CN115760347A - Bank product management system - Google Patents
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- CN115760347A CN115760347A CN202211504526.4A CN202211504526A CN115760347A CN 115760347 A CN115760347 A CN 115760347A CN 202211504526 A CN202211504526 A CN 202211504526A CN 115760347 A CN115760347 A CN 115760347A
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Abstract
The invention relates to the technical field of financial informatization management, in particular to a bank product management system, which comprises a server, wherein the server comprises the following modules: the user information acquisition module: the system is used for collecting user association information of a user; the user portrait analysis module: the user portrait is generated according to the user correlation information; the product information storage module: the system is used for storing the existing product information of the bank; a recommendation model training module: the recommendation model is used for acquiring a trained recommendation model; the product recommendation analysis module: the recommendation system is used for generating a recommended product list of each user according to the recommendation model; the similar correlation pushing module: and the product association pushing module is used for acquiring the historical browsing information of the new user when the user is detected to be the new user, searching the user with the similarity of the historical browsing information larger than a preset value as an associated user according to the historical browsing information, and then performing product association pushing on the new user according to the user figure of the associated user. The invention can improve the accuracy and the conversion power of bank product pushing.
Description
Technical Field
The invention relates to the technical field of financial informatization management, in particular to a bank product management system.
Background
In the process of selling bank products, a bank sends reservation reminding short messages or carries out telephone promotion to users in a reservation period in order to remind the users of reserving the bank products to purchase. Some users can make reservations of bank products by impulse at a moment due to reasons such as telephone sales, advertisements, friend recommendations and the like, so the reservation amount may be far higher than the actual demand number. And after the reservation, a member of the population will not be concerned about the reserved bank product. Even if the bank customer service and the sales send the appointment reminding short message or make a telephone notification before the user product is about to be sold, most people do not necessarily interest or do not meet the requirements of the user product after thinking, and only answer the user product orally and then know and see the user product. However, the actual open purchase date of the bank product is reached, the number of reservation users who make a purchase response to the bank product is small, the purchase intention is low, and the bank manager misjudges the fire of the bank product, so that too many propaganda resources and other costs are invested. The method causes the bank product to be converted into low power, and also causes the waste of the recommended resources of the bank product.
At present, some bank product recommendation systems exist, users can be simply classified according to user history data, and a certain type of products can be pushed directionally, but the recommendation mode is rough, the conversion power is also poor, and the recommendation effect on new users without history records is worse.
Disclosure of Invention
The invention aims to provide a bank product management system which can improve the pushing accuracy and the conversion power of bank products.
In order to achieve the above object, there is provided a bank product management system including a server including the following modules:
the user information acquisition module: the system comprises a user management server, a user management server and a user management server, wherein the user management server is used for acquiring user association information of a user, and the user association information comprises historical purchase information and historical browsing information of the user on bank products, and identity information and asset information of the user;
a user portrait analysis module: the user portrait is generated according to the user correlation information;
the product information storage module: the system is used for storing the existing product information of the bank;
a recommendation model training module: the recommendation model acquiring system is used for acquiring historical purchase information of each user, corresponding user portrait information and final profit information of the user, and training the recommendation model according to the acquired information to obtain a trained recommendation model;
the product recommendation analysis module: the system comprises a recommendation model input module, a recommendation module and a recommendation module input module, wherein the recommendation model input module is used for inputting user association information of each user, corresponding user portrait and currently existing product information of a bank to generate a recommended product list of each user;
the similar correlation pushing module: and the product association pushing module is used for acquiring the historical browsing information of the new user when the user is detected to be the new user, searching the user with the similarity of the historical browsing information larger than a preset value as an associated user according to the historical browsing information, and then performing product association pushing on the new user according to the user figure of the associated user.
