Business data processing method, device and server

Abstract

The specification provides a business data processing method, device and server, which can be used in the field of financial technology. Based on the method, before implementation, a preset business demand mining model capable of automatically analyzing and mining the business demand of a customer object is trained by using a large language model based on input information data of multiple data sources related to the customer object. During implementation, the server acquires multiple information data related to a candidate customer object that needs to be concerned through multiple data sources according to a preset business processing rule every interval of a preset time period; the preset business demand mining model is used to process the information data, automatically mine and find the business demand of the customer object and a target business suitable for the customer object; and a corresponding target task is automatically created in a timely manner, and the business terminal is prompted relatedly, so that the business terminal can efficiently and accurately realize offline business promotion and obtain a good promotion effect.

Description

Technical Field

[0001] This specification belongs to the field of Internet technology, and in particular to business data processing methods, devices and servers. Background Art

[0002] Financial transaction institutions (such as banks) often need to arrange for business personnel to visit customers offline and promote relevant business products launched by the institution to customers.

[0003] However, existing methods often require sales personnel to rely on their personal experience to determine customer preferences and then conduct offline promotions of relevant products and services to those customers. These methods are easily influenced by sales personnel's subjective factors during implementation, often resulting in less-than-ideal promotional results and potentially even causing customer dissatisfaction.

[0004] To address the above issues, no effective solutions have been proposed so far. Summary of the Invention

[0005] This specification provides a business data processing method, device and server, which can enable business terminals to efficiently and accurately implement offline business promotion and achieve better promotion effects.

[0006] This specification provides a business data processing method, which is applied to a server of a transaction service platform, including:

[0007] Receive and respond to business promotion attention requests and identify candidate customers who need attention;

[0008] According to the preset business processing rules, at every preset time period, the first type of information data released by the candidate customer objects, the second type of information data released by the transaction service platform, and the third type of information data released by the third party are obtained through multiple data sources;

[0009] combining the first type of information data, the second type of information data, and the third type of information data to obtain target joint information data;

[0010] Utilize the preset business demand mining model to process the target joint information data and obtain the corresponding target processing results; wherein the preset business demand mining model is a model trained based on the large language model;

[0011] Based on the target processing results, candidate customers with business needs are identified as target customers, and the target needs of the target customers are determined;

[0012] According to the target demand content, matching candidate businesses are determined from the preset candidate business set as the target business for the target customer object;

[0013] Create a target task for offline promotion of the target business to the target customer; and generate target prompt information corresponding to the target task;

[0014] The target prompt information is sent to the corresponding business terminal; wherein the business terminal receives and responds to the target prompt information, and promotes the target business to the target customer object offline.

[0015] In one embodiment, the first type of information data published by the candidate customer objects is obtained through multiple data sources, including:

[0016] Based on the object identifier of the candidate customer object, query and determine the website, official account, and social account of the candidate customer object;

[0017] According to the website, official account, and social account of the candidate customer object, the information data released by the candidate customer object in the current time period is queried as the first category of information data.

[0018] In one embodiment, the second type of information data published by the transaction service platform is obtained through multiple data sources, including:

[0019] Determining attribute information of the candidate customer object according to the object identifier of the candidate customer object;

[0020] Information data that matches the attribute information of the candidate customer object is screened out from the information data released in the current time period of the transaction service platform and the adjacent valid historical time period as the second type of information data.

[0021] In one embodiment, the third category of information data published by a third party is obtained through multiple data sources, including:

[0022] Determine attribute information of the candidate customer object and object identifiers of associated objects of the candidate customer object based on the object identifier of the candidate customer object;

[0023] Based on the attribute information of the candidate customer object, determine the third-party public platform related to the candidate customer object; based on the object identifier of the associated object, determine the website, official account, and social account of the associated object;

[0024] Filter out first-branch messages related to candidate customers from information data published in the current time period and adjacent valid historical time periods on third-party public platforms; filter out second-branch messages related to candidate customers from information data published in the current time period on websites, official accounts, and social media accounts of associated customers;

[0025] The first branch message and the second branch message are combined to obtain corresponding third type information data.

[0026] In one embodiment, after determining candidate customer objects with business needs as target customer objects based on the target processing result, the method further includes:

[0027] According to the target processing results, determine the target needs of the target customer objects;

[0028] According to target requirements, key information data is screened out from the first category of information data, the second category of information data, and the third category of information data;

[0029] Processing the key information data using a preset semantic extraction model to obtain a key information summary and key content text of the key information data;

[0030] Accordingly, the method further includes:

[0031] The key information summary, key content text, and link address of the key information data are delivered to the business terminal.

[0032] In one embodiment, after sending the target prompt information to the corresponding service terminal, the method further includes:

[0033] Receive target promotion records and target promotion results of offline target business promotions to target customers uploaded by business terminals;

[0034] Verify the target promotion results according to the target promotion records and obtain the corresponding target verification results;

[0035] According to the target verification results, when it is determined that the verification has passed, the quality evaluation of the offline business promotion of the business terminal for the target customer objects is carried out according to the target promotion records and target promotion results to obtain the corresponding target evaluation results.

[0036] In one embodiment, after obtaining the corresponding target evaluation result, the method further includes:

[0037] If, based on the target evaluation results, it is determined that the offline business promotion of the business terminal for the target customer does not meet the preset requirements and the target promotion result is a promotion failure, check whether the target customer and the target business meet the re-promotion conditions;

[0038] When it is determined that the target customer object and the target business meet the re-promotion conditions, a re-promotion task is created to re-promote the target business to the target customer object offline; and attribute information of the business terminal and the target customer object is obtained;

[0039] Using the preset promotion strategy generation model to process target promotion records, attribute information of business terminals, and attribute information of target customer objects, an improved promotion strategy is determined;

[0040] Sending re-promotion prompt information to the service terminal; wherein the re-promotion prompt information at least carries an improved promotion strategy.

[0041] This specification also provides a business data processing device, which is applied to a server of a transaction service platform, including:

[0042] The receiving module is used to receive and respond to business promotion attention requests and determine candidate customer objects that need attention;

[0043] An acquisition module is used to acquire, through multiple data sources, first-category information data published by candidate customer objects, second-category information data published by the transaction service platform, and third-category information data published by third parties at preset time intervals according to preset business processing rules;

[0044] a combining module, configured to combine the first type of information data, the second type of information data, and the third type of information data to obtain target joint information data;

[0045] A processing module is used to process the target joint information data using a preset business demand mining model to obtain a corresponding target processing result; wherein the preset business demand mining model is a model obtained by training based on a large language model;

[0046] The first determination module is used to determine candidate customer objects with business needs as target customer objects based on the target processing results; and determine the target needs of the target customer objects;

[0047] The second determination module is used to determine matching candidate services from a preset candidate service set according to target demand content as target services for target customers;

[0048] A creation module is used to create a target task for offline promotion of a target business to a target customer; and generate target prompt information corresponding to the target task;

[0049] The sending module is used to send the target prompt information to the corresponding business terminal; wherein, the business terminal receives and responds to the target prompt information and promotes the target business to the target customer object offline.

[0050] This specification also provides a server, including a processor and a memory for storing processor-executable instructions, and the processor implements relevant steps of the business data processing method when executing the instructions.

[0051] This specification also provides a computer-readable storage medium having computer instructions stored thereon, which implement the steps of the business data processing method when executed by a processor.

