CN113362039A - Business approval method and device, electronic equipment and storage medium - Google Patents
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Abstract
The invention relates to the field of data analysis, and discloses a business approval method, which comprises the following steps: receiving a service approval request, and collecting user information and service information of the service approval request; constructing a user portrait according to the user information, and calculating a user credit score of the user portrait; configuring the examination and approval logic and examination and approval modes of the service information, constructing a service wind control factor of the service information according to the examination and approval logic and examination and approval modes, and calculating the service authorization score of the service information according to the service wind control factor; and calculating the final credit score of the service approval request according to the user credit score and the service authorization score, and generating an approval result of the service approval request according to the final credit score. In addition, the invention also provides a business approval device, electronic equipment and a computer readable storage medium. Furthermore, the invention also relates to blockchain techniques, the final credit score may be stored in a blockchain. The invention can improve the accuracy of the business approval.
Description
Technical Field
The present invention relates to the field of data analysis, and in particular, to a method and an apparatus for business approval, an electronic device, and a computer-readable storage medium.
Background
With the development of information technology, the information-based office system is widely applied, so that all business processes can be processed on the information-based office system, and the business processing efficiency and the user work efficiency are greatly improved.
In an information office system, for a business process of business approval, since business approval is associated with authenticity verification of business information, an approval person needs to make an approval decision after the approval person audits an application business, and thus the business process is easily influenced by personal subjective intention of the approval person, and the approval accuracy of the application business can be influenced.
Disclosure of Invention
The invention provides a business approval method, a business approval device, electronic equipment and a computer readable storage medium, and mainly aims to improve the accuracy of business approval.
In order to achieve the above object, the present invention provides a method for examining and approving services, which comprises:
receiving a service approval request, and collecting user information and service information of the service approval request;
constructing a user portrait according to the user information, and calculating a user credit score of the user portrait;
configuring the examination and approval logic and examination and approval mode of the service information, constructing a service wind control factor of the service information according to the examination and approval logic and examination and approval mode, and calculating the service authorization score of the service information according to the service wind control factor;
and calculating the final credit score of the service approval request according to the user credit score and the service authorization score, and generating an approval result of the service approval request according to the final credit score.
Optionally, the collecting the user information and the service information of the service approval request includes:
acquiring a request field of the service approval request, and identifying a service entity and a user entity of the service approval request according to the request field;
and acquiring the information of the service entity and the user entity by using a preset data acquisition mode to obtain user information and service information.
Optionally, the constructing a user representation according to the user information includes:
extracting feature data of the user information, and constructing a decision tree of the user according to the feature data;
calculating a negative gradient of user information in the decision tree;
and updating the decision tree according to the negative gradient until the decision tree tends to be stable, so as to obtain the user portrait of the user.
Optionally, the extracting feature data of the user information includes:
calculating an information weight value of each user data in the user information;
and screening out the user data with the information weight value larger than a preset weight value from the user data, and taking the screened user data as feature data.
Optionally, the calculating a user credit score for the user representation includes:
acquiring user historical data corresponding to the user portrait, and training a pre-constructed credit scoring model according to the user historical data to obtain a training credit scoring model;
and inputting the feature data in the user portrait into the training credit score model to output the credit score of the feature data in the user portrait so as to obtain the user credit score of the user portrait.
Optionally, the calculating, according to the service wind control factor, a service authorization score of the service information includes:
sequentially inquiring information fields in the service information according to the approval mode in the service wind control factor;
searching an information field meeting the approval logic of the business wind control factor from the information field, and calculating the ratio of the searched information field in the business information;
and determining the service authorization score of the service information according to the ratio.
Optionally, the generating an approval result of the service approval request according to the final credit score includes:
if the final credit score meets a preset first credit score interval, generating an approval result of the service approval request as approval passing;
if the preset second credit scoring interval is met, generating an approval result of the service approval request as that the approval is not passed;
and if the final credit score does not meet the preset first credit score interval and the preset second credit score interval, generating an approval result of the service approval request as to-be-approved manually.
In order to solve the above problem, the present invention further provides a service approval apparatus, including:
the information acquisition module is used for receiving a service approval request and acquiring user information and service information of the service approval request;
the score calculation module is used for constructing a user portrait according to the user information and calculating a user credit score of the user portrait;
the score calculating module is further used for configuring the approval logic and the approval mode of the service information, constructing a service wind control factor of the service information according to the approval logic and the approval mode, and calculating the service authorization score of the service information according to the service wind control factor;
and the service approval module is used for calculating a final credit score of the service approval request according to the user credit score and the service authorization score and generating an approval result of the service approval request according to the final credit score.
In order to solve the above problem, the present invention also provides an electronic device, including:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores a computer program executable by the at least one processor, the computer program being executable by the at least one processor to implement the business approval method described above.
