CN111178744A - Distribution method, device, equipment and storage medium - Google Patents
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Abstract
The invention provides a distribution method, a device, equipment and a storage medium, wherein the method comprises the steps of receiving a resource distribution request sent by a resource application party; acquiring related data of the resource application party based on the resource allocation request of the resource application party; the related data of the resource application party comprises one or more of judicial data, industrial and commercial data, credit investigation data, tax data and bank data; determining a comprehensive rating of the resource applicant based on the relevant data of the resource applicant; performing resource allocation based on the comprehensive rating of the resource applicant; comprehensive rating of the resource application party, and finally, resource allocation is carried out according to the comprehensive rating of the resource application party; the comprehensive rating of the resource application party is determined based on the related data of the resource application party, and resource allocation is further performed based on the comprehensive rating of the resource application party, so that no manual participation is caused, and the resource allocation result is more accurate and objective.
Description
Technical Field
The present invention relates to the field of resource allocation technologies, and in particular, to an allocation method, an allocation apparatus, a device, and a storage medium.
Background
After receiving a resource allocation request of a resource application party, the existing resource allocation service mainly depends on the human-sea tactics to investigate the utilization capacity of the service resource application party on resources and analyzes through the experience and judgment of people in order to ensure the safety of resource allocation, and has the problem of strong subjectivity.
Disclosure of Invention
In view of the above, the present invention provides an allocation method, an apparatus, a device and a storage medium to solve the problem of strong subjectivity in resource allocation.
In view of the above object, a first aspect of the present invention provides an allocation method, including:
receiving a resource allocation request sent by a resource application party;
acquiring related data of the resource application party based on the resource allocation request of the resource application party; the related data of the resource application party comprises one or more of judicial data, industrial and commercial data, credit investigation data, tax data and bank data;
determining a comprehensive rating of the resource applicant based on the relevant data of the resource applicant;
and performing resource allocation based on the comprehensive rating of the resource applicant.
Optionally, the relevant data of the resource applicant comprises a first index data set, a second index data set and a third index data set;
the determining a comprehensive rating of the resource applicant based on the relevant data of the resource applicant comprises:
analyzing the related data of the resource applicant to obtain the first index data set, the second index data set and the third index data set;
determining a first rating based on the first set of metric data;
determining a second rating based on the first rating and the second set of metric data;
determining a composite rating for the resource applicant based on the second rating and the third set of metrics data.
Optionally, said determining a first rating based on said first set of metric data comprises:
respectively determining the weight and the score corresponding to each index data contained in the first index data set;
determining a first score based on the weight and the score corresponding to each index data contained in the first index data set;
and determining a first rating based on the first score according to a preset first mapping relation.
Optionally, said determining a second rating based on said first rating and said second set of metric data comprises:
respectively determining the weight and the score corresponding to each index data contained in the first rating and the second index data set;
determining a second score based on the first rating and the weight and the score corresponding to each index data contained in the second index data set;
and determining a second rating based on the second score according to a preset second mapping relation.
Optionally, the determining a composite rating of the resource applicant based on the second rating and the third set of metrics data comprises:
determining weights and scores corresponding to the second rating and the index data contained in the third index data set respectively;
determining a comprehensive score of the resource applicant based on the second rating and the weight and the score corresponding to each index data contained in the third index data set;
and determining the comprehensive rating of the resource applicant based on the comprehensive rating of the resource applicant according to a preset third mapping relation.
With the same object in mind, a second aspect of the present invention provides a dispensing device, the device comprising:
the receiving module is used for receiving a resource allocation request sent by a resource application party;
a related data acquisition module, configured to acquire related data of the resource applicant based on the resource allocation request of the resource applicant; the related data of the resource application party comprises one or more of judicial data, industrial and commercial data, credit investigation data, tax data and bank data;
the comprehensive rating determining module is used for determining the comprehensive rating of the resource applicant based on the related data of the resource applicant;
and the resource allocation module is used for allocating resources based on the comprehensive rating of the resource applicant.