[0052] Based on the business data processing method, device, and server provided in this specification, before implementation, a large language model can be used to train a preset business demand mining model that can automatically analyze and mine the business needs of customer objects based on the information data of customer objects input from multiple data sources. During implementation, the server can obtain first-category information data related to candidate customer objects of interest, as well as second-category information data released by the transaction service platform and third-category information data released by a third party through multiple data sources at intervals of a preset time period according to preset business processing rules; and combine the information data from the above multiple data sources to obtain target joint information data; then use the preset business demand mining model to process the target joint information data to obtain a corresponding target processing result; based on the target processing result, determine the candidate customer objects with business needs as target customer objects; and determine the target demand content of the target customer objects; based on the target demand content, determine a matching target business from the preset candidate business set; create a target task for offline promotion of the target business to the target customer objects; and generate target prompt information corresponding to the target task; and send the target prompt information to the corresponding business terminal. This can effectively assist business terminals in accurately and automatically discovering the business needs of target customers and the target businesses suitable for the target customers; and automatically create corresponding target tasks in a timely manner, while providing relevant prompts to the corresponding business terminals in a timely manner, so that the business terminals can efficiently and accurately realize offline business promotion and achieve better promotion results. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the embodiments of this specification, the following is a brief introduction to the drawings required for use in the embodiments. The drawings described below are only some of the embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0054] Figure 1 This is a flowchart of a business data processing method provided by an embodiment of this specification;

[0055] Figure 2 This is a schematic diagram of an embodiment of a business data processing method provided by an embodiment of this specification, in a scenario example;

[0056] Figure 3 This is a schematic diagram of an embodiment of a business data processing method provided by an embodiment of this specification, in a scenario example;

[0057] Figure 4This is a schematic diagram of an embodiment of a business data processing method provided by an embodiment of this specification, in a scenario example;

[0058] Figure 5 This is a schematic diagram of an embodiment of a business data processing method provided by an embodiment of this specification, in a scenario example;

[0059] Figure 6 This is a schematic diagram of an embodiment of a business data processing method provided by an embodiment of this specification, in a scenario example;

[0060] Figure 7 This is a schematic diagram of the structure of a server provided by an embodiment of this specification;

[0061] Figure 8 This is a schematic diagram of the structure of a business data processing device provided by an embodiment of this specification;

[0062] Figure 9 This is a schematic diagram of an embodiment of a business data processing method provided by an embodiment of this specification, in a scenario example. DETAILED DESCRIPTION

[0063] To help those skilled in the art better understand the technical solutions in this specification, the following will provide a clear and complete description of the technical solutions in the embodiments of this specification, in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of this specification, not all of them. All other embodiments derived by those skilled in the art based on the embodiments in this specification without creative effort shall fall within the scope of protection of this specification.

[0064] It should be noted that the user-related information and data involved in the embodiments of this specification are all information and data authorized by the user or fully authorized by relevant parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data comply with relevant laws, regulations and standards, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users or relevant parties to choose to authorize or refuse.

[0065] It should also be noted that in the embodiments of this specification, certain software, components, models and other existing solutions in the industry may be mentioned. They should be regarded as exemplary and their purpose is only to illustrate the feasibility of implementing the technical solution of this application, but it does not mean that the applicant has or will necessarily use the solution.

[0066] See Figure 1As shown, the embodiment of this specification provides a business data processing method. Among them, the method is specifically applied to the server side. When implemented, the method may include the following contents:

[0067] S101: Receive and respond to a business promotion attention request, and determine candidate customer objects that need attention;

[0068] S102: According to preset business processing rules, at every preset time period, first-category information data published by candidate customer objects, second-category information data published by the transaction service platform, and third-category information data published by a third party are obtained from multiple data sources;

[0069] S103: combining the first type of information data, the second type of information data, and the third type of information data to obtain target joint information data;

[0070] S104: Processing the target joint information data using a preset business demand mining model to obtain a corresponding target processing result; wherein the preset business demand mining model is a model trained based on a large language model;

[0071] S105: According to the target processing result, candidate customer objects with business needs are determined as target customer objects; and target demand content of the target customer objects is determined;

[0072] S106: According to the target demand content, a matching candidate business is determined from a preset candidate business set as a target business for the target customer object;

[0073] S107: Creating a target task for offline promotion of the target business to the target customer; and generating target prompt information corresponding to the target task;

[0074] S108: Sending the target prompt information to the corresponding business terminal; wherein the business terminal receives and responds to the target prompt information, and promotes the target business to the target customer object offline.

[0075] The above-mentioned preset business demand mining model can be specifically understood as an algorithm model that is pre-trained using a large language model and can automatically analyze and mine the business needs of customer objects based on the information of multiple data sources of the input customer objects.

[0076] The aforementioned business needs may specifically include direct business needs and / or potential business needs. Direct business needs may be understood as business needs directly expressed by a customer through information data. Potential business needs may be understood as business needs implicitly expressed by a customer through one or more relevant information data, as well as business needs that are not currently present but are likely to be present in the near future.

[0077] The target customers mentioned above can be specifically understood as customers who have business needs and are currently suitable for business promotion. The target services mentioned above can be specifically understood as products or services that match the business needs of the target customers and are likely to be accepted by the target customers. Specifically, for example, the target services mentioned above can be financial products or wealth management services. This specification does not limit the specific content and type of the target services.

[0078] Based on the above embodiments, the business terminal can be effectively assisted to accurately and automatically discover the business needs of the target customer object and the target business suitable for the target customer object; and the corresponding target tasks can be automatically created in a timely manner, and relevant prompts can be given to the business terminal, so that the business terminal can efficiently and accurately realize offline business promotion and obtain better promotion effects. At the same time, it also reduces the workload of business personnel.

[0079] In some embodiments, see Figure 2 As shown, the above-mentioned business data processing method can be specifically applied to the server side. Specifically, the server can include a background server applied to the transaction service platform (e.g., XX Bank) and capable of performing functions such as data transmission and data processing. Specifically, the server can be, for example, an electronic device with data computing, storage, and network interaction functions. Alternatively, the server can also be a software program running on the electronic device that provides support for data processing, storage, and network interaction. In this embodiment, the number of servers is not specifically limited. The server can be one server, several servers, or a server cluster formed by several servers.

[0080] In this embodiment, the business terminal may specifically include a front-end for the business personnel of the transaction service platform, capable of performing functions such as data collection and data transmission. Specifically, the business terminal may be, for example, an electronic device such as a desktop computer, tablet computer, laptop computer, or smartphone. Alternatively, the business terminal may be a software application capable of running on any of the above electronic devices.

[0081] In specific implementations, business personnel can log in to the business promotion and attention configuration interface of the transaction service platform through a business terminal. Within this interface, they can select the icon of a customer object they are responsible for connecting with and that they wish to follow as a candidate customer object. Accordingly, the business terminal can respond to this operation by obtaining the object identifier of the selected candidate customer object through the promotion and attention configuration interface, generating a corresponding business promotion and attention request, and sending this business promotion and attention request to the server. The business promotion and attention request carries at least the object identifier of the candidate customer object.

[0082] Furthermore, the business personnel can also select the icon of the business they are responsible for in the business promotion attention configuration interface as a candidate business. Accordingly, the above-mentioned business promotion attention request can also carry the business identifier of the candidate business.

[0083] During specific implementation, the server can respond to the business promotion attention request, determine the candidate customer objects that need to be paid attention to based on the object identifier of the candidate customer objects; and further determine the multiple data sources that need to be paid attention to for each candidate customer object; and then obtain multiple information data related to the candidate customer object through multiple data sources.

[0084] In some embodiments, the above-mentioned acquisition of the first type of information data published by the candidate customer objects through multiple data sources may include the following when implemented:

[0085] S1: Query and determine the website, official account, and social media account of the candidate customer object based on the object identifier of the candidate customer object;

[0086] S2: Based on the website, official account, and social account of the candidate customer object, query the information data released by the candidate customer object in the current time period as the first category of information data.