In order to solve the above problem, the present invention further provides a computer-readable storage medium, in which at least one computer program is stored, and the at least one computer program is executed by a processor in an electronic device to implement the business approval method described above.
The embodiment of the invention firstly collects the user information and the service information of the service approval request, can identify the approval information in the service approval request, guarantees the realization premise of the subsequent service approval request, and constructs the user portrait by combining the user information, can visually know the user data relationship in the user information, improves the calculation speed of the subsequent data, calculates the user credit score of the user portrait, and can obtain the first approval basis of the service approval request; secondly, by constructing the business wind control factor of the business information, the embodiment of the invention can clarify the approval rule of the business information in the business process approval process and ensure that the business information can orderly realize business approval, thereby improving the approval accuracy of the business information, calculating the business authorization grade of the business information according to the business wind control factor, acquiring the second approval basis of the business approval request, and determining the credit state of the corresponding user and the business information based on the first approval basis and the second approval basis, thereby ensuring the accuracy of subsequent business approval; furthermore, in the embodiment of the present invention, a final credit score of the service approval request is calculated according to the user credit score and the service authorization score, and an approval result of the service approval request is generated according to the final credit score, so that excessive labor is prevented from participating in a process of service approval, and accuracy of service approval is further improved. Therefore, the business approval method, the business approval device, the electronic equipment and the computer readable storage medium provided by the invention can improve the accuracy of business approval.
Drawings
Fig. 1 is a schematic flow chart of a business approval method according to an embodiment of the present invention;
fig. 2 is a detailed flowchart illustrating a step in the business approval method provided in fig. 1 according to an embodiment of the present invention;
fig. 3 is a schematic block diagram of a service approval apparatus according to an embodiment of the present invention;
fig. 4 is a schematic internal structural diagram of an electronic device implementing a service approval method according to an embodiment of the present invention;
the implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The embodiment of the application provides a business approval method. The execution subject of the business approval method includes, but is not limited to, at least one of electronic devices, such as a server and a terminal, which can be configured to execute the method provided by the embodiment of the present application. In other words, the business approval method may be executed by software or hardware installed in the terminal device or the server device, and the software may be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like.
Referring to fig. 1, a schematic flow chart of a service approval method according to an embodiment of the present invention is shown. In the embodiment of the invention, the business approval method comprises the following steps:
and S1, receiving the service approval request, and collecting the user information and the service information of the service approval request.
In the embodiment of the invention, the service approval request is generated based on different application services, such as an enterprise loan application service, and further, the embodiment of the invention receives the service approval request through a service approval system (such as a loan approval system) to realize the approval of the service approval request, wherein the service approval system realizes a micro-service architecture through a spring closed framework, so that each approval node in the service approval system can be configured, and the service processing speed is improved.
Furthermore, the embodiment of the invention identifies the approval information in the service approval request by collecting the user information and the service information of the service approval request, thereby ensuring the premise of realizing the subsequent service approval request. Wherein the user information includes: personal credit investigation data, loan data, property data, running data and the like, wherein the service information comprises: business data, judicial data, public opinion data, upstream customer data, downstream customer data, financial data, and industry data, among others.
As an embodiment of the present invention, the collecting user information and service information of the service approval request includes: and acquiring a request field of the service approval request, identifying a service entity and a user entity of the service approval request according to the request field, and acquiring information of the service entity and the user entity by using a preset data acquisition mode to obtain user information and service information.
Wherein, the request field can be obtained through SQL query statement, if the business approval request is 'Xiaoming requires 20 thousands of loans', the corresponding request field includes: "Ming," "loan," and the like, it is to be understood that an entity is a business or concept definable in a system, and a business entity can be understood as a business concept definable in a system, such as "loan" described above can be a business entity, and a user entity can be understood as a character object definable in a system, such as "Ming" described above can be a user entity.
Further, in an optional embodiment of the present invention, the preset data acquisition manner includes: background database queries, such as sky-eye queries, for professional web pages; offline collection of service personnel; on-line collection of collection tools, such as crawler tools. Based on the data acquisition mode, the diversity of the sources of the user information and the service information can be realized, and the comprehensiveness of the user information and the service information is ensured, so that the approval accuracy of the subsequent user information and the service information is ensured.
S2, constructing the user portrait according to the user information, and calculating the user credit score of the user portrait.
It should be understood that the user information includes a large amount of user data, and each user data has a corresponding hierarchical relationship, such as a parallel and inclusion relationship, in order to further understand the association relationship of the user data in the user information, in the embodiment of the present invention, a user portrait is constructed according to the user information, so as to intuitively understand the relationship between the user data in the user information, and improve the calculation speed of subsequent data.
Referring to fig. 2, the constructing a user representation according to the user information includes:
s201, extracting characteristic data of the user information, and constructing a decision tree of a user according to the characteristic data;
s202, calculating a negative gradient of user information in the decision tree;
and S203, updating the decision tree according to the negative gradient until the user portrait of the user is obtained when the decision tree tends to be stable.