Optionally, the relevant data of the resource applicant comprises a first index data set, a second index data set and a third index data set;
a composite rating determination module comprising:
a related data analysis unit, configured to analyze related data of the resource applicant to obtain the first index data set, the second index data set, and the third index data set;
a first rating determination unit for determining a first rating based on the first index data set;
a second rating determination unit for determining a second rating based on the first rating and the second index data set;
and the comprehensive rating determining unit is used for determining the comprehensive rating of the resource applicant based on the second rating and the third index data set.
Optionally, the first rating determining unit is specifically configured to:
respectively determining the weight and the score corresponding to each index data contained in the first index data set;
determining a first score based on the weight and the score corresponding to each index data contained in the first index data set;
and determining a first rating based on the first score according to a preset first mapping relation.
Optionally, the second rating determining unit is specifically configured to:
respectively determining the weight and the score corresponding to each index data contained in the first rating and the second index data set;
determining a second score based on the first rating and the weight and the score corresponding to each index data contained in the second index data set;
and determining a second rating based on the second score according to a preset second mapping relation.
Optionally, the comprehensive rating determining unit is specifically configured to:
determining weights and scores corresponding to the second rating and the index data contained in the third index data set respectively;
determining a comprehensive score of the resource applicant based on the second rating and the weight and the score corresponding to each index data contained in the third index data set;
and determining the comprehensive rating of the resource applicant based on the comprehensive rating of the resource applicant according to a preset third mapping relation.
With the same objects in view, the third aspect of the present invention also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the method according to any one of the first aspect of the present invention when executing the program.
For the same purpose, the fourth aspect of the present invention also provides a non-transitory computer-readable storage medium storing computer instructions for causing the computer to perform the method according to any one of the first aspect of the present invention.
As can be seen from the above, the allocation method, apparatus, device and storage medium provided by the present invention receive the resource allocation request of the resource applicant, obtain the relevant data of the resource applicant based on the resource allocation request, then determine the comprehensive rating of the resource applicant based on the obtained relevant data of the resource applicant, and finally perform resource allocation according to the comprehensive rating of the resource applicant; the comprehensive rating of the resource application party is determined based on the related data of the resource application party, and resource allocation is further performed based on the comprehensive rating of the resource application party, so that no manual participation is caused, and the resource allocation result is more accurate and objective.
Furthermore, the method adopts two-layer progressive rating when rating the resource applicant, determines a first rating according to the first index data set, then determines a second rating according to the first rating and the second index data set, and finally determines the comprehensive rating of the resource applicant according to the second rating and the third index data set; therefore, the secondary rating result depends on the primary rating result, the comprehensive rating result of the resource applicant depends on the secondary rating result, and the comprehensive rating result of the resource applicant is corrected by adding multiple layers and multiple factors, so that the accuracy and the authenticity of the comprehensive rating result of the resource applicant are improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of a distribution method according to an embodiment of the present invention;
fig. 2 is an explanation of step S03;
FIG. 3 is a schematic structural diagram of a dispensing device according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a more specific hardware structure of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to specific embodiments and the accompanying drawings.
It is to be noted that technical terms or scientific terms used in the embodiments of the present invention should have the ordinary meanings as understood by those having ordinary skill in the art to which the present disclosure belongs, unless otherwise defined. The use of "first," "second," and similar terms in this disclosure is not intended to indicate any order, quantity, or importance, but rather is used to distinguish one element from another. The word "comprising" or "comprises", and the like, means that the element or item listed before the word covers the element or item listed after the word and its equivalents, but does not exclude other elements or items. The terms "connected" or "coupled" and the like are not restricted to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "upper", "lower", "left", "right", and the like are used merely to indicate relative positional relationships, and when the absolute position of the object being described is changed, the relative positional relationships may also be changed accordingly.
After receiving a resource allocation request of a resource application party, the existing resource allocation service mainly depends on the human-sea tactics to investigate the utilization capacity of the service resource application party on resources and analyzes through the experience and judgment of people in order to ensure the safety of resource allocation, and has the problem of strong subjectivity.