[0087] The first type of information data mentioned above can be specifically understood as information data released by the candidate customer object itself. Specifically, the first type of information data mentioned above can be: official account articles, promotional short videos, external business plans, status messages, etc.

[0088] It should be noted that the first type of information data listed above is only an illustrative example. In specific implementations, depending on specific application scenarios and processing requirements, the first type of information data may also include information data of other types or contents. This specification does not limit this.

[0089] During specific implementation, the server can automatically track the update dynamics of multiple external media such as the candidate customer object's website, official account, social account, etc.; and obtain the full amount of information data released by the first candidate customer object in the current time period at every preset time period (for example, every 1 month, etc.) as the above-mentioned first category of information data.

[0090] Based on the above embodiment, through multiple data sources, the full amount of information data released by the candidate customer objects can be obtained more comprehensively, so that the business needs of the candidate customer objects can be mined more accurately and comprehensively later.

[0091] In some embodiments, the above-mentioned acquisition of the second type of information data published by the transaction service platform through multiple data sources may include the following when implemented:

[0092] S1: Determine attribute information of the candidate customer object based on the object identifier of the candidate customer object;

[0093] S2: Filter out information data that matches the attribute information of the candidate customer object from the information data released in the current time period and the adjacent valid historical time period of the transaction service platform as the second type of information data.

[0094] The second type of information data can be understood as information data related to candidate customers published by the transaction service platform to which the server belongs. The valid historical time period can be the previous time period adjacent to the current time period, or the previous and previous time periods adjacent to the current time period.

[0095] The attribute information of the candidate customer object may specifically include static attribute information and / or dynamic attribute information of the candidate customer object.

[0096] In specific implementation, the server can obtain characteristic data of the candidate customer object such as object type, user tag, city, monthly income, etc. as the above-mentioned static attribute information based on the object identifier of the candidate customer object by querying the user database of the platform.

[0097] During specific implementation, the server can also query the platform's user historical business operation records based on the object identifier of the candidate customer object, and obtain the candidate customer object's business operation records in the most recent historical time period (for example, the last six months); then, based on the business operation records in the most recent historical time period, perform big data analysis to determine the candidate customer object's recent relatively preferred business projects, promotion methods, operating habits and other characteristic data as the above-mentioned dynamic attribute information.

[0098] During specific implementation, the server first determines, based on the static attribute information and / or dynamic attribute information of the candidate customer object, from the multiple external information release channels of the transaction service platform, an information release channel that can be reached by the candidate customer object, as the target release channel; then, at each preset time period, the server searches the current time period (for example, the current month) and the previous time period adjacent to the current time period (for example, the previous month), for all information data released externally through the target information release channel by the transaction service platform, to find information data that matches the attribute information of the candidate customer object, as the second category of information data.

[0099] Based on the above embodiment, through multiple data sources, information data related to candidate customer objects and released by the transaction service platform can be obtained more comprehensively, so that the business needs of candidate customer objects can be mined more accurately and comprehensively later.

[0100] In some embodiments, see Figure 3 As shown, the third category of information data released by a third party obtained through multiple data sources may include the following when implemented:

[0101] S1: Determine attribute information of the candidate customer object and object identifiers of associated objects of the candidate customer object based on the object identifier of the candidate customer object;

[0102] S2: Determine a third-party public platform related to the candidate customer object based on the attribute information of the candidate customer object; determine the website, official account, and social account of the associated object based on the object identifier of the associated object;

[0103] S3: Filter out first-branch messages related to the candidate customer from the information data published in the current time period and the adjacent valid historical time period on the third-party public platform; filter out second-branch messages related to the candidate customer from the information data published in the current time period on the websites, official accounts, and social media accounts of the associated customers;

[0104] S4: Combine the first branch message and the second branch message to obtain corresponding third type information data.

[0105] The third category of message data may be specifically understood as information data related to candidate customer objects that is published third-party, in addition to candidate customer objects and transaction service platforms.

[0106] The above-mentioned third parties may specifically include: associated objects that have an associated relationship with the candidate customer object (for example, friends, partners, parent companies, etc. of the candidate customer object) and third-party public platforms (for example, regulatory agencies, service agencies, news media, etc. related to the candidate customer object).

[0107] Correspondingly, the above-mentioned third category of information data may specifically include: first-branch messages related to candidate customer objects published by associated objects (for example, text, video, audio, etc. related to candidate customer objects published by associated objects through websites, official accounts, and social accounts), and second-branch messages related to candidate customer objects published by third-party public platforms (for example, news, notifications, announcements, reward lists, etc. related to candidate customer objects published by third-party public platforms).

[0108] Before specific implementation, the server can pre-collect the interaction data of each customer object based on the transaction service platform; then, based on the attribute information of each customer object and the interaction data, construct a knowledge graph of customer object relationships based on the transaction service platform.

[0109] In specific implementations, the server can determine the associated objects associated with the candidate customer object by querying the customer object relationship knowledge graph based on the object identifier of the candidate customer object. Simultaneously, based on the attribute information of the candidate customer object, the server can filter out third-party public platforms related to the candidate customer object from public platforms that the transaction service platform has access to. Furthermore, at predetermined time intervals, the server can search the full amount of information data published by the associated objects during the current time period and the previous time period adjacent to the current time period, as well as the full amount of information data published by third-party public platforms, to filter out information data that matches the attribute information of the candidate customer object as the first branch message and the second branch message. The first and second branch messages are then combined to generate the third type of information data.

[0110] Based on the above embodiment, through multiple data sources, information data published by a third party and related to candidate customer objects can be obtained more comprehensively, so that the business needs of candidate customer objects can be mined more accurately and comprehensively later.

[0111] In some embodiments, more comprehensive and rich target joint information data can be obtained by combining the first category information data, the second category information data, and the third category information data.

[0112] During specific implementation, consider that the third category of information data, compared to the first and second category information data, is not directly released by the candidate customer object, making its actual relevance to the candidate customer object relatively uncertain; and is not released by the transaction service platform itself, making its reliability relatively uncertain. Based on these considerations, in order to enable more accurate subsequent use of information data from different data sources, when combining the first, second, and third category information data, weight tags can be set for each of the first, second, and third category information data, with corresponding weight coefficients set in the weight tags. The first, second, and third category information data carrying the weight tags can then be concatenated according to specified rules to obtain the corresponding target joint information data. The weight tags can be determined based on historical data through big data analysis. Specifically, the weight coefficient of the first category information data is generally greater than the weight coefficient of the second category information data, and the weight coefficient of the second category information data is generally greater than the weight coefficient of the third category information data.

[0113] Furthermore, for the third category of information data, corresponding sub-weight coefficients can be set for the information data provided by the corresponding data source based on the closeness of the relationship between the data source and the candidate customer object, as well as the credit value of the data source itself. The weight coefficient of the information data provided by the data source with a closer relationship with the candidate customer object and a higher credit value will be relatively larger.

[0114] In specific implementation, after obtaining the target joint information data, the target joint information data may be pre-processed. Specifically, the target joint information data may be pre-processed by first detecting whether the content of the information data is empty or invalid data, and deleting the empty information data and invalid information data.

[0115] Furthermore, the data type of the information data in the target joint information data can be determined; wherein the data type includes text data (for example, public account articles, news, etc.), video data (for example, promotional short videos, etc.), audio data (for example, voice call clips, etc.), picture data (for example, promotional pictures, etc.), etc.

[0116] According to the data type, the target joint information data is split into a first information data group (corresponding to text data), a second information data group (corresponding to video data), a third information data group (corresponding to audio data), and a fourth information data group (corresponding to picture data).

