CN117726358A - User information processing method and device - Google Patents

Abstract

The application discloses a user information processing method and device, and belongs to the technical field of data processing. The user information processing method comprises the following steps: obtaining portrait information corresponding to each bank user based on at least one of basic information, target stream files and upstream and downstream information corresponding to each bank user; classifying a plurality of bank users based on the portrait information to obtain user groups of a plurality of categories; and executing target operation corresponding to the category based on at least one of the category of each user group and the portrait information. According to the user information processing method, financial products with high matching degree can be pushed to a bank user according to user demands, so that layered marketing is conveniently carried out on the bank user, and the working efficiency of the bank and the conversion rate of the products are improved.

Description

User information processing method and device

Technical Field

The application belongs to the technical field of data processing, and particularly relates to a user information processing method and device.

Background

In the process of recommending financial products to users, banks often need to analyze the running water situation of users and the like to accurately recommend products to users. The common flow analysis method cannot generate a comprehensive and accurate analysis report for each user, so that the matching degree of the user demands and recommended financial products is low, and the product conversion rate is low; in addition, the method cannot screen recommended user groups according to products, and has limited applicable scenes.

Disclosure of Invention

The present application aims to solve at least one of the technical problems existing in the prior art. Therefore, the user information processing method and device can push the financial products with higher matching degree to the bank users according to the user demands, are convenient for carrying out layered marketing on the bank users, and improve the working efficiency of the banks and the conversion rate of the products.

In a first aspect, the present application provides a method for processing user information, where the method includes:

obtaining portrait information corresponding to each bank user based on at least one of basic information, target stream files and upstream and downstream information corresponding to each bank user;

classifying a plurality of bank users based on the portrait information to obtain user groups of a plurality of categories;

and executing target operation corresponding to the category based on at least one of the category of each user group and the portrait information.

According to the user information processing method provided by the embodiment of the application, the portrait information corresponding to each bank user is obtained by processing at least one of the basic information, the target stream file and the upstream and downstream information of the bank user, the bank user is classified based on the portrait information to obtain a plurality of types of user groups, then the target operation corresponding to the types is executed based on the types of the user groups, financial products with higher matching degree can be pushed to the bank user according to the user requirements, the bank user can be conveniently marketed in a layering mode, and the working efficiency of the bank and the conversion rate of the products are improved.

The user information processing method according to one embodiment of the present application classifies a plurality of banking users based on the portrait information to obtain a plurality of user groups, including:

processing the target pipeline file based on a plurality of pipeline threshold values and a plurality of risk threshold values to obtain at least one of a plurality of pipeline labels and risk levels corresponding to each bank user; the running water label is used for representing the running water condition corresponding to the bank user;

and classifying the plurality of bank users based on at least one of the plurality of running water labels and the risk level to obtain the plurality of user groups.

The method for processing user information according to one embodiment of the present application classifies the plurality of banking users based on at least one of the plurality of running water labels and the risk level, to obtain the plurality of user groups, including:

acquiring an account type corresponding to the bank user based on at least one of the plurality of running water labels and the risk level;

and classifying the plurality of bank users based on the account types to obtain the user groups.

The user information processing method according to an embodiment of the present application, based on at least one of the category of each user group and the portrait information, performs a target operation corresponding to the category, including:

Based on the category of each user group, obtaining a product group matched with each user group;

and pushing the plurality of product groups to user groups corresponding to the product groups respectively.

The user information processing method according to one embodiment of the present application, wherein the performing, based on at least one of the category of each user group and the portrait information, a target operation corresponding to the category further includes:

in the case of a new product, determining a target user group matching the new product from a plurality of the user groups based on product characteristics of the new product;

pushing the new product to the target user group.

The user information processing method according to one embodiment of the present application, before obtaining portrait information corresponding to each bank user based on at least one of basic information, a target pipeline file, and upstream and downstream information corresponding to each bank user, further includes:

identifying the acquired first serial file corresponding to the bank user to obtain a second serial file in a target format;

comparing and analyzing the second flow file based on a target feature library to obtain the category corresponding to the second flow file; the target feature library comprises features of flow files corresponding to a plurality of categories;

And mapping the data corresponding to the second stream file to the target data structure based on the mapping relation between the stream file corresponding to the category and the target data structure, so as to obtain the target stream file.

The user information processing method according to an embodiment of the present invention obtains portrait information corresponding to each bank user based on at least one of basic information, a target pipeline file, and upstream and downstream information corresponding to each bank user, including:

and under the condition that the portrait information is obtained based on the upstream and downstream information, the portrait information comprises at least one of an upstream and downstream relation map and a transaction network map corresponding to the bank user.

In one embodiment of the present application, in a case where the portrait information includes an upstream-downstream relationship map corresponding to the bank user, the method for processing the user information includes performing, based on at least one of a category of each user group and the portrait information, a target operation corresponding to the category, including:

acquiring an upstream user and a downstream user corresponding to the bank user based on the upstream-downstream relationship map;

pushing the first product to the upstream and downstream users.

