Transaction processing method and device, electronic equipment and computer program product

Abstract

The invention discloses a transaction processing method and device, electronic equipment and a computer program product. The method relates to the field of financial science and technology, and comprises the following steps: receiving a transaction processing request sent by a transaction object through a first client, and extracting transaction elements from the transaction processing request to obtain M transaction elements; obtaining N candidate processing objects, and screening out a target processing object from the N candidate processing objects through the M transaction elements; under the condition that a consultation request sent by a second client is received, calling a transaction analysis model according to the consultation request, and processing the M transaction elements by the transaction analysis model to obtain a transaction data interval; and when a confirmation operation of the transaction object on the transaction data interval is detected, generating a transaction protocol based on the transaction data interval, and executing a transaction operation based on the transaction protocol. Through the method and the device, the technical problem of low transaction efficiency during cross-regional transaction in related technologies is solved.

Description

Technical Field

[0001] This application relates to the field of financial technology, and more specifically, to a transaction processing method, apparatus, electronic device, and computer program product. Background Technology

[0002] In modern financial markets, transactions across different regions play a crucial role, with significant volumes and frequencies. Cross-regional transactions between financial institutions in different areas are particularly frequent and complex. Traditionally, this process has relied heavily on manual operations. This means that when conducting a transaction, inquiries must be made to traders in another region via non-instantaneous communication methods such as telephone, email, or instant messaging tools. Due to incomplete transaction information, both parties need to go through multiple rounds of communication and confirmation. This process is not only time-consuming and labor-intensive but also significantly reduces transaction efficiency. Furthermore, delays in manual processing often lead to missed trading windows, directly impacting the transaction completion rate and profits.

[0003] In recent years, although some financial institutions have attempted to introduce intelligent pricing systems, using rule engines or preset templates to automate parts of the trading process, these systems have proven inadequate in the face of complex and ever-changing trading environments. Rule engines have limited flexibility and struggle to handle diverse trading intentions; while preset templates have poor adaptability and limited responsiveness to unexpected situations or non-standard trading requests. This not only increases the system's maintenance costs but also limits its application in actual trading.

[0004] Breakthroughs in large language model technology have brought new possibilities for automating forex trading, especially its contextual understanding and intent recognition capabilities, which can theoretically significantly improve the intelligence level of trading dialogues. However, effectively applying this technology to key aspects of trading such as price inquiry, negotiation, and agreement generation, while ensuring the controllability and compliance of the trading process, still faces severe challenges and unresolved technical problems.

[0005] There is currently no effective solution to the technical problem of low transaction efficiency when conducting cross-regional transactions in related technologies. Summary of the Invention

[0006] The main objective of this application is to provide a transaction processing method, apparatus, electronic device, and computer program product to solve the technical problem of low transaction efficiency in cross-regional transactions in related technologies.

[0007] To achieve the above objectives, according to one aspect of this application, a transaction processing method is provided. The method includes: receiving a transaction processing request sent by a transaction object through a first client; extracting transaction elements from the transaction processing request to obtain M transaction elements, wherein the M transaction elements include at least: transaction object, transaction amount, transaction currency type, and transaction type, where M is a positive integer; obtaining N candidate processing objects; selecting a target processing object from the N candidate processing objects using the M transaction elements; and forwarding the transaction processing request to a second client of the target processing object, where N is a positive integer; upon receiving a consultation request sent by the second client, invoking a transaction analysis model according to the consultation request, and having the transaction analysis model process the M transaction elements to obtain a transaction data range, wherein the consultation request refers to a request generated by the target processing object based on the transaction processing request to obtain the transaction data range; and upon detecting a confirmation operation by the transaction object on the transaction data range, generating a transaction agreement based on the transaction data range, and executing the transaction operation based on the transaction agreement.

[0008] Further, extracting transaction elements from the transaction processing request to obtain M transaction elements includes: obtaining an element extraction task, determining an entity recognition model based on the element extraction task, wherein the element extraction task refers to the task of extracting different types of elements; inputting the transaction processing request into the entity recognition model, wherein the entity recognition model performs semantic parsing on the transaction processing request to obtain M initial elements; obtaining entity labeling rules, matching entity labels for the M initial elements based on the entity labeling rules to obtain M transaction elements, wherein the entity labeling rules include multiple types of elements and the entity label corresponding to each element.

[0009] Furthermore, selecting the target processing object from N candidate processing objects using M transaction elements includes: obtaining object information for each candidate processing object to obtain N sets of candidate object information, wherein each set of candidate object information includes at least: the total number of transactions to be processed for the candidate processing object, the accuracy rate of transaction processing, and geographical location information; obtaining conversion rules, and converting the format of each set of candidate object information based on the conversion rules to obtain N sets of processed object data, wherein the conversion rules include multiple object information and the corresponding value for each object information; obtaining a preset weight set, performing weighted calculation on each set of processed object data based on the preset weight set to obtain N candidate scores, and selecting the target processing object from the N candidate processing objects based on the N candidate scores.

[0010] Furthermore, after forwarding the transaction processing request to the second client of the target processing object, the method further includes: receiving Y interactive messages sent by the target processing object through the second client, identifying the Y interactive messages to obtain Y sets of interactive elements, wherein the Y interactive messages refer to the dialogue information between the target processing object and the transaction object, and Y is a positive integer; obtaining a summary generation model, inputting the Y sets of interactive elements into the summary generation model, outputting negotiation information, and sending the negotiation information to the second client, wherein the target processing object generates a consultation request based on the negotiation information.

[0011] Furthermore, after receiving Y interactive messages sent by the target processing object through the second client, the method further includes: obtaining interactive information monitoring rules, wherein the interactive information monitoring rules include multiple abnormal interactive messages and the risk level corresponding to each abnormal interactive message; performing risk monitoring on the Y interactive messages according to the interactive information monitoring rules; if there are no abnormal interactive messages among the Y interactive messages, performing a step of identifying the Y interactive messages; if there are K abnormal interactive messages among the Y interactive messages, obtaining the risk levels of the K abnormal interactive messages, wherein K is less than or equal to Y and K is a positive integer; generating interactive prompt messages according to the K risk levels, and sending the interactive prompt messages to the second client.

[0012] Furthermore, the transaction analysis model includes a statistical module and a quantitative module. The transaction analysis model processes M transaction elements to obtain a transaction data range, which includes: extracting the transaction currency type and transaction type from the M transaction elements; obtaining historical transaction data within a historical time period based on the transaction currency type; receiving initial transaction data sent by the second client and obtaining the transaction risk level associated with the transaction type, wherein the initial transaction data is the transaction data determined by the target processing object according to the transaction processing request; the statistical module calculates the transaction standard deviation based on the historical transaction data; the quantitative module adjusts the initial transaction data according to the transaction risk level to obtain adjusted transaction data; and the range of the adjusted transaction data is expanded based on the transaction standard deviation to obtain the transaction data range.

[0013] Furthermore, generating a transaction protocol based on a transaction data range includes: responding to a protocol generation instruction sent by the target processing object; obtaining a protocol template according to the protocol generation instruction; filling the protocol template with M transaction elements and a transaction data range to obtain an initial transaction protocol; and sending the initial transaction protocol to the second client of the target processing object and the third client of the transaction object through a preset interface; upon receiving confirmation information from the second client and the second client, sending a signature prompt message to the second client and the third client, wherein the target processing object and the transaction object respectively perform a signature operation on the initial transaction protocol based on the signature prompt message to obtain a signed transaction protocol; and upon receiving the signed transaction protocol, confirming the signed transaction protocol as the transaction protocol.

