CN117557381A

CN117557381A - Financial product screening method, system, terminal equipment and storage medium

Info

Publication number: CN117557381A
Application number: CN202311524104.8A
Authority: CN
Inventors: 陈厚含; 王浩轩; 陈侠; 王立彬; 叶张雯; 林朝曼; 苏雪玲; 王苏庆; 任军
Original assignee: Shaanxi Laocaichen Financial Management Co ltd
Current assignee: Shaanxi Laocaichen Financial Management Co ltd
Priority date: 2023-11-15
Filing date: 2023-11-15
Publication date: 2024-02-13

Abstract

The present application relates to the field of financial science and technology, and in particular, to a method, a system, a terminal device, and a storage medium for screening financial products. Acquiring target keywords corresponding to financial products in financial consultation information; screening the financial browsing information according to the target keywords to form a corresponding first-level financial product screening set; if the first-level financial product screening set contains the same type of financial products corresponding to the historical purchase financial product information, acquiring the corresponding same type of financial products and forming a corresponding second-level financial product screening set; if the second-level financial product screening set contains the same-series financial products corresponding to the current held financial product information, acquiring the corresponding same-series financial products; and the recommendation priority of each same-series financial product is set according to the association degree of the same-series financial product and the financial product in the current held financial product information. The technical scheme has the effect of improving the accuracy and reliability of directional screening of financial products.

Description

Financial product screening method, system, terminal equipment and storage medium

Technical Field

The present application relates to the field of financial science and technology, and in particular, to a method, a system, a terminal device, and a storage medium for screening financial products.

Background

The directional screening of the financial products refers to screening out products which best meet the demands of users from a plurality of financial products by using specific methods and tools according to the personalized demands of the users, the risk preference, the investment target and the like. The screening method can filter out products which do not meet the requirements according to the specific conditions and preferences of users, thereby providing more accurate and personalized financial product recommendation.

The purpose of the directional screening of the financial products is to meet the personalized requirements of users and optimize the user experience. Through directional screening, a user can more conveniently find financial products meeting the self requirements, and tedious screening and comparing processes in a large number of products are avoided. Meanwhile, the directional screening can provide more proper product recommendation according to the risk preference and the investment target of the user, and help the user to realize the investment target.

In practical application, the directional screening of the financial products needs to rely on a large amount of user data and product data, but at present, matching analysis between a large number of financial products and the user data is not in place, so that it is difficult to screen financial products with higher matching degree for the user, and the accuracy and reliability of the directional screening of the financial products are reduced.

Disclosure of Invention

In order to improve accuracy and reliability of directional screening of financial products, the application provides a method, a system, terminal equipment and a storage medium for screening financial products.

In a first aspect, the present application provides a financial product screening method, comprising the steps of:

acquiring financial association information corresponding to a target user, wherein the financial association information comprises financial product information, historical purchase financial product information, financial consultation information and financial browsing information which are currently held by the target user;

extracting keywords from the financial consultation information to obtain target keywords corresponding to financial products in the financial consultation information;

screening the financial browsing information according to the target keywords to form a corresponding first-level financial product screening set;

if the primary financial product screening set contains the same type of financial products corresponding to the historical purchase financial product information, acquiring the corresponding same type of financial products from the primary financial product screening set, and forming a corresponding secondary financial product screening set according to the same type of financial products;

if the second-level financial product screening set contains the same-series financial products corresponding to the current held financial product information, acquiring the corresponding same-series financial products from the second-level financial product screening set;

If the same-series financial products are multiple, the recommendation priority of each same-series financial product is set according to the association degree of the same-series financial products and the financial products in the current held financial product information, and the multiple same-series financial products are pushed to the user according to the recommendation priority.

By adopting the technical scheme, the financial browsing information is screened according to the target keywords to form the first-stage financial product screening set, so that financial products of interest to a user can be screened out at an early stage, immediately, whether the first-stage financial product screening set has the same type of financial products corresponding to historical purchase financial product information or not is analyzed and judged, the locking range of investment preference products of the user can be further enlarged, namely, the same type of financial products are calibrated and classified to form the corresponding second-stage financial product screening set, then the financial products in the same series with the current user are obtained from the second-stage financial product screening set, further, the financial products in the same series in the second-stage financial product screening set can be screened and filtered by taking the current interesting financial product information of the user as a selected condition, and then the recommendation priority of each financial product in the same series is set according to the association degree of the financial products in the current holding state, so that more personalized financial product recommendation can be provided according to the preference and association degree of the user, and the accuracy and reliability of directionally screening the financial products for the user are improved.

Optionally, the financial browsing information is screened according to the target keyword, and the forming of the corresponding first-level financial product screening set includes the following steps:

carrying out semantic association on the target keywords according to a preset keyword semantic rule to obtain corresponding associated semantic words;

and screening the financial browsing information according to the target keywords and the associated semantic words to form a corresponding first-level financial product screening set.

By adopting the technical scheme, financial products which are more in line with the interests of the user can be screened out according to the personal preferences and the demands of the user according to semantic association, so that more personalized financial product recommendation can be provided for the user, and the satisfaction degree of the user is improved.

Optionally, after performing semantic association on the target keyword according to a preset keyword semantic rule, the method further includes the following steps:

if the associated semantic words are a plurality of, acquiring financial characteristics of the financial products corresponding to the associated semantic words;

and setting feature labels corresponding to the associated semantic words according to the financial features to form a corresponding feature classification table.

