Banking business recommendation method and device, product and medium

Abstract

The embodiment of the invention discloses a bank business recommendation method and device, a product and a medium, and is suitable for the field of financial science and technology, and the method comprises the steps: obtaining a user identifier of a user, and determining the historical business information of the user and a user group to which the user belongs according to the user identifier; according to the historical business information of the user, determining the investment preference of the user for the historical business, and according to the investment preference of the historical business, determining candidate business; determining a target service based on the investment preference of the candidate service and holding information of other users in the user group for the candidate service; and recommending a target service to the user. According to the technical scheme provided by the invention, the target service can be accurately determined, so that the accuracy and efficiency of service recommendation are improved.

Description

Technical Field

[0001] This invention relates to the field of big data, and in particular to a recommendation method, apparatus, product, and medium for banking services. Background Technology

[0002] With the increasing variety of financial products, customers can easily feel confused when faced with diverse choices, while banks struggle to accurately recommend suitable services to their customers. For banks, accurate recommendations can effectively improve business conversion rates, increase revenue, and enhance customer stickiness and loyalty. For customers, personalized recommendations help them quickly find financial products that meet their needs, saving decision-making time and improving service satisfaction. At the industry competition level, optimizing recommendation systems has become a key point of competition among banks, enhancing their market competitiveness and helping them stand out in a fiercely competitive market.

[0003] However, current banking recommendations primarily rely on traversing all products, calculating the current purchase rate or yield, and then recommending products based on these rates. This approach has significant technical problems. Firstly, traversing a large number of products increases algorithm complexity, consumes significant resources, and results in slow response times, making real-time recommendations impossible. Secondly, this method cannot determine user investment preferences, leading to low matching rates between recommendations and customer needs, and consequently, low accuracy in business recommendations. Summary of the Invention

[0004] This invention provides a method, apparatus, product, and medium for recommending banking services. Through the technical solutions of the embodiments of this invention, resources required for service recommendations can be saved, the accuracy of service recommendations can be improved, and the efficiency of service recommendations can be increased.

[0005] In a first aspect, embodiments of the present invention provide a method for recommending banking services, comprising:

[0006] Obtain the user's user identifier, and determine the user's historical business information and the user group to which the user belongs based on the user identifier;

[0007] Based on the user's historical business information, determine the user's investment preference for the historical business, and based on the investment preference for the historical business, determine candidate businesses;

[0008] Based on the investment preferences of the candidate services and the holding information of other users in the user group regarding the candidate services, the target service is determined;

[0009] Recommend the target service to the user.

[0010] Secondly, embodiments of the present invention provide a recommendation device for banking services, comprising:

[0011] The acquisition module is used to acquire the user's user identifier and determine the user's historical business information and the user group to which the user belongs based on the user identifier;

[0012] The candidate service determination module is used to determine the user's investment preference for the historical services based on the user's historical service information, and to determine candidate services based on the investment preference for the historical services.

[0013] The target business determination module is used to determine the target business based on the investment preferences of the candidate businesses and the holding information of other users in the user group regarding the candidate businesses;

[0014] The recommendation module is used to recommend target services to the user.

[0015] Thirdly, embodiments of the present invention provide an electronic device, the electronic device comprising:

[0016] At least one processor; and,

[0017] A memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the recommended method for banking operations as described in any one of the embodiments of the present invention.

[0019] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the recommended method for banking operations as described in any one of the embodiments of the present invention.

[0020] This invention provides a method, apparatus, product, and medium for recommending banking services. The method includes: obtaining a user's user identifier; determining the user's historical business information and the user group to which the user belongs based on the user identifier; determining the user's investment preferences for the historical business based on the historical business information; determining candidate businesses based on the investment preferences for the historical business; determining a target business based on the investment preferences for the candidate businesses and the holding information of other users in the user group regarding the candidate businesses; and recommending the target business to the user. Specifically, historical business information can be used to determine investment preferences for historical businesses, and then, based on the investment preferences for candidate businesses and the holding information of other users in the user group regarding the candidate businesses, the target business can be accurately determined. Through the technical solution of this invention, the user's investment preferences for various businesses can be quickly determined with less data, thereby improving the accuracy of the recommended businesses and thus improving the efficiency and quality of business recommendations. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 A flowchart illustrating a recommendation method for banking services provided in Embodiment 1 of the present invention;