In an embodiment of the present application, in a case where the portrait information includes a transaction network map corresponding to the bank user, the method for processing user information further includes, based on at least one of a category of each user group and the portrait information, executing a target operation corresponding to the category, and further includes:

based on the transaction network map, acquiring transaction amounts corresponding to the upstream and downstream users;

and determining a target transaction amount greater than a target threshold value from the transaction amounts, and pushing the second product to a banking user corresponding to the target transaction amount.

In a second aspect, the present application provides a user information processing apparatus, the apparatus comprising:

the first processing module is used for obtaining portrait information corresponding to each bank user based on at least one of basic information, target stream files and upstream and downstream information corresponding to each bank user;

the second processing module is used for classifying a plurality of bank users based on the portrait information to obtain user groups of a plurality of categories;

and a third processing module, configured to execute a target operation corresponding to the category based on at least one of the category of each user group and the portrait information.

According to the user information processing device provided by the embodiment of the application, through processing at least one of basic information, target flow files and upstream and downstream information of a bank user, portrait information corresponding to each bank user is obtained, and further, the bank user is classified based on the portrait information to obtain a plurality of user groups, then, based on the categories of each user group, target operation corresponding to the categories is executed, financial products with higher matching degree can be pushed to the bank user according to user requirements, layered marketing is facilitated for the bank user, and the working efficiency of the bank and the conversion rate of the products are improved.

In a third aspect, the present application provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements the user information processing method according to the first aspect when executing the computer program.

In a fourth aspect, the present application provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a user information processing method as described in the first aspect above.

In a fifth aspect, the present application provides a computer program product comprising a computer program which, when executed by a processor, implements a user information processing method as described in the first aspect above.

The above technical solutions in the embodiments of the present application have at least one of the following technical effects:

the basic information, the target flow file and at least one of the upstream and downstream information of the bank users are processed to obtain the portrait information corresponding to each bank user, the bank users are classified based on the portrait information to obtain a plurality of user groups, then the target operation corresponding to the categories is executed based on the categories of each user group, financial products with high matching degree can be pushed to the bank users according to the user demands, the bank users can be marketed in a layering mode conveniently, and the working efficiency of banks and the conversion rate of the products are improved.

Further, by automatically identifying and analyzing the serial files and the like, the target serial files under the target data structure are obtained, the serial files of different banks can be identified and mapped to the target data structure with a uniform format under the condition that the serial file formats of different banks are different or the header meanings are different, so that the banks can conveniently check and find various risk points through the serial files, and the analysis and check efficiency is improved.

Furthermore, the target running file of the bank user is processed to obtain a plurality of running labels and risk levels corresponding to the bank user, so that account types corresponding to the bank user are obtained, the bank users are classified based on the account types to obtain a plurality of user groups, financial product groups corresponding to the user groups can be matched based on the user groups in the follow-up execution process, layered pushing and group pushing can be performed on the bank user, and pushing efficiency and pushing accuracy are improved.

Still further, under the condition that the bank pushes out the new product, the target user group matched with the new product is screened from a plurality of user groups of different categories through the product characteristics of the new product, and the new product is pushed to the target user group, so that audience screening of the new product can be realized, the matching degree between the new product and the requirements of the target user group is improved, and further, the conversion rate of the new product is improved.

Additional aspects and advantages of the application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the application.

Drawings

The foregoing and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings, wherein:

Fig. 1 is a flow chart of a user information processing method provided in an embodiment of the present application;

fig. 2 is a schematic diagram of a user information processing method according to an embodiment of the present application;

fig. 3 is a schematic structural diagram of a user information processing apparatus provided in an embodiment of the present application;

fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

Technical solutions in the embodiments of the present application will be clearly described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application are within the scope of the protection of the present application.

The terms first, second and the like in the description and in the claims, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged, as appropriate, such that embodiments of the present application may be implemented in sequences other than those illustrated or described herein, and that the objects identified by "first," "second," etc. are generally of a type and not limited to the number of objects, e.g., the first object may be one or more. Furthermore, in the description and claims, "and/or" means at least one of the connected objects, and the character "/", generally means that the associated object is an "or" relationship.

The user information processing method according to the embodiment of the present application is described below with reference to fig. 1 to 2.

The execution subject of the user information processing method may be a server, or may be a user information processing apparatus, or may also be a user's terminal, including but not limited to a mobile terminal and a non-mobile terminal.

For example, mobile terminals include, but are not limited to, cell phones, PDA smart terminals, tablet computers, vehicle-mounted smart terminals, and the like; non-mobile terminals include, but are not limited to, PC-side and the like.

As shown in fig. 1, the user information processing method includes: step 110, step 120 and step 130.