By adopting the technical scheme, the feature classification table can help the system to conduct directional recommendation. By matching the feature labels selected by the user according to the requirements and preferences of the user, more personalized financial product recommendation meeting the requirements of the user can be provided for the user, and the satisfaction degree of the user is improved.

Optionally, if the first-level financial product screening set includes financial products of the same type corresponding to the historical purchase financial product information, obtaining the corresponding financial products of the same type from the first-level financial product screening set, and forming a corresponding second-level financial product screening set according to the financial products of the same type, including the following steps:

if the first-level financial product screening set contains the same type of financial products corresponding to the historical purchase financial product information, judging whether the same type of financial products are a plurality of financial products or not;

if the number of the same type of financial products is multiple, acquiring the buyback rate and the periodic yield corresponding to each type of financial products;

setting corresponding screening and sorting conditions according to the buyback rate and the periodic yield, and screening and sorting a plurality of financial products of the same type according to the sorting and sorting conditions to form a corresponding recommended sorting table as the secondary financial product screening set.

By adopting the technical scheme, the screening and sorting conditions are set according to the buyback rate and the periodic yield, a plurality of financial products of the same type can be sorted according to the important indexes of the user preference, so that more personalized and accurate recommendation results can be provided for the user, and the satisfaction degree of the user and the screening reliability are improved.

Optionally, if the first-level financial product screening set has the same type of financial product corresponding to the historical purchase financial product information, the method further includes the following steps after judging whether the same type of financial product is plural:

acquiring a risk control strategy corresponding to each financial product of the same type, wherein the risk control strategy comprises a risk management method, investment combination dispersity and a risk control strategy;

combining the risk control strategy including a risk management method, the investment portfolio dispersity and the risk control strategy to form a corresponding target screening combination index;

and screening and combining the financial products of the same type according to the target screening and combining indexes to form a corresponding target directional screening group.

By adopting the technical scheme, the financial products of the same type are screened and combined according to the target screening combination index. Weights or rules can be set, and products are ordered according to the importance degree of the index to form a target directional screening group, so that financial product selection meeting the requirements of users is provided.

Optionally, if the second-level financial product screening set has a same series of financial products corresponding to the currently held financial product information, the method further includes the following steps after obtaining the corresponding same series of financial products from the second-level financial product screening set:

If the same-series financial products are multiple, performing risk assessment on each same-series financial product to obtain corresponding product characteristics;

combining the investment preference type corresponding to the user and the product characteristics to generate personalized identifiers corresponding to the same-series financial products;

and combining a plurality of the same-series financial products according to the personalized identification to form a corresponding personalized recommendation group.

By adopting the technical scheme, a plurality of financial products in the same series are combined according to the generated personalized identifier to form a personalized recommendation group. The products can be ordered and combined according to the matching degree of the personalized identifications by setting weights or rules, so that personalized product combination recommendation which meets the investment requirements and the risk preference of users can be provided.

Optionally, after combining the plurality of the same-series financial products according to the personalized identifier to form a corresponding personalized recommendation group, the method further includes the following steps:

if the personalized recommendation groups are multiple, carrying out diversified investment analysis on each personalized recommendation group to generate personalized analysis results corresponding to the users;

And carrying out risk performance evaluation on the personalized analysis results to generate risk performance evaluation reports corresponding to the personalized recommendation groups.

By adopting the technical scheme, the risk and performance of the personalized recommendation group are evaluated, and a corresponding report is generated. By evaluating the risks and the performances of the personalized recommendation group, the method can help users to better understand and compare the risks and the benefits of different investment combinations, and further improve the accuracy and the reliability of directional screening of financial products.

In a second aspect, the present application provides a financial product screening system comprising:

the information acquisition module is used for acquiring financial association information corresponding to a target user, wherein the financial association information comprises financial product information, historical purchase financial product information, financial consultation information and financial browsing information which are currently held by the target user;

the key information extraction module is used for extracting the key words of the financial consultation information and obtaining target key words corresponding to financial products in the financial consultation information;

the first-level screening module is used for screening the financial browsing information according to the target keywords to form a corresponding first-level financial product screening set;

The second-level screening module is used for acquiring the corresponding same type of financial products from the first-level financial product screening set and forming a corresponding second-level financial product screening set according to the same type of financial products if the first-level financial product screening set contains the same type of financial products corresponding to the historical purchase financial product information;

the same-series financial analysis module is used for acquiring the corresponding same-series financial products from the secondary financial product screening set if the secondary financial product screening set contains the same-series financial products corresponding to the current held financial product information;

and the financial product pushing module is used for setting the recommendation priority of each same-series financial product according to the association degree of the same-series financial products and the financial products in the current held financial product information and pushing the same-series financial products to the user according to the recommendation priority if the same-series financial products are multiple.

According to the technical scheme, the financial browsing information is screened through the key information extraction module according to the target keywords, the first-level financial product screening set is formed through the first-level screening module, so that interested financial products of a user can be screened out at an early stage, whether the financial products of the same type corresponding to the historical purchase financial product information exist in the first-level financial product screening set or not is judged through analysis of the second-level screening module, the locking range of investment preference products of the user can be further enlarged, namely, the financial products of the same type as the current user are calibrated and classified to form the corresponding second-level financial product screening set, then the financial products of the same type as the current user are obtained from the second-level financial product screening set, further, the financial products of the same type in the second-level financial product screening set can be screened through the same-series financial analysis module according to the association degree of the financial products of the same type and the current financial products, and recommendation priority of each financial product of the same type is set through the financial product pushing module, and accordingly, the accuracy and reliability of directional screening of the financial products for the user can be improved.