In an optional embodiment, the extracting the feature data of the user information includes: calculating an information weight value of each user data in the user information, screening the user data with the information weight value larger than a preset weight value from the user data, and taking the screened user data as feature data.
Further, in another optional embodiment of the present invention, the information weight value of each user data in the user information is calculated by using the following method:
wherein, CiInformation weight values representing user data, EiIndicating the ith user data in the user information, Ei TRepresents the eigenvector covariance of the ith user data in the user information, and trace () represents the spatial filter function.
In an optional embodiment, the decision tree algorithm includes an XGBoost algorithm, the negative gradient refers to a residual of the feature data, and by fitting the residual of the feature data, robustness and reliability of the entire decision tree may be enhanced.
Further, in another optional embodiment of the present invention, the negative gradient of the subscribed users in the decision tree is calculated by using the following method:
wherein r isimA negative gradient is indicated and the gradient is,
denotes the learning rate, L (y)i,f(xi) Represents the loss function, yiA predicted value f (x) representing the ith feature datai) Representing the true value of the ith feature data, f (x) representing the region function in the decision tree, fm-1(x)Representing the region fit function in the decision tree.
Furthermore, the embodiment of the invention calculates the user credit score of the user image to be used as an approval basis for evaluating the service approval request corresponding to the user, so as to determine the credit state of the corresponding user and improve the accuracy of subsequent service approval.
As an embodiment of the invention, the calculating the user credit score of the user representation comprises: acquiring user historical data corresponding to the user portrait, training a pre-constructed credit scoring model according to the user historical data to obtain a training credit scoring model, inputting the feature data in the user portrait into the training credit scoring model to output the credit score of the feature data in the user portrait and obtain the user credit score of the user portrait.
The pre-constructed credit scoring model can be constructed by algorithms based on logistic regression, decision trees, neural networks and the like, and it should be noted that the method takes the user historical data corresponding to the user portrait as the training data of the pre-constructed credit scoring model so as to improve the accuracy of calculating the credit score of the subsequent user portrait.
S3, configuring the examination and approval logic and examination and approval mode of the service information, constructing the service wind control factor of the service information according to the examination and approval logic and examination and approval mode, and calculating the service authorization score of the service information according to the service wind control factor.
In the embodiment of the present invention, the approval logic refers to an approval rule to be followed by the service information during the service approval process, for example, whether a data value is mandatory, whether a data filled letter is mandatory, and whether a data filled character length can exceed a preset threshold, and the approval mode refers to a method adopted by the service information during the service approval process, such as an advanced approval mode.
As an embodiment of the present invention, the configuring the approval logic and the approval mode of the service information includes: and acquiring the data attribute and the information field of the service information, and defining the approval logic of the information field and the approval mode of the information field according to the data attribute.
The data attribute may be understood as a data object feature of the service information, and is used to characterize a field type in the service information, including a nominal attribute, a binary attribute, an ordinal attribute, a numerical attribute, a discrete attribute, and the like. The definition of the approval logic and the approval mode of the information field is realized through a field configuration script, wherein the field configuration script can be compiled through a JavaScript scripting language.
Based on the configuration of the approval logic and the approval mode, the approval rule of the business information in the business process approval process can be determined, and business approval can be realized orderly by guaranteeing the business information, so that the approval accuracy of the business information can be improved.
As an embodiment of the present invention, the constructing a service wind control factor of the service information according to the approval logic and the approval method includes: and acquiring a logic configuration packet of the approval logic and a mode configuration packet of the approval mode, packaging and encrypting the logic configuration packet and the mode configuration packet to generate an encrypted configuration packet, and generating a service wind control factor of the service information according to the encrypted configuration packet.
The logic configuration package and the mode configuration package may be understood as a software package (such as a jar package) of the approval logic and the approval mode in the configuration process, the encryption of the logic configuration package and the mode configuration package may be implemented by a self-defined encryption algorithm of a packaging function in a Java language, for example, an MD5 encryption algorithm is added to a function packaging function to implement that the encryption configuration package only provides a call interface to the outside, so as to ensure data privacy in the encryption configuration package, the service wind control factor refers to an approval policy of the service information in the service approval process, and the service wind control factor may be implemented by loading the encryption configuration package in a wind control component.
Further, the embodiment of the present invention calculates the service authorization score of the service information according to the service wind control factor, and the service authorization score is used as an approval basis for evaluating the service approval request corresponding to the service information to determine the credit state of the corresponding service information.
As an embodiment of the present invention, the calculating a service authorization score of the service information according to the service wind control factor includes: and sequentially inquiring information fields in the service information according to the approval mode in the service wind control factor, searching the information fields meeting the approval logic of the service wind control factor from the information fields, calculating the proportion of the searched information fields in the service information, and determining the service authorization score of the service information according to the proportion.