[0014] To achieve the above objectives, according to another aspect of this application, a transaction processing apparatus is provided. The apparatus includes: a first receiving unit, configured to receive a transaction processing request sent by a transaction object through a first client, extract transaction elements from the transaction processing request to obtain M transaction elements, wherein the M transaction elements include at least: transaction object, transaction amount, transaction currency type, and transaction type, where M is a positive integer; a first obtaining unit, configured to obtain N candidate processing objects, filter out a target processing object from the N candidate processing objects using the M transaction elements, and forward the transaction processing request to a second client of the target processing object, where N is a positive integer; a calling unit, configured to, upon receiving a consultation request sent by the second client, call a transaction analysis model according to the consultation request, and have the transaction analysis model process the M transaction elements to obtain a transaction data range, wherein the consultation request refers to a request generated by the target processing object based on the transaction processing request to obtain the transaction data range; and a first generating unit, configured to, upon detecting a confirmation operation by the transaction object on the transaction data range, generate a transaction protocol based on the transaction data range, and execute a transaction operation based on the transaction protocol.

[0015] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored executable program, wherein, when the executable program is running, a processing method for controlling the device where the computer-readable storage medium is located to perform any of the above-mentioned transactions is provided.

[0016] According to another aspect of the present invention, an electronic device is also provided, including one or more processors and a memory, the memory storing an executable program, and the processor for running the program, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement the processing method of any of the above-described transactions.

[0017] According to another aspect of the present invention, a computer program product is also provided, the computer program product including a computer program, wherein when the computer program is executed by a processor, it implements the processing method of any of the above-described transactions.

[0018] In this embodiment, a transaction processing method is adopted. A transaction processing request is received from a transaction object via a first client. Transaction elements are extracted from the request to obtain M transaction elements, where each of the M elements includes at least: the transaction object, transaction amount, transaction currency type, and transaction type, where M is a positive integer. N candidate processing objects are obtained, and a target processing object is selected from these N candidates using the M transaction elements. The transaction processing request is then forwarded to a second client of the target processing object, where N is a positive integer. Upon receiving a consultation request from the second client, a transaction analysis model is invoked based on the consultation request. The transaction analysis model processes the M transaction elements to obtain a transaction data range. The consultation request refers to the target processing object's basic... This system generates a request to obtain a transaction data range from a transaction processing request. Upon detecting a confirmation operation by the transaction object on the transaction data range, it generates a transaction agreement based on the data range and executes the transaction operation based on the agreement. This solves the technical problem of low transaction efficiency in cross-regional transactions in related technologies. By acquiring transaction elements, filtering target processing objects from multiple candidate processing objects based on these elements, calling a transaction analysis model, and having the model process these transaction elements to obtain a transaction data range, generating a transaction agreement based on the data range, and executing the transaction operation based on the agreement, it achieves the goal of accurately identifying transaction intentions and elements, matching and negotiating with processing objects, thereby improving the technical efficiency of cross-regional transactions. Attached Figure Description

[0019] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0020] Figure 1 It is a hardware structure block diagram of a computer terminal (or mobile device) used to implement a transaction processing method;

[0021] Figure 2 This is a flowchart of a transaction processing method provided according to an embodiment of this application;

[0022] Figure 3 This is a schematic diagram of a transaction processing system provided according to an embodiment of this application;

[0023] Figure 4This is a schematic diagram of a transaction processing apparatus provided according to an embodiment of this application;

[0024] Figure 5 This is a structural block diagram of an electronic device according to an embodiment of this application. Detailed Implementation

[0025] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0026] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0027] It should be noted that all information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for display, data used for analysis, etc.) involved in this application are information and data authorized by the user or fully authorized by all parties. For example, this system has interfaces with relevant users or organizations to provide users with corresponding operation data for them to choose to agree to or refuse automated decision results. Before obtaining relevant information, a request for obtaining the information needs to be sent to the aforementioned user or organization through the interface, and the relevant information is obtained after receiving consent from the aforementioned user or organization; if the user chooses to refuse, the expert decision-making process is initiated. Users can view the purpose of data use in real time through authorization decoding and have the right to withdraw authorization or delete data at any time. After the authorization is withdrawn, the system will terminate the relevant data processing within 24 hours.

[0028] It should be noted that the information collected in this application is information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data all comply with the relevant laws, regulations and standards of the relevant regions, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation access points for users to choose to authorize use or refuse use.

[0029] Example 1

[0030] According to an embodiment of this application, a method embodiment for processing transactions is also provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0031] The method embodiment provided in Embodiment 1 of this application can be executed on a mobile terminal, computer terminal, or similar computing device. Figure 1 This is a hardware structure block diagram of a computer terminal (or mobile device) used to implement a transaction processing method, such as... Figure 1 As shown, computer terminal 10 (or mobile device) may include one or more ( Figure 1 The processor 102 (which may include, but is not limited to, a microprocessor MCU (Microcontroller Unit) or a programmable gate array (FPGA)) is illustrated using 102a, 102b, ..., 102n. It also includes a memory 104 for storing data and a transmission device 106 for communication functions. In addition, it may include: a display, an input / output interface (I / O interface), a Universal Serial Bus (USB) port (which may be included as one of the ports of a BUS bus), a network interface, a keyboard, a cursor control device, a power supply, and / or a camera. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, computer terminal 10 may also include... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0032] It should be noted that the aforementioned one or more processors 102 and / or other data processing circuits are generally referred to herein as "data processing circuits". These data processing circuits may be embodied, in whole or in part, in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuits may be a single, independent processing module, or may be integrated, in whole or in part, into any other element within the computer terminal 10 (or mobile device). As involved in the embodiments of this application, the data processing circuits serve as a processor control mechanism (e.g., selection of a variable resistor termination path connected to an interface).

[0033] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the transaction processing method in this embodiment. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, thereby implementing the aforementioned transaction processing method. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the computer terminal 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0034] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of the computer terminal 10. In one example, the transmission device 106 includes a network interface controller (NIC) and a network interface, which can be connected to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a radio frequency (RF) module, used for wireless communication with the Internet.

[0035] The display can be, for example, a touchscreen liquid crystal display (LCD), which allows the user to interact with the user interface of the computer terminal 10 (or mobile device).

[0036] Under the aforementioned operating environment, this application provides the following: Figure 2 The transaction processing method is shown. Figure 2 This is a flowchart of a transaction processing method provided according to an embodiment of this application, such as... Figure 2 As shown, the method includes the following steps:

[0037] Step S201: Receive the transaction processing request sent by the transaction object through the first client, extract the transaction elements from the transaction processing request, and obtain M transaction elements. The M transaction elements include at least: transaction object, transaction amount, transaction currency type and transaction type, where M is a positive integer.

[0038] It should be noted that a transaction processing request can be a transaction request initiated by a trader in a certain region through the first client. The request includes preliminary trading intentions and necessary trading parameters, such as the desired quantity to buy or sell and the expected trading price. The transaction processing request sent through the first client can transmit the trading intentions of traders in region A to region B in digital form, providing raw input for subsequent steps such as transaction element extraction, transaction matching, and negotiation.

[0039] Transaction elements refer to key transaction details identified and parsed from transaction processing requests, including but not limited to transaction amount, currency, direction, counterparty, and specific transaction requirements (such as special time requirements). Accurate extraction and parsing of these elements allows for a rapid understanding of the trader's intentions, laying a solid foundation for subsequent intelligent matching, transaction negotiation, and agreement generation.

[0040] Step S202: Obtain N candidate processing objects, select the target processing object from the N candidate processing objects through M transaction elements, and forward the transaction processing request to the second client of the target processing object, where N is a positive integer.