In a third aspect, the present application provides a terminal device, which adopts the following technical scheme:

the terminal equipment comprises a memory and a processor, wherein the memory stores computer instructions capable of running on the processor, and the processor adopts the financial product screening method when loading and executing the computer instructions.

By adopting the technical scheme, the computer instructions are generated by the financial product screening method and stored in the memory to be loaded and executed by the processor, so that the terminal equipment is manufactured according to the memory and the processor, and the financial product screening method is convenient to use.

In a fourth aspect, the present application provides a computer readable storage medium, which adopts the following technical scheme:

a computer readable storage medium having stored therein computer instructions which, when loaded and executed by a processor, employ a financial product screening method as described above.

By adopting the technical scheme, the financial product screening method generates the computer instructions, stores the computer instructions in the computer readable storage medium to be loaded and executed by the processor, and facilitates the reading and storage of the computer instructions through the computer readable storage medium.

In summary, the present application includes at least one of the following beneficial technical effects: the financial browsing information is screened according to the target keywords to form a first-stage financial product screening set, so that financial products of interest to a user can be screened out at an early stage, whether the first-stage financial product screening set has the same type of financial products corresponding to historical purchase financial product information or not is analyzed and judged immediately, the locking range of investment preference products of the user can be further achieved, namely, the same-type financial products are calibrated and classified to form a corresponding second-stage financial product screening set, then the financial products in the same series with the current user are obtained from the second-stage financial product screening set, further, the financial products in the same series in the second-stage financial product screening set can be screened and filtered according to the correlation degree of the financial products in the same series and the current holding financial products, and recommendation priority of each financial product in the same series is set according to the preference and the correlation degree of the user, so that more personalized financial product recommendation is provided, and the accuracy and reliability of directionally screening the financial products for the user are improved.

Drawings

Fig. 1 is a schematic flow chart of steps S101 to S106 in a financial product screening method of the present application.

Fig. 2 is a schematic flow chart of steps S201 to S202 in the financial product screening method of the present application.

Fig. 3 is a schematic flow chart of steps S301 to S302 in the financial product screening method of the present application.

Fig. 4 is a schematic flow chart of steps S401 to S403 in the financial product screening method of the present application.

Fig. 5 is a schematic flow chart of steps S501 to S503 in the financial product screening method of the present application.

Fig. 6 is a schematic flow chart of steps S601 to S603 in the financial product screening method of the present application.

Fig. 7 is a schematic flow chart of steps S701 to S702 in the financial product screening method of the present application.

Fig. 8 is a schematic block diagram of a financial product screening system according to the present application.

Reference numerals illustrate:

1. an information acquisition module; 2. a key information extraction module; 3. a first-stage screening module; 4. a secondary screening module; 5. the same-series financial analysis module; 6. and a financial product pushing module.

Detailed Description

The present application is described in further detail below in conjunction with figures 1-8.

The embodiment of the application discloses a financial product screening method, as shown in fig. 1, comprising the following steps:

S101, acquiring financial association information corresponding to a target user, wherein the financial association information comprises financial product information, historical purchase financial product information, financial consultation information and financial browsing information which are currently held by the target user;

s102, extracting keywords from the financial consultation information to obtain target keywords corresponding to financial products in the financial consultation information;

s103, screening the financial browsing information according to the target keywords to form a corresponding first-level financial product screening set;

s104, if the first-level financial product screening set contains financial products of the same type corresponding to the historical purchase financial product information, acquiring the corresponding financial products of the same type from the first-level financial product screening set, and forming a corresponding second-level financial product screening set according to the financial products of the same type;

s105, if the second-level financial product screening set has the same-series financial products corresponding to the current held financial product information, acquiring the corresponding same-series financial products from the second-level financial product screening set;

s106, if the same-series financial products are multiple, the recommendation priority of each same-series financial product is set according to the association degree of the same-series financial products and the financial products in the current held financial product information, and the multiple same-series financial products are pushed to the user according to the recommendation priority.

In step S101, the financial-related information refers to information related to financial behaviors and preferences of the user. Specifically, the currently held financial product information refers to information about a financial product currently held by a target user, including a product type, an investment amount, an investment period, etc., and by knowing the financial product currently held by the user, the user's investment preference and risk tolerance can be known. The historical purchase financial product information refers to related information of financial products purchased by a target user in the past, including product types, purchase amounts, purchase time and the like, and the historical purchase behavior of the user is analyzed to know the investment experience and preference of the user, so that references are provided for personalized recommendation.

And secondly, the financial consultation information refers to information of a target user consulting financial products or investment related problems on a financial institution or platform, and the attention points and the demands of the user can be known by knowing the consultation behaviors of the user, so that a basis is provided for providing personalized financial advice. The financial browsing information refers to the record of browsing financial products or related information on a financial website, application or platform by a target user, and the interest and attention degree of the user to different types of financial products can be known by analyzing the browsing behaviors of the user, so that guidance is provided for personalized recommendation.

In step S102, keyword extraction in financial consulting information may acquire financial products and investment fields of interest to the user. The target keywords corresponding to the financial products refer to keywords or terms related to the specific financial products in the financial consultation information. The type of financial products, the investment field or the specific investment tools focused by the user can be further known through the target related words of the related financial products in the financial consultation information.

In step S103, the first-level financial product screening set refers to screening the first-level financial products associated with the plurality of financial products according to the target keywords of the financial products focused by the user in the financial browsing information. Primary financial products refer to specific types of financial products, such as stocks, funds, bonds, insurance, etc.