[0023] Figure 2 A flowchart illustrating the recommendation method for banking services provided in Embodiment 2 of the present invention;

[0024] Figure 3 A schematic diagram of the structure of a recommendation system for banking services provided in an embodiment of the present invention;

[0025] Figure 4 This is a schematic diagram of the structure of a recommendation device for banking services provided in Embodiment 3 of the present invention;

[0026] Figure 5 This is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. Detailed Implementation

[0027] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0028] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0029] It should be noted that the collection, storage, use, processing, transmission, provision, and disclosure of user personal information involved in the technical solution disclosed herein all comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0030] Example 1

[0031] Figure 1 This is a flowchart illustrating a banking service recommendation method according to Embodiment 1 of the present invention. This method is applicable to both big data and fintech fields. Furthermore, it is applicable to situations requiring accurate service recommendations to bank customers. This method can be executed by a banking service recommendation device, which can be composed of software and / or hardware and configured in a computer or server.

[0032] like Figure 1 As shown, it includes:

[0033] Step 110: Obtain the user's user identifier, and determine the user's historical business information and the user group to which the user belongs based on the user identifier.

[0034] Among these, user identifiers are information used in the banking system to uniquely identify customers, such as bank card numbers or ID card numbers. These can be determined through basic information provided by the user when registering or opening an account with the bank, distinguishing different users and facilitating subsequent business inquiries and recommendations. Historical business information refers to records of various business activities a user has conducted at the bank, such as investments in bonds, precious metals, and deposits. This information is obtained through the bank's business database and used to analyze user behavior patterns and preferences, providing a basis for accurate recommendations. User groups are groups divided according to user types, where users within the same group share at least one common type of characteristic.

[0035] Optionally, user characteristics of each registered user are obtained, and users are clustered based on the user characteristics to obtain user groups.

[0036] User characteristics are the basic attributes of a user, such as age, region, and assets. Clustering is the process of grouping users with similar characteristics into one category, and users can be divided by age, region, and assets.

[0037] Specifically, users in the same user group share similar user characteristics and therefore may have the same investment intentions. By leveraging the business holding information of users within the same user group, it is possible to more accurately identify target businesses.

[0038] Step 120: Determine the user's investment preference for the historical services based on the user's historical service information, and determine candidate services based on the investment preference for the historical services.

[0039] Investment preferences reflect a user's liking for specific investment methods or products, such as a preference for high-risk, high-return stock investments or stable bond investments. These preferences are derived from historical business information analysis and are used to guide banks in recommending investment products that match a user's risk tolerance and return expectations. Investment preferences can be determined through historical business returns or the user's personal preferences; by analyzing the investment preferences of various historical business transactions, candidate businesses can be selected.

[0040] Specifically, if a user has achieved ideal returns or met preset investment standards by investing in a particular business or product during the past business process, it indicates that the user has a relatively high liking for that business or product. Therefore, when recommending that business or product to the user again, the success rate of the recommendation will be better.

[0041] Optionally, candidate businesses can be determined based on the investment preferences of the historical businesses, including:

[0042] Historical services with investment preferences below a preset threshold are deleted to obtain candidate services.

[0043] Specifically, a screening mechanism for candidate businesses was added. An investment preference threshold was set, narrowing the candidate pool by removing low-preference businesses. This design reduced unnecessary computation and improved the efficiency and targeting of the identification of target businesses.

[0044] Step 130: Based on the investment preferences of the candidate services and the holding information of other users in the user group regarding the candidate services, determine the target service.

[0045] Among them, the holding information refers to the frequency or quantity of each user in the user group holding the candidate business. By using the holding information of other users in the user group on the candidate business, it is possible to determine the holding attitude of users with the same characteristics as the user towards each candidate business. In addition, combined with the user's personal investment preferences, the target business can be accurately screened.