And S4, calculating a final credit score of the service approval request according to the user credit score and the service authorization score, and generating an approval result of the service approval request according to the final credit score.
In the embodiment of the invention, the final credit score of the service approval request is calculated according to the user credit score and the service authorization score, that is, the user credit score and the service authorization score are subjected to weighted average to obtain the final credit score of the service approval request. For example, if the user credit score is 80 points and the service authorization score is 70 points, the final credit score of the service approval request may be obtained as: 80+70/2 is 75 points.
Further, the generating an approval result of the service approval request according to the final credit score includes: if the final credit score meets a preset first credit score interval, generating an approval result of the service approval request as approval passing, if the final credit score meets a preset second credit score interval, generating an approval result of the service approval request as approval failing, and if the final credit score does not meet the preset first credit score interval and the preset second credit score interval, generating the approval result of the service approval request as pending manual approval.
The credit scoring interval is set based on the total scoring interval of the service approval, if the total scoring interval of the service approval is 0-100 points, the preset first credit scoring interval may be 90-100 points, the preset second credit scoring interval is 0-60 points, and it should be noted that the preset first credit scoring interval and the preset second credit scoring interval may also be set according to an actual service scene.
Further, to ensure privacy and security of the final credit score, the final credit score may also be stored in a blockchain node.
The embodiment of the invention firstly collects the user information and the service information of the service approval request, can identify the approval information in the service approval request, guarantees the realization premise of the subsequent service approval request, and constructs the user portrait by combining the user information, can visually know the user data relationship in the user information, improves the calculation speed of the subsequent data, calculates the user credit score of the user portrait, and can obtain the first approval basis of the service approval request; secondly, by constructing the business wind control factor of the business information, the embodiment of the invention can clarify the approval rule of the business information in the business process approval process and ensure that the business information can orderly realize business approval, thereby improving the approval accuracy of the business information, calculating the business authorization grade of the business information according to the business wind control factor, acquiring the second approval basis of the business approval request, and determining the credit state of the corresponding user and the business information based on the first approval basis and the second approval basis, thereby ensuring the accuracy of subsequent business approval; furthermore, in the embodiment of the present invention, a final credit score of the service approval request is calculated according to the user credit score and the service authorization score, and an approval result of the service approval request is generated according to the final credit score, so that excessive labor is prevented from participating in a process of service approval, and accuracy of service approval is further improved. Therefore, the business approval method provided by the invention can improve the accuracy of business approval.
Fig. 3 is a functional block diagram of the apparatus for approval of business according to the present invention.
The business approval apparatus 100 of the present invention may be installed in an electronic device. According to the realized function, the business approval device may include an information collection module 101, a score calculation module 102, and a business approval module 103. The module, which may also be referred to as a unit, refers to a series of computer program segments that can be executed by a processor of the electronic device 1 and that can perform a fixed function, and that are stored in a memory of the electronic device 1.
In the present embodiment, the functions regarding the respective modules/units are as follows:
the information collection module 101 is configured to receive a service approval request, and collect user information and service information of the service approval request.
In the embodiment of the invention, the service approval request is generated based on different application services, such as an enterprise loan application service, and further, the embodiment of the invention receives the service approval request through a service approval system (such as a loan approval system) to realize the approval of the service approval request, wherein the service approval system realizes a micro-service architecture through a spring closed framework, so that each approval node in the service approval system can be configured, and the service processing speed is improved.
Furthermore, the embodiment of the invention identifies the approval information in the service approval request by collecting the user information and the service information of the service approval request, thereby ensuring the premise of realizing the subsequent service approval request. Wherein the user information includes: personal credit investigation data, loan data, property data, running data and the like, wherein the service information comprises: business data, judicial data, public opinion data, upstream customer data, downstream customer data, financial data, and industry data, among others.
As an embodiment of the present invention, the information collecting module 101 collects the user information and the service information of the service approval request, and executes the following steps: and acquiring a request field of the service approval request, identifying a service entity and a user entity of the service approval request according to the request field, and acquiring information of the service entity and the user entity by using a preset data acquisition mode to obtain user information and service information.
Wherein, the request field can be obtained through SQL query statement, if the business approval request is 'Xiaoming requires 20 thousands of loans', the corresponding request field includes: "Ming," "loan," and the like, it is to be understood that an entity is a business or concept definable in a system, and a business entity can be understood as a business concept definable in a system, such as "loan" described above can be a business entity, and a user entity can be understood as a character object definable in a system, such as "Ming" described above can be a user entity.
Further, in an optional embodiment of the present invention, the preset data acquisition manner includes: background database queries, such as sky-eye queries, for professional web pages; offline collection of service personnel; on-line collection of collection tools, such as crawler tools. Based on the data acquisition mode, the diversity of the sources of the user information and the service information can be realized, and the comprehensiveness of the user information and the service information is ensured, so that the approval accuracy of the subsequent user information and the service information is ensured.