Specifically, when the financial browsing information is screened according to the target keywords, a first-level financial product screening set can be formed by the following steps: firstly, screening out financial browsing information related to keywords according to target keywords, wherein the information may comprise financial products browsed by a user, financial market analysis, investment strategies and the like; then, extracting specific financial product types from the screened financial browsing information, and identifying the related financial product types according to the financial product target keywords focused by the user; and finally, sorting and classifying the extracted financial product types to form a first-level financial product screening set, wherein the screening set can be used as the first-level classification of the financial products focused by the user, so that the follow-up data analysis and personalized recommendation are convenient.

Wherein, the same type of financial products refers to financial products having the same or similar financial attributes, functions and characteristics. They may belong to different issuers or different brands, but in essence belong to the same category. For example, the same category of financial products may include stocks, bonds, funds, insurance, and the like. There may be different types of subdivisions between these financial products, but they share similar market characteristics and investment attributes.

In step S104, the second-level financial product screening set further screens out the same type of financial products corresponding to the historical purchase financial product information based on the first-level financial product screening set, and through this screening process, the purchase history and preference of the user can be more accurately matched, so as to provide more personalized financial product recommendation meeting the user' S requirements.

Specifically, according to the historical purchase financial product information existing in the primary financial product screening set, the secondary financial product screening set may be formed according to the following steps: firstly, finding out the financial products of the same type as the information of the historical purchase financial products from a first-level financial product screening set, so that the financial products of the same type which are purchased or focused by a user can be screened out; and then, sorting and classifying the screened financial products of the same type to form a secondary financial product screening set. This screening set may serve as a secondary classification of the financial products of interest to the user, more specifically matching the user's purchase history and preferences; finally, according to the product information in the secondary financial product screening set, more targeted financial product recommendation and service can be provided, and personalized requirements of users are met.

And if the first-level financial product screening set does not have the same type of financial products corresponding to the historical purchase financial product information, the corresponding financial product types in the historical purchase financial product information are fused into the first-level financial product screening set to form an updated first-level financial product screening set.

In step S105, the same-series financial products refer to other financial products having the same or similar information as the currently held financial products, and by acquiring the same-series financial products, personalized recommendation to the user can be further refined, and financial product selection with more relevance and comparability can be provided.

Specifically, according to the information of the currently held financial products in the secondary financial product screening set, the same series of financial products can be obtained according to the following steps: firstly, finding out the financial products which are the same as or similar to the information of the currently held financial products from the secondary financial product screening set, so that other financial products in the same series with the financial products currently held by the user can be screened out; then, sorting and classifying the screened same-series financial products to form a same-series financial product set, wherein the set can be used as a supplement or alternative choice of the financial products currently held by a user; finally, according to the characteristics of the same-series financial products and the requirements of users, more relevant and comparable financial product recommendation and services are provided, so that the users can be helped to make more intelligent financial decisions.

The same series of financial products refer to financial products with the same or similar product characteristics and attributes under the same product issuing agency or brand. The same family of financial products is typically derived or variant products based on the original successful product. They may differ in risk-benefit characteristics, investment strategies, terms, etc., but still have similar product positioning and marketing goals. For example, the same series of financial products may include different deadlines of regular deposits, different types of fund products, and so forth.

And if the two-level financial product screening set does not have the same series of financial products corresponding to the current held financial product information, directly fusing the related financial products in the current held financial product information of the user into the two-level financial product screening set to serve as the updated two-level financial product screening set.

In step S106, the recommendation priority is determined according to the association degree between the same series of financial products and the currently held financial products, and the higher the association degree, the higher the recommendation priority is given to the financial products. By setting the recommendation priority, financial product recommendation which meets the requirements and interests of users can be provided, and user experience and satisfaction are improved.

Specifically, according to the association degree of the same-series financial products and the information of the currently held financial products, the recommendation priority and pushing can be set according to the following steps: firstly, analyzing and evaluating the association degree of the same-series financial products and the currently held financial products, wherein the association degree can be comprehensively evaluated according to the characteristics, the attributes, the risk and income characteristics and the like of the products; then, according to the evaluation result of the association degree, the recommendation priority of each financial product in the same series is set, and the financial products with high association degree are given higher recommendation priority, so that the financial products are more suitable for the selection of users; and finally, pushing the plurality of same-series financial products to the user according to the recommendation priority. The pushing can be performed through various channels, such as mobile application, email, short message, etc., so as to ensure that the user can receive the recommended information in time.

Moreover, if the same series of financial products are single, namely the financial products belong to one series, the financial products are pushed directly according to the association degree of each financial product in the same series and the financial product currently held by the user.

According to the financial product screening method provided by the embodiment, the financial browsing information is screened according to the target keywords to form the first-stage financial product screening set, so that the financial products of interest to the user can be screened out at an early stage, immediately, whether the first-stage financial product screening set has the same type of financial products corresponding to the historical purchase financial product information or not is analyzed and judged, the locking range of the investment preference products of the user can be further achieved, namely, the financial products of the same type are calibrated and classified to form the corresponding second-stage financial product screening set, then the financial products of the same type as the current user are obtained from the second-stage financial product screening set, further, the financial products of the same type in the second-stage financial product screening set can be screened and filtered according to the association degree of the financial products of the same type with the current financial products, and recommendation priority of each financial product of the same type is set according to the preference and association degree of the user, and accordingly more personalized financial product recommendation can be provided, and accuracy and reliability of targeted screening of the financial products for the user are improved.

In one implementation manner of this embodiment, as shown in fig. 2, step S103 of screening the financial browsing information according to the target keyword, to form a corresponding first-level financial product screening set includes the following steps:

s201, carrying out semantic association on target keywords according to preset key semantic rules to obtain corresponding associated semantic words;

s202, screening the financial browsing information according to the target keywords and the associated semantic words to form a corresponding first-level financial product screening set.

