CN111340553A - Financial service platform product personalized recommendation method and system - Google Patents
Financial service platform product personalized recommendation method and system Download PDFInfo
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- CN111340553A CN111340553A CN202010126849.9A CN202010126849A CN111340553A CN 111340553 A CN111340553 A CN 111340553A CN 202010126849 A CN202010126849 A CN 202010126849A CN 111340553 A CN111340553 A CN 111340553A
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Abstract
The invention relates to the technical field of big data, and particularly provides a financial service platform product personalized recommendation method. A financial service platform product personalized recommendation method comprises the following steps: s1, creating a user portrait, which comprises the following three parts: s101, collecting data, S102, analyzing the data, S103, and forming an image; s2, recommending financial products, which comprises the following two parts: s201, submitting requirements by a user, and S202, performing a financial product recommendation function. Compared with the prior art, the financial service platform product personalized recommendation method enables the recommendation of products to be more accurate. For the organizations or enterprises with huge data volume, the method can improve the efficiency of the financial service platform and has good popularization value.
Description
Technical Field
The invention relates to the technical field of big data, and particularly provides a financial service platform product personalized recommendation method and system.
Background
Due to the rapid development of the big data era, the data volume required to be maintained or analyzed by a plurality of organizations and enterprises is huge continuously, the financial service industry needs to accurately and directionally analyze images of users, and the traditional backward data use cannot adapt to the current big data volume. Most data are stored in the database and cannot be effectively utilized, and the extraction of relevant data is time-consuming and labor-consuming. At present, most financial service platforms need users to know detailed conditions of products one by one, namely time delay is delayed and much energy is spent; in addition, the user image has certain limitations, such as missing of partial data, low timeliness of data, and the like.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides the financial service platform product personalized recommendation method with strong practicability.
The invention further aims to provide a financial service platform product personalized recommendation system which is reasonable in design, safe and applicable.
The technical scheme adopted by the invention for solving the technical problems is as follows:
a financial service platform product personalized recommendation method comprises the following steps:
s1, creating a user portrait, which comprises the following three parts:
s101, collecting the data of the user,
s102, analyzing the data,
s103, forming an image;
s2, recommending financial products, which comprises the following two parts:
s201, the user submits the requirement,
s202, a financial product recommending function.
Further, in the step S101, in the data collection, government data related to finance is obtained by crawling through a web crawler technology or collaborating with government departments, the data mainly comes from a public security department, an industrial and commercial department and a tax department, standards of the data of the three government departments have certain differences, and after the data is obtained, preliminary processing and screening are performed, wherein the processing and screening include data association and data loss rate statistics of each department.
Further, in the step S102, in analyzing the data, the existing data is primarily analyzed by a trend analysis method, a contrast analysis method, a quadrant analysis method or a cross analysis method, the standard of the data analysis is established on the basis of various indexes set by the user,
the income capacity and the fixed assets can be divided into strong, general, poor and poor according to specific indexes, processed data are converted into the indexes through analyzing various relevant data of users, and the data missing condition of each special user needs to be counted simultaneously in the data analysis process.
Further, in the step S103 of forming the portrait, after the step of analyzing the data, various indexes of the user and the data loss rate are obtained, and when the non-critical data loss rate is lower than 12%, the portrait of the user has higher accuracy, and the user is portrait according to the debt repayment capability, the annual income level and the personal data yield obtained by data analysis and the characteristics of the financial products aiming at the user group, the credit or mortgage mode and the loan finance height.
Further, in the financial platform of the financial institution facing the user in step S201, a requirement submitting function is provided for the user, when the user is difficult to select a desired financial product in a short time, the user may submit the requirement of the user to the system, and when the submitted requirement is related to the related information of the financial product, the requirement of the user is combined with the user representation, and a product that is more likely to be satisfied and selected by the user is recommended to the user.
Further, in step S202, the user profile is owned, the existing financial products are screened, products that are more likely to meet the actual needs of the user are screened according to the conditions of various indexes of the user, the importance degree of the indexes, and the conditions of the used products, and the products are ranked and recommended to the user according to the possibility.