[0117] For the second information data set, a pre-trained video analysis model is used to perform video content recognition and extraction, and the corresponding content text is combined as the processed second information data set. For the third information data set, a pre-trained speech recognition model is used to perform speech recognition and organization, and the corresponding content text is combined as the processed third information data set. For the fourth information data set, a pre-trained OCR recognition model is used to perform text character recognition and extraction, and the corresponding content text is combined as the processed fourth information data.

[0118] The first information data group, the processed second information data group, the processed third information data group, and the processed fourth information data group are then combined to obtain pre-processed target joint information data.

[0119] During specific implementation, the pre-processed target joint information data can be stored in a corresponding text library for subsequent retrieval and use by a preset business demand mining model.

[0120] In some embodiments, during implementation, the aforementioned target joint information data (or pre-processed target joint information data) can be input into a preset business needs mining model to analyze and mine the business needs of the candidate customer. Accordingly, the preset business needs mining model, based on the input target joint information data, analyzes and mines the input target joint information data, and outputs multiple possible business needs predictions and corresponding probability values ​​as target processing results.

[0121] During specific implementation, the server may also combine the above target joint information data with the attribute information of the candidate customer object, and then input them together into a preset business demand mining model to obtain a more accurate target processing result.

[0122] Among them, the above-mentioned preset business demand mining model can specifically be to use a large amount of sample data in advance to train a large language model; and adjust the model parameters in a targeted manner according to the output results of the model during training; at the same time, adjust the sample data according to the output results; and then use the adjusted sample data to continue model training on the adjusted model until a preset business demand mining model that meets the requirements is obtained.

[0123] In some embodiments, during implementation, the server may first detect, based on the target processing result, whether there is at least one business demand forecast content with a probability value greater than a preset probability threshold. If it is determined that at least one business demand forecast content has a probability value greater than the preset probability threshold, the server may determine that the candidate customer object currently has a business demand, and mark the candidate customer object as a target customer object. Furthermore, the server may select the business demand forecast content with the highest probability value from the multiple business demand forecast contents in the target processing result as the target demand content for the target customer object.

[0124] On the contrary, when it is determined that the probability value of no business demand forecast content is greater than the preset probability threshold, it can be determined that the candidate customer object currently has no business demand; at this time, a prompt information can be generated that the candidate customer object does not need business promotion temporarily.

[0125] In a specific implementation, if it is determined that the probability value of at least one business demand forecast content is greater than a preset probability threshold, and if multiple business demand forecast contents with the highest probability values ​​exist in the target processing result, the business demand forecast contents with the highest probability values ​​can be determined as candidate forecast contents. The third category of information data is then removed from the target joint information data to obtain the target joint information data after removal. The target joint information data after removal is then processed using a preset business demand mining model to obtain a corresponding processing result as an auxiliary reference result. From the multiple candidate forecast contents, a candidate forecast content that relatively matches the auxiliary reference result is screened out as the target demand content.

[0126] In some embodiments, during specific implementation, the target customer object's attribute information and the target customer object's business processing records can be used to first screen out candidate businesses that match the target customer object's attribute information and have not yet been processed by the target customer object from a large number of candidate businesses; then the above candidate businesses can be combined to construct a preset candidate business set for the target customer object.

[0127] Furthermore, the server can obtain the business introduction texts of the candidate businesses in the preset candidate business set; then based on the corresponding mapping rules, map each candidate business introduction text and target demand content into corresponding business feature vectors and demand feature vectors respectively; use each business feature vector and the demand feature vector to calculate the matching degree of the target demand content of each candidate business domain; based on the matching degree, select the candidate business with the highest matching degree from multiple candidate businesses as the target business for the target customer object.

[0128] In some embodiments, the server can automatically create a target task on the transaction service platform for offline promotion of a target business to a target customer, and send the target task to a manager for review. After the manager approves and confirms the execution of the target task, the server can further generate target prompt information corresponding to the target task, simultaneously determine a business terminal that matches the target task (e.g., the business terminal responsible for the target customer), and then send the target prompt information to the business terminal.

[0129] Accordingly, the business terminal can display the target prompt information to the business personnel. The business personnel can visit the target customer object offline according to the target prompt information and carry out specific target business promotion for the target customer object.

[0130] In addition, upon approval, the administrator can also send an assignment instruction regarding the target task to the server. This assignment instruction can include the terminal identifier of the business terminal assigned by the administrator. In response, the server can send the target prompt information to the corresponding business terminal.

[0131] In some embodiments, after determining a candidate customer object with business needs as a target customer object based on the target processing result, refer to Figure 4 As shown, when the method is implemented, it may also include the following contents:

[0132] S1: Determine the target needs of target customers based on the target processing results;

[0133] S2: Filtering key information data from the first, second, and third categories of information data according to target requirements;

[0134] S3: Processing the key information data using a preset semantic extraction model to obtain a key information summary and key content text of the key information data.

[0135] Accordingly, after sending the target prompt information to the corresponding service terminal, the method may further include:

[0136] The key information summary, key content text, and link address of the key information data are delivered to the business terminal.

[0137] During specific implementation, information data with a relatively high correlation with the target demand content (for example, ranked high based on correlation) can be screened out from the first, second, and third categories of information data as key information data. The above key information data is then processed using a preset semantic extraction model to obtain the corresponding key information summary and key content text. Furthermore, only the key information summary, key content text, and key information data can be uploaded to the information database of the transaction service platform (for example, Message Square); and the key information summary, key content text, and key information data can be obtained based on the link address of the information database.

[0138] Accordingly, the link address can be added to the target prompt information, and then the target prompt information is sent to the service terminal. The service terminal can also display the corresponding link address simultaneously with the target prompt information.

[0139] Before preparing to conduct offline business promotion to target customers, business personnel can click on the corresponding link address to enter the information database, browse and refer to the above-mentioned key information summary, key content text, and the specific content of the key information data, so that they can formulate corresponding promotion strategies in advance, and then conduct offline promotion of the target business to target customers based on the promotion strategy to obtain relatively better promotion effects.

[0140] Furthermore, the server can also construct a user portrait of the target customer object based on the attribute information of the target customer object; then use the user portrait of the target customer object, the target demand content, the introduction text of the target business, and the relevant key information summary and key content text to automatically generate a matching promotion strategy through the corresponding strategy decision model; and provide the promotion strategy to the business terminal so that the business terminal can use the above promotion strategy as a reference to better realize offline business promotion for the target customer object.

[0141] In some embodiments, after sending the target prompt information to the corresponding service terminal, refer to Figure 5 As shown, when the method is implemented, it may also include the following contents:

[0142] S1: Receive target promotion records and target promotion results of offline target business promotion to target customers uploaded by the business terminal;

[0143] S2: Verify the target promotion results according to the target promotion records and obtain the corresponding target verification results;

[0144] S3: Based on the target verification results, when it is determined that the verification has passed, the quality of the offline business promotion of the business terminal for the target customer object is evaluated according to the target promotion records and target promotion results to obtain the corresponding target evaluation results.

[0145] During specific implementation, after completing the offline promotion of the target business to the target customer object, the business personnel can use the business terminal to upload the target promotion record of the offline promotion of the target business to the target customer object, as well as the target promotion results.

[0146] The target promotion record may be in the form of text or audio. The target promotion result may be one of promotion success, promotion failure, and pending result.

[0147] During specific implementation, the server can verify the target promotion results based on the target promotion records by cross-validating the target promotion records with the target promotion results.

[0148] If the target promotion records and target promotion results match each other and can be verified with each other, it can be determined that the received target promotion records and target promotion results are accurate and valid, and then the verification is confirmed to be passed, and subsequent quality evaluation can be carried out.

