A method and system for implementing installment payment based on user orders

Abstract

The application discloses a kind of based on the realization method and system of user order's installment payment, comprising the following steps: record the payment mode selected by user, and save the payment behavior of user in cache;Payment behavior data is reported to server in time, and payment behavior data cache is cleaned up;Server receives and analyzes payment behavior data, saves data;Background service according to the installment payment rule created, order is processed in installment;According to the installment information of order, analyze its payment, build order state model, and generate corresponding payment plan and reminder notice.The application is based on detailed and dynamically updated order data, can realize highly personalized payment management, significantly improve management efficiency and user satisfaction.Personalized payment plan not only optimizes the payment experience of user, but also increases the efficiency of platform's fund circulation and user loyalty, at the same time makes fund management more accurate, effectively improves the efficiency of fund use and recovery rate.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of e-commerce and financial technology, specifically, a method and system for implementing installment payment based on user orders. BACKGROUND

[0002] In the current e-commerce environment, user demand is diversified, and payment methods are gradually diversified and personalized. Traditional lump-sum payment mode may bring certain economic pressure to users for some large-value goods or services. In order to alleviate this pressure, it is particularly important to provide a flexible installment payment method. Existing installment payment methods are mostly concentrated on online payment, and offline payment implementation methods are less common.

[0003] In view of this situation, the present application proposes an order installment payment implementation method supporting offline collection code and sales two-dimensional code payment modes. SUMMARY

[0004] To solve the problems existing in the prior art, the present application provides a method and system for implementing installment payment based on user orders, which has the advantages of automatically processing installment payment, providing in-depth financial insight for enterprises, and optimizing user payment experience. The method analyzes the purchase history and credit data of the user to realize the installment payment function of the order, so that the user can flexibly manage the payment according to his own financial situation. In addition, the system can also provide personalized shopping suggestions and preferential activities by building user portraits, so as to improve the user experience and increase the sales efficiency of the merchant.

[0005] To achieve the above purpose, the present application adopts the following scheme: a method for implementing installment payment based on user orders, comprising the following steps:

[0006] S1, when the user browses the goods and decides to make a purchase, the system provides an installment payment option; after the order is generated, the system generates an offline collection code or a sales two-dimensional code in real time, and the user pays the deposit by scanning the code; after the payment is completed, the system automatically records the payment information and updates the order status to "deposit paid", ensuring the clear understanding of the payment status by both parties;

[0007] S2, the system periodically collects order payment data from the database, and the order payment data is first cleaned to remove all invalid and erroneous data entries, and then standardized by using a special format conversion tool to ensure that all data meet the analysis requirements; the cleaned and standardized data is stored in a relational database and a non-relational database to support subsequent data analysis and report generation;

[0008] S3, the system background service analyzes the stored payment data using a machine learning algorithm, the analysis includes but is not limited to the frequency distribution of payment time, the preference of payment method, and the statistical data of payment amount; based on the analysis results, the system generates a corresponding payment label for each order using predefined rules and algorithms; the generation and update of the payment label are dynamic to ensure that the latest trends of payment behavior can be reflected in real time;

[0009] S4, after the user pays the down payment, the user continues to pay the balance by scanning the offline collection code or the sales two-dimensional code; after each successful balance payment, the system captures the payment behavior in real time and updates the order status to "balance paid", while recording the detailed payment information; after the payment is successful, the system automatically sends a payment confirmation notification to the user to ensure that the user is clearly aware of his payment behavior;

[0010] S5, the system provides a user interface that allows users to query their order payment status at any time, including the specific amount of down payment and balance that has been paid; at the same time, the system generates detailed payment record reports for the background administrator, and the administrator monitors payment behavior and evaluates the overall performance of the installment payment system through these reports; the report generation function supports customization options.

[0011] Optionally, in some embodiments of the present application, step S1 includes defining the collection event name and the information required to be reported, the server side extracts the information triggered by the user payment event, and the information is encrypted by RSA, and the encrypted information is saved in the server.

[0012] Optionally, in some embodiments of the application, step S2 includes: the server side reports the payment behavior data recorded in the server to the application API interface in batches every 10 seconds, if the data reporting fails, it will enter the retry queue, if the user terminates the process, it will be reported again when it enters next time, if the data reporting is successful, the encrypted data of the completed reporting will be cleaned up.

[0013] Optionally, in some embodiments of the present application, the step S3 includes: the application API interface receives the data, checks the data to prevent the interface from being attacked, if the verification is passed, the data is decrypted, and the decrypted data is filtered again, and finally the payment behavior data is saved in the order library.