The score calculating module 102 is configured to construct a user portrait according to the user information, and calculate a user credit score of the user portrait.
It should be understood that the user information includes a large amount of user data, and each user data has a corresponding hierarchical relationship, such as a parallel and inclusion relationship, in order to further understand the association relationship of the user data in the user information, in the embodiment of the present invention, a user portrait is constructed according to the user information, so as to intuitively understand the relationship between the user data in the user information, and improve the calculation speed of subsequent data.
As an embodiment of the present invention, the user representation is constructed according to the user information, and the score calculating module 102 performs the following steps: extracting feature data of the user information, and constructing a decision tree of the user according to the feature data; calculating a negative gradient of user information in the decision tree; and updating the decision tree according to the negative gradient until the decision tree tends to be stable, so as to obtain the user portrait of the user.
In an optional embodiment, the extracting the feature data of the user information is performed by the score calculating module 102 in the following manner: calculating an information weight value of each user data in the user information, screening the user data with the information weight value larger than a preset weight value from the user data, and taking the screened user data as feature data.
Further, in another optional embodiment of the present invention, the score calculating module 102 calculates an information weight value of each user data in the user information by using the following method:
wherein, CiInformation weight values representing user data, EiRepresents the ith user data in the user information,
represents the eigenvector covariance of the ith user data in the user information, and trace () represents the spatial filter function.
In an optional embodiment, the decision tree algorithm includes an XGBoost algorithm, the negative gradient refers to a residual of the feature data, and by fitting the residual of the feature data, robustness and reliability of the entire decision tree may be enhanced.
Further, in another optional embodiment of the present invention, the score calculating module 102 calculates a negative gradient of the subscribed users in the decision tree by using the following method:
wherein r isimA negative gradient is indicated and the gradient is,
denotes the learning rate, L (y)i,f(xi) Represents the loss function, yiA predicted value f (x) representing the ith feature datai) Representing the true value of the ith feature data, f (x) representing the region function in the decision tree, fm-1(x)Representing the region fit function in the decision tree.
Furthermore, the embodiment of the invention calculates the user credit score of the user image to be used as an approval basis for evaluating the service approval request corresponding to the user, so as to determine the credit state of the corresponding user and improve the accuracy of subsequent service approval.
As an embodiment of the present invention, the calculating the user credit score of the user representation is performed by the score calculating module 102 in the following manner: acquiring user historical data corresponding to the user portrait, training a pre-constructed credit scoring model according to the user historical data to obtain a training credit scoring model, inputting the feature data in the user portrait into the training credit scoring model to output the credit score of the feature data in the user portrait and obtain the user credit score of the user portrait.
The pre-constructed credit scoring model can be constructed by algorithms based on logistic regression, decision trees, neural networks and the like, and it should be noted that the method takes the user historical data corresponding to the user portrait as the training data of the pre-constructed credit scoring model so as to improve the accuracy of calculating the credit score of the subsequent user portrait.
The score calculating module 102 is further configured to configure an approval logic and an approval mode of the service information, construct a service wind control factor of the service information according to the approval logic and the approval mode, and calculate a service authorization score of the service information according to the service wind control factor.
In the embodiment of the present invention, the approval logic refers to an approval rule to be followed by the service information during the service approval process, for example, whether a data value is mandatory, whether a data filled letter is mandatory, and whether a data filled character length can exceed a preset threshold, and the approval mode refers to a method adopted by the service information during the service approval process, such as an advanced approval mode.
As an embodiment of the present invention, the configuration of the approval logic and the approval mode of the service information, the score calculating module 102 is executed in the following manner: and acquiring the data attribute and the information field of the service information, and defining the approval logic of the information field and the approval mode of the information field according to the data attribute.
The data attribute may be understood as a data object feature of the service information, and is used to characterize a field type in the service information, including a nominal attribute, a binary attribute, an ordinal attribute, a numerical attribute, a discrete attribute, and the like. The definition of the approval logic and the approval mode of the information field is realized through a field configuration script, wherein the field configuration script can be compiled through a JavaScript scripting language.
Based on the configuration of the approval logic and the approval mode, the approval rule of the business information in the business process approval process can be determined, and business approval can be realized orderly by guaranteeing the business information, so that the approval accuracy of the business information can be improved.
As an embodiment of the present invention, the service wind control factor of the service information is constructed according to the approval logic and the approval method, and the score calculating module 102 is executed in the following manner: and acquiring a logic configuration packet of the approval logic and a mode configuration packet of the approval mode, packaging and encrypting the logic configuration packet and the mode configuration packet to generate an encrypted configuration packet, and generating a service wind control factor of the service information according to the encrypted configuration packet.