And 110, obtaining portrait information corresponding to each bank user based on at least one of basic information, target stream files and upstream and downstream information corresponding to each bank user.

In this step, the banking user is a user who transacts business at the bank.

The basic information corresponding to the bank user may include: gender, age, academic and monthly income.

The basic information of the bank user may further include: cash flow status, financial requirements, credit requirements, financial preferences, consumption preferences, repayment risk, and the like.

The target pipeline file is used for representing the fund status of a bank user and the like.

The target pipeline file may include bank pipelines, bill of payment treasures, micro-letter bill, digital currency bill, etc. of the bank user.

The upstream and downstream information of the banking user may be used to characterize the user's business, for example, the upstream and downstream information may characterize the user's business years, sales revenue, civil loans, credit, etc.

The upstream and downstream information may include the aggregate information and transaction amounts of the upstream and downstream users, etc.

The upstream users of the banking user may include suppliers of the banking user, etc.

The downstream users of the banking user may include customers of the banking user, etc.

The portrait information corresponding to the bank user may include: at least one of income summary, expense summary, daily deposit balance, income type summary, expense type summary, financial detail, expense detail, loan borrowing detail, behavior analysis, running verification, trade opponent expense detail, first five opponent income fluctuation, first five opponent expense fluctuation, income contribution detail, expense contribution detail, trade network map, enterprise upstream and downstream relation map and the like of the bank user.

In some embodiments, step 110 may further comprise:

in the case of obtaining the portrait information based on the upstream and downstream information, the portrait information includes at least one of an upstream and downstream relationship map and a transaction network map corresponding to the bank user.

In this embodiment, under the condition that the upstream and downstream information of the bank user is acquired, the upstream and downstream information of the bank user may be analyzed to obtain at least one of an upstream and downstream relationship map and a transaction network map of the bank user.

The upstream and downstream relationship map may include upstream users and downstream users corresponding to the bank users.

The transaction network map can comprise the transaction amount, frequency, fund flow direction and the like between the bank user and the first five counter parties, and the transaction network map can also comprise the information of the transaction amount and the like of the upstream and downstream users of the bank user at the bank.

In some embodiments, before step 110, the user information processing method may further include:

identifying the first serial file corresponding to the obtained bank user to obtain a second serial file in a target format;

comparing and analyzing the second flow file based on the target feature library to obtain the category corresponding to the second flow file; the target feature library comprises features of the flow files corresponding to various categories;

and mapping the data corresponding to the second streaming file to the target data structure based on the mapping relation between the streaming file corresponding to the category and the target data structure, so as to obtain the target streaming file.

In this embodiment, the first streamlet may be uploaded based on the user.

The first running water file may include a banking running water of a banking user, a bill of payment, a micro bill, a digital currency bill, and the like.

After the bank logs in the flow analysis system, the first flow file of the bank user can be uploaded.

The second streaming file is in a different file format than the first streaming file.

And identifying the first flow file to obtain a second flow file in the target format.

For example, the target format may be a Comma Separated Values (CSV) format.

In an actual implementation process, the first serial file may be identified based on an optical character recognition (Optical Character Recognition, OCR) technology, and in the identification process, the first serial file may be identified as a picture to output a second serial file in CSV format.

The category may be a bank to which the pipeline file corresponds.

The target feature library can be established based on the features of the corresponding flow files of each bank.

For example, the target feature library may include a feature of which row the form starts and the file content, and the like, and it may be determined which bank the running file belongs to based on the target feature library.

In the actual execution process, the second flow file can be compared based on the target feature library, weight scoring is carried out, then the feature with the weight score larger than the target preset threshold value is obtained, and the category of the second flow file is judged based on the feature.

The target data structure is a unified data structure corresponding to various categories.

The method can be used for summarizing the streaming files corresponding to various categories to obtain the data structure of the header of all the streaming files as a unified format, namely a target data structure.

Based on the stream files corresponding to the categories, the mapping relation between the header of the stream file corresponding to the category and the header of the target data structure can be obtained.

In the actual execution process, the data corresponding to the second streaming file can be mapped to the target data structure based on the mapping relation between the streaming file corresponding to the category and the target data structure, so as to obtain the target streaming file.

According to the user information processing method provided by the embodiment of the application, the target running files under the target data structure are obtained through automatic identification, analysis and the like of the running files, the running files of different banks can be identified under the condition that the running file formats of the different banks are different or the header meanings are different, and the running files of the different banks are mapped to the target data structure with the uniform format, so that the banks can conveniently find various risk points and the like through checking the running files, and the analysis and checking efficiency is improved.

And 120, classifying the plurality of bank users based on the portrait information to obtain user groups of a plurality of categories.

In this step, the categories corresponding to the bank user may include a financial conservation type, a financial robustness type, a financial balance type, a financial accumulation type, a financial aggressive type, and the like.

The categories corresponding to the banking user may also include high-yield levels, medium-yield levels, low-yield levels, and the like.