Currently, when rating is performed on resource applicants, models such as expert scoring cards or logistic regression are mainly adopted to calculate each index value to obtain a score of the resource applicants, the scores are subjected to box separation to obtain each risk rating, all the resource applicants perform evaluation through the same scoring rating system, and the obtained score and the rating are applied to subsequent resource allocation.
The resource application parties are graded and graded by the same grading card, and the difference of the resource application parties is large, so that the grading result is only effective for part of customers and the results of other customers are distorted.
In order to solve the above problems, the present invention provides an allocation method, which receives a resource allocation request from a resource applicant, obtains relevant data of the resource applicant based on the resource allocation request, determines a comprehensive rating of the resource applicant based on the obtained relevant data of the resource applicant, and finally performs resource allocation according to the comprehensive rating of the resource applicant. The method can be applied to various electronic devices such as mobile phones and tablet computers, and is not limited specifically. The resource mentioned in the method may be a credit resource, and the service mentioned may be a credit service, and is not limited specifically. The scoring method will be described in detail later by taking a credit service as an example.
For ease of understanding, the dispensing method is described in detail below with reference to the accompanying drawings.
Fig. 1 is a schematic flow chart of an allocation method according to an embodiment of the present invention, where the method includes:
and S01, receiving the resource allocation request sent by the resource application party.
In the embodiment of the present invention, in order to apply for resource allocation to a resource allocation party, a resource allocation request may be first sent, and an electronic device (hereinafter referred to as the present electronic device) executing the method receives the resource allocation request sent by the resource application party.
The details will be described by taking a credit service as an example. The resource is credit resource, the resource allocation request is credit request, the resource applicant is credit applicant, and the resource allocation formula is credit operator.
Credit, i.e., credit loan; the credit operator is the party providing the credit application to the credit application party; for example, the credit operator may be a bank or a qualified regular credit operator outside the bank, and the like, without limitation. The credit applicant is the party who applies for the credit loan to the credit operator, for example, the credit applicant may be an individual or a business, etc., and is not limited in particular.
In practical applications, the electronic device receives a credit request after a credit applicant proposes a credit application.
S02, acquiring the relevant data of the resource application party based on the resource allocation request of the resource application party; the related data of the resource application party comprises one or more of judicial data, industrial and commercial data, credit investigation data, tax data and bank data.
In the embodiment of the invention, in order to objectively and comprehensively evaluate the resource application party, after receiving the resource allocation request of the resource application party, the relevant data of the resource application party can be obtained from the relevant data source based on the resource allocation request; the relevant data includes one or more of tax data, jurisdictional data, industry and commerce data, credit investigation data and banking data. In practical applications, the relevant data sources may include tax authorities, banks, and third party data platforms.
In one case, the resource allocation request may include authorization information of the resource applicant, the electronic device may obtain authorization information of the resource applicant when receiving the resource allocation request of the resource applicant, and the electronic device may obtain related data of the resource applicant based on the authorization information of the resource applicant.
The detailed description will be continued by taking the credit service as an example. After the electronic equipment receives the credit request of the credit applicant, one or more of tax data, industrial and commercial data, credit investigation data, judicial data and bank data of the credit applicant can be acquired by data sources such as a tax bureau, a bank, a third-party data platform and the like based on the credit request.
And S03, determining the comprehensive rating of the resource applicant based on the related data of the resource applicant.
In the embodiment of the invention, after the relevant data of the resource applicant is obtained, the comprehensive rating of the resource applicant can be further determined based on the relevant data of the resource applicant.
The process of determining the comprehensive rating of the resource applicant based on the related data of the resource applicant will be described in detail later, and will not be described herein again.
The detailed description will be continued by taking the credit service as an example. After the electronic equipment receives the relevant data of the credit applicant, the comprehensive rating of the credit applicant can be further determined based on the relevant data of the credit applicant.
And S04, performing resource allocation based on the comprehensive rating of the resource applicant.