[0149] On the other hand, if the target promotion record and the target promotion result do not match or even contradict each other, it can be determined that at least one of the received target promotion record and target promotion result is incorrect, and the verification is determined to have failed. In this case, an error message indicating that the target promotion record and target promotion result should be retransmitted can be sent to the service terminal.

[0150] In specific implementations, the server can process the target promotion records and target promotion results according to preset evaluation rules to evaluate the quality of the business terminal's offline business promotion activities for target customers and obtain corresponding target evaluation results. The preset evaluation rules are pre-determined by clustering sample promotion records and sample promotion results from a large number of business terminals that meet the required specifications in different business scenarios.

[0151] Furthermore, matching reward data may be determined based on the target evaluation results, and then the reward data may be distributed to the service terminal.

[0152] In addition, based on the target evaluation results, business terminals with problems in business promotion quality (or not meeting the preset requirements) are identified; and quality prompt information is sent to such business terminals to guide the business terminals to subsequently adjust their business promotion methods and strategies in a targeted manner.

[0153] Based on the above embodiments, the quality evaluation of the offline business promotion behavior of the business terminal for the target customer objects can be automatically and accurately achieved.

[0154] Specifically, when receiving the target promotion results, the business terminal can first encrypt the target promotion results using its private identity key to obtain the ciphertext data of the target promotion results. It then adds the terminal identifier based on the business terminal to the ciphertext data of the target promotion results to generate the identity certificate. Simultaneously, it also encrypts the target promotion record using the private identity key to obtain the ciphertext data of the target promotion record. The ciphertext data of the target promotion results carrying the identity certificate and the ciphertext data of the target promotion record are then uploaded to the server together.

[0155] Correspondingly, the server can first detect whether the target promotion result carries an identity credential; and verify the identity credential; when it is determined that the identity credential is true, it can determine the matching identity public key based on the identity credential; and then use the identity public key to decrypt the ciphertext data of the target promotion result and the ciphertext data of the target promotion record respectively to obtain the corresponding plaintext target promotion record and target promotion result.

[0156] In some embodiments, after obtaining the corresponding target evaluation result, refer to Figure 6 As shown, when the method is implemented, it may also include the following contents:

[0157] S1: If, based on the target evaluation results, it is determined that the offline business promotion of the business terminal for the target customer does not meet the preset requirements and the target promotion result is a promotion failure, check whether the target customer and the target business meet the re-promotion conditions;

[0158] S2: When it is determined that the target customer and the target business meet the re-promotion conditions, a re-promotion task is created to re-promote the target business to the target customer offline; and attribute information of the business terminal and the target customer is obtained;

[0159] S3: Using the preset promotion strategy generation model to process the target promotion records, attribute information of the business terminal, and attribute information of the target customer object, an improved promotion strategy is determined;

[0160] S4: Sending re-promotion prompt information to the service terminal; wherein the re-promotion prompt information at least carries an improved promotion strategy.

[0161] The above-mentioned non-compliance with the preset requirements can be specifically understood as the number of behavioral operations that do not comply with the preset evaluation rules during the offline business promotion of the target customer by the business terminal being greater than the preset number threshold (for example, 5 times).

[0162] During specific implementation, it is possible to detect whether the target customer object is an important customer based on the attribute information of the target customer object; at the same time, based on the relevant information of the target business, it is possible to detect whether the target business is a key business of the transaction service platform; when it is determined that the target customer object is an important customer and the target business is a key business, it is determined that the target customer object and the target business meet the re-promotion conditions.

[0163] Furthermore, a pre-trained promotion strategy generation model can be used to jointly process the target promotion records, the attribute information of the service terminal, and the attribute information of the target customer object to generate an improved re-promotion strategy for the target promotion record. The improved re-promotion strategy is then sent to the service terminal via a re-promotion prompt message.

[0164] Correspondingly, the business terminal can respond to the re-promotion prompt information and, based on the improved re-promotion strategy, specifically correct and adjust the behavioral operations that did not comply with the preset evaluation rules during the previous offline promotion of the target customer object; and visit the target customer object again and conduct offline promotion of the target business again to obtain relatively better promotion effects.

[0165] Based on the above embodiments, the loss of important customers can be effectively avoided, and the success rate of promoting key services to important customers can be improved; at the same time, it can also help improve the relevant business capabilities of the business terminal.

[0166] As can be seen from the above, the business data processing method provided by the embodiment of this specification can be pre-trained using a large language model to obtain a preset business demand mining model that can automatically analyze and mine the business needs of customer objects based on the information data of customer objects input from multiple data sources before implementation. During implementation, the server can obtain the first type of information data associated with the candidate customer objects that need to be paid attention to, as well as the second type of information data released by the transaction service platform and the third type of information data released by a third party through multiple data sources at intervals of a preset time period according to the preset business processing rules; and combine the information data of the above multiple data sources to obtain target joint information data; then use the preset business demand mining model to process the target joint information data to obtain the corresponding target processing result; according to the target processing result, the candidate customer objects with business needs are determined as target customer objects; and the target demand content of the target customer objects is determined; according to the target demand content, a matching target business is determined from the preset candidate business set; a target task for offline promotion of the target business to the target customer objects is created; and target prompt information corresponding to the target task is generated; and the target prompt information is sent to the corresponding business terminal. This can effectively assist business terminals in accurately and automatically discovering the business needs of target customers and the target businesses suitable for the target customers; and automatically create corresponding target tasks in a timely manner, and provide relevant prompts to the business terminals, so that the business terminals can efficiently and accurately implement offline business promotion and achieve better promotion results.

[0167] This specification embodiment provides a server, see Figure 7 The server includes a network communication port 701, a processor 702 and a memory 703, and the above structures are connected through internal cables so that each structure can perform specific data interaction.

[0168] The network communication port 701 may be used to receive a service promotion attention request.

[0169] The processor 702 may be specifically configured to respond to a business promotion attention request and determine a candidate customer object requiring attention; obtain, at each preset time interval according to a preset business processing rule, first-category information data published by the candidate customer object, second-category information data published by the transaction service platform, and third-category information data published by a third party from multiple data sources; combine the first-category information data, the second-category information data, and the third-category information data to obtain target joint information data; process the target joint information data using a preset business demand mining model to obtain a corresponding target processing result; wherein the preset business demand mining model is a model trained based on a large language model; based on the target processing result, determine a candidate customer object with a business demand as a target customer object; and determine the target demand content of the target customer object; based on the target demand content, determine a matching candidate business from a preset candidate business set as a target business for the target customer object; create a target task for offline promotion of the target business to the target customer object; and generate target prompt information corresponding to the target task; and send the target prompt information to a corresponding business terminal; wherein the business terminal receives and responds to the target prompt information and promotes the target business to the target customer object offline.

[0170] The memory 703 may be specifically used to store corresponding instruction programs, as well as target joint information data, target demand content and other related data.

[0171] Based on the above method, the relevant structural performance of the server can be effectively utilized, the data processing speed of the electronic equipment can be improved, and business data processing can be realized efficiently.

[0172] In this embodiment, the network communication port 701 can be a virtual port that is bound to different communication protocols, thereby being capable of sending or receiving different data. For example, the network communication port can be a port responsible for web data communication, a port responsible for FTP data communication, or a port responsible for email data communication. Furthermore, the network communication port can also be a physical communication interface or communication chip. For example, it can be a wireless mobile network communication chip, such as GSM or CDMA; it can also be a Wi-Fi chip; or it can be a Bluetooth chip.