The principle and the advantages are as follows:
according to the scheme, the user and the product are not simply associated in the conventional technical means, and then the product is recommended to the user according to the user portrait. Historical purchase information, user portrait information and final income information are used as input of the neural network model, after the neural network model is trained to obtain a recommendation model, prediction recommendation of bank products suitable for each user can be achieved through the recommendation model, so that the user preference is met, meanwhile, the benefit return requirements of the user are met to a certain extent, the accuracy and the acceptability of the recommended products are guaranteed, and the conversion rate of the bank products is improved. Meanwhile, the users served by the scheme are not limited to old users, the service area is too narrow, in order to widen the service area, the scheme is used for matching the corresponding old users by analyzing the similarity of the historical browsing information for new users without historical data, the historical browsing information can represent the preference of the users to a certain extent, and the preference of the new and old users can be similar due to the similarity of the historical browsing information, so that the product association pushing is carried out on the new users according to the user figures of the associated users, the accurate pushing of bank products is further realized for the new users, and the pushing accuracy and the conversion power are improved. And the system can serve new and old users at the same time, thereby greatly widening the service range.
Further, the server comprises the following modules:
a comparison analysis module: the system is used for comparing and analyzing the historical purchasing information and the historical browsing information of the bank products by the user, analyzing the purchasing conversion rate of the user on the browsed bank products, and setting the promotion coefficient of the user image corresponding to the user according to the purchasing conversion rate.
Has the beneficial effects that: the setting of contrastive analysis module can carry out contrastive analysis with the historical purchase information and the historical browse information of user to bank product's that the analysis user browsed purchase conversion rate, can set up the popularization coefficient for corresponding user's user portrait through purchasing the conversion rate, and then better, more accurate carries out the recommendation of bank product for new user, so that improve the degree of accuracy of propelling movement and change into power.
Further, the server comprises the following modules:
a product policy management module: the system comprises a database, a database and a database, wherein the database is used for acquiring product charges, relevant preferential policy elements and product rule elements of each bank product, sorting the product charges, the relevant preferential policy elements and the product rule elements according to a preset lookup template, and storing the product charges, the relevant preferential policy elements and the product rule elements in a preset database after sorting;
a search module: the search keyword is used for obtaining the search keyword of the user for the bank product, searching the reference template of the corresponding bank product according to the search keyword, and pushing the reference template to the user.
Has the advantages that: the product policy management module can collect product charges, relevant preferential policy elements and product rule elements of bank products and arrange the product charges, the relevant preferential policy elements and the product rule elements into a lookup template, so that a user can search and find the product through the search module and know relevant information of the bank products in detail, and the phenomenon that the purchase willingness of the user on the bank products is reduced due to unclear publication of the charges, the preferential policies and the rules is avoided, and the conversion power of the bank products is influenced.
Further, the server comprises the following modules:
the rule graph culture display module: the system is used for acquiring a purchase case of a bank product, acquiring an image-text explanation schematic diagram which is manufactured by combining the purchase case with product rule elements, and storing the image-text explanation schematic diagram and a reference template into a database in a correlation mode.
Has the beneficial effects that: the rule graph culture display module is arranged, and the graph-text explanation schematic diagram is manufactured by combining the collected purchase cases and product rule elements, so that a new user can know the rules of bank products more easily, and after all, everyone can not research the thorough character rules.
Further, the server comprises the following modules:
the product marketing management module: the system is used for acquiring popularization activities of various bank products and filling activity rules and propaganda advertisements corresponding to the popularization activities into a preset activity popularization template; the system is also used for matching users suitable for popularization activities according to the user association information of each user and the corresponding user portrait; and the method is also used for popularizing the activity popularization template of the bank product to the corresponding user.
Has the advantages that: the product marketing management module can automatically and accurately send promotion activities to users, so that the conversion power of bank products is improved.
Further, the similar association pushing module is further configured to, when it is detected that the user is a new user, obtain personal information and an interpersonal relationship of the user, obtain the user having an interpersonal relationship with the new user or having a degree of similarity of the personal information greater than a preset value as an associated user, and recommend a bank product to the new user based on the user association information of the associated user.
Has the advantages that: because the information data of the new user is limited, the bank products which are matched, analyzed and recommended only through the historical browsing information may not be proper, the scheme introduces the personal information and the interpersonal relationship of the user, finds out the more proper associated user based on the personal information and the interpersonal relationship, and therefore the recommended bank products are more in line with the preference and interest relevance of the user. Thereby improving the accuracy and conversion to power of the push.