In the embodiment of the invention, after the comprehensive rating of the resource applicant is obtained, the resource can be distributed based on the comprehensive rating result of the resource applicant.
In practical application, when resource allocation is performed, resource allocation quota and execution interest rate for a resource applicant can be determined based on a comprehensive rating result of the resource applicant, and the determination is not limited specifically.
The detailed description will be continued by taking the credit service as an example. After determining the comprehensive rating of the credit applicant, information such as a credit line and a credit interest rate can be determined based on the comprehensive rating set of the resource applicant.
It can be understood that the comprehensive rating of the resource applicant is determined based on the related data of the resource applicant, and the resource allocation is further performed based on the comprehensive rating of the resource applicant, so that no manual participation is caused, and the resource allocation result is more accurate and objective.
In practical application, in order to perform comprehensive and objective evaluation on the resource applicant, the comprehensive rating of the resource applicant can be further determined; FIG. 2 is an explanation of step S03, and as shown in FIG. 2, the related data of the resource applicant includes a first index data set, a second index data set and a third index data set;
determining a comprehensive rating of the resource applicant based on the relevant data of the resource applicant, comprising:
s21, analyzing relevant data of the resource applicant to obtain a first index data set, a second index data set and a third index data set;
s22, determining a first rating based on the first index data set;
s23, determining a second rating based on the first rating and the second index data set;
and S24, determining the comprehensive rating of the resource applicant based on the second rating and the third index data set.
In practical application, the related data of the resource applicant comprises a first index data set, a second index data set and a third index data set; indexes corresponding to the index data included in the first index data set comprise enterprise types, value-added tax payer types and annual average sales income; indexes corresponding to the index data in the second index data set comprise an industry grade, a model grade and a tax payment credit grade of the last year; indexes corresponding to the index data included in the third index data set comprise sales income growth rate, credit card examination and approval times of nearly 12 months, credit investigation and inquiry times of nearly 12 months, loan examination and approval times of nearly 12 months, credit loan institution number average amount and current credit balance.
In order to perform objective and comprehensive evaluation on the resource applicant, after the relevant data of the resource applicant is obtained, the relevant data is firstly analyzed, a first index data set, a second index data set and a third index data set are extracted from the relevant data of the resource applicant, and finally, the comprehensive rating of the resource applicant is obtained from the first index data set, the second index data set and the third index data set.
The process of determining the first rating from the first index data set, determining the second rating from the first rating and the second index data set, and determining the comprehensive rating of the resource applicant from the second rating and the third index data set will be described in detail later, and details are not repeated herein.
It can be understood that two-layer progressive rating is adopted when rating is carried out on the resource application side, the second rating result depends on the first rating result, the comprehensive rating result of the resource application side depends on the second rating result, the comprehensive rating result of the resource application side is corrected by adding multiple layers and multiple factors, and the accuracy and the authenticity of the comprehensive rating result of the resource application side are improved.
In one possible implementation, determining a first rating based on a first set of metric data includes:
respectively determining the weight and the score corresponding to each index data contained in the first index data set;
determining a first score based on the weight and score corresponding to each index data contained in the first index data set;
and determining a first rating based on the first score according to a preset first mapping relation.
In order to determine the first rating, a weight and a score corresponding to each index data included in the first index data set may be determined according to a weight and score configuration table of an index corresponding to each index data included in a preset first index data set. In practical applications, the weight and score configuration table of the index corresponding to each index data included in the first index data set may be preset according to experience, and is not limited specifically.
The method includes determining a weight and a score of an index corresponding to each index data included in a first index data set according to a preset weight and score configuration table of the index corresponding to each index data included in the first index data set, that is, determining a weight and a score of a business type, a weight and a score of a value-added tax payer type, and a weight and a score of annual average sales income.