The user group corresponding to each category may include at least one banking user.

Based on the portrayal information, a plurality of banking users may be categorized to obtain a plurality of categories of user groups.

In some embodiments, step 120 may include:

processing the target running file based on the running threshold values and the risk threshold values to obtain at least one of a plurality of running labels and risk levels corresponding to each bank user; the running water label is used for representing the running water condition corresponding to the bank user;

and classifying the plurality of bank users based on at least one of the plurality of running water labels and the risk grades to obtain a plurality of user groups.

In this embodiment, the flowing water threshold may include a revenue threshold, a payout threshold, a rate of return threshold, a number of days of financial positive return threshold, and so on.

The risk threshold may include a bill risk threshold, a potential lending threshold, and the like.

The running water label is used for representing the running water condition of the bank user.

As shown in fig. 2, the running water label may include: the "average deposit balance" label a, label B, label C, etc., and the "financial details" label a, label B, label C, etc.

For example, a "average daily deposit balance" tag a may be set to mark running water of more than 10 ten thousand, a "financial detail" tag B to mark running water with a profit margin of 3% -5%, and a "financial detail" tag C to mark running water with a profit margin of more than 200 days.

As shown in fig. 2, the risk items may include: bill risk detection, potential lending, folk lending, potential complaint information, associated transaction identification, periodic expense prompts, and abnormal transaction prompts.

And analyzing the risk items corresponding to the bank users to obtain the risk grades corresponding to the bank users.

The risk level may include high risk, medium risk, low risk, and the like.

In some embodiments, classifying the plurality of banking users based on at least one of the plurality of pipeline labels and the risk level to obtain a plurality of user groups may include:

Acquiring an account type corresponding to a bank user based on at least one of a plurality of running water labels and risk levels;

based on the account types, classifying the bank users to obtain user groups.

In this embodiment, the account types corresponding to the bank user may include a financial conservation type, a financial robustness type, a financial balance type, a financial accumulation type, a financial aggressive type, and the like.

Based on account types corresponding to the bank users, the bank users of the same type can be classified into one type, and a user group is obtained.

Based on the account types, the bank users are classified to obtain user groups.

A user community may include at least one banking user.

In the actual execution process, when the daily deposit balance label A is set to mark running water of more than 10 ten thousand, the financial detail label B is set to mark running water with the profit margin of 3% -5%, the financial detail label C is set to mark running water with the profit margin of more than 200 days, and the risk grade is low risk, the second layer can mark a financial robustness label for bank users meeting the ABC label simultaneously and having low risk grade, namely account types corresponding to the bank users meeting the ABC label simultaneously are financial robustness.

Setting a plurality of running labels, marking each bank user based on the running labels satisfied by each bank user, obtaining the account types of each bank user, and classifying the plurality of bank users based on the plurality of account types to obtain a plurality of user groups.

According to the user information processing method provided by the embodiment of the application, the target running file of the bank user is processed to obtain a plurality of running labels and risk levels corresponding to the bank user, and then account types corresponding to the bank user are obtained, so that the plurality of bank users are classified based on the plurality of account types to obtain a plurality of user groups, financial product groups corresponding to the user groups can be matched based on the user groups in the follow-up execution process, layered pushing and group pushing can be performed on the bank user, and pushing efficiency and pushing accuracy are improved.

And 130, executing target operation corresponding to the category based on at least one of the category and the portrait information of each user group.

In this step, the target operation corresponds to a category of the user population.

The target operation may be to match a financial product group corresponding to the user group based on the category of the user group and push the financial product group to the user group.

The target operation may also be to match a user population corresponding to a product based on the product and push the product to the user population.

The target operations may also include pushing the product to users upstream and downstream of the banking user.

In actual execution, at least one financial product corresponding to the user community may be periodically pushed to the user community.

In some embodiments, the user information processing method may further include:

and processing the target flow file of the bank user to obtain a target analysis report corresponding to the bank user.

In this embodiment, the target analysis report may include a data overview and multidimensional risk assessment corresponding to the banking user.

The target pipeline file may be processed by Python, or may be processed by another algorithm, and may be selected based on a user, which is not limited in this application.

In actual execution, as shown in fig. 2, a target analysis report may be generated based on 7 risk models, 15 tag models, and 2 relationship maps.

The risk model may include, among other things, bill risk detection, potential lending, folk lending, potential complaint information, associated transaction identification, periodic expense cues, and abnormal transaction cues.

The tag model may include revenue summary, expense summary, average daily deposit balance, revenue type summary, expense type summary, financial details, loan borrowing details, behavioral analysis, running verification, trade opponent expense details, top five opponent revenue fluctuations, top five opponent expense fluctuations, revenue contribution details, and expense contribution details.

The relationship profile may include a transaction network profile and an upstream-downstream relationship profile (enterprise account).