[0014] Optionally, in some embodiments of the present application, step S4 includes: the background service cleans, denoises and formats the data, and then extracts the payment behavior label of the down payment order and the balance order from the processed data to create corresponding labels for the user.

[0015] Optionally, in some embodiments of the present application, step S5 includes: constructing an order state model according to the payment behavior tag, visualizing the payment behavior tag of the user through the payment behavior and the order information of the user, configuring display content and display rules for the tag by analyzing and understanding the payment preference of the user, and displaying the filtered and sorted recommended tag configured content to the user in a user-friendly manner when the user triggers a certain payment behavior.

[0016] Optionally, in some embodiments of the present application, the payment behavior includes user browsing goods, selecting a payment mode, submitting payment, and confirming an order.

[0017] In another aspect, the present application provides a system for implementing installment payment based on user orders, comprising a data collection module, a payment behavior tag extraction module, an order state construction module, and an application interface module; the data collection module is responsible for obtaining payment behavior data of a user from multiple data sources; the payment behavior tag extraction module uses natural language processing and machine learning techniques to process and analyze the payment behavior data of the user, and extracts payment behavior tags; the order state construction module associates and integrates the extracted payment behavior tags with the payment behavior of the user to generate an order state; and the application interface module allows other applications or services to access the system through an API to obtain order state data and perform related applications.

[0018] Optionally, in some embodiments of the present application, the personal information of the user includes user browsing goods, selecting a payment mode, submitting payment, and confirming an order behavior, and non-private information of the user.

[0019] Optionally, in some embodiments of the present application, the order state construction module configures display content and display rules for the tag, and displays the filtered and sorted recommended tag configured content to the user in a user-friendly manner when the user triggers a certain payment behavior.

[0020] The beneficial effects of the present application are:

[0021] (1) By constructing an accurate order state, the system can better understand the payment needs, capabilities, and preferences of the user, thereby providing optimized payment plans, reminder notifications, and service experiences;

[0022] (2) Through accurate classification and identification of payment behavior tags, the system can more accurately perform financial management and user credit assessment;

[0023] (3) Payment behavior tags can help the system to subdivide and classify users, optimize resource allocation and service provision;

[0024] (4) Compared with traditional order management methods, the method based on user payment behavior of the application is more accurate and dynamic, which can capture the user's payment changes and behavior patterns in real time, so as to better understand the user's needs and preferences. The system has wide application prospects in the fields of financial management, credit evaluation, payment behavior analysis, etc. BRIEF DESCRIPTION OF DRAWINGS

[0025] Figure 1 A flowchart of a user order-based installment payment implementation method according to an embodiment of the application. DETAILED DESCRIPTION

[0026] The embodiments of the application will be described in detail below with reference to the accompanying drawings.

[0027] Based on the problem of lack of flexible installment payment method in the current offline payment method, as shown in the drawings, the application is a user order-based installment payment implementation method, which comprises the following steps: Figure 1

[0028] S1, record the payment method selected by the user, and save the payment behavior of the user in the cache; the user selects installment payment and payment deposit, and the system provides the option of installment payment when the user browses the goods and decides to purchase. The user can select this method when creating an order. After the order is generated, the system generates an offline collection code or a sales two-dimensional code in time, and the user can pay the deposit by scanning the code. This step not only facilitates the user, but also provides the instant nature of the fund flow for the merchant. After payment is completed, the system automatically records the payment information and updates the order status to "deposit paid", ensuring the clear understanding of the payment status by both parties.

[0029] S2, report the payment behavior data to the server at regular intervals, and clean up the payment behavior data cache; it is crucial to process the data generated after the user pays the deposit. The system regularly collects order payment data from the database, including payment time, amount, method and other information. These data are first cleaned to remove all invalid and erroneous data entries (such as duplicate payments, format errors, etc.). Then, a special format conversion tool is used to standardize the data, ensuring that all data meet the analysis requirements. The cleaned and standardized data are stored in a relational database and a non-relational database to support subsequent data analysis and report generation.

[0030] ​S3, the server receives and parses the payment behavior data, saves the data, analyzes the payment behavior and generates payment tags, and the system background service uses machine learning algorithms to analyze the stored payment data in depth. The analysis includes but is not limited to the frequency distribution of payment time, the preference of payment method, and the statistical data of payment amount. Based on these analysis results, the system uses predefined rules and algorithms to generate corresponding payment tags for each order, such as "fast payment user", "digital payment preference" and so on. These tags help the system better understand user behavior and optimize the payment experience accordingly. The generation and update of payment tags are dynamic to ensure that the latest trends of payment behavior can be reflected in real time.