Further, the server comprises the following modules:
the user number analysis and prediction module comprises: the bank product management system is used for analyzing the number of potential users, the number of current users and the number of lost users of the current period of the bank product according to the user representation of each user; the system is also used for predicting the user data of the bank product in the next period according to the number of potential users, the number of current users, the number of lost users and a preset neural network prediction model;
a promotion strategy adjustment module: the system is used for dynamically adjusting the promotion strategies of the bank products according to the user data of the bank products in the next period, wherein the promotion strategies comprise product charging pricing, preferential strategies and advertisement promotion strength.
Has the advantages that: the sales volume of bank products is as the tide of sea waves, so that the adjustment of product charging pricing, preferential strategies and advertising promotion strength at proper time is very necessary. According to the scheme, the user data of the bank products in the next period can be predicted through the neural network prediction model, so that the popularization strategy of each bank product is dynamically adjusted, and the pushing accuracy and the conversion power are improved.
Drawings
Fig. 1 is a logic block diagram of a bank product management system according to an embodiment of the present invention.
Detailed Description
The following is further detailed by way of specific embodiments:
examples
The utility model provides a bank product management system, is basically as shown in figure 1, includes server and user side, the user side carries on APP for with server communication connection, the server carries on bank product show platform, can demonstrate various bank products, the user side can look over the information of relevant bank product at bank product show platform, perhaps the server carries out the propelling movement of bank product to the user side. The server comprises the following modules:
the user information acquisition module: the system comprises a user management server, a user management server and a user management server, wherein the user management server is used for acquiring user association information of a user, and the user association information comprises historical purchase information and historical browsing information of the user on bank products, and identity information and asset information of the user; the historical purchase information is the bank product purchased by the user through the user terminal, and records the relevant purchase record of the bank product, such as basic information (price), time and place (platform) of purchasing the bank product. The historical browsing information is the browsing information of the bank products on the bank product display platform by the user through the user side. The asset information is the total evaluation price of the purchased bank products or the asset forecast made according to the purchase types and times of the bank products.
A user portrait analysis module: the user portrait is generated according to the user correlation information; the manner of generating the user portrait is the same as that in the prior art, and the relevant information of the user, such as habits, hobbies, consumption ability and the like, is collected in advance through a big data manner, so that which kind of products the user is suitable for is analyzed, and therefore the user portrait is not described in detail in this embodiment.
The product information storage module: the system is used for storing the existing product information of the bank at present in a database, storing the product information of cancelled bank products and recording the cancellation reason; so as to be displayed on a bank product display platform and facilitate the data calling without threshold of other functions. And is also used for storing the user portrait, historical purchasing information, historical browsing information and other contents of each old user.
A recommendation model training module: the recommendation model training system is used for acquiring historical purchase information of each user, corresponding user portrait information and final income information of the user, and training the recommendation model according to the acquired three information to obtain a trained recommendation model; in the embodiment, the recommendation model is a neural network model, and is trained and tested through a large amount of sample data; and continuously optimizing the model according to the test result to finally obtain a qualified recommendation model, wherein the neural network model is a BP neural network, a Convolutional Neural Network (CNN), a long-short term memory network (LSTM), a Hopfield network, a Boltzmann machine and the like, the neural network algorithm belongs to a mature technology, and the specific training and testing of the recommendation model are not described in detail in the embodiment.
The product recommendation analysis module: the system comprises a recommendation model input module, a recommendation module and a recommendation module input module, wherein the recommendation model input module is used for inputting user association information of each user, corresponding user portrait and currently existing product information of a bank to generate a recommended product list of each user;
a comparison analysis module: the system is used for comparing and analyzing historical purchasing information and historical browsing information of the bank products by the user, analyzing the purchasing conversion rate of the user on the browsed bank products, and setting the promotion coefficient of the user image corresponding to the user according to the purchasing conversion rate. The setting of contrastive analysis module can carry out contrastive analysis with the historical purchase information and the historical browse information of user to bank product's that the analysis user browsed purchase conversion rate, can set up the popularization coefficient for corresponding user's user portrait through purchasing the conversion rate, and then better, more accurate carries out the recommendation of bank product for new user, so that improve the degree of accuracy of propelling movement and change into power.