[0046] Step 140: Recommend the target service to the user.

[0047] Specifically, you can directly recommend the target business to the user. If the user already holds the target business, you can also recommend other businesses of the same type. For example, if the target business is investing in gold, you can also recommend precious metals such as silver.

[0048] This invention provides a method for recommending banking services. The method includes: obtaining a user's user identifier; determining the user's historical transaction information and the user group to which the user belongs based on the user identifier; determining the user's investment preferences for the historical transactions based on the historical transaction information; determining candidate transactions based on the investment preferences for the historical transactions; determining a target transaction based on the investment preferences for the candidate transactions and the holding information of other users in the user group regarding the candidate transactions; and recommending the target transaction to the user. Specifically, historical transaction information can be used to determine investment preferences for historical transactions, and then, based on the investment preferences for candidate transactions and the holding information of other users in the user group regarding the candidate transactions, the target transaction can be accurately determined. Through the technical solution of this invention, the user's investment preferences for various transactions can be quickly determined with less data, thereby improving the accuracy of the recommended transactions and thus improving the efficiency and quality of transaction recommendations.

[0049] Example 2

[0050] Figure 2 The flowchart illustrates a banking business recommendation method provided in Embodiment 2 of the present invention. This method, based on the above embodiments, further defines the method for determining investment preferences in historical business.

[0051] like Figure 2 As shown, it includes:

[0052] Step 210: Obtain the user's user identifier, and determine the user's historical business information and the user group to which the user belongs based on the user identifier.

[0053] Step 220: For any historical holding year of any historical business, determine the business factor of the historical business in the historical holding year based on the time difference between the historical holding year and the current year, and the total duration of the statistics, wherein the business factor of the historical business in the historical holding year characterizes the importance of the historical business in the historical holding year.

[0054] The historical business information includes the investment results of historical businesses in each historical holding year, where the historical holding year is the year the user held the historical business. The investment results represent the returns of the historical business during those holding years. The total statistical period covers the entire time span corresponding to the historical business information, which can include all historical business information from the user's previous ten years. The business factor of the historical business in the historical holding year represents the importance of that historical business during those years. The higher the business factor in a given year, the greater the importance attached to that historical business during those years.

[0055] Specifically, for any historical holding year of a business, the further back in time it is from the present, the smaller the business factor becomes. In this way, the business weights of different years can be adjusted so that businesses further back in time have less impact on investment preferences, thereby improving the accuracy of investment preferences for historical businesses.

[0056] Step 230: Determine the investment preference of the historical business based on the business factors and investment results of the historical business in each of the historical holding years.

[0057] Specifically, based on the business factors of the historical holding years, and the investment results and costs of the historical holding years, the year score of the historical holding years is determined; based on the year score and investment results of each historical holding year, the investment preference of the historical business is determined.

[0058] Among them, the annual score of historical business in the historical holding years is used to measure the overall performance of historical business in the historical holding years, which can be used to measure the profitability.

[0059] Specifically, the rules for scoring based on business factors, investment results, and the year of cost calculation improve the objectivity of investment preference assessment through quantitative indicators. This design avoids the bias of assessment based on a single factor and enhances the accuracy of preference judgment.

[0060] Furthermore, based on the investment results and costs of historical holding years, the returns of historical holding years can be determined, and then the year scores of historical holding years can be determined based on the returns. By statistically analyzing the year scores of historical businesses in each historical holding year, the investment preferences of historical businesses can be obtained.

[0061] Optionally, the investment preferences of the historical business can be determined based on the annual scores and investment results of each historical holding year, including:

[0062] A first score is determined based on the scores of each year in which the investment results meet the preset conditions; a second score is determined based on the scores of each year in which the investment results do not meet the preset conditions; and the investment preference for historical business is determined based on the first score and the second score.

[0063] The preset conditions can be return-based conditions based on investment results, such as whether the return is positive or whether the return exceeds a preset threshold. The first score is the sum of the year scores for each historical holding year where the investment results meet the preset conditions, and the second score is the sum of the year scores for each historical holding year where the investment results do not meet the preset conditions.