[0031] S4, the background service processes the order according to the created installment payment rules; after paying the down payment, the user needs to continue to pay the balance by scanning the offline collection code or sales two-dimensional code. After each successful payment of the balance, the system immediately captures this payment behavior and updates the order status to "balance paid", while recording the detailed payment information, including the payment amount and time. After successful payment, the system will also automatically send a payment confirmation notice to the user to ensure that the user is fully aware of their payment behavior and enhance the user experience.

[0032] S5, according to the installment information of the order, analyze its payment situation, build order state model, and generate corresponding payment plan and reminder. The system provides a user interface that allows users to query their order payment status at any time, including the specific amount of down payment and balance paid. At the same time, the system generates detailed payment record reports for the background administrator, who can monitor payment behavior and evaluate the overall performance of the installment payment system through these reports. The report generation function supports customization options such as selecting specific time periods, order types or payment methods for analysis to meet different management needs.

[0033] In this technical solution, when the user selects the offline collection code or sales two-dimensional code payment method, the client will record the payment behavior and report it to the application API interface, and through the service, the reported data will be cleaned, denoised, and format converted, etc. to generate corresponding installment payment tags for the order. Finally, according to the installment payment tags of the order, the order state model is established, and the order state can be applied to financial management, user credit evaluation, payment behavior analysis and other scenarios. By combining order state with specific business scenarios, more accurate financial monitoring and user payment experience optimization can be achieved.

[0034] In further technical solutions, the collection of payment behavior in step S1 includes:

[0035] Record the payment method selected by the user and save the user's payment behavior in the cache.

[0036] In the technical solution, the collection event name needs to be defined and the information to be reported, such as payment method, payment amount, order number, information extraction of the payment event triggered by the client to the user, and RSA encryption of the information, saving the encrypted information in the cache.

[0037] In a further technical solution, step S2 comprises:

[0038] The payment behavior data is reported to the server at a fixed time, and the payment behavior data cache is cleaned up.

[0039] In the technical solution, because there may be many payment behaviors, the client will report payment behavior data to the application API interface every 10s, if the data reporting fails, it will enter the retry queue, if the user terminates the process, it will be re-reported when it enters next time, if the data reporting is successful, the encrypted data of the reporting completion will be cleaned up.

[0040] In a further technical solution, step S3 comprises:

[0041] The server receives and parses the payment behavior data, and saves the data.

[0042] In the technical solution, the application API interface receives the data, checks the data to prevent the interface from being attacked, decrypts the data if the verification is passed, and filters the decrypted data again, and finally saves the payment behavior data in the order management system.

[0043] In a further technical solution, step S4 comprises:

[0044] The background service processes the order according to the created installment payment rule.

[0045] In the technical solution, in order to improve the flexibility and applicability of payment, the order needs to be set by the service, to ensure that the payment plan is accurate, consistent, complete, and meets the user's payment ability, and then generate the corresponding installment payment plan from the processed data.

[0046] In a further technical solution, step S5 comprises:

[0047] According to the installment information of the order and the payment behavior and order information of the user, an order state model is constructed, and a corresponding payment plan and reminder notification is generated.

[0048] In the technical solution, according to the installment payment information of an order, an order state model is constructed by using the payment history, order amount, payment method and other behaviors and order information of a user, the payment progress of the order is visually displayed, the payment preference of the user is analyzed and understood, and reminder content and reminder rules are configured for the order in the background, when a certain payment behavior of the user is triggered, the filtered and sorted reminder configuration content is displayed to the user in a user-friendly manner.

[0049] The application also provides a system for constructing a more accurate order state by analyzing the payment behavior of a user, which includes a data collection module, a payment behavior label extraction module, an order state construction module and an application interface module. The data collection module is responsible for obtaining the payment behavior data of a user from multiple data sources, such as payment method, payment amount, order number, etc. The payment behavior label extraction module uses natural language processing and machine learning techniques to process and analyze the original data, and extracts payment behavior labels such as payment method, payment frequency, etc. The order state construction module associates and integrates the extracted payment behavior labels with the order information of the user to generate accurate states of the order. These states include the payment progress of the order, the remaining payment amount, the estimated completion time, etc. to better understand the user's needs and provide optimized payment experience and management. The application interface module allows other applications or services to access the system through API to obtain order state data and related applications.