Then, determining a first score according to the weight and the score corresponding to each index data contained in the first index data set, namely, respectively obtaining the product of the weight and the score corresponding to each index data contained in the first index data set, and then adding the products of the weight and the score corresponding to each index data contained in the first index data set to obtain the first score; the first score is the sum of the product of the weight and the score of the business type, the product of the weight and the score of the value-added tax payer type, and the product of the weight and the score of the annual average sales income.
After obtaining the first score, the first rating may be further determined based on the first score according to a preset first mapping relationship. In practical applications, the first mapping relationship may be determined empirically, and is not particularly limited.
For example, the weight and score configuration table of the index corresponding to each index data included in the first index set may be set as shown in the following table:
first score ═ Σ (score × weight)
That is, the first score is the sum of the product of the weight and the score corresponding to the business type, the product of the weight and the score corresponding to the taxpayer type, and the product of the weight and the score corresponding to the sales income.
For a business with an annual average sales revenue of 4000 ten thousand, if the business is a general taxpayer, the first score of the business is 97.
The first mapping relationship may be set as shown in the following table:
when the first rating is 97, the first rating may be determined to be a1 according to the first mapping.
As one implementation, determining a second rating based on the first rating and the second set of metric data includes:
respectively determining the weight and the score corresponding to each index data contained in the first rating data set and the second index data set;
determining a second score based on the first rating and the weight and the score corresponding to each index data contained in the second index data set;
and determining a second rating based on the second score according to a preset second mapping relation.
In order to determine the second rating, the weight and the score corresponding to each index data included in the first rating and the second index data set may be determined according to a preset weight and score configuration table of the index corresponding to each index data included in the first rating and the second index data set. In practical applications, the weight and score configuration table of the index corresponding to each index data included in the first rating data set and the second rating data set may be preset according to experience, and is not limited specifically.
The method includes determining weights and scores of indexes corresponding to index data included in a first rating and a second rating data set, namely determining the weight and score of the first rating, the weight and score of an industry level, the weight and score of a model score and the weight and score of a tax credit level in a last year according to a weight and score configuration table of the indexes corresponding to the index data included in the first rating and the second rating data set; in practical applications, the model score may be a score for the resource applicant obtained according to an existing conventional model for scoring the resource applicant.
Then, determining a second score according to the weight and the score corresponding to each index data contained in the first rating and the second index data set, namely, respectively obtaining the product of the weight and the score corresponding to each index data contained in the first rating and the second index data set, and then adding the products of the weight and the score corresponding to each index data contained in the first rating and the second index data set to obtain a second score; the second score is the sum of the product of the weight and the score of the first rating, the product of the weight and the score of the industry level, the product of the weight and the score of the model score and the product of the weight and the score of the tax credit level in the last year.
After obtaining the second score, a second rating may be further determined based on the second score according to a preset second mapping relationship. In practical applications, the second mapping relationship may be determined empirically, and is not particularly limited.
For example, continuing the above example, the weight and score configuration table for the indexes corresponding to each index data included in the first rating and second index data set may be set as shown in the following table:
second score ═ Σ (score × weight)
I.e., the second score is the sum of the product of the weight and the score of the first score, the product of the weight and the score of the industry level, the product of the weight and the score of the model score, and the product of the weight and the score of the tax rate level.
Continuing with the above example, for an enterprise having a first rating of 97 and a first rating of A1, if the enterprise has an industry rating of L2, a model rating of R1, and a tax payment rating of A, the enterprise has a second rating of 94.
The second mapping relationship may be set as shown in the following table:
when the second rating is 94, the first rating may be determined to be B1 according to the second mapping.
In one possible embodiment, determining a composite rating for the resource applicant based on the second rating and the third set of metrics data includes:
respectively determining the weights and scores corresponding to the index data contained in the second rating and the third index data set;
determining a comprehensive score of the resource applicant based on the second rating and the weight and the score corresponding to each index data contained in the third index data set;
and determining the comprehensive rating of the resource applicant based on the comprehensive rating of the resource applicant according to a preset third mapping relation.