A financial service platform product personalized recommendation system comprises a user portrait creation module and a financial product recommendation module which are connected in sequence,
the user portrait creation module comprises a data collection submodule, a data analysis submodule and a portrait formation submodule which are sequentially connected, wherein the data collection submodule is used for crawling through a web crawler technology or obtaining government data related to finance in cooperation with government departments, the data mainly come from public security departments, industrial and commercial departments and tax departments, the standards of the data of the three government departments have certain differences, and preliminary processing and screening are performed after the data are obtained, and the processing and screening comprise data association and data missing rate statistics of each department;
the analysis data submodule is used for carrying out primary analysis on the existing data through a trend analysis method, a contrast analysis method, a quadrant analysis method or a cross analysis method, and the standard of data analysis is established on the basis of various indexes set by a user;
the portrait forming sub-module is used for obtaining various indexes of the user and the missing rate of data, when the missing rate of non-key data is lower than 12%, the portrait of the user has higher accuracy, and the portrait of the user is drawn according to the debt repayment capability, the annual income level and the personal data yield obtained by data analysis and the characteristics of financial products aiming at user groups, credit or mortgage modes and loan finance heights;
the financial product recommending module comprises a user submitting requirement submodule and a financial product recommending function submodule which are sequentially connected, wherein the user submitting requirement submodule is used for providing a requirement submitting function for a user in a financial platform of a financial institution facing the user, when the user is difficult to select a financial product which the user wants in a short time, the user can submit the requirement of the user to the system, and when the submitted requirement is related to related information of the financial product, the requirement of the user is combined with a user portrait, and the product which is more likely to be satisfied and selected by the user is recommended to the user;
the financial product recommending function sub-module is used for screening the existing financial products when the user portrait is possessed, screening products which are more likely to meet the actual requirements of the user according to the conditions of various indexes of the user, the importance degree of the indexes and the conditions of the used products, and sequencing and recommending the products to the user according to the possibility.
Preferably, in the data analysis submodule, the income capacity and the fixed assets can be divided into strong, general, poor and poor according to specific indexes, processed data is converted into each index through the analysis of each item of relevant data of the user, and the data missing condition of each special user needs to be counted simultaneously in the data analysis process.
Compared with the prior art, the financial service platform product personalized recommendation method and system have the following outstanding beneficial effects:
1. the user portrait is created, accurate product recommendation is facilitated for different users, and the problem that the user is difficult to quickly decide when facing various financial products is solved.
2. Financial institutions may utilize some of the statistical data of user portraits to customize financial products that better meet the needs of the user.
3. And product recommendation is carried out according to the user portrait and the user requirement, so that the operating efficiency of the financial service platform can be 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 introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a schematic structural diagram of a financial service platform product personalized recommendation method.
Detailed Description
The present invention will be described in further detail with reference to specific embodiments in order to better understand the technical solutions of the present invention. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
A preferred embodiment is given below:
as shown in fig. 1, the method for recommending financial service platform product personalization in this embodiment includes the following steps:
s1, creating a user portrait, which comprises the following three parts:
s101, collecting the data of the user,
s102, analyzing the data,
s103, forming an image;
s2, recommending financial products, which comprises the following two parts:
s201, the user submits the requirement,
s202, a financial product recommending function.
In the step S101, in collecting data, government data related to finance is obtained by crawling through a web crawler technology or collaborating with government departments, the data mainly comes from a public security department, an industrial and commercial department and a tax department, standards of the data of the three government departments have certain differences, and after the data are obtained, preliminary processing and screening are performed, wherein the processing and screening include data association and data loss rate statistics of each department.
In the step S102, in analyzing the data, the existing data is primarily analyzed by a trend analysis method, a contrast analysis method, a quadrant analysis method or a cross analysis method, the standard of data analysis is established on the basis of various indexes set by the user,
the income capacity and the fixed assets can be divided into strong, general, poor and poor according to specific indexes, processed data are converted into the indexes through analyzing various relevant data of users, and the data missing condition of each special user needs to be counted simultaneously in the data analysis process.