The logic configuration package and the mode configuration package may be understood as a software package (such as a jar package) of the approval logic and the approval mode in the configuration process, the encryption of the logic configuration package and the mode configuration package may be implemented by a self-defined encryption algorithm of a packaging function in a Java language, for example, an MD5 encryption algorithm is added to a function packaging function to implement that the encryption configuration package only provides a call interface to the outside, so as to ensure data privacy in the encryption configuration package, the service wind control factor refers to an approval policy of the service information in the service approval process, and the service wind control factor may be implemented by loading the encryption configuration package in a wind control component.
Further, the embodiment of the present invention calculates the service authorization score of the service information according to the service wind control factor, and the service authorization score is used as an approval basis for evaluating the service approval request corresponding to the service information to determine the credit state of the corresponding service information.
As an embodiment of the present invention, the service authorization score of the service information is calculated according to the service wind control factor, and the score calculating module 102 performs the following steps: and sequentially inquiring information fields in the service information according to the approval mode in the service wind control factor, searching the information fields meeting the approval logic of the service wind control factor from the information fields, calculating the proportion of the searched information fields in the service information, and determining the service authorization score of the service information according to the proportion.
The service approval module 103 is configured to calculate a final credit score of the service approval request according to the user credit score and the service authorization score, and generate an approval result of the service approval request according to the final credit score.
In the embodiment of the invention, the final credit score of the service approval request is calculated according to the user credit score and the service authorization score, that is, the user credit score and the service authorization score are subjected to weighted average to obtain the final credit score of the service approval request. For example, if the user credit score is 80 points and the service authorization score is 70 points, the final credit score of the service approval request may be obtained as: 80+70/2 is 75 points.
Further, the approval result of the service approval request is generated according to the final credit score, and the service approval module 103 is executed in the following manner: if the final credit score meets a preset first credit score interval, generating an approval result of the service approval request as approval passing, if the final credit score meets a preset second credit score interval, generating an approval result of the service approval request as approval failing, and if the final credit score does not meet the preset first credit score interval and the preset second credit score interval, generating the approval result of the service approval request as pending manual approval.
The credit scoring interval is set based on the total scoring interval of the service approval, if the total scoring interval of the service approval is 0-100 points, the preset first credit scoring interval may be 90-100 points, the preset second credit scoring interval is 0-60 points, and it should be noted that the preset first credit scoring interval and the preset second credit scoring interval may also be set according to an actual service scene.
Further, to ensure privacy and security of the final credit score, the final credit score may also be stored in a blockchain node.
The embodiment of the invention firstly collects the user information and the service information of the service approval request, can identify the approval information in the service approval request, guarantees the realization premise of the subsequent service approval request, and constructs the user portrait by combining the user information, can visually know the user data relationship in the user information, improves the calculation speed of the subsequent data, calculates the user credit score of the user portrait, and can obtain the first approval basis of the service approval request; secondly, by constructing the business wind control factor of the business information, the embodiment of the invention can clarify the approval rule of the business information in the business process approval process and ensure that the business information can orderly realize business approval, thereby improving the approval accuracy of the business information, calculating the business authorization grade of the business information according to the business wind control factor, acquiring the second approval basis of the business approval request, and determining the credit state of the corresponding user and the business information based on the first approval basis and the second approval basis, thereby ensuring the accuracy of subsequent business approval; furthermore, in the embodiment of the present invention, a final credit score of the service approval request is calculated according to the user credit score and the service authorization score, and an approval result of the service approval request is generated according to the final credit score, so that excessive labor is prevented from participating in a process of service approval, and accuracy of service approval is further improved. Therefore, the business approval device provided by the invention can improve the accuracy of business approval.
Fig. 4 is a schematic structural diagram of an electronic device 1 implementing the business approval method according to the present invention.
The electronic device 1 may comprise a processor 10, a memory 11, a communication bus 12 and a communication interface 13, and may further comprise a computer program, such as a business approval program, stored in the memory 11 and executable on the processor 10.
In some embodiments, the processor 10 may be composed of an integrated circuit, for example, a single packaged integrated circuit, or may be composed of a plurality of integrated circuits packaged with the same function or different functions, and includes one or more Central Processing Units (CPUs), a microprocessor, a digital Processing chip, a graphics processor, a combination of various control chips, and the like. The processor 10 is a Control Unit (Control Unit) of the electronic device 1, connects various components of the electronic device 1 by using various interfaces and lines, and executes various functions and processes data of the electronic device 1 by running or executing programs or modules (e.g., executing a service approval program) stored in the memory 11 and calling data stored in the memory 11.
The memory 11 includes at least one type of readable storage medium including flash memory, removable hard disks, multimedia cards, card-type memory (e.g., SD or DX memory, etc.), magnetic memory, magnetic disks, optical disks, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device 1, such as a removable hard disk of the electronic device 1. The memory 11 may also be an external storage device of the electronic device 1 in other embodiments, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the electronic device 1. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device 1. The memory 11 may be used not only to store application software installed in the electronic device 1 and various types of data, such as codes of business approval programs, but also to temporarily store data that has been output or will be output.