In steps S201 to S202, the preset keyword semantic rule is a set of rules or rule sets that are determined in advance for the target keyword by the pointer, and is used for deducing the semantic related word related to the target keyword according to the current target keyword. These rules may be designed based on linguistic features such as word sense, part of speech, context, etc., to capture the semantic meaning of keywords and find other words or concepts related thereto. And screening the financial browsing information according to the target keywords and the associated semantic words to form a first-level financial product screening set.

For example, the target keyword is "a stock", and according to a preset key semantic rule, an associated semantic word related to "a stock" may be obtained, such as "a stock related stock market", "a stock trade", "a stock market", and the like. And then, screening the financial browsing information according to the target keyword 'A stock' and the associated semantic words to form a first-level financial product screening set. Only the financial product information related to the stock A and the related semantic words thereof, such as the stock A trading platform, the stock A investment financial products and the like, is selected, so that the financial products related to the target keywords can be screened out and provided for the user to select and reference.

According to the financial product screening method, financial products which are more in line with the interests of the user can be screened out according to the personal preferences and the demands of the user according to semantic association, so that more personalized financial product recommendation can be provided for the user, and the user satisfaction is improved.

In one implementation manner of this embodiment, as shown in fig. 3, in step S201, semantic association is performed on the target keyword according to a preset key semantic rule, and after obtaining the corresponding associated semantic word, the method further includes the following steps:

s301, if a plurality of associated semantic words are provided, acquiring financial characteristics of financial products corresponding to each associated semantic word;

s302, setting feature labels of all corresponding associated semantic words according to the financial features to form a corresponding feature classification table.

In steps S301 to S302, the financial characteristics refer to characteristics or attributes of the financial products in various aspects, and may be used to describe and distinguish different financial products. Then, according to the financial characteristics, characteristic labels of the associated semantic words can be set to form a corresponding characteristic classification table. Therefore, the financial products can be classified and generalized according to the financial characteristics, and the user can conveniently select and compare the financial products.

For example, there are three associated semantic words: A. b, C. And acquiring corresponding financial characteristics aiming at each associated semantic word. For the associated semantic word a, the corresponding financial features are: high risk, high yield, short term investment, etc.; for the associated semantic word B, the corresponding financial features are: low risk, stable returns, long term investments, etc.; for the associated semantic word C, the corresponding financial features are: medium risk, average benefit, medium-to-long investment, etc.

Further, feature tags of the respective associated semantic words are set based on the obtained financial features. For example, the associated semantic word a is labeled "high risk high benefit", the associated semantic word B is labeled "low risk steady benefit", and the associated semantic word C is labeled "medium risk average benefit". Thus, a corresponding feature classification table is formed.

According to the financial product screening method provided by the embodiment, the feature classification table can help the system to conduct directional recommendation. By matching the feature labels selected by the user according to the requirements and preferences of the user, more personalized financial product recommendation meeting the requirements of the user can be provided for the user, and the satisfaction degree of the user is improved.

In one implementation manner of the present embodiment, as shown in fig. 4, step S104, if the first-stage financial product screening set includes the same type of financial products corresponding to the historical purchase financial product information, acquires the corresponding same type of financial products from the first-stage financial product screening set, and forms a corresponding second-stage financial product screening set according to the same type of financial products, includes the following steps:

S401, if the first-level financial product screening set has the same type of financial products corresponding to the historical purchase financial product information, judging whether the same type of financial products are a plurality of financial products;

s402, if the number of the same type of financial products is multiple, acquiring the buyback rate and the periodic yield corresponding to each type of financial products;

s403, setting corresponding screening and sorting conditions according to the buyback rate and the periodic yield, and screening and sorting a plurality of financial products of the same type according to the sorting and sorting conditions to form a corresponding recommended sorting table as a secondary financial product screening set.

In steps S401 to S402, the repurchase rate refers to a ratio in which the financial product can be repurchased within a certain period, and the period rate of return refers to a rate of return of the financial product within a certain period. By obtaining the return rates and periodic return rates for the same type of financial product, the products can be compared and evaluated. The rate of return may reflect the liquidity of the financial product, i.e., the liquidity that the user may obtain through return when funds are needed, while the rate of return may reflect the profitability of the financial product over a period.

For example, the financial products historically purchased by the user are money funds, and a plurality of money-based products corresponding to the money-based products are screened and concentrated by the first-level financial products, so that the buyback rate and the periodic yield rate of the money-based products can be obtained for comparison. Wherein, the buyback rate of the money-based foundation A is 95%, the cycle rate of return is 3%, the buyback rate of the money-based foundation B is 98%, the cycle rate of return is 4%, the buyback rate of the money-based foundation C is 90%, and the cycle rate of return is 2%.

Further, by comparing the rate of return and the periodic rate of return of these monetary-based products, their liquidity and profitability can be assessed. For example, money funds with high buyback rate are more mobile, and money funds with high periodic rate of return can obtain more returns.

In step S403, corresponding screening and sorting conditions may be set according to the buyback rate and the periodic yield, so as to screen and sort a plurality of financial products of the same type. By setting the sorting conditions, the financial products can be sorted according to the preference and the demand of the user, so that a recommendation sorting table is formed as a secondary financial product screening set.