[0041] Specifically, in order to realize the transaction, potential transaction matching objects are first identified from the set of processing objects associated with the database, that is, multiple candidate processing objects are obtained. Then, the candidate processing objects are filtered using the above-mentioned transaction elements. By comparing the current working status and other information of the candidate processing objects with the matching degree of the transaction elements, one or more of the most matching target processing objects are finally determined, and the transaction processing request is forwarded to the second client of the target processing object, ensuring that the transaction request can reach the target trader in time and start the real-time transaction dialogue between the two parties.

[0042] Step S203: Upon receiving a consultation request from the second client, the transaction analysis model is invoked according to the consultation request, and the transaction analysis model processes the M transaction elements to obtain the transaction data range. Here, the consultation request refers to the request generated by the target processing object based on the transaction processing request to obtain the transaction data range.

[0043] Specifically, after receiving a transaction processing request, the target processing object initiates a specific request to the system to further analyze transaction elements and evaluate transaction conditions, i.e., a consultation request. At this time, the transaction analysis model can be invoked according to the consultation request, transforming the trader's needs into analyzable data input. Through the model's calculation and analysis, a transaction data range is output. This range not only encompasses a reasonable price range but may also include additional information such as market trends and liquidity analysis, providing traders with a comprehensive market perspective and helping to formulate more reasonable pricing or counter-pricing strategies. The transaction analysis model can generate a transaction data range that reflects market dynamics, transaction risks, and expected prices based on transaction elements, combined with real-time market conditions, historical transaction records, macroeconomic indicators, and other data, through statistical or machine learning algorithms.

[0044] Step S204: If a confirmation operation of the transaction object on the transaction data range is detected, a transaction agreement is generated based on the transaction data range, and the transaction operation is executed based on the transaction agreement.

[0045] Specifically, after the transaction data range is generated, the trading parties take action on the system interface, such as clicking "Confirm," "Agree," or similar buttons, to electronically indicate their acceptance and recognition of the transaction data range. When the trading party's confirmation action is detected, it indicates that both parties have reached a preliminary consensus on the core elements of the transaction. At this point, a standardized document can be generated based on the transaction data range, providing a formal basis for the execution of the transaction, i.e., a transaction agreement. The transaction agreement records all the details of the transaction, including the trading parties, transaction amount, transaction currency type, transaction type, transaction price, settlement date, and account information.

[0046] Furthermore, after the transaction agreement is generated and confirmed by both parties, the transaction process can be executed, including but not limited to the transfer of funds, the locking of exchange rates, the updating of transaction records, and the electronic signing and sending of confirmation documents.

[0047] The transaction processing method provided in this application embodiment receives a transaction processing request sent by a transaction object through a first client, extracts transaction elements from the transaction processing request to obtain M transaction elements, wherein the M transaction elements include at least: transaction object, transaction amount, transaction currency type, and transaction type, and M is a positive integer; obtains N candidate processing objects, selects a target processing object from the N candidate processing objects based on the M transaction elements, and forwards the transaction processing request to a second client of the target processing object, wherein N is a positive integer; upon receiving a consultation request sent by the second client, invokes a transaction analysis model according to the consultation request, and the transaction analysis model processes the M transaction elements to obtain a transaction data range, wherein the consultation request refers to the target processing object based on the transaction... This system easily handles requests to obtain transaction data ranges. Upon detecting a confirmation operation by a transaction object on the transaction data range, it generates a transaction agreement based on the data range and executes the transaction operation based on the agreement. This solves the technical problem of low transaction efficiency in cross-regional transactions. By acquiring transaction elements, selecting the target processing object from multiple candidate processing objects, calling the transaction analysis model, and having the model process these transaction elements to obtain the transaction data range, generating a transaction agreement based on the data range, and executing the transaction operation based on the agreement, it achieves the goal of accurately identifying transaction intentions and elements, matching and negotiating with processing objects, thereby improving the technical effect of cross-regional transaction efficiency.

[0048] Optionally, in the transaction processing method provided in this application embodiment, extracting transaction elements from the transaction processing request to obtain M transaction elements includes: obtaining an element extraction task, determining an entity recognition model based on the element extraction task, wherein the element extraction task refers to the task of extracting different types of elements; inputting the transaction processing request into the entity recognition model, and having the entity recognition model perform semantic parsing on the transaction processing request to obtain M initial elements; obtaining entity labeling rules, and matching entity labels for the M initial elements based on the entity labeling rules to obtain M transaction elements, wherein the entity labeling rules include multiple types of elements and entity labels corresponding to each element.

[0049] Specifically, in order to accurately understand and interpret transaction processing requests, the system can first receive element extraction tasks. These tasks include extracting different types of information, such as transaction currency, transaction direction, transaction amount, counterparty information, and transaction time zone. This information then guides the entity recognition model to perform targeted analysis of the transaction processing request in order to extract all the necessary transaction elements.

[0050] Furthermore, an entity recognition model is determined based on the element extraction task. The entity recognition model is a natural language processing technology based on a large language model, used to identify and classify named entities in transaction texts, such as currency pairs, amounts, and institution names. The selection of the entity recognition model needs to be adjusted according to the specific element extraction task and transaction scenario to ensure the best recognition accuracy and efficiency.

[0051] After selecting the most suitable language model for parsing the current transaction request, the transaction processing request can be input into the entity recognition model to transform the unstructured transaction request into structured data, resulting in multiple initial elements. These initial elements can be directly extracted from the transaction processing request by the entity recognition model. Since these elements have not yet undergone further verification and standardized labeling, entity labeling rules can be obtained at this time to match entity labels for the initial elements, thereby obtaining multiple transaction elements.

[0052] It's important to note that entity labeling rules are a predefined set of rules. These rules encompass various types of transaction elements and corresponding label definitions for each element. For example, "USDCNY" is labeled as the "transaction currency type." Entity labels represent the standardized representation of transaction elements, ensuring consistency and traceability, and facilitating subsequent transaction analysis and monitoring. By matching entity labels to initial elements based on entity labeling rules, transaction elements are obtained. This not only standardizes the representation of transaction elements but also clarifies the meaning and purpose of each element by adding entity labels, facilitating tasks such as transaction matching, negotiation assistance, and protocol generation.

[0053] This embodiment determines the entity recognition model through an element extraction task, and then generates transaction elements based on the model and entity labeling rules. It effectively solves the problems of inaccurate information extraction, low processing efficiency, and inconsistent definitions of transaction elements in traditional foreign exchange trading, and achieves the effects of rapid conversion of transaction requests, accurate identification of transaction elements, and efficient transmission.

[0054] Optionally, in the transaction processing method provided in this application embodiment, selecting the target processing object from N candidate processing objects using M transaction elements includes: obtaining object information for each candidate processing object to obtain N sets of candidate object information, wherein each set of candidate object information includes at least: the total number of pending transactions for the candidate processing object, the accuracy rate of transaction processing, and geographical location information; obtaining conversion rules, and converting the format of each set of candidate object information based on the conversion rules to obtain N sets of processed object data, wherein the conversion rules include multiple object information and the numerical value corresponding to each object information; obtaining a preset weight set, performing weighted calculation on each set of processed object data based on the preset weight set to obtain N candidate scores, and selecting the target processing object from the N candidate processing objects based on the N candidate scores.

[0055] Specifically, in order to determine the most suitable target processing object, the object information of each candidate processing object can be obtained first. For example, the total number of pending transactions of the candidate processing object, the accuracy rate of past transaction processing, and its current geographical location information can be obtained. By fully understanding the current status, past performance, and geographical conditions of the candidate processing object, the comprehensive ability and matching degree of each candidate processing object can be more accurately evaluated, so as to achieve more efficient and reasonable trader matching.