[0173] In this embodiment, the processor 702 may be implemented in any suitable manner. For example, the processor may take the form of a microprocessor or a processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, a logic gate, a switch, an application-specific integrated circuit (ASIC), a programmable logic controller, an embedded microcontroller, etc. This specification is not intended to limit this.

[0174] In this embodiment, the memory 703 may include multiple levels. In a digital system, anything that can store binary data can be a memory. In an integrated circuit, a circuit with a storage function that does not have a physical form is also called a memory, such as RAM, FIFO, etc. In a system, a storage device with a physical form is also called a memory, such as a memory stick, TF card, etc.

[0175] The embodiment of this specification also provides a computer-readable storage medium based on the above-mentioned business data processing method, wherein the computer-readable storage medium stores computer program instructions, which, when executed, realize the following: receiving and responding to a business promotion attention request, determining a candidate customer object that needs attention; obtaining, through multiple data sources, first-category information data published by the candidate customer object, as well as second-category information data published by the transaction service platform and third-category information data published by a third party at intervals of a preset time period according to a preset business processing rule; combining the first-category information data, the second-category information data, and the third-category information data to obtain target joint information data; and processing the target joint information data using a preset business demand mining model. According to the target processing result, the corresponding target processing result is obtained; wherein, the preset business demand mining model is a model obtained by training based on the large language model; according to the target processing result, the candidate customer objects with business needs are determined as target customer objects; and the target demand content of the target customer objects is determined; according to the target demand content, matching candidate businesses are determined from the preset candidate business set as the target business for the target customer objects; a target task for offline promotion of the target business to the target customer objects is created; and target prompt information corresponding to the target task is generated; the target prompt information is sent to the corresponding business terminal; wherein, the business terminal receives and responds to the target prompt information, and promotes the target business to the target customer objects offline.

[0176] In this embodiment, the storage medium includes, but is not limited to, random access memory (RAM), read-only memory (ROM), cache, hard disk drive (HDD), or memory card. The memory can be used to store computer program instructions. The network communication unit can be an interface configured in accordance with the standards specified by the communication protocol for network connection communication.

[0177] In this embodiment, the functions and effects specifically implemented by the program instructions stored in the computer-readable storage medium can be explained in comparison with other implementations and will not be repeated here.

[0178] The embodiments of the present specification also provide a computer program product, which at least includes a computer program, and when the computer program is executed by a processor, implements the following method steps: receiving and responding to a business promotion attention request, and determining a candidate customer object that needs attention; according to a preset business processing rule, at each preset time period, obtaining first-category information data released by the candidate customer object, as well as second-category information data released by the transaction service platform and third-category information data released by a third party through multiple data sources; combining the first-category information data, the second-category information data, and the third-category information data to obtain target joint information data; using a preset business demand mining model to process the target joint information data, and obtain the corresponding target processing data; processing results; wherein, the preset business demand mining model is a model obtained by training based on the large language model; according to the target processing results, the candidate customer objects with business needs are determined as target customer objects; and the target demand content of the target customer objects is determined; according to the target demand content, matching candidate businesses are determined from the preset candidate business set as the target business for the target customer objects; a target task for offline promotion of the target business to the target customer objects is created; and target prompt information corresponding to the target task is generated; the target prompt information is sent to the corresponding business terminal; wherein, the business terminal receives and responds to the target prompt information, and promotes the target business to the target customer objects offline.

[0179] See Figure 8 As shown, the embodiment of this specification also provides a business data processing device, which may specifically include the following structural modules:

[0180] The receiving module 801 may be specifically configured to receive and respond to a business promotion attention request and determine candidate customer objects that require attention;

[0181] The acquisition module 802 may be specifically configured to acquire, from multiple data sources, first-category information data published by candidate customer objects, second-category information data published by the transaction service platform, and third-category information data published by third parties at predetermined time intervals, according to predetermined business processing rules;

[0182] The combining module 803 may be specifically configured to combine the first type of information data, the second type of information data, and the third type of information data to obtain target joint information data;

[0183] The processing module 804 may be specifically configured to process the target joint information data using a preset business demand mining model to obtain a corresponding target processing result; wherein the preset business demand mining model is a model trained based on a large language model;

[0184] The first determination module 805 may be specifically configured to determine candidate customer objects with business needs as target customer objects based on the target processing result, and determine the target needs of the target customer objects;

[0185] The second determination module 806 may be specifically configured to determine matching candidate services from a preset candidate service set according to target demand content as target services for the target customer object;

[0186] The creation module 807 may be used to create a target task for offline promotion of a target business to a target customer object; and generate target prompt information corresponding to the target task;

[0187] The sending module 808 may be specifically configured to send the target prompt information to a corresponding business terminal; wherein the business terminal receives and responds to the target prompt information, and promotes the target business to the target customer object offline.

[0188] In some embodiments, when the above-mentioned acquisition module 802 is implemented, the first category of information data released by the candidate customer object can be obtained through multiple data sources in the following manner: based on the object identifier of the candidate customer object, query and determine the website, official account, and social account of the candidate customer object; based on the website, official account, and social account of the candidate customer object, query the information data released by the candidate customer object in the current time period as the first category of information data.

[0189] In some embodiments, when the above-mentioned acquisition module 802 is implemented, the second category of information data released by the transaction service platform can be obtained through multiple data sources in the following manner: based on the object identifier of the candidate customer object, the attribute information of the candidate customer object is determined; from the information data released in the current time period of the transaction service platform and the adjacent valid historical time period, information data that matches the attribute information of the candidate customer object is filtered out as the second category of information data.

[0190] In some embodiments, when the above-mentioned acquisition module 802 is implemented, the third category of information data published by a third party can be obtained through multiple data sources in the following manner: based on the object identifier of the candidate customer object, determine the attribute information of the candidate customer object and the object identifier of the associated object of the candidate customer object; based on the attribute information of the candidate customer object, determine the third-party public platform related to the candidate customer object; based on the object identifier of the associated object, determine the website, official account, and social account of the associated object; filter out the first branch message related to the candidate customer object from the information data published in the current time period of the third-party public platform and the adjacent valid historical time period; filter out the second branch message related to the candidate customer object from the information data published in the current time period on the website, official account, and social account of the associated object; combine the first branch message and the second branch message to obtain the corresponding third category of information data.

[0191] In some embodiments, after candidate customer objects with business needs are determined as target customer objects based on the target processing results, the device can also be used, when implemented, to: determine the target demand content of the target customer object based on the target processing results; filter out key information data from the first category of information data, the second category of information data, and the third category of information data based on the target demand content; and process the key information data using a preset semantic extraction model to obtain a key information summary and key content text of the key information data.

[0192] Accordingly, after sending the target prompt information to the corresponding business terminal, the device can also be used to: reach the business terminal with the key information summary, key content text, and link address of the key information data.

[0193] In some embodiments, after the target prompt information is sent to the corresponding business terminal, the device can also be used, when implemented, to: receive the target promotion records and target promotion results of offline target business promotions to target customer objects uploaded by the business terminal; verify the target promotion results according to the target promotion records to obtain corresponding target verification results; based on the target verification results, if it is determined that the verification is passed, perform a quality evaluation on the offline business promotion of the business terminal for the target customer objects based on the target promotion records and the target promotion results to obtain corresponding target evaluation results.

[0194] In some embodiments, after obtaining the corresponding target evaluation result, the device can also be used for: when it is determined based on the target evaluation result that the offline business promotion of the business terminal for the target customer object does not meet the preset requirements and the target promotion result is a promotion failure, detect whether the target customer object and the target business meet the re-promotion conditions; when it is determined that the target customer object and the target business meet the re-promotion conditions, create a re-promotion task for offline re-promoting the target business to the target customer object; and obtain the attribute information of the business terminal and the attribute information of the target customer object; use the preset promotion strategy generation model to process the target promotion record, the attribute information of the business terminal, and the attribute information of the target customer object to determine an improved promotion strategy; send a re-promotion prompt message to the business terminal; wherein, the re-promotion prompt message carries at least the improved promotion strategy.