For example, order from high to low with buyback rate: the financial products of the same type are ordered from high to low in buyback rate. A high return rate product means higher flowability and faster funds recovery capacity; ordered from high to low in cycle rate of return: the financial products of the same type are ranked from high to low in terms of periodic yield. A product with a high cycle yield means that a higher profitability can be obtained in a certain cycle; comprehensive sequencing: the buyback rate and the periodic yield are comprehensively considered, the buyback rate and the periodic yield are ranked according to a certain weight, and different weights can be set to comprehensively rank according to the importance degree of the buyback rate and the periodic yield of a user.

And secondly, sorting a plurality of financial products of the same type by setting a screening sorting condition, thereby forming a recommended sorting table as a secondary financial product screening set, and selecting financial products meeting the requirements of users according to the sorting set. For example, if the user has a high mobility requirement, a financial product with a high purchase rate may be selected; if the user pursues higher revenue, a financial product with higher periodic revenue rate may be selected.

According to the financial product screening method, screening and sorting conditions are set according to the buyback rate and the periodic yield, a plurality of financial products of the same type can be sorted according to important indexes of user preference, so that more personalized and accurate recommendation results can be provided for users, and the satisfaction degree of the users and the screening reliability are improved.

In one implementation manner of this embodiment, as shown in fig. 5, in step S401, if the first-level financial product screening set has the same type of financial products corresponding to the historical purchase financial product information, the method further includes the following steps after determining whether the same type of financial products are plural:

s501, acquiring risk control strategies corresponding to various types of financial products, wherein the risk control strategies comprise a risk management method, investment combination dispersity and a risk control strategy;

S502, combining a risk control strategy comprising a risk management method, investment combination dispersity and a risk control strategy to form a corresponding target screening combination index;

s503, screening and combining the financial products of the same type according to the target screening and combining indexes to form a corresponding target directional screening group.

In step S501, for each type of financial product, there is a corresponding risk control policy. Risk control strategies include risk management approaches, portfolio dispersion, and risk control strategies that can help users reduce risk and preserve funds security.

In particular, different financial products may employ different risk management approaches. The risk management method in the scheme comprises the steps of establishing a risk control system, setting risk tolerance, formulating a risk control rule and the like, wherein the risk can be evaluated and managed by establishing the risk control system, and corresponding measures are taken to reduce the risk; the dispersity of the investment portfolio refers to that investment funds are dispersed to different asset types or different financial products so as to reduce the overall risk of the investment portfolio, the risk of a single asset or a single financial product can be prevented from greatly influencing the whole investment portfolio through the dispersion investment, and a user can select financial products in different types, industries and areas to realize the dispersion of the investment portfolio; the risk control strategy is specific countermeasures adopted by the pointer to different risk situations, for example, damage stopping measures, dynamic adjustment of bin positions and the like can be adopted for market risks; for credit risk, financial products with higher credit ratings may be selected; for the fluidity risk, a financial product or the like having good fluidity may be selected.

Secondly, combining the risk control strategies including a risk management method, investment portfolio dispersion degree and a risk control strategy can form corresponding target screening combination indexes. The target screening combination index is set according to the requirements and the preference of the user on risk control, and can comprise maximum allowable loss, maximum withdrawal, risk and benefit ratio and the like. By setting the target screening combination index, the user can be helped to select financial products which meet the risk bearing capacity and investment targets of the user.

In step S503, according to the target screening combination index, screening and combining can be performed on each type of financial product to form a corresponding target directional screening group. The target directional screening group screens a group of products meeting the requirements of the users from the same type of financial products according to the requirements and targets of the users.

Specifically, for each target screening combination indicator, a corresponding threshold or requirement may be set. For example, the maximum allowable loss may be set to 10%, the maximum withdrawal may be set to 20%, and the risk-benefit ratio may be set to 2. Then, for each type of financial product, a corresponding index value is calculated according to its risk control strategy and historical performance. And screening out products meeting the user setting requirements to form a target directional screening group.

Second, the formation of targeted screening groups may help users find products that meet their needs among many types of financial products. The user can select the target directional screening group which is most suitable for the user according to the risk bearing capacity, the investment target and the preference of the user. Through screening the combination, the user can obtain better investment effect on the premise of reducing risk.

According to the financial product screening method provided by the embodiment, all the financial products of the same type are screened and combined according to the target screening combination index. Weights or rules can be set, and products are ordered according to the importance degree of the index to form a target directional screening group, so that financial product selection meeting the requirements of users is provided.

In one implementation manner of the present embodiment, as shown in fig. 6, in step S105, if the second-level financial product screening set has a same-series financial product corresponding to the current held financial product information, the method further includes the following steps after obtaining the corresponding same-series financial product from the second-level financial product screening set:

s601, if a plurality of same-series financial products are provided, performing risk assessment on each same-series financial product to obtain corresponding product characteristics;

S602, combining investment preference types and product characteristics corresponding to users to generate personalized identifiers corresponding to each same-series financial product;

s603, combining the plurality of same-series financial products according to the personalized identification to form a corresponding personalized recommendation group.

In step S601, when there are a plurality of financial products in the same series, in order to improve the reliability of pushing the financial products to the user, risk assessment needs to be performed for each series. Through risk assessment, corresponding product characteristics can be obtained, so that a user can better know the risk characteristics and the suitability of the product.

The risk assessment is a process of comprehensively assessing and analyzing the risk of the financial product. In risk assessment, market risk, credit risk, liquidity risk, operational risk, and the like may be considered. Corresponding product features can be obtained through risk assessment. Product characteristics refer to specific attributes and characteristics of a financial product that are used to describe and distinguish differences between different products. They provide important information about the product, helping the user to better understand the nature, characteristics and fitness of the product.