In order to determine the comprehensive rating of the resource applicant, the weight and the score corresponding to each index data included in the second rating and the third index data set may be determined according to a weight and score configuration table of indexes corresponding to each index data included in the second rating and the third index data set. In practical applications, the weight and score configuration table of the index corresponding to each index data included in the second rating and the third index data set may be preset according to experience, and is not limited specifically.
That is, the weights and scores of the indexes corresponding to the index data included in the second and third index data sets, that is, the weights and scores of the second ratings, the sales income increase rate, the credit card approval times of approximately 12 months, the credit inquiry times of approximately 12 months, the credit approval times of approximately 12 months, the credit in the credit institutions, the average credit amount in the credit institutions, and the current credit balance may be determined based on a preset weight and score arrangement table of the indexes corresponding to the index data included in the second and third index data sets.
Then, determining a comprehensive score of the resource applicant according to the weight and the score corresponding to each index data contained in the second rating and the third index data set, namely, respectively obtaining the product of the weight and the score corresponding to each index data contained in the second rating and the third index data set, and then adding the products of the weight and the score corresponding to each index data contained in the second rating and the third index data set to obtain the comprehensive score of the resource applicant; the comprehensive score of the resource applicant is the sum of the product of the weight and the score of the second rating, the product of the weight and the score of the sales income increase rate, the product of the weight and the score of the credit card examination and approval times of the last 12 months, the product of the weight and the score of the credit inquiry times of the last 12 months, the product of the weight and the score of the loan examination and approval times of the last 12 months, the product of the weight and the score of the credit in the credit institution number, the product of the weight and the score of the average credit line in the credit institution number and the product of the weight and the score of the current credit balance.
After the comprehensive rating of the resource applicant is obtained, the comprehensive rating of the resource applicant can be further determined based on the comprehensive rating of the resource applicant according to a preset third mapping relation. In practical applications, the third mapping relationship may be determined empirically, and is not particularly limited.
For example, continuing the above example, the weight and score configuration table for the indexes corresponding to the index data included in the second rating and third index data set may be set as shown in the following table:
resource applicant's composite score ═ Σ (score × weight)
Namely, the comprehensive score of the resource applicant is the sum of the product of the weight and the score of the second rating, the product of the weight and the score of the sales income increase rate, the product of the weight and the score of the credit card approval times of the last 12 months, the product of the weight and the score of the credit inquiry times of the last 12 months, the product of the weight and the score of the loan approval times of the last 12 months, the product of the weight and the score of the credit in the credit institution number, the product of the weight and the score of the credit average credit line in the credit institution number and the product of the weight and the score of the current credit balance.
Continuing with the above example, for a business with a second rating of 94 and a second level of B1, if the business has a sales income growth rate of 40%, a credit card approval count of 3 times in approximately 12 months, a credit investigation count of 3 times in approximately 12 months, a loan approval count of 2 times in approximately 12 months, a credit institution count of 1, an average credit limit of 120 ten thousand in the credit institution count, and a current credit balance of 100 ten thousand, the resource applicant has a composite rating of 88.
The third mapping relationship may be set as shown in the following table:
when the comprehensive rating of the resource applicant is 88, the comprehensive rating of the resource applicant can be determined to be one level according to the third mapping relationship.
It should be noted that the method of the embodiment of the present invention may be executed by a single device, such as a computer or a server. The method of the embodiment can also be applied to a distributed scene and completed by the mutual cooperation of a plurality of devices. In the case of such a distributed scenario, one of the multiple devices may only perform one or more steps of the method according to the embodiment of the present invention, and the multiple devices interact with each other to complete the method.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
Fig. 3 is a schematic structural diagram of a dispensing device according to an embodiment of the present invention, and as shown in fig. 3, the dispensing device includes:
a receiving module 31, configured to receive a resource allocation request sent by a resource applying party;
a related data obtaining module 32, configured to obtain related data of the resource applying party based on the resource allocation request of the resource applying party; the related data of the resource application party comprises one or more of judicial data, industrial and commercial data, credit investigation data, tax data and bank data;
a comprehensive rating determining module 33, configured to determine a comprehensive rating of the resource applicant based on the relevant data of the resource applicant;
and the resource allocation module 34 is used for allocating resources based on the comprehensive rating of the resource applicant.