[0064] Specifically, the investment preference K for historical business can be determined using the following formula:

[0065]

[0066] Among them, positive returns (investment results meet preset conditions) and negative returns (investment results do not meet preset conditions) can be determined by the investment results, α i and β i These are all business factors, corresponding to the business factors of years with positive returns and years with negative returns, respectively. n and m represent the number of years with positive returns and years with negative returns, respectively. The year score for a year with positive returns is... The year score for a year with negative returns is F is the multiplication factor used to amplify the statistical results, and n+m is the total statistical duration. Furthermore, α... i and β i The numerators are the year numbers corresponding to the years with positive and negative returns, respectively, while the denominators are both the total statistical duration. Therefore, the first score is... The second rating is

[0067] Specifically, it clarifies the classification rules for determining investment preferences based on year scores. It distinguishes between how year scores meet and do not meet preset conditions, highlighting users' differentiated preferences for different types of investment processes. This classification assessment makes preference judgments more aligned with users' actual decision-making logic.

[0068] Step 240: Determine candidate businesses based on the investment preferences of the historical businesses.

[0069] Step 250: Based on the investment preferences of the candidate services and the holding information of other users in the user group regarding the candidate services, determine the target service.

[0070] Specifically, step 250 includes:

[0071] Obtain a first preset weight and a second preset weight; determine a first score for the candidate business based on the investment preference of the candidate business and the first preset weight; determine a second score for the candidate business based on the holding frequency of the candidate business in the user group and the second preset weight; determine the target business based on the first score and the second score of the candidate business.

[0072] Among them, the first preset weight and the second preset weight respectively represent the importance of individual investment preferences and user group holding intentions to the determination of target business.

[0073] Specifically, based on their historical business information, users can determine their investment preferences for past businesses, which inherently represent their investment intentions. Furthermore, the holding frequency of candidate businesses within a user group represents the investment intentions of groups with similar characteristics to the user. Therefore, a first score for a candidate business can be determined based on its investment preferences and a first preset weight; a second score can be determined based on its holding frequency within the user group and a second preset weight; and a target business can be determined based on both the first and second scores. The target business obtained in this way is determined based on two levels corresponding to users and groups, thus possessing high accuracy.

[0074] Step 260: Recommend the target service to the user.

[0075] For example, Figure 3 This invention provides a schematic diagram of the structure of a recommendation system for banking services, specifically including a bank product acquisition module, a customer identification module, a customer group bank product acquisition module, a customer product benefit analysis module, and a customer-targeted marketing module. The entire process begins with a customer visiting the bank to conduct business. First, the customer identification module identifies the user and obtains a user identifier, for example, by retrieving the bank's enterprise-level customer information subsystem, using the customer information number as a unique identifier. Next, the bank product acquisition module retrieves all customer asset data (including deposits, loans, investments, funds, bonds, insurance, precious metals, paper gold, and accumulated gold, etc.) from various bank application subsystems, performs data cleaning (removing duplicate fields based on region code, gender, and age group as category features), and sorts the data to form a list of the top ten bank products (grouped by region, gender, and age group). For example, for male customers aged 40-50 in Beijing, products are sorted by the number of times they have been owned to generate a business product sequence. The customer group bank product acquisition module then combines the above information to obtain a list of the top ten products held by the customer's group (same region, same gender, and same age group). Subsequently, the customer product profitability analysis module analyzes the customer's historical business information over the past five years to calculate investment preferences and assess product profitability. Then, combining the business's investment preferences and its holding ratio within the group, target businesses are identified. The customer-targeted marketing module guides bank staff to conduct face-to-face marketing accordingly, prioritizing the recommendation of profitable target products to improve marketing effectiveness and customer loyalty.

[0076] This invention provides a method for recommending banking services. By characterizing the investment preferences of individual users and the holding frequency of investment intentions of user groups, this invention can accurately determine target services, thereby improving the accuracy and efficiency of service recommendations.