[0195] It should be noted that the units, devices or modules described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. For the convenience of description, the above devices are described in terms of functions and are divided into various modules and described separately. Of course, when implementing this specification, the functions of each module can be implemented in the same or multiple software and / or hardware, or the module that implements the same function can be implemented by a combination of multiple sub-modules or sub-units. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0196] As can be seen from the above, the business data processing device provided in the embodiment of this specification can effectively assist the business terminal to accurately and automatically discover the business needs of the target customer object, as well as the target business suitable for the target customer object; and automatically create corresponding target tasks in a timely manner, and provide relevant prompts to the business terminal, so that the business terminal can efficiently and accurately realize offline business promotion and obtain better promotion effects.

[0197] In a specific example scenario, the business data processing method provided in this specification can be used to implement a bank's news opportunity (e.g., business demand) analysis and customer visits (e.g., customer business promotion) based on a financial macro model (e.g., a preset business demand mining model). The specific implementation process can be found below.

[0198] In this scenario example, consider that by combining financial big models, account managers (e.g., business personnel) can implement AI analysis of the entire process from business opportunity identification (e.g., exploring business needs), business opportunity analysis to customer visits and post-visit summaries.

[0199] In this example scenario, see Figure 9 As shown, the big model can be used to analyze news in a specified direction (for example, third-category information data) first, and then, based on the content of the news, the financial big model can be called to generate a news summary and business opportunity objects (for example, customer objects) in the news, and list business opportunity information (for example, business demand content), and then similarity matching of in-bank customer names can be performed by combining the small model, and business information such as the customer survey report of the customer can be queried.

[0200] At the same time, based on the business opportunity objects and business opportunity information generated in the previous step, the administrator can publish business opportunity visit tasks through the business opportunity analysis system. The customer manager can check the relevant information of the customer through the business opportunity analysis system and prepare better marketing strategies.

[0201] After a visit is completed, the account manager can also describe the visit process (for example, target promotion records) through voice. The system generates the visit content through voice recognition and uses financial models to generate and analyze the visit records. The system also regularly uses AI to score the account manager's customer visit content to assess the quality of the customer visit, allowing administrators to systematically assign and manage customer visit tasks and improve efficiency.

[0202] For specific implementation, see Figure 9 As shown in the figure, after acquiring potential news opportunity data, the system will regularly store the news and use AI skills to analyze the news objects for user browsing. At the same time, the business opportunity system can be linked with other management applications to ensure the availability and efficiency of the branch business opportunity visit process.

[0203] For news opportunity acquisition, analysis, and field visits, the primary data source is business opportunity news provided by business departments. After users maintain news hotspots, the latest business opportunity news content is saved to the system, and the article text is regularly entered into the database for subsequent system access and user browsing. Data sources can be expanded to meet specific business needs. For example, regular article content acquisition can be performed on specific websites, and existing hot content and keywords can be searched through the public interfaces of common search engines to obtain the latest relevant articles.

[0204] News business opportunity analysis is mainly divided into four parts: data maintenance, news square, projects, and enterprise analysis.

[0205] 1) Data maintenance

[0206] On the data maintenance page, users can maintain their own business opportunity news. At the same time, users can also maintain their own favorite projects and corporate clients in the industry for AI system data analysis.

[0207] 2) News Plaza

[0208] Users can view news and business opportunity articles on the News Square page. The business opportunity system leverages the skills of the large model scheduling platform to implement functions such as summaries of business opportunity news, detection of news description objects, and business opportunity exploration. Compared to manually browsing business opportunity news to obtain opportunities, the business opportunity system reduces the amount of reading required to obtain opportunities. Users can quickly access opportunity content by reading summaries and business opportunity exploration information. Users can also add and maintain news description objects and view the specific content of news description objects in the news.

[0209] Users can click on the news description object, and the system will perform similarity matching based on the news description object, automatically find the corresponding customers in the industry, and display the customer's detailed information in the customer group system for users' reference.

[0210] At the same time, on the News Square page, the business opportunity system has been linked with the customer visit system and the customer express system. The business opportunity visit administrator can click on the news description object to initiate the customer express business opportunity push of the news description object, publish the visit task and assign it to the customer's maintenance account manager.

[0211] 3) Project / Enterprise Analysis

[0212] Based on the projects / enterprises maintained by the user on the data maintenance page, the system generates a timeline of business opportunity events for the projects / enterprises that the user is following on the project / enterprise analysis page. The user can browse all business opportunity news and related summaries on the timeline as well as historical business opportunity exploration information generated by the AI ​​large model.

[0213] At the same time, users can conduct AI summary and analysis of the projects / enterprises they are interested in under a customized time dimension. Users can view the AI ​​big model under the selected time dimension, including a brief summary of news events within the project / enterprise's cycle, the project / enterprise's funding needs within the cycle, the discovery of possible areas of in-depth cooperation between the project / enterprise and the bank, and relevant suggestions for the project / enterprise to the account manager.

[0214] 4) Release of visit tasks

[0215] Users can initiate business opportunity visits to the objects described in the news through the business opportunity system, and push the business opportunity visit tasks to the account managers of the in-bank customers corresponding to the objects.

[0216] After completing a business opportunity visit, the visiting account manager can record the progress and results of the visit via voice. The system then generates text based on the recorded voice in real time. Using the platform's large model, the system generates detailed information about the visit, including the purpose of the visit, customer needs, customer business conditions, customer cooperation intentions, and bank strategies. The system also generates AI-based scoring based on the visit content for managers' reference and unified management.

[0217] Through the above scenario examples, it is verified that the business data processing method provided in this manual can better realize business opportunity acquisition, especially for existing customers and potential customers, with higher search condition accuracy and higher crawling efficiency; use AI big models to generate industry-specific analysis and reports: combine existing customer data and financial products to conduct customer feature analysis and generate industry-specific reports; it can also be analyzed through internal self-adjusting big models, combined with special visit tasks, to meet the platform visit needs.

[0218] Although this specification provides the method operation steps as described in the embodiments or flow charts, more or fewer operation steps may be included based on conventional or non-creative means. The order of steps listed in the embodiments is only one way of executing the order of many steps and does not represent the only execution order. When the device or client product in practice is executed, it can be executed in sequence or in parallel according to the method shown in the embodiments or the drawings (for example, a parallel processor or a multi-threaded processing environment, or even a distributed data processing environment). The term "comprise", "include" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, product or device including a series of elements includes not only those elements, but also includes other elements that are not explicitly listed, or also includes elements inherent to such process, method, product or device. In the absence of more restrictions, it is not excluded that there are other identical or equivalent elements in the process, method, product or device including the elements. Words such as first and second are used to represent names and do not represent any particular order.

[0219] Those skilled in the art will also appreciate that, in addition to implementing the controller in pure computer-readable program code, it is entirely possible to implement the same functionality by logically programming the method steps in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, embedded microcontrollers, and the like. Therefore, such a controller can be considered a hardware component, and the devices included therein for implementing various functions can also be considered structures within the hardware component. Alternatively, the devices for implementing various functions can be considered both software modules implementing the method and structures within the hardware component.

[0220] This specification may be described in the general context of computer-executable instructions, such as program modules, executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, classes, and the like that perform specific tasks or implement specific abstract data types. This specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communications network. In a distributed computing environment, program modules may be located in local and remote computer-readable storage media, including storage devices.