[0050] Based on detailed and dynamically updated order data, the above-mentioned user order-based installment payment implementation method and system can achieve highly personalized payment management, significantly improving management efficiency and user satisfaction. Personalized payment plans not only optimize the user's payment experience, but also increase the efficiency of the platform's capital flow and user loyalty, while making capital management more accurate, effectively improving the efficiency and recovery rate of capital.

[0051] In order to better illustrate the user order-based installment payment implementation method and system of the application, the following specific embodiments are used for detailed description. It should be noted that the following embodiments are only illustrative of the application, and the protection scope of the application is not limited thereto.

[0052] Embodiment:

[0053] As shown in Figure 1 , the application provides a user order-based installment payment implementation method, which includes the following steps:

[0054] S1, record the payment method selected by the user, and save the related information of the user's payment in the cache;

[0055] S2, report the payment information data to the server at regular intervals, and clean up the payment information data cache;

[0056] S3, the server receives and parses the payment information data, and saves the data;

[0057] S4, the background service processes the order according to the created installment payment rule;

[0058] S5, according to the installment information of the order, analyze its payment status, build order state model, and generate corresponding payment plan and reminder.

[0059] In this embodiment, when the user selects the offline collection code or the sales two-dimensional code payment method, the client records the payment information and reports it to the application API interface. The service performs cleaning, denoising, format conversion and other operations on the reported data, generates a corresponding installment payment plan for the order, and finally establishes an order state model according to the installment information of the order. The order state can be applied to financial management, user credit assessment, payment behavior analysis and other scenarios. By combining the order state with specific business scenarios, more accurate financial monitoring and user payment experience optimization can be achieved.

[0060] In another embodiment, step S1 includes:

[0061] A1, determine the collection payment method;

[0062] A2, determine the collection payment information;

[0063] A3, cache payment data;

[0064] In this embodiment, the collection event name and the information to be reported need to be defined, such as payment method, payment amount, order number, etc. The client extracts information from the payment event triggered by the user, and performs RSA encryption on the information. The encrypted information is saved in the cache.

[0065] In another embodiment, step S2 includes:

[0066] Report the payment information data to the server at regular intervals, and clean up the payment information data cache.

[0067] In this embodiment, because there may be a lot of payment information, the client will report the payment information data to the application API interface every 10s. If the data reporting fails, it will enter the retry queue. If the user terminates the process, it will be re-reported when it enters next time. If the data reporting is successful, the encrypted data of the completed reporting will be cleaned up.

[0068] In another embodiment, step S3 includes:

[0069] The server receives and parses the payment information data, and saves the data.

[0070] In this embodiment, the application API interface receives data, checks the data to prevent interface attacks, decrypts the data if the verification is passed, and filters the decrypted data again. Finally, the payment information data is saved in the order management system.

[0071] In another embodiment, step S4 includes:

[0072] The background service processes the order according to the created installment payment rule.

[0073] In this embodiment, a custom installment payment rule needs to be created. Since the payment information data is relatively large, the service needs to set a corresponding installment payment plan for the order.

[0074] In another embodiment, step S5 includes:

[0075] According to the installment information of the order and the payment behavior and order information of the user, an order state model is constructed, and a corresponding payment plan and reminder notification are generated.

[0076] In this embodiment, according to the installment payment information of the order, the order state model is constructed by analyzing the payment history, order amount, payment method, and other behaviors and order information of the user. The payment progress of the order is visually displayed. By analyzing and understanding the payment preferences of the user, the reminder content and reminder rules are configured for the order in the background. When the user triggers a certain payment behavior, the filtered and sorted reminder configuration content is displayed to the user in a user-friendly manner. The payment progress of the order is visually displayed, that is, the order state model, and the display data of the installment payment plan configuration is generated, that is, the payment plan and reminder notification for the user.

[0077] The application also provides a system for constructing a more accurate order state by analyzing the payment behavior of a user. The system includes a data collection module, a payment behavior label extraction module, an order state construction module, and an application interface module. The data collection module is responsible for obtaining the payment behavior data of the user from multiple data sources, such as payment methods, payment amounts, order numbers, etc. The payment behavior label extraction module uses natural language processing and machine learning techniques to process and analyze the original data, and extracts payment behavior labels such as payment methods and payment frequencies.

[0078] The order state construction module associates and integrates the extracted payment behavior labels with the order information of the user to generate an accurate state of the order. These states include the payment progress of the order, the remaining payment amount, the estimated completion time, and other detailed information to better understand the user's needs and provide optimized payment experience and management. The application interface module allows other applications or services to access the system through an API to obtain order state data and perform related applications.