In the actual execution process, the target running file can be analyzed through Python, the transaction opponents are induced, and then the information of the transaction amount, the transaction time, the transaction flow direction and the like of each transaction opponent is obtained.

And then, expressing the information such as the transaction amount, the frequency, the fund flow direction and the like of the first five opponents in a map rendering mode, so that the fund condition of the bank user can be more intuitively analyzed.

In some embodiments, the identification and expansion of potential users can be rapidly realized by further condition screening of the upstream and downstream relationship maps and the transaction network maps in the target analysis report.

In some embodiments, where the image information includes a corresponding upstream-downstream relationship map for the bank user, step 130 may further include:

Acquiring an upstream user and a downstream user corresponding to a bank user based on the upstream-downstream relationship map;

pushing the first product to the downstream user.

In this embodiment, the first product may be a credit product, or may be another financial product, without limitation.

Under the condition that the upstream and downstream relation maps corresponding to the bank users are obtained, the upstream and downstream users of the bank users can be obtained, for example, suppliers of the bank users can be obtained.

Credit products may be pushed to the vendor.

In some embodiments, where the image information includes a transaction network map corresponding to the bank user, step 130 may further include:

based on the transaction network map, obtaining the corresponding transaction amount of each upstream and downstream user;

and determining a target transaction amount greater than a target threshold from the transaction amounts, and pushing the second product to a banking user corresponding to the target transaction amount.

In this embodiment, the transaction amounts of the upstream and downstream users may be acquired under the condition that the transaction network map corresponding to the banking user is obtained.

The transaction amount corresponding to the upstream and downstream users can include flow information of the upstream and downstream users, transaction amount at the bank or opponent bank, and the like.

The target threshold may be 10w or 20w, or the like, or may be other values, may be user-defined, and is not limited in this application.

Each upstream and downstream user corresponds to a transaction amount, the target transaction amount being a transaction amount greater than a target threshold.

The banking user to which the target transaction amount corresponds may be an upstream user, or may be a downstream user.

The second product may be a financial product, a credit product, or other product, without limitation.

Based on the transaction network map, a user with a large transfer transaction can be identified from a plurality of upstream and downstream users, and financial products or credit products can be pushed to the batch of users.

The inventor finds that in the research and development process, a method for assisting a investigation department to process job crime cases based on a bank bill analysis result exists in the related technology, the method cannot process flow files except for bank bills, financial products with higher matching degree cannot be pushed to users based on the flow files of the users, and the application scene is limited.

According to the method and the system for analyzing the cash flow state of the bank users, the cash flow state, the demand, the preference, the risk and the like of the bank users are comprehensively evaluated, comprehensive and accurate analysis reports can be generated for each bank user, multidimensional risk indexes, enterprise upstream and downstream relation patterns and transaction opponent fund business patterns of the bank users can be further mined and calculated for the bank, financial products can be more accurately recommended to the bank users, and the conversion rate is improved.

By customizing the thresholds corresponding to the indexes such as user behavior habit, repayment capability, account balance, fund fluctuation and the like, the users meeting the thresholds can be screened out, so that personalized and accurate pushing of products can be performed.

Potential users and financial requirements thereof are accurately matched in daily flow analysis, bad account rate and repudiation can be reduced, and fine user management and continuous marketing are realized.

By classifying the bank users to obtain a plurality of user groups, the bank users with potential requirements and good fund flows, the bank users with potential other lines and the bank users with the loan amount needing to be adjusted can be screened and marked, the difficulty of mining the potential other lines is reduced, the further screening and pushing can be carried out through the relationship chain in the existing users, the channels of the bank expansion users are enriched, and more financial products are pushed.

According to the user information processing method provided by the embodiment of the application, the portrait information corresponding to each bank user is obtained by processing at least one of the basic information, the target stream file and the upstream and downstream information of the bank user, the bank user is classified based on the portrait information to obtain a plurality of types of user groups, then the target operation corresponding to the types is executed based on the types of the user groups, financial products with higher matching degree can be pushed to the bank user according to the user requirements, the bank user can be conveniently marketed in a layering mode, and the working efficiency of the bank and the conversion rate of the products are improved.

In some embodiments, step 130 may include:

based on the category of each user group, obtaining a product group matched with each user group;

and pushing the plurality of product groups to user groups corresponding to the product groups respectively.

In this embodiment, at least one financial product may be included in the product group.

Based on the categories of the user groups, product groups that match the user groups may be obtained.

After obtaining the product group that matches the user group, the product group may be pushed to the user group corresponding to the product group.

For example, in the case where the user community is "financing-robust," a robust financial product may be acquired and then pushed to the user community.

In some embodiments, step 130 may further comprise:

in the case of a new product, determining a target user group matching the new product from a plurality of user groups based on product characteristics of the new product;

and pushing the new product to the target user group.

In this embodiment, the new product may be a new financial product that is offered by a bank.

In the case where a new product exists, the product characteristics of the new product can be acquired.