[0221] Through the description of the above embodiments, it can be seen that those skilled in the art can clearly understand that this specification can be implemented by means of software plus the necessary general hardware platform. Based on this understanding, the technical solution of this specification can essentially be embodied in the form of a software product. This computer software product can be stored in a storage medium such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a mobile terminal, a server, or a network device, etc.) to execute the methods described in various embodiments or certain parts of the embodiments of this specification.

[0222] The various embodiments in this specification are described in a progressive manner. References to the common or similar parts of the various embodiments are sufficient. Each embodiment focuses on the differences from the other embodiments. This specification can be used in a variety of general-purpose or specialized computer system environments or configurations. For example, personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable electronic devices, network PCs, minicomputers, mainframe computers, and distributed computing environments that include any of the above systems or devices.

[0223] Although the present specification is described through embodiments, those skilled in the art will appreciate that there are many modifications and variations to the present specification without departing from the spirit of the present specification. It is intended that the appended claims include these modifications and variations without departing from the spirit of the present specification.

Claims

1. A business data processing method, characterized in that: Servers used in the trading service platform include: Receive and respond to business promotion attention requests and identify candidate customers who need attention; According to the preset business processing rules, at every preset time period, the first type of information data released by the candidate customer objects, the second type of information data released by the transaction service platform, and the third type of information data released by the third party are obtained through multiple data sources; combining the first type of information data, the second type of information data, and the third type of information data to obtain target joint information data; Utilize the preset business demand mining model to process the target joint information data and obtain the corresponding target processing results; wherein the preset business demand mining model is a model trained based on the large language model; Based on the target processing results, candidate customers with business needs are identified as target customers, and the target needs of the target customers are determined; According to the target demand content, matching candidate businesses are determined from the preset candidate business set as the target business for the target customer object; Create a target task for offline promotion of the target business to the target customer; and generate target prompt information corresponding to the target task; Sending target prompt information to a corresponding business terminal; wherein the business terminal receives and responds to the target prompt information and promotes the target business to the target customer object offline; Among them, the first category of information data released by candidate customer objects is obtained through multiple data sources, including: querying and determining the website, official account, and social account of the candidate customer object based on the object identifier of the candidate customer object; querying the information data released by the candidate customer object in the current time period based on the website, official account, and social account of the candidate customer object as the first category of information data; obtaining the second category of information data released by the transaction service platform through multiple data sources, including: determining the attribute information of the candidate customer object based on the object identifier of the candidate customer object; screening out information data that matches the attribute information of the candidate customer object from the information data released in the current time period of the transaction service platform and the adjacent valid historical time period as the second category of information data; obtaining information data released by third parties through multiple data sources. The third category of information data released includes: determining the attribute information of the candidate customer object and the object identifier of the associated object of the candidate customer object based on the object identifier of the candidate customer object; determining the third-party public platform related to the candidate customer object based on the attribute information of the candidate customer object; determining the website, official account, and social account of the associated object based on the object identifier of the associated object; filtering out the first branch message related to the candidate customer object from the information data released in the current time period of the third-party public platform and the adjacent valid historical time period; filtering out the second branch message related to the candidate customer object from the information data released in the current time period on the website, official account, and social account of the associated object; combining the first branch message and the second branch message to obtain the corresponding third category of information data.

2. The method according to claim 1, characterized in that After determining candidate customer objects with business needs as target customer objects based on the target processing result, the method further includes: According to the target processing results, determine the target needs of the target customer objects; According to target requirements, key information data is screened out from the first category of information data, the second category of information data, and the third category of information data; Processing the key information data using a preset semantic extraction model to obtain a key information summary and key content text of the key information data; Accordingly, the method further includes: The key information summary, key content text, and link address of the key information data are delivered to the business terminal.

3. The method according to claim 1, characterized in that After sending the target prompt information to the corresponding service terminal, the method further includes: Receive target promotion records and target promotion results of offline target business promotions to target customers uploaded by business terminals; Verify the target promotion results according to the target promotion records and obtain the corresponding target verification results; According to the target verification results, when it is determined that the verification has passed, the quality evaluation of the offline business promotion of the business terminal for the target customer objects is carried out according to the target promotion records and target promotion results to obtain the corresponding target evaluation results.

4. The method according to claim 3, characterized in that After obtaining the corresponding target evaluation result, the method further includes: If, based on the target evaluation results, it is determined that the offline business promotion of the business terminal for the target customer does not meet the preset requirements and the target promotion result is a promotion failure, check whether the target customer and the target business meet the re-promotion conditions; When it is determined that the target customer object and the target business meet the re-promotion conditions, a re-promotion task is created to re-promote the target business to the target customer object offline; and attribute information of the business terminal and the target customer object is obtained; Using the preset promotion strategy generation model to process target promotion records, attribute information of business terminals, and attribute information of target customer objects, an improved promotion strategy is determined; Sending re-promotion prompt information to the service terminal; wherein the re-promotion prompt information at least carries an improved promotion strategy.

5. A business data processing device, characterized in that: Servers used in the trading service platform include: The receiving module is used to receive and respond to business promotion attention requests and determine candidate customer objects that need attention; An acquisition module is used to acquire, through multiple data sources, first-category information data published by candidate customer objects, second-category information data published by the transaction service platform, and third-category information data published by third parties at preset time intervals according to preset business processing rules; a combining module, configured to combine the first type of information data, the second type of information data, and the third type of information data to obtain target joint information data; A processing module is used to process the target joint information data using a preset business demand mining model to obtain a corresponding target processing result; wherein the preset business demand mining model is a model obtained by training based on a large language model; The first determination module is used to determine candidate customer objects with business needs as target customer objects based on the target processing results; and determine the target needs of the target customer objects; The second determination module is used to determine matching candidate services from a preset candidate service set according to target demand content as target services for target customers; A creation module is used to create a target task for offline promotion of a target business to a target customer; and generate target prompt information corresponding to the target task; A sending module is used to send the target prompt information to the corresponding business terminal; wherein the business terminal receives and responds to the target prompt information and promotes the target business to the target customer object offline; Among them, the first category of information data released by candidate customer objects is obtained through multiple data sources, including: querying and determining the website, official account, and social account of the candidate customer object based on the object identifier of the candidate customer object; querying the information data released by the candidate customer object in the current time period based on the website, official account, and social account of the candidate customer object as the first category of information data; obtaining the second category of information data released by the transaction service platform through multiple data sources, including: determining the attribute information of the candidate customer object based on the object identifier of the candidate customer object; screening out information data that matches the attribute information of the candidate customer object from the information data released in the current time period of the transaction service platform and the adjacent valid historical time period as the second category of information data; obtaining information data released by third parties through multiple data sources. The third category of information data released includes: determining the attribute information of the candidate customer object and the object identifier of the associated object of the candidate customer object based on the object identifier of the candidate customer object; determining the third-party public platform related to the candidate customer object based on the attribute information of the candidate customer object; determining the website, official account, and social account of the associated object based on the object identifier of the associated object; filtering out the first branch message related to the candidate customer object from the information data released in the current time period of the third-party public platform and the adjacent valid historical time period; filtering out the second branch message related to the candidate customer object from the information data released in the current time period on the website, official account, and social account of the associated object; combining the first branch message and the second branch message to obtain the corresponding third category of information data.

6. A server, characterized in that: The method comprises a processor and a memory for storing processor-executable instructions, wherein the processor implements the steps of the method according to any one of claims 1 to 4 when executing the instructions.

7. A computer-readable storage medium, characterized in that Computer instructions are stored thereon, and when the instructions are executed by a processor, the steps of the method according to any one of claims 1 to 4 are implemented.

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