[0056] Furthermore, conversion rules are obtained to transform the object information of each candidate processing object into a dataset in a numerical format that can be directly used for calculation, resulting in processed object data. For example, "total number of transactions to be processed" is converted into a number, "accuracy rate of transaction processing" is converted into a percentage, and "geographical location information" is converted into a numerical value indicating the overlap with the target transaction's time zone. This ensures that the information of all candidate processing objects can be processed within a unified computational framework, avoiding computational errors caused by data incompatibility or format confusion. Then, a preset set of weights corresponding to the importance of each candidate processing object's attributes (such as total number of transactions to be processed, accuracy rate of transaction processing, and geographic location information) is obtained. By weighting and calculating each set of processed object data, a score that comprehensively reflects the business capabilities and matching degree of the candidate processing object can be obtained, i.e., a candidate score. This score serves as the main basis for selecting target processing objects. Finally, the target processing object is selected from all candidate processing objects based on each candidate score.

[0057] This embodiment ensures the comprehensiveness and detail of the matching decision by comprehensively collecting various key information of candidate processing objects. Based on a preset weight set, the processed object data is weighted and calculated. Through mathematical operations, these attributes are converted into an intuitive scoring index, which greatly simplifies the decision-making process and can quickly and objectively determine the comprehensive competitiveness of each candidate processing object, thereby selecting the optimal target processing object.

[0058] Optionally, in the transaction processing method provided in this application embodiment, after forwarding the transaction processing request to the second client of the target processing object, the method further includes: receiving Y interactive information sent by the target processing object through the second client, and identifying the Y interactive information to obtain Y sets of interactive elements, wherein the Y interactive information refers to the dialogue information between the target processing object and the transaction object, and Y is a positive integer; obtaining a summary generation model, inputting the Y sets of interactive elements into the summary generation model, outputting negotiation information, and sending the negotiation information to the second client, wherein the target processing object generates a consultation request based on the negotiation information.

[0059] Specifically, to assist the target processing object and the trading object in negotiating a transaction, the system first receives dialogue information between the target processing object and the trading object sent through a second client. This involves receiving multiple interaction messages. Then, by identifying these interactions, the unstructured dialogue information is transformed into structured interaction elements, providing clear data input for subsequent negotiation summaries. Next, a summary generation model that understands the contextual relationships in the transaction negotiation is obtained. These interaction elements are input into the summary generation model, which extracts key negotiation information from the interaction elements. This involves identifying the main transaction intentions of both parties, changes in transaction conditions, and any key information that may affect the transaction progress, generating a comprehensive negotiation summary report that reflects the negotiation progress—in other words, obtaining the negotiation information.

[0060] Furthermore, after the model outputs negotiation information including the latest status of transaction conditions, the negotiation range of both parties, the points of agreement reached, and matters requiring further clarification or negotiation, the negotiation information also needs to be sent to the second client to ensure that the target processing object can keep abreast of the dynamics of the transaction negotiation in real time and understand the changes in the needs of the transaction object. This not only promotes efficient communication between the two parties, but also provides the target processing object with a direct basis for generating consultation requests, further promoting the smooth progress of the transaction negotiation.

[0061] This embodiment ensures that information during the transaction negotiation process can be captured and synchronized quickly and accurately by receiving and recognizing interactive information, generating a negotiation summary report using a summary generation model, and promptly feeding back the core information of the report to both parties. This reduces communication barriers caused by information delays. Through the deep understanding capabilities of the large model, a negotiation summary report can be generated, extracting key information from the transaction negotiation to assist in transaction decisions. This not only improves the transparency of the negotiation but also accelerates the process of reaching an agreement between the two parties by providing a clear communication overview.

[0062] Optionally, in the transaction processing method provided in this application embodiment, after receiving Y interactive messages sent by the target processing object through the second client, the method further includes: obtaining interactive information monitoring rules, wherein the interactive information monitoring rules include multiple abnormal interactive messages and a risk level corresponding to each abnormal interactive message; performing risk monitoring on the Y interactive messages according to the interactive information monitoring rules; if there are no abnormal interactive messages among the Y interactive messages, performing a step of identifying the Y interactive messages; if there are K abnormal interactive messages among the Y interactive messages, obtaining the risk levels of the K abnormal interactive messages, wherein K is less than or equal to Y and K is a positive integer; generating interactive prompt messages according to the K risk levels, and sending the interactive prompt messages to the second client.

[0063] Specifically, to identify potential risks and ensure compliant and transparent communication between the transacting parties, after receiving Y interactive messages sent by the target processing object through the second client, it is also necessary to obtain interactive message monitoring rules. These rules define which types of interactive messages may constitute violations or potential risks, and the corresponding risk levels, ensuring the professionalism and comprehensiveness of the monitoring process. Then, based on the interactive message monitoring rules, risk monitoring is performed on the interactive messages sent by the target processing object, analyzing each interactive message to determine whether it contains abnormal interactive information.

[0064] If no abnormal interaction information is found, the subsequent information identification steps can continue. Conversely, if multiple abnormal interaction information exists, meaning multiple potentially non-compliant or high-risk pieces of information, these can be marked as abnormal interaction information. Each abnormal interaction information is assigned a risk level based on its degree of non-compliance or potential risk, and interactive prompts are generated based on these risk levels. This means risk warnings or compliance suggestions are generated according to the risk level and sent to the second client to alert the target to specific compliance risk points or provide corrective suggestions to avoid violations and ensure the compliance and controllability of transactions.

[0065] This embodiment monitors the information communicated between the two parties in a transaction, quickly identifies potential risk points in the transaction dialogue, and generates interactive prompts to immediately remind the target party to pay attention and correct the situation, effectively preventing violations from occurring. This ensures that the communication between the two parties is always conducted within a compliant framework, significantly reducing compliance risks caused by improper communication. It also enhances the trust of both parties in the automated system and promotes more efficient and smoother transaction dialogues.

[0066] Optionally, in the transaction processing method provided in this application embodiment, the transaction analysis model includes a statistical module and a quantitative module. The transaction analysis model processes M transaction elements to obtain a transaction data range, including: extracting the transaction currency type and transaction type from the M transaction elements; obtaining historical transaction data within a historical time period based on the transaction currency type; receiving initial transaction data sent by a second client and obtaining the transaction risk level associated with the transaction type, wherein the initial transaction data is the transaction data determined by the target processing object according to the transaction processing request; the statistical module calculates the transaction standard deviation based on the historical transaction data; the quantitative module adjusts the initial transaction data according to the transaction risk level to obtain adjusted transaction data; and the adjusted transaction data is expanded in range based on the transaction standard deviation to obtain a transaction data range.

[0067] Specifically, after obtaining multiple trading elements, a trading analysis model consisting of a statistical module and a quantitative module can be acquired first. The statistical module calculates market volatility based on historical trading data, while the quantitative module adjusts the initial trading data according to the trading risk level. When processing using this model, the trading currency type and trading type are first extracted from the trading elements. The trading currency type refers to the currency pair involved in the transaction, and the trading type distinguishes the nature of the transaction, such as buying, selling, or swaps. Then, historical trading data is obtained based on the trading currency type. This historical trading data also includes information such as price, volume, and trading time, used to analyze historical market trends and volatility.

[0068] By analyzing historical data, the statistics module can calculate the fluctuation range of the trading currency type, providing background information on market conditions for generating trading data intervals. In other words, the statistics module calculates the trading standard deviation based on historical trading data. A higher standard deviation may indicate greater market volatility, while a lower standard deviation indicates a relatively stable market. The size of the standard deviation directly affects the width of the trading data interval, ensuring that the interval can reasonably reflect market risks.