Product characteristics of a new product may include "low and medium risk" and "Ji Jizheng benefit", etc.

Based on the product characteristics of the new product, a target user population that matches the new product may be determined from the plurality of user populations.

The categories of the target user population correspond to the product features of the new product.

For example, in the case where the product characteristics of the new product are "low and medium risk" and "Ji Jizheng benefit", a target user population of the category "financial robustness" will be obtained.

After determining the target user population that matches the new product, the new product may be pushed to the target user population.

In the actual execution process, when a new financial product is pushed out by a bank and needs to be promoted, the product characteristics of the new product can be obtained.

Based on the product characteristics of the new product, a product tag corresponding to the new product can be set.

In the event that the product tag matches an account tag corresponding to a user population, the user population may be determined to be the target user population.

And pushing the new product to the target user group.

In some embodiments, after pushing the new product to the target user population, the conversion of the new product may also be recorded.

After the target user group is determined, the screening conditions may also be reset to determine that other user groups are performing new product pushing.

After pushing the new product to other user groups, the user may keep track of the conversion rate of the new product.

According to the user information processing method provided by the embodiment of the application, under the condition that a new product is pushed out by a bank, the target user group matched with the new product is screened from a plurality of user groups of different categories through the product characteristics of the new product, and the new product is pushed to the target user group, so that audience screening of the new product can be realized, the matching degree between the new product and the requirements of the target user group is improved, and further the conversion rate of the new product is improved.

The overall mode of the user information processing method provided in the embodiment of the present application is specifically described below.

In the actual execution process, the bank can log in the running water analysis system, establish an independent project folder for the bank user A, and upload the target running water file of the user A to the project folder.

The method comprises the steps of carrying out data analysis on a target flowing water file of a user A to obtain income summary, expense summary and daily deposit balance of all uploaded flowing water of the user A, and displaying 15 labels of income type summary, expense type summary, financial statement, income and expense statement, loan borrowing statement, behavior analysis, flowing water verification, trading opponent income details, front 5 large opponent income fluctuation, front 5 large opponent expense fluctuation, income contribution statement, expense contribution statement and trading network map and upstream and downstream relation map (enterprise account) in a visual chart mode.

And displaying the risk items and the risk numbers of the user A through 7 risk prediction models of bill risk detection, potential borrowing, folk borrowing, potential complaint information, associated transaction identification, periodic expense prompt and abnormal transaction prompt.

And classifying the plurality of financial products, setting a label and threshold combination condition based on the user requirement, and accurately pushing the screened financial products to the user A based on the combination condition.

For example, in the case that the running water file of the user a is analyzed to obtain that the financial habit of the user a is to ensure a smooth positive profit, a combination condition of a profit margin higher than 5%, a daily balance exceeding 80 ten thousand and a steady financial product may be set, and a financial product conforming to the condition is pushed to the user a based on the combination condition.

And classifying all the bank users according to indexes such as balance, balance fluctuation, risk level, behavior habit and the like to obtain user groups of a plurality of categories, and pushing product groups matched with the user groups to the user groups based on the categories of the user groups.

For example, when the category corresponding to the user a is the middle-yielding category B, product groups with matched requirements and matched conditions can be uniformly screened for the category B users, so as to perform group pushing.

The method can carry out further condition screening based on the upstream and downstream relation patterns and the transaction network patterns corresponding to the users, and the identified potential users are drawn into the user group to carry out group pushing, and the identified important users are accurately pushed.

In the case of a new product being launched by a bank, conditions may be set for the new product to screen a target user population matching the new product, and the new product may be pushed to the target user population, and then the conversion rate of the new product may be recorded.

In the method, the system and the device, the running files of the users are identified to obtain various running data and multidimensional risk assessment analysis results corresponding to the bank users, and corresponding operations are executed based on the categories of the bank users, so that the problems of full credit adjustment, risk assessment and accurate pushing of financial products of the banks can be solved, and marketing and customer extension of the banks are facilitated.

The user information processing apparatus provided in the present application will be described below, and the user information processing apparatus described below and the user information processing method described above may be referred to correspondingly to each other.

According to the user information processing method provided by the embodiment of the application, the execution subject can be the user information processing device. In the embodiment of the present application, a user information processing apparatus provided in the embodiment of the present application will be described by taking a user information processing method performed by the user information processing apparatus as an example.

The embodiment of the application also provides a user information processing device.

As shown in fig. 3, the user information processing apparatus includes: a first processing module 310, a second processing module 320, and a third processing module 330.

The first processing module 310 obtains portrait information corresponding to each bank user based on at least one of basic information, a target pipeline file and upstream and downstream information corresponding to each bank user;

the second processing module 320 is configured to classify a plurality of banking users based on the image information, to obtain a plurality of user groups of categories;

the third processing module 330 is configured to execute a target operation corresponding to the category based on at least one of the category and the portrait information of each user group.