In the step S103, in the step of forming the portrait, after the step of analyzing the data, various indexes of the user and the data loss rate are obtained, and when the non-critical data loss rate is lower than 12%, the portrait of the user has higher accuracy, and the user is portrait according to the debt repayment capability, the annual income level and the personal data yield obtained by the data analysis and the characteristics of the financial products aiming at the user group, the credit or mortgage mode and the loan finance height.
In step S201, the financial institution provides a user with a request submitting function, and when it is difficult for the user to select a desired financial product in a short time, the user can submit his/her request to the system, and when the submitted request is related to the related information of the financial product, the user request is combined with the user representation to recommend a product to the user that is more likely to be satisfied and selected by the user.
In step S202, the user representation is owned, the existing financial products are screened, products which are more likely to meet the actual needs of the user are screened according to the conditions of various indexes of the user, the importance degree of the indexes and the conditions of the used products, and the products are ranked and recommended to the user according to the possibility.
The operation method is based on a financial service platform product personalized recommendation system, and the system comprises a user portrait creation module and a financial product recommendation module which are sequentially connected.
The user portrait creation module comprises a data collection sub-module, a data analysis sub-module and a portrait formation sub-module which are sequentially connected, wherein the data collection sub-module is used for crawling through a web crawler technology or obtaining government data related to finance in cooperation with government departments, the data mainly come from public security departments, industrial and commercial departments and tax departments, the standards of the data of the three government departments have certain difference, preliminary processing and screening are carried out after the data are obtained, and the processing and screening comprise data association and data missing rate statistics of each department.
The analysis data submodule is used for carrying out primary analysis on the existing data through a trend analysis method, a contrast analysis method, a quadrant analysis method or a cross analysis method, and the standard of data analysis is established on the basis of various indexes set by a user.
The income capacity and the fixed assets can be divided into strong, general, poor and poor according to specific indexes, processed data are converted into the indexes through analyzing various relevant data of users, and the data missing condition of each special user needs to be counted simultaneously in the data analysis process.
The method comprises the steps that a portrait sub-module is formed and used for obtaining various indexes of a user and the missing rate of data, when the missing rate of non-key data is lower than 12%, the portrait of the user has high accuracy, and the user is portrait according to debt repayment capacity, annual income level and personal data yield obtained through data analysis and the characteristics of financial products aiming at user groups, credit or mortgage modes and loan finance height;
the financial product recommending module comprises a user submitting requirement submodule and a financial product recommending function submodule which are sequentially connected, wherein the user submitting requirement submodule is used for providing a requirement submitting function for a user in a financial platform facing the user of a financial institution, when the user is difficult to select a financial product which the user wants in a short time, the user can submit the requirement of the user to the system, and when the submitted requirement is related to related information of the financial product, the requirement of the user is combined with the user portrait, and the product which is more likely to be satisfied and selected by the user is recommended to the user;
the financial product recommending function sub-module is used for screening the existing financial products when the user portrait is possessed, screening products which are more likely to meet the actual requirements of the user according to the conditions of various indexes of the user, the importance degree of the indexes and the conditions of the used products, and sequencing and recommending the products to the user according to the possibility.
The above embodiments are only specific ones of the present invention, and the protection scope of the present invention includes but is not limited to the above embodiments, and any suitable changes or substitutions that are consistent with the claims of the financial services platform product personalized recommendation method and system of the present invention and are made by those skilled in the art should fall within the protection scope of the present invention.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (8)
1. A financial service platform product personalized recommendation method is characterized by comprising the following steps:
s1, creating a user portrait, which comprises the following three parts:
s101, collecting the data of the user,
s102, analyzing the data,
s103, forming an image;
s2, recommending financial products, which comprises the following two parts:
s201, the user submits the requirement,
s202, a financial product recommending function.
2. The method as claimed in claim 1, wherein in the step S101, in the data collected, government data related to finance is obtained by crawling through web crawler technology or cooperating with government departments, the data mainly comes from police departments, industrial and commercial departments and tax departments, and the data of the three government departments have certain differences in standard, and after the data are obtained, preliminary processing and screening are performed, wherein the processing and screening include data association and data loss rate statistics of each department.