In one possible embodiment, the relevant data of the resource applicant comprises a first index data set, a second index data set and a third index data set;
a composite rating determination module 33 comprising:
the relevant data analysis unit is used for analyzing the relevant data of the resource applicant to obtain a first index data set, a second index data set and a third index data set;
a first rating determination unit for determining a first rating based on the first index data set;
a second rating determination unit for determining a second rating based on the first rating and the second index data set;
and the comprehensive rating determining unit is used for determining the comprehensive rating of the resource applicant based on the second rating and the third index data set.
As an embodiment, the first rating determination unit is specifically configured to:
respectively determining the weight and the score corresponding to each index data contained in the first index data set;
determining a first score based on the weight and score corresponding to each index data contained in the first index data set;
and determining a first rating based on the first score according to a preset first mapping relation.
In a possible implementation, the second rating determination unit is specifically configured to:
respectively determining the weight and the score corresponding to each index data contained in the first rating data set and the second index data set;
determining a second score based on the first rating and the weight and the score corresponding to each index data contained in the second index data set;
and determining a second rating based on the second score according to a preset second mapping relation.
As an embodiment, the comprehensive rating determining unit is specifically configured to:
respectively determining the weights and scores corresponding to the index data contained in the second rating and the third index data set;
determining a comprehensive score of the resource applicant based on the second rating and the weight and the score corresponding to each index data contained in the third index data set;
and determining the comprehensive rating of the resource applicant based on the comprehensive rating of the resource applicant according to a preset third mapping relation.
The apparatus of the foregoing embodiment is used to implement the corresponding method in the foregoing embodiment, and has the beneficial effects of the corresponding method embodiment, which are not described herein again.
An embodiment of the present invention further provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor executes the computer program to implement the allocation method according to any one of the above-mentioned embodiments.
Fig. 4 is a schematic diagram illustrating a more specific hardware structure of an electronic device according to this embodiment, where the electronic device may include: a processor 1010, a memory 1020, an input/output interface 1030, a communication interface 1040, and a bus 1050. Wherein the processor 1010, memory 1020, input/output interface 1030, and communication interface 1040 are communicatively coupled to each other within the device via bus 1050.
The processor 1010 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits, and is configured to execute related programs to implement the technical solutions provided in the embodiments of the present disclosure.
The Memory 1020 may be implemented in the form of a ROM (Read Only Memory), a RAM (Random access Memory), a static storage device, a dynamic storage device, or the like. The memory 1020 may store an operating system and other application programs, and when the technical solution provided by the embodiments of the present specification is implemented by software or firmware, the relevant program codes are stored in the memory 1020 and called to be executed by the processor 1010.
The input/output interface 1030 is used for connecting an input/output module to input and output information. The i/o module may be configured as a component in a device (not shown) or may be external to the device to provide a corresponding function. The input devices may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output devices may include a display, a speaker, a vibrator, an indicator light, etc.
The communication interface 1040 is used for connecting a communication module (not shown in the drawings) to implement communication interaction between the present apparatus and other apparatuses. The communication module can realize communication in a wired mode (such as USB, network cable and the like) and also can realize communication in a wireless mode (such as mobile network, WIFI, Bluetooth and the like).
It should be noted that although the above-mentioned device only shows the processor 1010, the memory 1020, the input/output interface 1030, the communication interface 1040 and the bus 1050, in a specific implementation, the device may also include other components necessary for normal operation. In addition, those skilled in the art will appreciate that the above-described apparatus may also include only those components necessary to implement the embodiments of the present description, and not necessarily all of the components shown in the figures.
Embodiments of the present invention also provide a non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform any of the above-described dispensing methods.
Computer-readable media of the present embodiments, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device.