In steps S602 to S603, according to the investment preference type and product characteristics of the user, a corresponding personalized identifier may be generated for identifying the financial product that the user is suitable for. The investment preference type refers to the preference tendency of the user in terms of different investment directions, investment deadlines, risk preferences, etc. during the investment process. Investment preference types are typically categorized according to factors such as the risk bearing capacity of the user, investment goals and time expectations.

For example, a personalized identity for a product of the same family is a robust + long term investment deadline + invested in stocks and bonds + open funds + profit model is a capital increment + management team focused on a value investment strategy, the personalized identity is applicable to robust users who prefer long term investments, willing to invest in various asset categories such as stocks and bonds, open funds facilitate the purchase and redemption of users, the profit model is primarily achieved by capital increment, the product to which the identity is directed is focused by the management team using the value investment strategy focusing on finding underestimated investment opportunities.

The personalized recommendation group can be formed by personalized identification of the investment preference type and the product characteristics of the user and combining a plurality of financial products in the same series according to different identifications. The personalized recommendation group is used for recommending the matched financial products to the user together according to the preference and the demand of the user and the characteristics and the attributes of the products so as to meet the personalized investment demand of the user.

According to the financial product screening method provided by the embodiment, a plurality of financial products in the same series are combined according to the generated personalized identifier to form a personalized recommendation group. The products can be ordered and combined according to the matching degree of the personalized identifications by setting weights or rules, so that personalized product combination recommendation which meets the investment requirements and the risk preference of users can be provided.

In one implementation manner of this embodiment, as shown in fig. 7, in step S603, a plurality of peer-series financial products are combined according to the personalized identifier to form a corresponding personalized recommendation group, and then the method further includes the following steps:

s701, if the personalized recommendation groups are multiple, carrying out diversified investment analysis on each personalized recommendation group to generate personalized analysis results corresponding to the user;

s702, performing risk performance evaluation on the personalized analysis results, and generating risk performance evaluation reports corresponding to the personalized recommendation groups.

In steps S701 to S702, diversified investments are a strategy for reducing risks and improving reliability of portfolios by dispersing investments in different types, different risk levels, and different time periods of financial products.

For example, disperse investment risk: by investing funds in different types of financial products, such as stocks, bonds, funds, real estate, etc., the risk of a particular investment target may be reduced. Different types of assets may behave differently in different market environments, so dispersing investments into different asset classes may reduce the volatility of the overall portfolio.

The personalized analysis result is generated by generating a corresponding personalized investment scheme for the user according to the investment preference type of the user and the characteristics of investment products in the recommendation group. The personalized analysis results may include specific investment advice, asset allocation proportions, expected returns, and the like.

Secondly, risk performance assessment is to evaluate personalized analysis results, and mainly comprises assessment of risk and performance of investment portfolios. Risk assessment may be assessed by calculating the volatility, maximum withdrawal, etc. of the portfolio. Performance assessment may be assessed by calculating annual rate of return for portfolios, summer ratio, etc. Through risk performance assessment, risk and performance of investment schemes of different personalized recommendation groups can be objectively assessed.

It should be noted that, the risk performance evaluation report corresponding to each personalized recommendation group is generated by arranging the result of risk performance evaluation into a report form, and providing detailed risk performance analysis and interpretation for the user. The report may include the portfolio constituents of each recommendation group, the interpretation of risk assessment indicators, the interpretation of performance assessment indicators, etc., to help the user better understand and assess the risk and performance of the individual recommendation groups to make more informed investment decisions.

The embodiment of the application discloses a financial product screening system, as shown in fig. 8, includes:

the information acquisition module 1 is used for acquiring financial association information corresponding to a target user, wherein the financial association information comprises financial product information currently held by the target user, historical purchase financial product information, financial consultation information and financial browsing information;

the key information extraction module 2 is used for extracting key words of the financial consultation information and obtaining target key words corresponding to financial products in the financial consultation information;

the first-level screening module 3 is used for screening the financial browsing information according to the target keywords to form a corresponding first-level financial product screening set;

the second-level screening module 4 is used for acquiring corresponding financial products of the same type from the first-level financial product screening set and forming a corresponding second-level financial product screening set according to the financial products of the same type if the first-level financial product screening set contains the financial products of the same type corresponding to the historical purchase financial product information;

the same-series financial analysis module 5 is used for acquiring corresponding same-series financial products from the secondary financial product screening set if the same-series financial products corresponding to the current held financial product information exist in the secondary financial product screening set;

And the financial product pushing module 6 is used for setting the recommendation priority of each same-series financial product according to the association degree of the same-series financial product and the financial product in the current holding financial product information if the same-series financial products are multiple, and pushing the multiple same-series financial products to the user according to the recommendation priority.

According to the financial product screening system provided by the embodiment, the financial browsing information is screened through the key information extraction module 2 according to the target key words, and the primary financial product screening set is formed through the primary screening module 3, so that interested financial products of a user can be screened out at an early stage, whether the primary financial product screening set has the same type of financial products corresponding to the historical purchase financial product information or not is judged through the secondary screening module 4, the investment preference products of the user can be further locked in scope, namely, the financial products of the same type are calibrated and classified to form the corresponding secondary financial product screening set, then the financial products of the same type as the current user are obtained from the secondary financial product screening set, further, the financial products of the same type in the secondary financial product screening set can be screened and filtered through the same-series financial analysis module 5 according to the association degree of the financial products of the same type and the current financial products, and recommendation priority of each financial product of the same type is set through the financial product pushing module 6, accordingly, more personalized financial products can be provided according to the preference and association degree of the user, and the reliability of the financial products of the user oriented screening can be improved.