[0069] When receiving initial transaction data from the second client, it's also necessary to obtain the transaction risk level associated with the transaction type. Initial transaction data refers to the preliminary transaction data provided by the target processing object based on the transaction request, typically including information such as expected price and trading volume. The transaction risk level is the assessment of the transaction risk level based on factors such as transaction type, trading environment, and counterparty credit, influencing the range adjustment strategy. At this point, the quantitative module can adjust the initial transaction data according to the transaction risk level, obtaining adjusted transaction data. The adjustment strategy can include weighted averaging, dynamic spread addition, etc., to ensure the rationality and security of the transaction data. Finally, the adjusted transaction data is range-expanded based on the transaction standard deviation to obtain a transaction data range reflecting the current market conditions and risk level of the traded currency type.

[0070] This embodiment greatly improves the efficiency and quality of transaction decision-making by constructing a transaction analysis model and intelligently processing transaction elements and generating transaction data ranges. It reduces the uncertainty of manual decision-making, and the dynamic adjustment of transaction data ranges and consideration of transaction risk levels effectively control transaction risks, ensuring that transactions are conducted within a controllable range and enhancing the compliance and security of transactions.

[0071] Optionally, in the transaction processing method provided in this application embodiment, generating a transaction protocol based on a transaction data range includes: responding to a protocol generation instruction sent by a target processing object, obtaining a protocol template according to the protocol generation instruction; filling the protocol template according to M transaction elements and a transaction data range to obtain an initial transaction protocol, and sending the initial transaction protocol to a second client of the target processing object and a third client of the transaction object through a preset interface; upon receiving confirmation information sent by the second client and the second client, sending signature prompt information to the second client and the third client, wherein the target processing object and the transaction object respectively perform a signature operation on the initial transaction protocol based on the signature prompt information to obtain a signed transaction protocol; upon receiving the signed transaction protocol, determining the signed transaction protocol as the transaction protocol.

[0072] Specifically, to facilitate the smooth operation of the transaction, once the two parties reach an agreement through negotiation, the target processing object will send a protocol generation instruction through a second client. At this point, based on the transaction type and elements in the protocol generation instruction, the most matching protocol template is selected, providing a framework for subsequent protocol content filling. Then, the protocol template is filled in according to the transaction elements and transaction data range to generate an initial transaction protocol containing all transaction details.

[0073] Furthermore, the initial transaction agreement is sent to the second client (target processing object) and the third client (transaction object) via a pre-defined interface. This ensures that both parties can simultaneously review the agreement content and confirm that all transaction details are correct. The use of the pre-defined interface guarantees the security and immediacy of the agreement transmission, allowing both parties to review and provide feedback on the received agreement immediately. After both parties confirm the agreement content is correct, a prompt message is sent to the second client (target processing object) and the third client (transaction object) to guide them to confirm the transaction agreement through electronic signatures. That is, a signature prompt message is sent to the second and third clients, prompting both parties to perform the final legal confirmation, i.e., electronic signature.

[0074] After the target processing object and the transaction object sign the initial transaction agreement based on the signature prompt information, the signed transaction agreement is deemed to be effective and can then be identified as the transaction agreement.

[0075] This embodiment, through an intelligent protocol generation and signing process, can generate industry-standard transaction agreements based on transaction elements and data ranges, reducing human error and improving the efficiency of agreement generation. By integrating electronic signature functionality, it ensures the legal validity of the transaction agreement, records the signing process, enhances transaction compliance and auditing capabilities, simplifies the transaction process, and improves the ease of operation and satisfaction for both parties.

[0076] This application also provides a transaction processing system. Figure 3 This is a schematic diagram of a transaction processing system provided according to an embodiment of this application, such as... Figure 3 As shown, the system includes: an element extraction module, a transaction matching module, a negotiation and coordination module, a price negotiation assistance module, an agreement generation module, and a monitoring module.

[0077] First, when a trader in a certain region initiates a foreign exchange transaction request through the first client, the element extraction module can extract and parse these elements. That is, the transaction processing request is input into the entity recognition model, which transforms the unstructured transaction request into structured data, obtaining multiple initial elements. Then, based on the entity labeling rules, entity labels are matched to the initial elements to obtain the transaction elements, laying a solid foundation for subsequent intelligent matching, transaction negotiation, and agreement generation. After obtaining the transaction elements, the transaction matching module can comprehensively collect various key information of the candidate processing objects and filter the target processing objects from multiple candidate processing objects based on the above transaction elements. In order to determine the most suitable target processing object, the object information of each candidate processing object can be obtained first. For example, the total number of pending transactions of the candidate processing object, the accuracy rate of past transaction processing, and its current geographical location information can be obtained. By fully understanding the current status, past performance, and geographical conditions of the candidate processing objects, the comprehensive ability and matching degree of each candidate processing object can be more accurately evaluated, so as to achieve more efficient and reasonable trader matching. When calculating the score of each candidate, the object data of each candidate processing object can be calculated by weighting the preset weight set, such as the current number of pending orders (the less the better, the higher the weight) and the length of overlapping working time with the target time zone (the longer the time length, the higher the weight).

[0078] Furthermore, to guide both parties in real-time, natural language-based negotiation and facilitate consensus, the negotiation and coordination module receives multiple interactive messages. These messages are then identified, transforming unstructured dialogue into structured interactive elements. These elements are input into a summary generation model, which extracts key negotiation information—identifying the parties' primary intentions, changes in transaction terms, and any other information potentially affecting the transaction's progress. This generates a comprehensive negotiation summary report, or negotiation information, reflecting the negotiation's progress. This information is then sent to a second client, ensuring the target client can monitor the negotiation dynamics in real-time and understand changes in the client's needs. This not only promotes efficient communication between the parties but also provides the target client with direct evidence for generating consultation requests, further facilitating the smooth progress of the negotiation.

[0079] During the transaction negotiation process, this module assists traders in making price judgments and negotiation decisions. After obtaining multiple transaction elements, the negotiation assistance module first acquires a transaction analysis model composed of statistical and quantitative modules. Then, the transaction analysis model processes the aforementioned transaction elements to obtain a transaction data range. Once both parties reach an agreement based on this transaction data range, the protocol generation module generates a transaction agreement based on the transaction data range. That is, after obtaining the agreement template, the module fills in the template according to the transaction elements and the transaction data range to obtain an initial transaction agreement. This initial transaction agreement is then sent to the second client of the target processing object and the third client of the transaction object through a preset interface. Upon receiving confirmation information from the second and third clients, a signature prompt is sent to both clients. Upon receiving the signed transaction agreement from both parties, the signed transaction agreement is confirmed as the final transaction agreement.

[0080] It should be noted that, in order to identify potential risks and ensure that communication between the two parties is compliant and transparent, after receiving Y interactive messages sent by the target processing object through the second client, the monitoring module also needs to obtain the interactive information monitoring rules, perform risk monitoring on the interactive information sent by the target processing object according to the interactive information monitoring rules, analyze each interactive message, determine whether it contains abnormal interactive information, and then promptly remind both parties to ensure the compliance and controllability of the transaction.

[0081] This embodiment performs transaction operations through multiple modules, achieving full-chain automation of unstructured language processing, automatic matching, real-time negotiation, reasonable pricing, and protocol generation. This not only significantly improves transaction efficiency but also ensures the compliance and security of transactions.

[0082] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0083] Example 2

[0084] This application also provides a transaction processing apparatus. It should be noted that the transaction processing apparatus of this application can be used to execute the transaction processing method provided in this application. The transaction processing apparatus provided in this application will be described below.