Those of ordinary skill in the art will understand that: the discussion of any embodiment above is meant to be exemplary only, and is not intended to intimate that the scope of the disclosure, including the claims, is limited to these examples; within the idea of the invention, also features in the above embodiments or in different embodiments may be combined, steps may be implemented in any order, and there are many other variations of the different aspects of the invention as described above, which are not provided in detail for the sake of brevity.
In addition, well known power/ground connections to Integrated Circuit (IC) chips and other components may or may not be shown within the provided figures for simplicity of illustration and discussion, and so as not to obscure the invention. Furthermore, devices may be shown in block diagram form in order to avoid obscuring the invention, and also in view of the fact that specifics with respect to implementation of such block diagram devices are highly dependent upon the platform within which the present invention is to be implemented (i.e., specifics should be well within purview of one skilled in the art). Where specific details (e.g., circuits) are set forth in order to describe example embodiments of the invention, it should be apparent to one skilled in the art that the invention can be practiced without, or with variation of, these specific details. Accordingly, the description is to be regarded as illustrative instead of restrictive.
While the present invention has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations of these embodiments will be apparent to those of ordinary skill in the art in light of the foregoing description. For example, other memory architectures, such as Dynamic RAM (DRAM), may use the discussed embodiments.
The embodiments of the invention are intended to embrace all such alternatives, modifications and variances that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, substitutions, improvements and the like that may be made without departing from the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (8)
1. A method of distribution, the method comprising:
receiving a resource allocation request sent by a resource application party;
acquiring related data of the resource application party based on the resource allocation request of the resource application party; the related data of the resource application party comprises one or more of judicial data, industrial and commercial data, credit investigation data, tax data and bank data;
determining a comprehensive rating of the resource applicant based on the relevant data of the resource applicant;
and performing resource allocation based on the comprehensive rating of the resource applicant.
2. The allocation method according to claim 1, wherein the related data of the resource applicant comprises a first index data set, a second index data set and a third index data set;
the determining a comprehensive rating of the resource applicant based on the relevant data of the resource applicant comprises:
analyzing the related data of the resource applicant to obtain the first index data set, the second index data set and the third index data set;
determining a first rating based on the first set of metric data;
determining a second rating based on the first rating and the second set of metric data;
determining a composite rating for the resource applicant based on the second rating and the third set of metrics data.
3. The assignment method of claim 2, wherein determining a first rating based on the first set of metric data comprises:
respectively determining the weight and the score corresponding to each index data contained in the first index data set;
determining a first score based on the weight and the score corresponding to each index data contained in the first index data set;
and determining a first rating based on the first score according to a preset first mapping relation.
4. The assignment method of claim 2, wherein determining a second rating based on the first rating and the second metric data set comprises:
respectively determining the weight and the score corresponding to each index data contained in the first rating and the second index data set;
determining a second score based on the first rating and the weight and the score corresponding to each index data contained in the second index data set;
and determining a second rating based on the second score according to a preset second mapping relation.
5. The allocation method according to claim 2, wherein said determining a composite rating of the resource applicant based on the second rating and the third metric data set comprises:
determining weights and scores corresponding to the second rating and the index data contained in the third index data set respectively;
determining a comprehensive score of the resource applicant based on the second rating and the weight and the score corresponding to each index data contained in the third index data set;
and determining the comprehensive rating of the resource applicant based on the comprehensive rating of the resource applicant according to a preset third mapping relation.
6. A dispensing device, the device comprising:
the receiving module is used for receiving a resource allocation request sent by a resource application party;
a related data acquisition module, configured to acquire related data of the resource applicant based on the resource allocation request of the resource applicant; the related data of the resource application party comprises one or more of judicial data, industrial and commercial data, credit investigation data, tax data and bank data;
the comprehensive rating determining module is used for determining the comprehensive rating of the resource applicant based on the related data of the resource applicant;
and the resource allocation module is used for allocating resources based on the comprehensive rating of the resource applicant.
7. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1 to 5 when executing the program.
8. A non-transitory computer readable storage medium storing computer instructions for causing a computer to perform the method of any one of claims 1 to 5.
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