It should be noted that, the financial product screening system provided in this embodiment of the present application further includes each module and/or corresponding sub-module corresponding to the logic function or logic step of any one of the foregoing financial product screening methods, so that the same effects as each logic function or logic step are achieved, and specifically will not be described herein.

The embodiment of the application also discloses a terminal device, which comprises a memory, a processor and computer instructions stored in the memory and capable of running on the processor, wherein when the processor executes the computer instructions, any one of the financial product screening methods in the embodiment is adopted.

The terminal device may be a computer device such as a desktop computer, a notebook computer, or a cloud server, and the terminal device includes, but is not limited to, a processor and a memory, for example, the terminal device may further include an input/output device, a network access device, a bus, and the like.

The processor may be a Central Processing Unit (CPU), or of course, according to actual use, other general purpose processors, digital Signal Processors (DSP), application Specific Integrated Circuits (ASIC), ready-made programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc., and the general purpose processor may be a microprocessor or any conventional processor, etc., which is not limited in this application.

The memory may be an internal storage unit of the terminal device, for example, a hard disk or a memory of the terminal device, or may be an external storage device of the terminal device, for example, a plug-in hard disk, a Smart Memory Card (SMC), a secure digital card (SD), or a flash memory card (FC) provided on the terminal device, or the like, and may be a combination of the internal storage unit of the terminal device and the external storage device, where the memory is used to store computer instructions and other instructions and data required by the terminal device, and the memory may be used to temporarily store data that has been output or is to be output, which is not limited in this application.

Any one of the financial product screening methods in the embodiments is stored in the memory of the terminal device through the terminal device, and is loaded and executed on the processor of the terminal device, so that the terminal device is convenient to use.

The embodiment of the application also discloses a computer readable storage medium, and the computer readable storage medium stores computer instructions, wherein when the computer instructions are executed by a processor, any one of the financial product screening methods in the embodiment is adopted.

The computer instructions may be stored in a computer readable medium, where the computer instructions include computer instruction codes, where the computer instruction codes may be in a source code form, an object code form, an executable file form, or some middleware form, etc., and the computer readable medium includes any entity or device capable of carrying the computer instruction codes, a recording medium, a usb disk, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a Random Access Memory (RAM), an electrical carrier signal, a telecommunication signal, a software distribution medium, etc., where the computer readable medium includes but is not limited to the above components.

Wherein, through the present computer readable storage medium, any one of the financial product screening methods of the above embodiments is stored in the computer readable storage medium and loaded and executed on a processor to facilitate the storage and application of the above methods.

The foregoing are all preferred embodiments of the present application, and are not intended to limit the scope of the present application in any way, therefore: all equivalent changes in structure, shape and principle of this application should be covered in the protection scope of this application.

Claims

1. A financial product screening method, comprising the steps of:

2. The method of claim 1, wherein the step of screening the financial browsing information according to the target keyword to form a corresponding first-level financial product screening set comprises the steps of:

3. The financial product screening method according to claim 2, further comprising the steps of, after semantically associating the target keywords according to a preset keyword semantic rule, obtaining corresponding keyword semantic words:

4. The method of claim 1, wherein if the primary financial product screening set has the same type of financial product corresponding to the historical purchase financial product information, obtaining the corresponding same type of financial product from the primary financial product screening set, and forming a corresponding secondary financial product screening set according to the same type of financial product comprises the steps of:

5. The method of claim 4, further comprising the steps of, if the primary financial product screening set has a plurality of types of financial products corresponding to the historical purchase financial product information, determining whether the plurality of types of financial products are present:

6. The method of claim 1, further comprising the steps of, if the second-level financial product screening set has a same series of financial products corresponding to the currently held financial product information, acquiring the corresponding same series of financial products from the second-level financial product screening set:

7. The method of claim 6, further comprising the steps of, after combining the plurality of the same-series financial products according to the personalized identifier to form a corresponding personalized recommendation group:

8. A financial product screening system, comprising:

the information acquisition module (1) is used for acquiring financial association information corresponding to a target user, wherein the financial association information comprises financial product information, historical purchase financial product information, financial consultation information and financial browsing information which are currently held by the target user;

the key information extraction module (2) is used for extracting the key words of the financial consultation information and obtaining target key words corresponding to financial products in the financial consultation information;

the first-level screening module (3) is used for screening the financial browsing information according to the target keywords to form a corresponding first-level financial product screening set;

the second-level screening module (4) is used for acquiring the corresponding same type of financial products from the first-level financial product screening set and forming a corresponding second-level financial product screening set according to the same type of financial products if the first-level financial product screening set contains the same type of financial products corresponding to the historical purchase financial product information;

The same-series financial analysis module (5) is used for acquiring the corresponding same-series financial products from the secondary financial product screening set if the secondary financial product screening set contains the same-series financial products corresponding to the current held financial product information;

and the financial product pushing module (6) is used for setting the recommendation priority of each same-series financial product according to the association degree of the same-series financial product and the financial product in the current held financial product information and pushing a plurality of the same-series financial products to the user according to the recommendation priority if the same-series financial products are a plurality of the financial products.

9. A terminal device comprising a memory and a processor, wherein the memory has stored therein computer instructions executable on the processor, the processor employing a financial product screening method according to any one of claims 1 to 7 when the computer instructions are loaded and executed by the processor.

10. A computer readable storage medium having stored therein computer instructions which, when loaded and executed by a processor, employ a financial product screening method according to any one of claims 1 to 7.