Staging scheme determination method and device, electronic equipment, storage medium and product

Abstract

Embodiments of the present application provide a method and device for determining installment plan, electronic equipment, storage medium and product, which are related to the field of financial technology or other related fields. The method comprises: obtaining feature information of a user and to-be-repaid bill information of the user; the to-be-repaid bill information comprises at least one piece of consumption information; the consumption information comprises: consumption amount; according to the feature information and the to-be-repaid bill information, a target installment preferential activity is selected from a plurality of installment preferential activities; and according to the feature information and the to-be-repaid bill information, at least one installment plan is determined through the target installment preferential activity. In this way, through automatic screening and matching, the user is liberated from a large number of, scattered, and complex rule preferential activities, without the need for manual collection and comparison of information, which greatly shortens the decision-making time, reduces the selection cost, and through the consideration of the user feature information and real-time bill information at the same time, the recommended result is more suitable for the actual needs and repayment ability of the user, and the applicability of the plan is improved.

Description

Technical Field

[0001] This application relates to the field of financial technology or other related fields, and in particular to a method, apparatus, electronic device, storage medium and product for determining installment plans. Background Technology

[0002] With the rapid development of the consumer finance market, credit card installment services have become an important part of the modern consumer payment system. In recent years, the transaction volume of credit card installment in my country has shown a significant growth trend. According to statistics, the transaction volume exceeded 5 trillion yuan in 2022, with an average annual compound growth rate of over 15%. This growth is mainly due to the increasing demand of consumers for flexible payment methods. Installment payments can effectively alleviate short-term financial pressure and promote consumption upgrading.

[0003] Currently, the vast majority of credit card holders have used installment payment services, with data showing that approximately 78% of cardholders have used installment payment services at least once. To attract users and increase card usage activity, commercial banks have launched various installment payment promotions for different consumption scenarios, such as interest-free installments for shopping, discounts on travel installments, and subsidies for education installments. These promotions typically have time-sensitive, scenario-specific, and rule-differentiated characteristics, such as varying interest rate periods, fee waiver conditions, and restrictions on participating merchants.

[0004] However, with the increasing variety and complexity of installment payment options, cardholders face challenges such as low efficiency and high decision-making costs when confronted with numerous installment offers. They struggle to quickly and accurately select the most suitable option for their needs. Users must compare various parameters, including rates, terms, applicable scenarios, and participation conditions, for different offers. This process is not only time-consuming and laborious, but also prone to errors due to information asymmetry or misunderstandings, potentially leading to the selection of the optimal installment plan or even unnecessary charges due to misinterpretation of the rules. Summary of the Invention

[0005] This application provides a method, apparatus, electronic device, storage medium, and product for determining installment payment plans, in order to improve the efficiency of users in selecting installment payment plans and reduce decision-making costs.

[0006] In a first aspect, embodiments of this application provide a method for determining a phased implementation plan, the method comprising:

[0007] Obtain user characteristic information and the user's outstanding bill information; the outstanding bill information includes at least one transaction; the transaction information includes: the transaction amount;

[0008] Based on the feature information and the outstanding bill information, a target installment discount activity is selected from multiple installment discount activities;

[0009] Based on the aforementioned feature information and the outstanding bill information, at least one installment plan is determined through the target installment promotion.

[0010] Optionally, the consumption information further includes: the consumption area; and, based on the feature information and the outstanding bill information, filtering out a target installment discount activity from multiple installment discount activities, including:

[0011] Obtain the target region where the user is located;

[0012] Target consumption information is selected from at least one consumption record; the consumption region corresponding to the target consumption information is the target region.

[0013] The candidate installment payment offers are selected from multiple installment payment offers, and the target region is the region targeted by the candidate installment payment offers.

[0014] Based on the aforementioned feature information and target consumption information, a target installment discount activity is selected from multiple alternative installment discount activities.

[0015] Optionally, based on the aforementioned feature information and target consumption information, a target installment payment promotion is selected from multiple alternative installment payment promotions, including:

[0016] The feature information and target consumption information are input into the promotional activity determination model. The promotional activity determination model selects the target installment promotional activity from multiple candidate installment promotional activities and outputs the corresponding identification information of the target installment promotional activity.