According to the user information processing device provided by the embodiment of the application, through processing at least one of basic information, target flow files and upstream and downstream information of a bank user, portrait information corresponding to each bank user is obtained, and further, the bank user is classified based on the portrait information to obtain a plurality of user groups, then, based on the categories of each user group, target operation corresponding to the categories is executed, financial products with higher matching degree can be pushed to the bank user according to user requirements, layered marketing is facilitated for the bank user, and the working efficiency of the bank and the conversion rate of the products are improved.

In some embodiments, the second processing module 320 may also be configured to:

processing the target running file based on the running threshold values and the risk threshold values to obtain at least one of a plurality of running labels and risk levels corresponding to each bank user; the running water label is used for representing the running water condition corresponding to the bank user;

and classifying the plurality of bank users based on at least one of the plurality of running water labels and the risk grades to obtain a plurality of user groups.

In some embodiments, the second processing module 320 may also be configured to:

acquiring an account type corresponding to a bank user based on at least one of a plurality of running water labels and risk levels;

based on the account types, classifying the bank users to obtain user groups.

In some embodiments, the third processing module 330 may also be configured to:

based on the category of each user group, obtaining a product group matched with each user group;

and pushing the plurality of product groups to user groups corresponding to the product groups respectively.

In some embodiments, the third processing module 330 may also be configured to:

in the case of a new product, determining a target user group matching the new product from a plurality of user groups based on product characteristics of the new product;

And pushing the new product to the target user group.

In some embodiments, the user information processing apparatus may further include a fourth processing module, configured to identify, before obtaining the portrait information corresponding to each bank user based on at least one of the basic information, the target pipeline file, and the upstream and downstream information corresponding to each bank user, the first pipeline file corresponding to the obtained bank user, and obtain the second pipeline file in the target format;

comparing and analyzing the second flow file based on the target feature library to obtain the category corresponding to the second flow file; the target feature library comprises features of the flow files corresponding to various categories;

and mapping the data corresponding to the second streaming file to the target data structure based on the mapping relation between the streaming file corresponding to the category and the target data structure, so as to obtain the target streaming file.

In some embodiments, the first processing module 310 may also be configured to:

in the case of obtaining the portrait information based on the upstream and downstream information, the portrait information includes at least one of an upstream and downstream relationship map and a transaction network map corresponding to the bank user.

In some embodiments, where the image information includes a corresponding upstream-downstream relationship map for the bank user, the third processing module 330 may be further configured to:

Acquiring an upstream user and a downstream user corresponding to a bank user based on the upstream-downstream relationship map;

pushing the first product to the downstream user.

In some embodiments, where the image information includes a transaction network map corresponding to a banking user, the third processing module 330 may be further configured to:

based on the transaction network map, obtaining the corresponding transaction amount of each upstream and downstream user;

and determining a target transaction amount greater than a target threshold from the transaction amounts, and pushing the second product to a banking user corresponding to the target transaction amount.

The user information processing apparatus in the embodiment of the present application may be an electronic device, or may be a component in an electronic device, for example, an integrated circuit or a chip. The electronic device may be a terminal, or may be other devices than a terminal. By way of example, the electronic device may be a mobile phone, tablet computer, notebook computer, palm computer, vehicle-mounted electronic device, mobile internet appliance (Mobile Internet Device, MID), augmented reality (augmented reality, AR)/Virtual Reality (VR) device, robot, wearable device, ultra-mobile personal computer, UMPC, netbook or personal digital assistant (personal digital assistant, PDA), etc., but may also be a server, network attached storage (Network Attached Storage, NAS), personal computer (personal computer, PC), television (TV), teller machine or self-service machine, etc., and the embodiments of the present application are not limited in particular.

The user information processing apparatus in the embodiment of the present application may be an apparatus having an operating system. The operating system may be an Android operating system, an IOS operating system, or other possible operating systems, which is not specifically limited in the embodiments of the present application.

The user information processing apparatus provided in the embodiment of the present application can implement each process implemented by the embodiments of the methods of fig. 1 to 2, and in order to avoid repetition, a detailed description is omitted here.

In some embodiments, as shown in fig. 4, the embodiment of the present application further provides an electronic device 400, including a processor 401, a memory 402, and a computer program stored in the memory 402 and capable of running on the processor 401, where the program when executed by the processor 401 implements the respective processes of the above-mentioned user information processing method embodiment, and the same technical effects can be achieved, and for avoiding repetition, a description is omitted herein.

The electronic device in the embodiment of the application includes the mobile electronic device and the non-mobile electronic device described above.

In another aspect, the present application further provides a computer program product, where the computer program product includes a computer program stored on a non-transitory computer readable storage medium, where the computer program includes program instructions, when the program instructions are executed by a computer, can execute each process of the above-mentioned user information processing method embodiment, and achieve the same technical effects, and for avoiding repetition, a description is omitted herein.