[0085] According to an embodiment of this application, an apparatus for implementing the above-described transaction processing method is also provided. Figure 4 This is a schematic diagram of a transaction processing apparatus provided according to an embodiment of this application, such as... Figure 4As shown, the device includes: a first receiving unit 40, a first acquiring unit 41, a calling unit 42, and a first generating unit 43.

[0086] The first receiving unit 40 is used to receive a transaction processing request sent by the transaction object through the first client, extract transaction elements from the transaction processing request, and obtain M transaction elements, wherein the M transaction elements include at least: transaction object, transaction amount, transaction currency type and transaction type, and M is a positive integer;

[0087] The first acquisition unit 41 is used to acquire N candidate processing objects, filter out the target processing object from the N candidate processing objects through M transaction elements, and forward the transaction processing request to the second client of the target processing object, where N is a positive integer;

[0088] Calling unit 42 is used to call the transaction analysis model according to the consultation request when receiving the consultation request sent by the second client, and the transaction analysis model processes the M transaction elements to obtain the transaction data range. The consultation request refers to the request to obtain the transaction data range generated by the target processing object based on the transaction processing request.

[0089] The first generation unit 43 is used to generate a transaction protocol based on the transaction data range and execute the transaction operation based on the transaction protocol when a confirmation operation of the transaction object on the transaction data range is detected.

[0090] The transaction processing apparatus provided in this application embodiment receives a transaction processing request sent by a transaction object through a first client by a first receiving unit 40, extracts transaction elements from the transaction processing request to obtain M transaction elements, wherein the M transaction elements include at least: transaction object, transaction amount, transaction currency type, and transaction type, and M is a positive integer; a first obtaining unit 41 obtains N candidate processing objects, selects a target processing object from the N candidate processing objects based on the M transaction elements, and forwards the transaction processing request to a second client of the target processing object, wherein N is a positive integer; and a calling unit 42, upon receiving a consultation request sent by the second client, calls a transaction analysis model according to the consultation request, and the transaction analysis model processes the M transaction elements to obtain a transaction data range, wherein the consultation request refers to the target... The processing object generates a request to obtain a transaction data range based on the transaction processing request; when the first generation unit 43 detects the transaction object's confirmation operation on the transaction data range, it generates a transaction agreement based on the transaction data range and executes the transaction operation based on the transaction agreement. This solves the technical problem of low transaction efficiency in cross-regional transactions in related technologies. By obtaining transaction elements, selecting the target processing object from multiple candidate processing objects based on the transaction elements, calling the transaction analysis model, and having the transaction analysis model process these transaction elements to obtain the transaction data range, generating a transaction agreement based on the transaction data range, and executing the transaction operation based on the transaction agreement, it achieves the purpose of accurately identifying transaction intentions and elements, and realizing the matching and negotiation dialogue of processing objects, thereby achieving the technical effect of improving the transaction efficiency of cross-regional transactions.

[0091] Optionally, in the transaction processing apparatus provided in this application embodiment, the first receiving unit 40 includes: a first acquisition module, used to acquire an element extraction task and determine an entity recognition model based on the element extraction task, wherein the element extraction task refers to the task of extracting different types of elements; an input module, used to input the transaction processing request into the entity recognition model, and the entity recognition model performs semantic parsing on the transaction processing request to obtain M initial elements; and a second acquisition module, used to acquire entity labeling rules and match entity labels for the M initial elements based on the entity labeling rules to obtain M transaction elements, wherein the entity labeling rules include multiple types of elements and entity labels corresponding to each element.

[0092] Optionally, in the transaction processing apparatus provided in this application embodiment, the first acquisition unit 41 includes: a third acquisition module, used to acquire object information of each candidate processing object to obtain N sets of candidate object information, wherein each set of candidate object information includes at least: the total number of pending transactions of the candidate processing object, the accuracy rate of transaction processing, and geographical location information; a fourth acquisition module, used to acquire conversion rules, and convert the format of each set of candidate object information based on the conversion rules to obtain N sets of processed object data, wherein the conversion rules include multiple object information and the numerical value corresponding to each object information; and a fifth acquisition module, used to acquire a preset weight set, perform weighted calculation on each set of processed object data based on the preset weight set to obtain N candidate scores, and select the target processing object from the N candidate processing objects according to the N candidate scores.

[0093] Optionally, in the transaction processing apparatus provided in this application embodiment, the apparatus further includes: a second receiving unit, configured to receive Y interactive messages sent by the target processing object through the second client after forwarding the transaction processing request to the second client of the target processing object, and identify the Y interactive messages to obtain Y sets of interactive elements, wherein the Y interactive messages refer to the dialogue information between the target processing object and the transaction object, and Y is a positive integer; and a second obtaining unit, configured to obtain a summary generation model, input the Y sets of interactive elements into the summary generation model, output negotiation information, and send the negotiation information to the second client, wherein the target processing object generates a consultation request based on the negotiation information.

[0094] Optionally, in the transaction processing apparatus provided in this application embodiment, the apparatus further includes: a third acquisition unit, configured to acquire interaction information monitoring rules after receiving Y interaction information sent by the target processing object through a second client, wherein the interaction information monitoring rules include multiple abnormal interaction information and a risk level corresponding to each abnormal interaction information; a monitoring unit, configured to perform risk monitoring on the Y interaction information according to the interaction information monitoring rules, and if there is no abnormal interaction information among the Y interaction information, execute a step of identifying the Y interaction information; a fourth acquisition unit, configured to acquire the risk levels of K abnormal interaction information if there are K abnormal interaction information among the Y interaction information, wherein K is less than or equal to Y and K is a positive integer; and a second generation unit, configured to generate interaction prompt information according to the K risk levels and send the interaction prompt information to the second client.

[0095] Optionally, in the transaction processing apparatus provided in this application embodiment, the calling unit 42 includes: an extraction module, used to extract the transaction currency type and transaction type from M transaction elements, and obtain historical transaction data within a historical time period according to the transaction currency type; a receiving module, used to receive initial transaction data sent by a second client, and obtain the transaction risk level associated with the transaction type, wherein the initial transaction data is the transaction data determined by the target processing object according to the transaction processing request; and a calculation module, used to have the statistical module calculate the transaction standard deviation based on the historical transaction data, and have the quantitative module adjust the initial transaction data according to the transaction risk level to obtain the adjusted transaction data, and expand the range of the adjusted transaction data according to the transaction standard deviation to obtain the transaction data range.

[0096] Optionally, in the transaction processing apparatus provided in this application embodiment, the first generation unit 43 includes: a response module, used to respond to a protocol generation instruction sent by the target processing object and obtain a protocol template according to the protocol generation instruction; a filling module, used to fill the protocol template according to M transaction elements and transaction data ranges to obtain an initial transaction protocol, and send the initial transaction protocol to the second client of the target processing object and the third client of the transaction object through a preset interface; a sending module, used to send a signature prompt message to the second client and the third client when receiving confirmation information sent by the second client and the second client, wherein the target processing object and the transaction object respectively perform a signature operation on the initial transaction protocol based on the signature prompt message to obtain a signed transaction protocol; and a determining module, used to determine the signed transaction protocol as a transaction protocol when receiving the signed transaction protocol.

[0097] It should be noted that the first receiving unit 40, the first acquiring unit 41, the calling unit 42, and the first generating unit 43 mentioned above correspond to steps S201 to S204 in Embodiment 1. The instances and application scenarios implemented by the above units and the corresponding steps are the same, but are not limited to the content disclosed in Embodiment 1. It should be noted that the above modules or units can be hardware or software components stored in memory (e.g., memory 104) and processed by one or more processors (e.g., processors 102a, 102b, ..., 102n). The above units can also be part of a device and can run in the computer terminal 10 provided in Embodiment 1.