The communication bus 12 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is arranged to enable connection communication between the memory 11 and at least one processor 10 or the like.
The communication interface 13 is used for communication between the electronic device 1 and other devices, and includes a network interface and a user interface. Optionally, the network interface may include a wired interface and/or a wireless interface (e.g., WI-FI interface, bluetooth interface, etc.), which are generally used for establishing a communication connection between the electronic device 1 and other electronic devices 1. The user interface may be a Display (Display), an input unit such as a Keyboard (Keyboard), and optionally a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, or the like. The display, which may also be referred to as a display screen or display unit, is suitable for displaying information processed in the electronic device 1 and for displaying a visualized user interface, among other things.
Fig. 4 only shows the electronic device 1 with components, and it will be understood by those skilled in the art that the structure shown in fig. 4 does not constitute a limitation of the electronic device 1, and may comprise fewer or more components than those shown, or some components may be combined, or a different arrangement of components.
For example, although not shown, the electronic device 1 may further include a power supply (such as a battery) for supplying power to each component, and preferably, the power supply may be logically connected to the at least one processor 10 through a power management device, so as to implement functions of charge management, discharge management, power consumption management, and the like through the power management device. The power supply may also include any component of one or more dc or ac power sources, recharging devices, power failure detection circuitry, power converters or inverters, power status indicators, and the like. The electronic device 1 may further include various sensors, a bluetooth module, a Wi-Fi module, and the like, which are not described herein again.
It is to be understood that the described embodiments are for purposes of illustration only and that the scope of the appended claims is not limited to such structures.
The business approval program stored in the memory 11 of the electronic device 1 is a combination of a plurality of computer programs, and when running in the processor 10, can realize:
receiving a service approval request, and collecting user information and service information of the service approval request;
constructing a user portrait according to the user information, and calculating a user credit score of the user portrait;
configuring the examination and approval logic and examination and approval mode of the service information, constructing a service wind control factor of the service information according to the examination and approval logic and examination and approval mode, and calculating the service authorization score of the service information according to the service wind control factor;
and calculating the final credit score of the service approval request according to the user credit score and the service authorization score, and generating an approval result of the service approval request according to the final credit score.
Specifically, the processor 10 may refer to the description of the relevant steps in the embodiment corresponding to fig. 1 for a specific implementation method of the computer program, which is not described herein again.
Further, the integrated modules/units of the electronic device 1, if implemented in the form of software functional units and sold or used as separate products, may be stored in a non-volatile computer-readable storage medium. The computer readable storage medium may be volatile or non-volatile. For example, the computer-readable medium may include: any entity or device capable of carrying said computer program code, recording medium, U-disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM).
The present invention also provides a computer-readable storage medium, storing a computer program which, when executed by a processor of an electronic device 1, may implement:
receiving a service approval request, and collecting user information and service information of the service approval request;
constructing a user portrait according to the user information, and calculating a user credit score of the user portrait;
configuring the examination and approval logic and examination and approval mode of the service information, constructing a service wind control factor of the service information according to the examination and approval logic and examination and approval mode, and calculating the service authorization score of the service information according to the service wind control factor;
and calculating the final credit score of the service approval request according to the user credit score and the service authorization score, and generating an approval result of the service approval request according to the final credit score.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method can be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof.
The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
The block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.
Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the system claims may also be implemented by one unit or means in software or hardware. The terms second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (10)
1. A business approval method, the method comprising:
receiving a service approval request, and collecting user information and service information of the service approval request;
constructing a user portrait according to the user information, and calculating a user credit score of the user portrait;
configuring the examination and approval logic and examination and approval mode of the service information, constructing a service wind control factor of the service information according to the examination and approval logic and examination and approval mode, and calculating the service authorization score of the service information according to the service wind control factor;
and calculating the final credit score of the service approval request according to the user credit score and the service authorization score, and generating an approval result of the service approval request according to the final credit score.
2. The business approval method of claim 1, wherein the collecting user information and business information of the business approval request comprises:
acquiring a request field of the service approval request, and identifying a service entity and a user entity of the service approval request according to the request field;
and acquiring the information of the service entity and the user entity by using a preset data acquisition mode to obtain user information and service information.
3. The business approval method of claim 1, wherein said constructing a user representation from said user information comprises:
extracting feature data of the user information, and constructing a decision tree of the user according to the feature data;
calculating a negative gradient of user information in the decision tree;
and updating the decision tree according to the negative gradient until the decision tree tends to be stable, so as to obtain the user portrait of the user.
4. The business approval method of claim 3, wherein the extracting the feature data of the user information comprises:
calculating an information weight value of each user data in the user information;
and screening out the user data with the information weight value larger than a preset weight value from the user data, and taking the screened user data as feature data.