[0017] Optionally, the installment plan includes: a target installment period, a target installment interest rate, and discount information of the target installment interest rate relative to the original installment interest rate.

[0018] Optionally, the method further includes:

[0019] Get the user's set "Do Not Disturb" time period;

[0020] Based on the Do Not Disturb period, a target time is determined, wherein the target time is not located within the Do Not Disturb period;

[0021] At the target time, at least one installment plan will be pushed to the user.

[0022] Optionally, the feature information includes at least one of the following: basic information, credit rating, historical installment records, consumption frequency during a preset period, and merchant category.

[0023] Secondly, embodiments of this application provide a device for determining a phased implementation plan, the device comprising:

[0024] The acquisition module is used to acquire the user's characteristic information and the user's outstanding bill information; the outstanding bill information includes at least one transaction; the transaction information includes: the transaction amount;

[0025] The filtering module is used to filter out the target installment discount activity from multiple installment discount activities based on the feature information and the bill information to be repaid;

[0026] The determining module is used to determine at least one installment plan based on the feature information and the outstanding bill information, through the target installment promotion.

[0027] Thirdly, embodiments of this application provide an electronic device, including: a memory and a processor;

[0028] The memory stores computer-executed instructions;

[0029] The processor executes computer execution instructions stored in the memory, causing the processor to perform various possible implementations as described above.

[0030] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement various possible implementations as described in any of the above aspects.

[0031] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements various possible implementations as described in any of the above aspects.

[0032] The installment plan determination method, apparatus, electronic device, storage medium, and product provided in this application embodiment include: obtaining user feature information and the user's outstanding bill information; the outstanding bill information includes at least one consumption record; the consumption information includes the consumption amount; filtering a target installment promotion from multiple installment promotions based on the feature information and the outstanding bill information; and determining at least one installment plan through the target installment promotion based on the feature information and the outstanding bill information. This automated filtering and matching frees users from a vast amount of scattered and complex promotional activities, eliminating the need for manual information collection and comparison, significantly shortening decision-making time, reducing selection costs, and by simultaneously considering user feature information and real-time bill information, making the recommended results more aligned with the user's actual needs and repayment ability, improving the applicability of the plan, and helping users choose installment methods with lower costs, more flexible terms, or more matching benefits. Attached Figure Description

[0033] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0034] Figure 1 An application scenario diagram provided for an embodiment of this application;

[0035] Figure 2 A flowchart illustrating a method for determining a phased implementation scheme provided in an embodiment of this application;

[0036] Figure 3 This is a schematic diagram of a phased scheme determination device provided in an embodiment of this application;

[0037] Figure 4 A schematic diagram of the structure of the electronic device provided in this application.

[0038] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0039] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0040] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, 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 countries and regions, have taken necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation access points for users to choose to authorize or refuse.

[0041] Furthermore, the technical solution involved in this application, which involves big data analysis of user information (including but not limited to personal biometrics, identity data, consumption data, asset data, electronic terminal operation data, etc.) and the use of artificial intelligence technology for automated decision-making, and makes decisions that have a significant impact on personal rights based on the results of automated decision-making, provides users with corresponding operation entry points for users to choose to agree to or reject the results of automated decision-making; if the user chooses to reject, the process will proceed to the expert decision-making process.

[0042] It should be noted that the installment plan determination method, apparatus, electronic device, storage medium and product provided in this application can be used in the financial technology field, or in any field other than the financial technology field. The application field of the installment plan determination method, apparatus, electronic device, storage medium and product in this application is not limited.

[0043] With the rapid development of the consumer finance market and the deepening of digital transformation, credit card installment services have become an important part of the modern consumer payment system, playing an increasingly significant role in promoting consumption expansion and serving the real economy. In recent years, the scale of credit card installment transactions in my country has shown a sustained and significant compound growth trend. Industry data shows that as of 2022, the total scale of credit card installment transactions nationwide had historically exceeded 5 trillion yuan, with an average annual compound growth rate of over 15% in the past few years. This rapid growth not only stems from the expansion of the macro-consumer market but also reflects a deeper structural shift in consumer payment habits—a growing demand for flexible, convenient, and affordable payment solutions. Installment payment models effectively alleviate consumers' short-term liquidity pressure and lower the threshold for immediate payment by smoothly distributing large consumer expenditures over multiple periods, thereby stimulating potential consumer demand and contributing to consumption upgrading and the release of domestic demand.