[0077] Example 3

[0078] Figure 4 This is a schematic diagram of a recommendation device for banking services provided in Embodiment 3 of the present invention. Figure 4 As shown, the device includes:

[0079] The acquisition module 310 is used to acquire the user's user identifier and determine the user's historical business information and the user group to which the user belongs based on the user identifier;

[0080] The candidate service determination module 320 is used to determine the user's investment preference for the historical services based on the user's historical service information, and to determine candidate services based on the investment preference for the historical services.

[0081] The target business determination module 330 is used to determine the target business based on the investment preferences of the candidate businesses and the holding information of other users in the user group regarding the candidate businesses;

[0082] The recommendation module 340 is used to recommend target services to the user.

[0083] This invention provides a banking service recommendation device. The device works by: acquiring a user's identifier; determining the user's historical transaction information and the user group to which the user belongs based on the user identifier; determining the user's investment preferences for the historical transactions based on the historical transaction information; determining candidate transactions based on the investment preferences for the historical transactions; determining a target transaction based on the investment preferences for the candidate transactions and the holding information of other users in the user group regarding the candidate transactions; and recommending the target transaction to the user. Specifically, historical transaction information can determine investment preferences for historical transactions, and then, based on the investment preferences for candidate transactions and the holding information of other users in the user group regarding the candidate transactions, the target transaction can be accurately determined. Through the technical solution of this invention, the user's investment preferences for various transactions can be quickly determined with less data, thereby improving the accuracy of the recommended transactions and thus improving the efficiency and quality of transaction recommendations.

[0084] Optionally, the candidate business determination module 320 includes: an investment preference determination submodule and a candidate business determination submodule.

[0085] The investment preference determination submodule includes:

[0086] The business factor determination unit is used to determine the business factor of any historical business in any historical holding year based on the time difference between the historical holding year and the current year, and the total statistical duration, wherein the business factor of the historical business in the historical holding year characterizes the importance of the historical business in the historical holding year.

[0087] The investment preference determination unit is used to determine the investment preference of the historical business based on the business factors and investment results of the historical business in each of the historical holding years.

[0088] The investment preference determination unit includes:

[0089] The year rating determination subunit is used to determine the year rating of the historical holding year based on the business factors of the historical holding year and the investment results and costs of the historical holding year.

[0090] The investment preference determination subunit is used to determine the investment preference of the historical business based on the annual score and investment results of each historical holding year.

[0091] The investment preference determination sub-unit includes:

[0092] The classification micro-unit is used to determine the first score based on the scores of each year in which the investment results meet the preset conditions in each historical holding year; and to determine the second score based on the scores of each year in which the investment results do not meet the preset conditions in each historical holding year.

[0093] A micro-unit is identified for determining investment preferences for historical business based on the first and second scores.

[0094] Optionally, the candidate business determination submodule is specifically used to: delete historical businesses whose investment preferences are less than a preset threshold to obtain candidate businesses.

[0095] Optionally, the target business determination module includes:

[0096] The acquisition unit is used to acquire the first preset weight and the second preset weight;

[0097] The calculation unit is used to determine a first score for the candidate business based on the investment preference of the candidate business and a first preset weight; and to determine a second score for the candidate business based on the holding frequency of the candidate business in the user group and a second preset weight.

[0098] The determining unit is used to determine the target service based on the first score and the second score of the candidate services.

[0099] Optionally, the device is further configured to: acquire user characteristics of each registered user, and cluster the users based on the user characteristics to obtain user groups.

[0100] The banking service recommendation device provided in this embodiment of the invention can execute the banking service recommendation method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method execution.

[0101] Example 4

[0102] Figure 5 A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0103] like Figure 5 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory 12 or a random access memory 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the read-only memory 12 or loaded from storage unit 18 into the random access memory 13. The random access memory 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, read-only memory 12, and random access memory 13 are interconnected via a bus 14. An input / output interface 15 is also connected to the bus 14.

[0104] Multiple components in electronic device 10 are connected to input / output interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of monitors, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0105] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, central processing units, graphics processing units, various special-purpose artificial intelligence computing chips, various processors running machine learning model algorithms, digital signal processors, and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as recommendation methods in banking operations.