The similar correlation pushing module: and the product association pushing module is used for acquiring the historical browsing information of the new user when the user is detected to be the new user, searching the user with the similarity of the historical browsing information larger than a preset value as an associated user according to the historical browsing information, and then performing product association pushing on the new user according to the user figure of the associated user. According to the scheme, for a new user without historical data, the corresponding old user is matched in a mode of analyzing the similarity of historical browsing information, the historical browsing information can express the preference of the user to a certain degree, and the preference of the new user and the preference of the old user are possibly similar due to the similarity of the historical browsing information, so that the new user is subjected to product association pushing according to the user portrait of the associated user, the new user is accurately pushed, and the pushing accuracy and the conversion power are improved. But also can serve new and old users at the same time, thereby greatly widening the service range.
The same-class association pushing module is further used for acquiring personal information and interpersonal relationship of the user when the user is detected to be a new user, acquiring the user with the interpersonal relationship with the new user or with the similarity of the personal information larger than a preset value as an associated user, and recommending bank products to the new user based on the user association information of the associated user. Because the information data of the new user is limited, the bank products which are matched, analyzed and recommended only through the historical browsing information may not be proper, the scheme introduces the personal information and the interpersonal relationship of the user, finds out the more proper associated user based on the personal information and the interpersonal relationship, and therefore the recommended bank products are more in line with the preference and interest relevance of the user. Thereby improving the accuracy and conversion to power of the push.
A product policy management module: the system comprises a database, a database and a database, wherein the database is used for acquiring product charges, related preferential policy elements and product rule elements of bank products, sorting the product charges, the related preferential policy elements and the product rule elements according to a preset lookup template, and storing the sorted product charges, the related preferential policy elements and the product rule elements in a preset database;
a search module: the search module is used for acquiring search keywords of the bank products of the user, searching the reference module of the corresponding bank products according to the search keywords, and pushing the reference module to the user. The product policy management module can collect product charges, relevant preferential policy elements and product rule elements of bank products and arrange the product charges, the relevant preferential policy elements and the product rule elements into a lookup template, so that a user can search and find the product through the search module and know relevant information of the bank products in detail, and the phenomenon that the purchase intention of the user on the bank products is reduced due to the fact that the charges, the preferential policy and the rule are not published clearly is avoided, and the conversion power of the bank products is influenced.
The rule graph culture display module: the system is used for acquiring a purchase case of a bank product, acquiring an image-text explanation schematic diagram which is manufactured by combining the purchase case with product rule elements, and storing the image-text explanation schematic diagram and a reference template into a database in a correlation mode. Compared with a pure text design, the rule graph culture display module is made by collecting the image-text explanation schematic diagram which is made by combining the purchase case with the product rule elements, so that a new user can know the rule of the bank product more easily, and after all, not everyone can research the thorough text rule, and the user is prevented from giving up because the user does not know the bank product through the image-text explanation schematic diagram which is easier to understand, so that the conversion power of the bank product is influenced.
A product marketing management module; the system is used for acquiring popularization activities of various bank products and filling activity rules and propaganda advertisements corresponding to the popularization activities into a preset activity popularization template; the system is also used for matching users suitable for popularization activities according to the user association information of each user and the corresponding user portrait; and the method is also used for popularizing the activity popularization template of the bank product to the corresponding user.
The user number analysis and prediction module: the system comprises a database, a database server and a bank product, wherein the database is used for analyzing the number of potential users, the current user and the lost user of the current period of the bank product according to the user portrait of each user; and the system is also used for predicting the user data of the bank product in the next period according to the number of the potential users, the number of the current users, the number of the lost users and a preset neural network prediction model.
The promotion strategy adjusting module: the system is used for dynamically adjusting the promotion strategies of the bank products according to the user data of the bank products in the next period, wherein the promotion strategies comprise product charging pricing, preferential strategies and advertisement promotion strength. The sales volume of bank products is as the tide of sea waves, so that the adjustment of product charging pricing, preferential strategies and advertising promotion strength at proper time is very necessary. According to the scheme, the user data of the bank products in the next period can be predicted through the neural network prediction model, so that the popularization strategy of each bank product is dynamically adjusted, and the pushing accuracy and the conversion power are improved.