[0044] In terms of market penetration, credit card installment services have gained a broad user base. Surveys indicate that approximately 78% of credit card holders have used installment payment services at least once, demonstrating that this business has evolved from an early innovative product into a mainstream financial tool. To acquire customers and enhance user stickiness and transaction activity in a highly competitive market, commercial banks and card issuers continue to increase investment in product innovation and marketing, launching a wide variety of distinctive installment promotions targeting diverse consumption scenarios. These promotions cover numerous sectors including retail shopping, outbound travel, education and training, home improvement and appliances, healthcare, and car maintenance, and include, but are not limited to, interest-free installments, fee discounts, instant reductions for spending over a certain amount, reward points, and exclusive offers from partner merchants. Such promotional activities typically exhibit distinct characteristics in their design: First, they are highly time-sensitive, often tied to specific time periods such as holidays, e-commerce promotions, and brand cooperation periods; second, they are highly scenario-specific, with preferential benefits often limited to designated merchants, product categories, or consumption channels; and third, their rule systems are complex and significantly different. For example, different activities may have many inconsistencies in terms of installment periods (e.g., 3, 6, 12, 24 installments), nominal interest rates and actual annualized rates, handling fee collection methods (lump-sum collection or installment collection), early repayment regulations, and eligibility restrictions (e.g., minimum transaction amount, customer credit rating requirements).

[0045] However, with the continuous enrichment of installment product systems, the increase in market participants, and the refinement of marketing strategies, a prominent user pain point has gradually emerged: faced with massive, fragmented, varied, and dynamically updated installment offer information, cardholders face severe information overload and choice dilemmas when making decisions. To find the installment plan most suitable for their financial situation, consumption needs, and preferences, users have to invest a significant amount of time and energy, navigating multiple information channels such as bank apps, official websites, SMS notifications, and promotional materials, manually collecting, interpreting, and comparing key parameters of different promotions, including but not limited to total cost, actual annualized interest rate, installment term flexibility, penalty clauses, and additional benefits. This process is not only inefficient and provides a poor user experience, but also, due to the professional and complex nature of financial information, ordinary consumers are prone to making suboptimal decisions due to information asymmetry, misunderstanding of terms, or overlooking hidden conditions. For example, they might choose a plan that appears "interest-free" but has high handling fees, or mistakenly enter into an installment term unsuitable for their cash flow, or even fail to enjoy expected benefits due to unmet additional conditions, thus invisibly increasing financial costs, reducing consumer satisfaction, and potentially leading to unnecessary disputes.

[0046] In view of this, this application provides a method for determining installment payment plans. The server obtains the user's characteristic information and the user's outstanding bill information, wherein the outstanding bill information includes at least one consumption record, and the consumption information includes the consumption amount. Based on the aforementioned characteristic information and outstanding bill information, a target installment payment promotion is selected from multiple installment promotion activities. Then, based on the characteristic information and outstanding bill information, at least one installment payment plan is determined through the target installment payment promotion activity. In this way, through automated screening and matching, users are freed from a large number of scattered and complex promotional activities, eliminating the need for manual information collection and comparison, significantly shortening decision-making time, reducing selection costs, and by simultaneously considering user characteristic information and real-time bill information, the recommended results are more in line with the user's actual needs and repayment ability, improving the applicability of the plan and helping users choose installment methods with lower costs, more flexible terms, or more matching benefits.

[0047] Figure 1 An application scenario diagram provided for an embodiment of this application, such as... Figure 1 As shown, after a user's outstanding bill is generated, the server obtains the user's feature information and outstanding bill information. The outstanding bill information includes at least one transaction, including the transaction amount. Then, based on the aforementioned feature information and outstanding bill information, the server can filter out a target installment promotion from multiple installment promotions. Based on the feature information and outstanding bill information, and through the target installment promotion, the server determines at least one installment plan and sends it to the user's client device. The client device then displays the at least one installment plan on the interface.