[0079] The above embodiments only express the specific implementation of the present application, which is described in more detail and in more detail, but it cannot be understood as a limitation on the scope of the patent of the present application. It should be noted that for ordinary skilled in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which are within the scope of protection of the present application.

Claims

1. A method for implementing installment payments based on user orders, characterized in that, Includes the following steps: S1. When a user browses a product and decides to make a purchase, the system provides an installment payment option; after the order is generated, the system immediately generates an offline payment code or sales QR code, which the user scans to pay a deposit; after payment is completed, the system automatically records the payment information and updates the order status to "deposit paid", ensuring that both parties are clear about the payment status; S2. The system periodically collects order payment data from the database. The order payment data is first cleaned to remove all invalid and erroneous data entries. Then, a specialized format conversion tool is used to standardize the data to ensure that all data meets the analysis requirements. The cleaned and standardized data is stored in relational databases and non-relational databases to support subsequent data analysis and report generation. S3. The system's backend service uses machine learning algorithms to analyze the stored payment data. The analysis includes, but is not limited to, the frequency distribution of payment time, payment method preferences, and statistical data on payment amounts. Based on the analysis results, the system uses predefined rules and algorithms to generate corresponding payment tags for each order. The generation and updating of payment tags are dynamic to ensure that the latest trends in payment behavior can be reflected in real time. S4. After paying the deposit, users continue to pay the balance by scanning the offline payment code or sales QR code. Each time the balance payment is successful, the system immediately captures this payment behavior and updates the order status to "balance payment has been paid", while recording the payment details. After the payment is successful, the system automatically sends a payment confirmation notification to the user to ensure that the user is clearly aware of their payment behavior. S5. The system provides a user interface that allows users to check their order payment status at any time, including the specific amounts of deposits and final payments. At the same time, the system generates detailed payment record reports for backend administrators, who can use these reports to analyze revenue, monitor payment behavior, and evaluate the overall performance of the installment payment system. The report generation function supports customization options.

2. The method for implementing installment payments based on user orders according to claim 1, characterized in that, Step S1 includes: defining the name of the event to be collected and the information to be reported; the server extracts information from the payment event triggered by the user, encrypts the information using RSA, and saves the encrypted information on the server.

3. The method for implementing installment payments based on user orders according to claim 1, characterized in that, Step S2 includes: The server reports the payment behavior data recorded on the server to the application API interface in batches every 10 seconds. If the data reporting fails, it will enter the retry queue. If the user terminates the process, it will be re-reported the next time it enters. If the data reporting is successful, the encrypted data that has been reported will be cleaned up.

4. The method for implementing installment payments based on user orders according to claim 1, characterized in that, Step S3 includes: receiving data through the application API interface, verifying the data to prevent the interface from being attacked, decrypting the data if the verification passes, filtering the decrypted data again, and finally storing the payment behavior data in the order database.

5. The method for implementing installment payments based on user orders according to claim 1, characterized in that, Step S4 includes: the background service cleans, denoises, and converts the data, and then extracts payment behavior tags for deposit orders and final payment orders from the processed data to create corresponding tags for users.

6. The method for implementing installment payments based on user orders according to claim 1, characterized in that, Step S5 includes: constructing an order status model based on payment behavior tags and user order information; visualizing user payment behavior tags; configuring display content and display rules for tags in the background by analyzing and understanding user payment preferences; and displaying filtered and sorted recommended tag content to user in a user-friendly manner when a user triggers a payment behavior.

7. The method for implementing installment payment based on user orders according to claim 6, characterized in that, Payment activities include browsing products, selecting a payment method, submitting payment, and confirming the order.

8. A system for implementing installment payment based on user orders as described in any one of claims 1-7, characterized in that, It includes a data collection module, a payment behavior tag extraction module, an order status construction module, and an application interface module; The data collection module is responsible for acquiring users' payment behavior data from multiple data sources; The payment behavior tag extraction module uses natural language processing and machine learning technologies to process and analyze users' payment behavior data and extract payment behavior tags. The order status construction module associates and integrates the extracted payment behavior tags with the user's payment behavior to generate the order status; The application interface module allows other applications or services to access the system via API to obtain order status data and perform related applications.

9. A system for implementing installment payments based on user orders according to claim 8, characterized in that, The user's personal information includes the user's browsing of products, selection of payment methods, submission of payment and confirmation of orders, as well as the user's non-privacy information.

10. A system for implementing installment payments based on user orders according to claim 8, characterized in that, The order status building module configures the display content and rules for tags. When a user triggers a payment action, the filtered and sorted recommended tag content is displayed to the user in a user-friendly way.

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