[0098] Example 3

[0099] Embodiments of this application may provide a computer terminal, which may be any computer terminal device in a group of computer terminals. Optionally, in this embodiment, the aforementioned computer terminal may also be replaced with a mobile terminal or an electronic device, etc.

[0100] Optionally, in this embodiment, the computer terminal may be located in at least one of a plurality of network devices in a computer network.

[0101] In this embodiment, the computer terminal described above can execute the following steps of the transaction processing method: receiving a transaction processing request sent by a transaction object through a first client, extracting transaction elements from the transaction processing request to obtain M transaction elements, wherein the M transaction elements include at least: transaction object, transaction amount, transaction currency type, and transaction type, where M is a positive integer; obtaining N candidate processing objects, selecting a target processing object from the N candidate processing objects using the M transaction elements, and forwarding the transaction processing request to the second client of the target processing object, where N is a positive integer; upon receiving a consultation request sent by the second client, invoking a transaction analysis model according to the consultation request, and having the transaction analysis model process the M transaction elements to obtain a transaction data range, wherein the consultation request refers to a request generated by the target processing object based on the transaction processing request to obtain a transaction data range; upon detecting a confirmation operation of the transaction object on the transaction data range, generating a transaction agreement based on the transaction data range, and executing the transaction operation based on the transaction agreement.

[0102] Optionally, the computer terminal described above can execute the program code for the following steps in the transaction processing method: obtaining an element extraction task, determining an entity recognition model based on the element extraction task, wherein the element extraction task refers to the task of extracting different types of elements; inputting the transaction processing request into the entity recognition model, wherein the entity recognition model performs semantic parsing on the transaction processing request to obtain M initial elements; obtaining entity labeling rules, matching entity labels for the M initial elements based on the entity labeling rules to obtain M transaction elements, wherein the entity labeling rules include multiple types of elements and the entity label corresponding to each element.

[0103] Optionally, the computer terminal described above can execute the following steps in the transaction processing method: obtaining object information for each candidate processing object to obtain N sets of candidate object information, wherein each set of candidate object information includes at least: the total number of transactions to be processed for the candidate processing object, the accuracy rate of transaction processing, and geographical location information; obtaining conversion rules, and converting the format of each set of candidate object information based on the conversion rules to obtain N sets of processed object data, wherein the conversion rules include multiple object information and the numerical value corresponding to each object information; obtaining a preset weight set, performing weighted calculation on each set of processed object data based on the preset weight set to obtain N candidate scores, and selecting the target processing object from the N candidate processing objects according to the N candidate scores.

[0104] Optionally, the computer terminal described above can execute the following steps in the transaction processing method: receiving Y interactive messages sent by the target processing object through a second client, identifying the Y interactive messages to obtain Y sets of interactive elements, wherein the Y interactive messages refer to the dialogue information between the target processing object and the transaction object, and Y is a positive integer; obtaining a summary generation model, inputting the Y sets of interactive elements into the summary generation model, outputting negotiation information, and sending the negotiation information to the second client, wherein the target processing object generates a consultation request based on the negotiation information.

[0105] Optionally, the computer terminal described above can execute the following steps in the transaction processing method: obtaining interaction information monitoring rules, wherein the interaction information monitoring rules include multiple abnormal interaction information and the risk level corresponding to each abnormal interaction information; performing risk monitoring on Y interaction information according to the interaction information monitoring rules, and if there is no abnormal interaction information among the Y interaction information, performing the step of identifying the Y interaction information; if there are K abnormal interaction information among the Y interaction information, obtaining the risk levels of the K abnormal interaction information, wherein K is less than or equal to Y and K is a positive integer; generating interaction prompt information according to the K risk levels, and sending the interaction prompt information to the second client.

[0106] Optionally, the computer terminal described above can execute the following steps in the transaction processing method: extracting the transaction currency type and transaction type from M transaction elements; obtaining historical transaction data within a historical time period based on the transaction currency type; receiving initial transaction data sent by the second client and obtaining the transaction risk level associated with the transaction type, wherein the initial transaction data is the transaction data determined by the target processing object according to the transaction processing request; the statistics module calculates the transaction standard deviation based on the historical transaction data; the quantitative module adjusts the initial transaction data according to the transaction risk level to obtain the adjusted transaction data; and the adjusted transaction data is range-expanded based on the transaction standard deviation to obtain the transaction data range.

[0107] Optionally, the computer terminal described above can execute the following steps in the transaction processing method: responding to a protocol generation instruction sent by the target processing object, obtaining a protocol template according to the protocol generation instruction; filling the protocol template according to M transaction elements and transaction data ranges to obtain an initial transaction protocol, and sending the initial transaction protocol to the second client of the target processing object and the third client of the transaction object through a preset interface; upon receiving confirmation information sent by the second client and the second client, sending signature prompt information to the second client and the third client, wherein the target processing object and the transaction object respectively perform a signature operation on the initial transaction protocol based on the signature prompt information to obtain a signed transaction protocol; upon receiving the signed transaction protocol, determining the signed transaction protocol as the transaction protocol.

[0108] Optionally, Figure 5 This is a structural block diagram of an electronic device according to an embodiment of this application. Figure 5 As shown, the electronic device may include: one or more ( Figure 5 Only one of the components is shown: processor 502, memory 504, memory controller, and peripheral interface, wherein the peripheral interface is connected to the radio frequency module, audio module, and display.

[0109] The memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the transaction processing method and apparatus in this embodiment. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, thereby implementing the aforementioned transaction processing method. The memory may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include memory remotely located relative to the processor, and these remote memories can be connected to the terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0110] The processor can access the information and application programs stored in the memory via the transmission device to execute the steps described above in the transaction processing method.

[0111] This application provides a transaction processing scheme. It involves receiving a transaction processing request sent by a transaction object through a first client, extracting transaction elements from the request to obtain M transaction elements, where the M elements include at least: transaction object, transaction amount, transaction currency type, and transaction type, where M is a positive integer; obtaining N candidate processing objects, selecting a target processing object from the N candidate objects using the M transaction elements, and forwarding the transaction processing request to a second client of the target processing object, where N is a positive integer; and upon receiving a consultation request from the second client, invoking a transaction analysis model based on the consultation request, and processing the M transaction elements using the transaction analysis model to obtain a transaction data range, where the consultation request refers to data generated by the target processing object based on the transaction processing request. The system requests to obtain a transaction data range; upon detecting a confirmation operation by a transaction object on the transaction data range, it generates a transaction agreement based on the transaction data range and executes the transaction operation based on the transaction agreement. This solves the technical problem of low transaction efficiency in cross-regional transactions in related technologies. By obtaining transaction elements, the system filters the target processing object from multiple candidate processing objects based on the transaction elements, calls the transaction analysis model, and the transaction analysis model processes these transaction elements to obtain the transaction data range. Based on the transaction data range, a transaction agreement is generated, and the transaction operation is executed based on the transaction agreement. This achieves the goal of accurately identifying transaction intentions and elements, and realizing the matching and negotiation dialogue of processing objects, thereby improving the technical effect of cross-regional transaction efficiency.

[0112] Those skilled in the art will understand that Figure 5 The structure shown is for illustrative purposes only. Electronic devices can also be smartphones, tablets, handheld computers, mobile internet devices (MIDs), PADs, and other terminal devices. Figure 5 This does not limit the structure of the aforementioned electronic device. For example, electronic devices may also include components that are more... Figure 5 The more or fewer components shown (such as network interfaces, display devices, etc.), or having the same Figure 5 The different configurations shown.