5. The business approval method of claim 1, wherein said calculating a user credit score for said user representation comprises:
acquiring user historical data corresponding to the user portrait, and training a pre-constructed credit scoring model according to the user historical data to obtain a training credit scoring model;
and inputting the feature data in the user portrait into the training credit score model to output the credit score of the feature data in the user portrait so as to obtain the user credit score of the user portrait.
6. The business approval method of claim 1, wherein the calculating a business authorization score of the business information according to the business wind control factor comprises:
sequentially inquiring information fields in the service information according to the approval mode in the service wind control factor;
searching an information field meeting the approval logic of the business wind control factor from the information field, and calculating the ratio of the searched information field in the business information;
and determining the service authorization score of the service information according to the ratio.
7. The business approval method of any one of claims 1 to 6, wherein the generating of the approval result of the business approval request according to the final credit score comprises:
if the final credit score meets a preset first credit score interval, generating an approval result of the service approval request as approval passing;
if the preset second credit scoring interval is met, generating an approval result of the service approval request as that the approval is not passed;
and if the final credit score does not meet the preset first credit score interval and the preset second credit score interval, generating an approval result of the service approval request as to-be-approved manually.
8. A business approval apparatus, comprising:
the information acquisition module is used for receiving a service approval request and acquiring user information and service information of the service approval request;
the score calculation module is used for constructing a user portrait according to the user information and calculating a user credit score of the user portrait;
the score calculating module is further used for configuring the approval logic and the approval mode of the service information, constructing a service wind control factor of the service information according to the approval logic and the approval mode, and calculating the service authorization score of the service information according to the service wind control factor;
and the service approval module is used for calculating a final credit score of the service approval request according to the user credit score and the service authorization score and generating an approval result of the service approval request according to the final credit score.
9. An electronic device, characterized in that the electronic device comprises:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the business approval method of any one of claims 1 to 7.
10. A computer-readable storage medium, storing a computer program, wherein the computer program, when executed by a processor, implements a business approval method according to any one of claims 1 to 7.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107767263A (en) * | 2017-08-10 | 2018-03-06 | 深圳前海达飞金融服务有限公司 | A kind of measures and procedures for the examination and approval of consumptive credit, device and server |
| CN108090829A (en) * | 2017-12-21 | 2018-05-29 | 深圳市买买提信息科技有限公司 | A kind of data managing method, data administrator and electronic equipment |
| CN109670835A (en) * | 2018-09-25 | 2019-04-23 | 深圳壹账通智能科技有限公司 | Air control method, apparatus, equipment and readable storage medium storing program for executing based on service node |
| CN111340616A (en) * | 2020-03-10 | 2020-06-26 | 中国建设银行股份有限公司 | Method, device, equipment and medium for approving online loan |
| CN111507831A (en) * | 2020-05-29 | 2020-08-07 | 长安汽车金融有限公司 | Credit risk automatic assessment method and device |
| CN111861174A (en) * | 2020-07-09 | 2020-10-30 | 北京睿知图远科技有限公司 | Credit assessment method for user portrait |
| CN112016796A (en) * | 2020-07-15 | 2020-12-01 | 北京淇瑀信息科技有限公司 | Comprehensive risk scoring request processing method and device and electronic equipment |
| CN112581227A (en) * | 2020-12-22 | 2021-03-30 | 平安银行股份有限公司 | Product recommendation method and device, electronic equipment and storage medium |
-
2021
- 2021-06-30 CN CN202110736075.6A patent/CN113362039A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107767263A (en) * | 2017-08-10 | 2018-03-06 | 深圳前海达飞金融服务有限公司 | A kind of measures and procedures for the examination and approval of consumptive credit, device and server |
| CN108090829A (en) * | 2017-12-21 | 2018-05-29 | 深圳市买买提信息科技有限公司 | A kind of data managing method, data administrator and electronic equipment |
| CN109670835A (en) * | 2018-09-25 | 2019-04-23 | 深圳壹账通智能科技有限公司 | Air control method, apparatus, equipment and readable storage medium storing program for executing based on service node |
| CN111340616A (en) * | 2020-03-10 | 2020-06-26 | 中国建设银行股份有限公司 | Method, device, equipment and medium for approving online loan |
| CN111507831A (en) * | 2020-05-29 | 2020-08-07 | 长安汽车金融有限公司 | Credit risk automatic assessment method and device |
| CN111861174A (en) * | 2020-07-09 | 2020-10-30 | 北京睿知图远科技有限公司 | Credit assessment method for user portrait |
| CN112016796A (en) * | 2020-07-15 | 2020-12-01 | 北京淇瑀信息科技有限公司 | Comprehensive risk scoring request processing method and device and electronic equipment |
| CN112581227A (en) * | 2020-12-22 | 2021-03-30 | 平安银行股份有限公司 | Product recommendation method and device, electronic equipment and storage medium |
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