The foregoing is merely an example of the present invention, and common general knowledge in the field of known specific structures and characteristics is described herein in more detail, so that a person of ordinary skill in the art can understand all the prior art in the field and have the ability to apply routine experimentation before the present date, after knowing that all the common general knowledge in the field of the invention before the application date or the priority date of the invention, and the person of ordinary skill in the art can, in light of the teaching provided herein, combine his or her own abilities to complete and implement the present invention, and some typical known structures or known methods should not become an obstacle to the implementation of the present invention. It should be noted that, for those skilled in the art, without departing from the structure of the present invention, several changes and modifications can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicability of the patent. The scope of the claims of the present application shall be determined by the contents of the claims, and the description of the embodiments and the like in the specification shall be used to explain the contents of the claims.
Claims (7)
1. A bank product management system, characterized by: the server is included, and comprises the following modules:
the user information acquisition module: the system comprises a user management server, a user management server and a user management server, wherein the user management server is used for acquiring user association information of a user, and the user association information comprises historical purchase information and historical browsing information of the user on bank products, and identity information and asset information of the user;
a user portrait analysis module: the user portrait is generated according to the user correlation information;
the product information storage module: the system is used for storing the existing product information of the bank;
a recommendation model training module: the recommendation model training system is used for acquiring historical purchase information of each user, corresponding user portrait information and final income information of the user, and training the recommendation model according to the acquired information to obtain a trained recommendation model;
the product recommendation analysis module: the system comprises a recommendation model input module, a recommendation module and a recommendation module input module, wherein the recommendation model input module is used for inputting user association information of each user, corresponding user portrait and currently existing product information of a bank to generate a recommended product list of each user;
the similar correlation pushing module: and the product association pushing module is used for acquiring the historical browsing information of the new user when the user is detected to be the new user, searching the user with the similarity of the historical browsing information larger than a preset value as an associated user according to the historical browsing information, and then performing product association pushing on the new user according to the user figure of the associated user.
2. A banking product management system according to claim 1, characterized in that: the server comprises the following modules:
a comparison analysis module: the system is used for comparing and analyzing the historical purchasing information and the historical browsing information of the bank products by the user, analyzing the purchasing conversion rate of the user on the browsed bank products, and setting the promotion coefficient of the user image corresponding to the user according to the purchasing conversion rate.
3. A banking product management system according to claim 2, wherein: the server comprises the following modules:
a product policy management module: the system comprises a database, a database and a database, wherein the database is used for acquiring product charges, relevant preferential policy elements and product rule elements of each bank product, sorting the product charges, the relevant preferential policy elements and the product rule elements according to a preset lookup template, and storing the product charges, the relevant preferential policy elements and the product rule elements in a preset database after sorting;
a search module: the search module is used for acquiring search keywords of the bank products of the user, searching the reference module of the corresponding bank products according to the search keywords, and pushing the reference module to the user.
4. A banking product management system according to claim 3, characterized in that: the server comprises the following modules:
the rule graph culture display module: the system is used for acquiring a purchase case of a bank product, acquiring an image-text explanation schematic diagram which is manufactured by combining the purchase case with product rule elements, and storing the image-text explanation schematic diagram and a reference template into a database in a correlation mode.
5. A banking product management system according to claim 4, characterized in that: the server comprises the following modules:
a product marketing management module; the system is used for acquiring popularization activities of various bank products and filling activity rules and propaganda advertisements corresponding to the popularization activities into a preset activity popularization template; the system is also used for matching users suitable for popularization activities according to the user association information of each user and the corresponding user portrait; and the method is also used for popularizing the activity popularization template of the bank product to the corresponding user.
6. A banking product management system according to claim 1, characterized in that: the similar association pushing module is further used for acquiring personal information and interpersonal relationship of the user when the user is detected to be a new user, acquiring the user with the interpersonal relationship or the similarity of the personal information of the user to the new user larger than a preset value as an associated user, and recommending bank products to the new user based on the user association information of the associated user.
7. A banking product management system according to claim 6, wherein: the server comprises the following modules:
the user number analysis and prediction module comprises: the bank product management system is used for analyzing the number of potential users, the number of current users and the number of lost users of the current period of the bank product according to the user representation of each user; the system is also used for predicting the user data of the bank product in the next period according to the number of potential users, the number of current users, the number of lost users and a preset neural network prediction model;
the promotion strategy adjusting module: the system is used for dynamically adjusting the promotion strategies of the bank products according to the user data of the bank products in the next period, wherein the promotion strategies comprise product charging pricing, preferential strategies and advertisement promotion strength.
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