and the credit information according to the historical service data of the target service providers, the business management credit rating data and the credit information of the target responsible person, so that the target user terminal is facilitated to screen out the expected service providers, particularly when the financial service providers are screened out, the expected service providers can be accurately identified by the risk service provider identification method when the financial service providers are invested in the target user terminal, the financial investment loss of the target user is reduced, the situation that the target user is cheated by the unqualified financial service providers is avoided, and the target user is helped to select the regular financial investment service providers as much as possible.
The present application also provides another embodiment, namely, a computer readable storage medium, where computer readable instructions are stored, where the computer readable instructions are executable by a processor, to cause the processor to perform the steps of the risk service provider identification method as described above.
The computer readable storage medium provided by the embodiment belongs to the technical field of financial science and technology, and is applied to a financial industry risk service provider identification scene. The method comprises the steps of obtaining historical service data of a target service provider, credit rating data of business administration and credit rating data of a target responsible person; determining the credit information of the target service provider according to the business administration credit rating data and the credit investigation data of the target responsible person; identifying data of successful history service and data of failed history service; determining service information of a target service provider according to the data of the successful history service, the data of the failed history service and the credit information; determining the service risk of a target service provider; pushing the service risk to a target user terminal for the target user terminal to select a service provider. The service providers with high risk, medium risk and low risk are determined from the service information and the credit information according to the historical service data of the target service providers, the business management credit rating data and the credit information of the target responsible person, so that the target user terminal is facilitated to screen out the expected service providers, particularly when the financial service providers are screened out, the expected service providers can be accurately identified by the risk service provider identification method when the financial service providers are invested in the target user terminal, the financial investment loss of the target user is reduced, the situation that the target user is cheated by the unqualified financial service providers is avoided, and the target user is helped to select the regular financial investment service providers as much as possible.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk), comprising several instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method described in the embodiments of the present application.
It is apparent that the embodiments described above are only some embodiments of the present application, but not all embodiments, the preferred embodiments of the present application are given in the drawings, but not limiting the patent scope of the present application. This application may be embodied in many different forms, but rather, embodiments are provided in order to provide a more thorough understanding of the present disclosure. Although the present application has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the embodiments described in the foregoing, or equivalents may be substituted for elements thereof. All equivalent structures made by the specification and the drawings of the application are directly or indirectly applied to other related technical fields, and are also within the protection scope of the application.
Claims (10)
1. A risk service provider identification method, comprising the steps of:
acquiring historical service data of a target service provider, business administration credit rating data and credit investigation data of a target responsible person, wherein the historical service data at least comprises service result state identifiers, and the service result state identifiers comprise service success identifiers and service failure identifiers;
inputting the business management credit rating data and the credit rating data of the target responsible person into a preset first evaluation model, and acquiring and determining the credit information of the target server according to a first output result;
inputting the historical service data into a preset service result classification model, and identifying successful data and failed data of the historical service through the service result classification model;
inputting the data of successful history service, the data of failed history service and the credit information into a preset second evaluation model, and acquiring and determining service information of the target service provider according to a second output result;
determining the service risk of the target service provider based on the service information and a preset risk identification strategy;
Pushing the service risk to a target user terminal for the target user terminal to select a service provider.
2. The risk service provider identification method according to claim 1, wherein the step of acquiring historical service data of the target service provider, business administration credit rating data and credit investigation data of the target responsible person specifically comprises:
receiving the history service data pushed from the service information cache database of the target service provider in an asynchronous receiving mode;
and acquiring the business management credit rating data of the target service provider from a preset authority platform in a query receiving mode, and acquiring credit rating data of a target responsible person.
3. The risk service provider identification method according to claim 1, wherein the step of inputting the business administration credit rating data and the credit rating data of the target responsible person into a preset first evaluation model, obtaining and determining the credit information of the target service provider according to a first output result specifically comprises:
carrying out numerical conversion on the business management credit rating data and the credit investigation data of the target responsible person according to a preset numerical conversion component to obtain numerical conversion results respectively corresponding to the business management credit rating data and the credit investigation data of the target responsible person;
According to a preset evaluation algorithm in the first evaluation model: c=a×ω 1 +B*ω 2 Obtaining the first output result, wherein a represents a numeric conversion result corresponding to the business administration credit rating data, B represents a numeric conversion result corresponding to the credit rating data of the target responsible person, ω 1 Representing the evaluation weight omega corresponding to the business management credit rating data 2 Representing the evaluation weight corresponding to the credit investigation data of the target responsible person;
and determining the credit information of the target service provider according to the first output result and a preset credit score interval.