3. The method as claimed in claim 2, wherein in the step S102, the existing data is primarily analyzed by a trend analysis method, a contrast analysis method, a quadrant analysis method or a cross analysis method, the data analysis criteria is based on various indexes set for the user,
the income capacity and the fixed assets can be divided into strong, general, poor and poor according to specific indexes, processed data are converted into the indexes through analyzing various relevant data of users, and the data missing condition of each special user needs to be counted simultaneously in the data analysis process.
4. The method as claimed in claim 3, wherein in the step S103 of forming the portrait, after the step of analyzing the data, the indexes of the user and the data loss rate are obtained, when the non-critical data loss rate is lower than 12%, the portrait of the user has higher accuracy, and the portrait of the user is represented according to the debt repayment ability, the annual income level and the personal data yield obtained by the data analysis and the characteristics of the financial product for the user group, the credit or mortgage mode and the loan finance height.
5. The method as claimed in claim 4, wherein the financial service platform product personalized recommendation method provides a user with a request submission function in the financial platform of the financial institution facing the user at step S201, and when the user has difficulty in selecting a financial product desired by the user in a short time, the user can submit his/her request to the system, and the submitted request is related to the information related to the financial product, and the user is recommended a product that is more likely to be satisfied and selected by the user by combining the user request with the user profile.
6. The method as claimed in claim 5, wherein in step S202, the user image is possessed, the existing financial products are screened, the products which are more likely to meet the actual needs of the user are screened according to the user' S various index conditions and the importance degree of the index, and the used products, and the products are ranked and recommended to the user according to the possibility.
7. A financial service platform product personalized recommendation system is characterized by comprising a user portrait creation module and a financial product recommendation module which are sequentially connected,
the user portrait creation module comprises a data collection submodule, a data analysis submodule and a portrait formation submodule which are sequentially connected, wherein the data collection submodule is used for crawling through a web crawler technology or obtaining government data related to finance in cooperation with government departments, the data mainly come from public security departments, industrial and commercial departments and tax departments, the standards of the data of the three government departments have certain differences, and preliminary processing and screening are performed after the data are obtained, and the processing and screening comprise data association and data missing rate statistics of each department;
the analysis data submodule is used for carrying out primary analysis on the existing data through a trend analysis method, a contrast analysis method, a quadrant analysis method or a cross analysis method, and the standard of data analysis is established on the basis of various indexes set by a user;
the portrait forming sub-module is used for obtaining various indexes of the user and the missing rate of data, when the missing rate of non-key data is lower than 12%, the portrait of the user has higher accuracy, and the portrait of the user is drawn according to the debt repayment capability, the annual income level and the personal data yield obtained by data analysis and the characteristics of financial products aiming at user groups, credit or mortgage modes and loan finance heights;
the financial product recommending module comprises a user submitting requirement submodule and a financial product recommending function submodule which are sequentially connected, wherein the user submitting requirement submodule is used for providing a requirement submitting function for a user in a financial platform of a financial institution facing the user, when the user is difficult to select a financial product which the user wants in a short time, the user can submit the requirement of the user to the system, and when the submitted requirement is related to related information of the financial product, the requirement of the user is combined with a user portrait, and the product which is more likely to be satisfied and selected by the user is recommended to the user;
the financial product recommending function sub-module is used for screening the existing financial products when the user portrait is possessed, screening products which are more likely to meet the actual requirements of the user according to the conditions of various indexes of the user, the importance degree of the indexes and the conditions of the used products, and sequencing and recommending the products to the user according to the possibility.
8. The system of claim 7, wherein the sub-module for analyzing data is configured to classify the income ability and the fixed assets into strong, general, poor and bad according to specific criteria, and convert the processed data into the respective criteria by analyzing the data related to the user, and count the data missing condition of each specific user during the data analysis.
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| CN111815150A (en) * | 2020-07-06 | 2020-10-23 | 天元大数据信用管理有限公司 | Financial service platform user scoring system and method based on user data |
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| CN111815150A (en) * | 2020-07-06 | 2020-10-23 | 天元大数据信用管理有限公司 | Financial service platform user scoring system and method based on user data |
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