In yet another aspect, the present application further provides a non-transitory computer readable storage medium, on which a computer program is stored, where the computer program is implemented when executed by a processor to perform each process of the above-mentioned user information processing method embodiment, and the same technical effects can be achieved, and for avoiding repetition, a description is omitted herein.

In still another aspect, an embodiment of the present application further provides a chip, where the chip includes a processor and a communication interface, where the communication interface is coupled to the processor, and the processor is configured to run a program or an instruction, implement each process of the above embodiment of the user information processing method, and achieve the same technical effect, so that repetition is avoided, and no further description is given here.

It should be understood that the chips referred to in the embodiments of the present application may also be referred to as system-on-chip chips, chip systems, or system-on-chip chips, etc.

The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.

From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.

Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and are not limiting thereof; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the corresponding technical solutions.

Claims (11)

1. A user information processing method, comprising:

obtaining portrait information corresponding to each bank user based on at least one of basic information, target stream files and upstream and downstream information corresponding to each bank user;

classifying a plurality of bank users based on the portrait information to obtain user groups of a plurality of categories;

and executing target operation corresponding to the category based on at least one of the category of each user group and the portrait information.

2. The method for processing user information according to claim 1, wherein the classifying the plurality of bank users based on the portrait information to obtain a plurality of categories of user groups includes:

processing the target pipeline file based on a plurality of pipeline threshold values and a plurality of risk threshold values to obtain at least one of a plurality of pipeline labels and risk levels corresponding to each bank user; the running water label is used for representing the running water condition corresponding to the bank user;

and classifying the plurality of bank users based on at least one of the plurality of running water labels and the risk level to obtain the plurality of user groups.

3. The method of claim 2, wherein classifying the plurality of banking users based on at least one of the plurality of running water labels and the risk level to obtain the plurality of user groups comprises:

acquiring an account type corresponding to the bank user based on at least one of the plurality of running water labels and the risk level;

and classifying the plurality of bank users based on the account types to obtain the user groups.

4. A user information processing method according to any one of claims 1 to 3, wherein the performing a target operation corresponding to the category based on at least one of the category of each of the user groups and the portrait information includes:

based on the category of each user group, obtaining a product group matched with each user group;

and pushing the plurality of product groups to user groups corresponding to the product groups respectively.

5. A user information processing method according to any one of claims 1 to 3, wherein the performing a target operation corresponding to the category based on at least one of the category of each of the user groups and the portrait information further includes:

In the case of a new product, determining a target user group matching the new product from a plurality of the user groups based on product characteristics of the new product;

pushing the new product to the target user group.

6. A user information processing method according to any one of claims 1 to 3, wherein before the image information corresponding to each bank user is obtained based on at least one of the basic information, the target pipeline file, and the upstream and downstream information corresponding to each bank user, the method further comprises:

identifying the acquired first serial file corresponding to the bank user to obtain a second serial file in a target format;

comparing and analyzing the second flow file based on a target feature library to obtain the category corresponding to the second flow file; the target feature library comprises features of flow files corresponding to a plurality of categories;

and mapping the data corresponding to the second stream file to the target data structure based on the mapping relation between the stream file corresponding to the category and the target data structure, so as to obtain the target stream file.

7. The method for processing user information according to any one of claims 1 to 3, wherein the obtaining of the portrait information corresponding to each bank user based on at least one of basic information, a target pipeline file, and upstream and downstream information corresponding to each bank user includes:

And under the condition that the portrait information is obtained based on the upstream and downstream information, the portrait information comprises at least one of an upstream and downstream relation map and a transaction network map corresponding to the bank user.

8. The method according to claim 7, wherein in a case where the portrait information includes an upstream-downstream relationship map corresponding to the bank user, the performing a target operation corresponding to a category based on at least one of the category of each user group and the portrait information includes:

acquiring an upstream user and a downstream user corresponding to the bank user based on the upstream-downstream relationship map;

pushing the first product to the upstream and downstream users.

9. The method according to claim 8, wherein in a case where the portrayal information includes a transaction network map corresponding to the bank user, the performing a target operation corresponding to the category based on at least one of the category of each user group and the portrayal information, further comprises:

based on the transaction network map, acquiring transaction amounts corresponding to the upstream and downstream users;

and determining a target transaction amount greater than a target threshold value from the transaction amounts, and pushing the second product to a banking user corresponding to the target transaction amount.

10. A user information processing apparatus, comprising:

the first processing module is used for obtaining portrait information corresponding to each bank user based on at least one of basic information, target stream files and upstream and downstream information corresponding to each bank user;

the second processing module is used for classifying a plurality of bank users based on the portrait information to obtain user groups of a plurality of categories;

and a third processing module, configured to execute a target operation corresponding to the category based on at least one of the category of each user group and the portrait information.

11. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the user information processing method according to any one of claims 1-9 when the program is executed by the processor.