4. The risk service provider identification method according to claim 1, wherein the step of inputting the history service data into a preset service result classification model, and identifying the data of successful history service and the data of failed history service through the service result classification model specifically comprises:
the service result state identification corresponding to each piece of service data in the historical service data is identified through a preset service result state identification component in the service result classification model, and an identification result is obtained;
generating service data subsets respectively corresponding to the service success identification and the service failure identification according to the identification result;
And outputting the service data subsets corresponding to the service success identification and the service failure identification respectively as classification results from the service result classification model.
5. The risk service provider identification method according to claim 1, wherein the step of inputting the history service success data, the history service failure data, and the credit information into a preset second evaluation model, obtaining and determining service information of the target service provider according to a second output result specifically includes:
calculating the proportion relation between the data of the successful history service and the data of the failed history service by adopting a proportion calculation component in the second evaluation model to obtain the success-failure ratio of the history service;
distributing a confidence level for the historical service success-failure ratio according to the credit information and a preset confidence level, wherein the preset confidence level is preset according to different credit information;
taking the confidence level corresponding to the historical service success-failure ratio and the historical service success-failure ratio as the second output result;
judging the authenticity of the historical service data of the target service provider according to the confidence level and a preset confidence level threshold;
And taking the authenticity of the historical service data and the success-failure ratio of the historical service as the service information of the target service provider.
6. The risk service provider identification method according to claim 5, wherein the step of determining the service risk of the target service provider based on the service information and a preset risk identification policy specifically comprises:
identifying the authenticity of the historical service data and the success-failure ratio of the historical service corresponding to the service information;
if the authenticity of the history service is false, the service risk of the target service provider is a high risk;
judging whether the historical service success-failure ratio meets a preset service success-failure ratio threshold value or not;
if the authenticity of the historical service is true and the historical service success-failure ratio does not meet the service success-failure ratio threshold, the service risk of the target service provider is a moderate risk;
and if the historical service authenticity is true and the historical service success-failure ratio meets the service success-failure ratio threshold, the service risk of the target service provider is low risk.
7. The risk service provider identification method according to claim 1 or 6, characterized in that before performing the step of pushing the service risk to a target user terminal for service provider selection by the target user terminal, the method further comprises:
The communication modes of all service providers are sent to the target user terminal in advance;
the step of pushing the service risk to a target user terminal for the target user terminal to select a service provider specifically includes:
receiving communication modes of all service providers and service risks of all service providers through the target user terminal;
screening expected service providers and unexpected service providers from all service providers according to the service risk and preset risk screening conditions;
after the step of pushing the service risk to the target user terminal for the target user terminal to select a service provider is performed, the method further includes:
acquiring communication modes of all unexpected service providers;
and setting the communication modes of all the unexpected service providers as intercepted communication modes by adopting a Spring Boot risk interception component.
8. A risk service provider identification device, comprising:
the system comprises a target data acquisition module, a service management module and a service management module, wherein the target data acquisition module is used for acquiring historical service data of a target service provider, business management credit rating data and credit investigation data of a target responsible person, the historical service data at least comprises a service result state identifier, and the service result state identifier comprises a service success identifier and a service failure identifier;
The credit information determining module is used for inputting the business administration credit rating data and the credit investigation data of the target responsible person into a preset first evaluation model, and obtaining and determining the credit information of the target service provider according to a first output result;
the historical service data classification module is used for inputting the historical service data into a preset service result classification model, and identifying data of successful historical service and data of failed historical service through the service result classification model;
the service information determining module is used for inputting the data of successful history service, the data of failed history service and the credit information into a preset second evaluation model, and obtaining and determining the service information of the target service provider according to a second output result;
the service risk determining module is used for determining the service risk of the target service provider based on the service information and a preset risk identification strategy;
and the service risk pushing module is used for pushing the service risk to a target user terminal for the target user terminal to select a service provider.
9. A computer device comprising a memory and a processor, the memory having stored therein computer readable instructions which when executed by the processor implement the steps of the risk service provider identification method of any one of claims 1 to 7.
10. A computer readable storage medium having stored thereon computer readable instructions which when executed by a processor implement the steps of the risk service provider identification method of any of claims 1 to 7.
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