[0106] In some embodiments, the banking recommendation method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via read-only memory 12 and / or communication unit 19. When the computer program is loaded into random access memory 13 and executed by processor 11, one or more steps of the banking recommendation method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the banking recommendation method by any other suitable means (e.g., by means of firmware).

[0107] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays, application-specific integrated circuits (ASICs), application-specific standard products (ASICs), systems-on-a-chip (SoCs), complex programmable logic devices, computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0108] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0109] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory, read-only memory, erasable programmable read-only memory (EP memory or flash memory), optical fibers, portable compact disk read-only memory, optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0110] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a cathode ray tube or liquid crystal display, a monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0111] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0112] A computing system can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a host product within the cloud computing service system. This addresses the shortcomings of traditional physical hosts and cloud host services, such as high management difficulty and weak business scalability.

[0113] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0114] This disclosure also provides a computer program product, including a computer program and / or indicating that, when executed by a processor, the computer program implements the recommended methods for banking operations as provided in any embodiment of this application. In implementing the computer program product, computer program code for performing the operations of the embodiments of this disclosure can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN).

[0115] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for recommending banking services, characterized in that, include: Obtain the user's user identifier, and determine the user's historical business information and the user group to which the user belongs based on the user identifier; Based on the user's historical business information, determine the user's investment preference for the historical business, and based on the investment preference for the historical business, determine candidate businesses; Based on the investment preferences of the candidate services and the holding information of other users in the user group regarding the candidate services, the target service is determined; Recommend the target service to the user.

2. The method according to claim 1, characterized in that, The historical business information includes: the investment results of historical businesses in each historical holding year; The step of determining the user's investment preference for the historical services based on the user's historical service information includes: For any historical holding year of any historical business, the business factor of the historical business in the historical holding year is determined based on the time difference between the historical holding year and the current year, and the total statistical duration. The business factor of the historical business in the historical holding year represents the importance of the historical business in the historical holding year. The investment preferences of the historical business are determined based on the business factors and investment results of the historical business in each of the historical holding years.

3. The method according to claim 2, characterized in that, The step of determining the investment preference of the historical business based on the business factors and investment results of the historical business in each of the historical holding years includes: Based on the business factors of the historical holding years, and the investment results and costs of the historical holding years, determine the year score of the historical holding years; The investment preferences of the historical business are determined based on the annual scores and investment results of each historical holding year.

4. The method according to claim 3, characterized in that, The determination of investment preferences for the historical business based on the year scores and investment results of each historical holding year includes: The first score is determined based on the scores of each year in which the investment results in each historical holding year meet the preset conditions. The second score is determined based on the scores of each year in which the investment results in each historical holding year do not meet the preset conditions. Investment preferences for historical businesses are determined based on the first and second scores.

5. The method according to claim 1, characterized in that, The step of determining candidate businesses based on the investment preferences of the historical businesses includes: Historical services with investment preferences below a preset threshold are deleted to obtain candidate services.

6. The method according to claim 1, characterized in that, The determination of the target business based on investment preferences for the candidate businesses and holding information of other users in the user group regarding the candidate businesses includes: Obtain the first preset weight and the second preset weight; Based on the investment preferences and first preset weights of the candidate businesses, a first score is determined for each candidate business. The second score of the candidate service is determined based on the frequency of the candidate service in the user group and the second preset weight; The target service is determined based on the first and second scores of the candidate services.

7. The method according to claim 1, characterized in that, Also includes: Obtain the user characteristics of each registered user, and cluster the users based on the user characteristics to obtain user groups.

8. A recommendation device for banking services, characterized in that, include: The acquisition module is used to acquire the user's user identifier and determine the user's historical business information and the user group to which the user belongs based on the user identifier; The candidate service determination module is used to determine the user's investment preference for the historical services based on the user's historical service information, and to determine candidate services based on the investment preference for the historical services. The target business determination module is used to determine the target business based on the investment preferences of the candidate businesses and the holding information of other users in the user group regarding the candidate businesses; The recommendation module is used to recommend target services to the user.

9. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the recommended method for banking operations as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the recommended method for banking operations as described in any one of claims 1-7.

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