[0113] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing the hardware related to the terminal device. The program can be stored in a computer-readable storage medium, which may include: flash drive, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0114] Example 4

[0115] Embodiments of this application also provide a storage medium. Optionally, in this embodiment, the storage medium can be used to store the program code executed by the transaction processing method provided in Embodiment 1.

[0116] Optionally, in this embodiment, the storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any mobile terminal in a group of mobile terminals.

[0117] Optionally, in this embodiment, the storage medium is configured to store program code for performing the following steps: receiving a transaction processing request sent by a transaction object through a first client, extracting transaction elements from the transaction processing request to obtain M transaction elements, wherein the M transaction elements include at least: transaction object, transaction amount, transaction currency type, and transaction type, and M is a positive integer; obtaining N candidate processing objects, filtering out the target processing object from the N candidate processing objects using the M transaction elements, and forwarding the transaction processing request to the second client of the target processing object, wherein N is a positive integer; upon receiving a consultation request sent by the second client, invoking a transaction analysis model according to the consultation request, and having the transaction analysis model process the M transaction elements to obtain a transaction data range, wherein the consultation request refers to a request generated by the target processing object based on the transaction processing request to obtain the transaction data range; upon detecting a confirmation operation of the transaction object on the transaction data range, generating a transaction agreement based on the transaction data range, and executing the transaction operation based on the transaction agreement.

[0118] This application also provides a computer program product, which, when executed on a data processing device, is a program adapted to perform transaction processing method steps.

[0119] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0120] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0121] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection of units or modules may be electrical or other forms.

[0122] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0123] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0124] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0125] The above are merely preferred embodiments of this application. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method of processing a transaction, characterized by, The method comprises: receiving a transaction processing request sent by a first client, extracting transaction elements from the transaction processing request, and obtaining M transaction elements, wherein the M transaction elements at least include: a transaction object, a transaction amount, a transaction currency type, and a transaction type, and M is a positive integer; obtaining N candidate processing objects, screening a target processing object from the N candidate processing objects through the M transaction elements, and forwarding the transaction processing request to a second client of the target processing object, wherein N is a positive integer; in the case of receiving a consultation request sent by the second client, calling a transaction analysis model according to the consultation request, and processing the M transaction elements by the transaction analysis model to obtain a transaction data interval, wherein the consultation request is a request for obtaining the transaction data interval generated by the target processing object based on the transaction processing request; in the case of detecting a confirmation operation of the transaction object on the transaction data interval, generating a transaction agreement based on the transaction data interval, and performing a transaction operation based on the transaction agreement.

2. The method of claim 1, wherein, extracting transaction elements from the transaction processing request to obtain M transaction elements comprises: obtaining an element extraction task, determining an entity recognition model according to the element extraction task, wherein the element extraction task refers to a task of extracting different types of elements; inputting the transaction processing request into the entity recognition model, and performing semantic analysis on the transaction processing request by the entity recognition model to obtain M initial elements; obtaining an entity labeling rule, matching an entity label for the M initial elements based on the entity labeling rule to obtain the M transaction elements, wherein the entity labeling rule includes multiple types of elements and an entity label corresponding to each element.

3. The method of claim 1, wherein, screening a target processing object from the N candidate processing objects through the M transaction elements comprises: obtaining object information of each candidate processing object to obtain N sets of candidate object information, wherein each set of candidate object information at least includes: a total number of transactions to be processed of the candidate processing object, an accuracy rate of processing transactions, and geographic location information; obtaining a conversion rule, performing format conversion on each set of candidate object information based on the conversion rule to obtain N sets of processed object data, wherein the conversion rule includes multiple object information and a numerical value corresponding to each object information; obtaining a set of preset weights, performing weighted calculation on each set of processed object data based on the set of preset weights to obtain N candidate scores, and screening the target processing object from the N candidate processing objects according to the N candidate scores.

4. The method of claim 1, wherein, After forwarding the transaction processing request to the second client of the target processing object, the method further comprises: receiving Y pieces of interaction information sent by the target processing object through the second client, and identifying the Y pieces of interaction information to obtain Y sets of interaction elements, wherein the Y pieces of interaction information refer to dialogue information between the target processing object and the transaction object, and Y is a positive integer; The method further comprises:

5. The method of claim 4, wherein, After receiving the Y pieces of interaction information sent by the target processing object through the second client, the method further comprises: obtaining an interaction information monitoring rule, wherein the interaction information monitoring rule comprises a plurality of abnormal interaction information and a risk level corresponding to each abnormal interaction information; performing risk monitoring on the Y pieces of interaction information according to the interaction information monitoring rule, and if there is no abnormal interaction information in the Y pieces of interaction information, performing the step of identifying the Y pieces of interaction information; if there are K pieces of abnormal interaction information in the Y pieces of interaction information, obtaining the risk levels of the K pieces of abnormal interaction information, wherein K is less than or equal to Y, and K is a positive integer; generating interaction prompt information according to the K risk levels and sending the interaction prompt information to the second client.

6. The method of claim 1, wherein, The transaction analysis model comprises a statistical module and a quantification module. The transaction analysis model processes the M transaction elements to obtain a transaction data interval, which comprises: extracting the transaction currency type and the transaction type from the M transaction elements, and obtaining historical transaction data in a historical time period according to the transaction currency type; receiving initial transaction data sent by the second client, and obtaining a transaction risk level associated with the transaction type, wherein the initial transaction data is transaction data determined by the target processing object according to the transaction processing request; calculating a transaction standard deviation from the historical transaction data by the statistical module, adjusting the initial transaction data according to the transaction risk level by the quantification module to obtain adjusted transaction data, and expanding the range of the adjusted transaction data according to the transaction standard deviation to obtain the transaction data interval.

7. The method of claim 1, wherein, generating a transaction protocol based on the transaction data interval, which comprises: in response to a protocol generation instruction sent by the target processing object, obtaining a protocol template according to the protocol generation instruction; filling the protocol template according to the M transaction elements and the transaction data interval to obtain an initial transaction protocol, and sending the initial transaction protocol to the second client of the target processing object and the third client of the transaction object through a preset interface; in the case of receiving confirmation information sent by the second client and the second client, sending signature prompt information to the second client and the third client, wherein the target processing object and the transaction object perform signature operations on the initial transaction protocol based on the signature prompt information to obtain a signed transaction protocol; in the case of receiving the signed transaction protocol, determining the signed transaction protocol as the transaction protocol.

8. A processing apparatus of a transaction, characterized by, ​ The first receiving unit is configured to receive a transaction processing request sent by a transaction object through a first client, and extract transaction elements from the transaction processing request to obtain M transaction elements, wherein the M transaction elements at least include a transaction object, a transaction amount, a transaction currency type, and a transaction type, and M is a positive integer; The first obtaining unit is configured to obtain N candidate processing objects, filter a target processing object from the N candidate processing objects according to the M transaction elements, and forward the transaction processing request to a second client of the target processing object, wherein N is a positive integer; The calling unit is configured to, in a case where a consultation request sent by the second client is received, call a transaction analysis model according to the consultation request, and process the M transaction elements by the transaction analysis model to obtain a transaction data interval, wherein the consultation request is a request for obtaining the transaction data interval generated by the target processing object based on the transaction processing request; The first generating unit is configured to, in a case where a confirmation operation of the transaction data interval by the transaction object is detected, generate a transaction agreement based on the transaction data interval, and perform a transaction operation based on the transaction agreement.

9. An electronic device, comprising: comprise: a memory storing an executable program; a processor configured to run the program, wherein the program performs the transaction processing method of any one of claims 1 to 7 when running.

10. A computer program product comprising computer instructions, characterized in that, The computer instructions are executed by the processor to implement the steps of the transaction processing method of any one of claims 1 to 7.

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