[0048] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0049] Figure 2 This is a flowchart illustrating a method for determining a phased implementation scheme provided in an embodiment of this application. The executing entity in this embodiment can be any device with data processing capabilities. This application uses a server as an example for specific illustration. Figure 2 As shown in the embodiment of this application, a method for determining a phased implementation plan is provided, the method comprising:

[0050] Step 201: Obtain the user's characteristic information and the user's outstanding bill information; the outstanding bill information includes at least one consumption record; the consumption information includes: the consumption amount.

[0051] The user's characteristic information is a structured data set describing the user's identity attributes, credit status, behavioral preferences and risk characteristics, including but not limited to: basic information, credit rating, historical installment records, consumption frequency during preset periods, types of merchants, and risk characteristics, etc.

[0052] Basic information may include age, occupation, income range, and city of residence; credit rating may include historical repayment records, credit card limit, credit score, debt ratio, etc.; historical installment records may include historical installment usage frequency, preferred installment periods, and frequent consumption scenarios, such as e-commerce and travel; consumption frequency within a preset period indicates the number of consumptions within a preset period, such as the number of consumptions in more than one month; risk characteristics may include the bank's internal risk rating and abnormal transaction indicators.

[0053] Outstanding bill information refers to the summary information of consumer debts that a user has incurred but has not yet fully paid within the current billing cycle, with the core component being individual consumption information.

[0054] Consumer information refers to the detailed data of a single consumer transaction in the outstanding bill. In addition to the amount spent, it can also include: transaction scenario, time and space information, product information and basic identifiers, etc.

[0055] The transaction scenarios can include merchant types, transaction channels, etc. Merchant types can be department stores, restaurants, etc., and transaction channels can be divided into online and offline.

[0056] Spatiotemporal information can include transaction time and transaction location.

[0057] Product information may include the product category and whether it participates in specific promotional activities.

[0058] Basic identifiers may include transaction serial number, merchant name, etc.

[0059] The pre-acquisition compliance process includes:

[0060] 1. User Authorization Verification: The server first verifies whether the user has signed the "Credit Card Personal Information Processing Authorization", "Credit Inquiry Authorization", and "Personalized Recommendation Authorization for Installment Services". The scope of authorization includes: collection of basic information, credit information, historical installment, transaction behavior, consumption preferences, and do-not-disturb periods for intelligent matching, risk assessment, and precise push of installment plans.

[0061] 2. Access to legitimate data sources:

[0062] Basic information: This bank's account opening system (user information + identity verification);

[0063] Credit rating / risk level: Central bank credit information system (authorized inquiry) + internal risk control model;

[0064] Historical installment / bills / consumption data: Bank's core system + UnionPay clearing data (anonymized);

[0065] Purchase frequency / merchant category: Anonymized analysis of transaction data;

[0066] Do Not Disturb Time / Preference: User-defined settings within the app (explicit consent required);

[0067] Data minimization and desensitization: Only the necessary fields for installment matching (amount, number of installments, scenario, risk level, preference) are extracted, and sensitive information such as ID card and mobile phone number are de-identified.

[0068] Compliance log retention: Record the time, source, purpose, and authorization status of each data query, and retain them for no less than 5 years for regulatory audits.

[0069] Specifically, the triggering events for the server to obtain user characteristic information and user's outstanding bill information include, but are not limited to, the following:

[0070] 1. When a user clicks on the "Bill Installment" or "Single Installment" function through a bank's APP, online banking, or other channels.

[0071] 2. During the window period between the billing date and the payment due date, the server can automatically scan bills that meet the installment conditions and push installment suggestions based on user characteristics.

[0072] 3. When a user makes a large purchase, such as a single transaction exceeding a preset threshold, the server can immediately obtain the purchase information and user characteristics, and pre-generate an installment plan for the user to choose from later.

[0073] 4. When users inquire about installment payment services through customer service hotlines, offline outlets, or other channels, the business system obtains the user's characteristic information and outstanding payment bill information in real time to generate installment plans and provide data support for customer service personnel.

[0074] Optionally, the feature information may include at least one of the following: basic information, credit rating, historical installment records, consumption frequency during preset time periods, and merchant category.

[0075] Step 202: Based on the feature information and outstanding bill information, select the target installment promotion from multiple installment promotions.

[0076] In one alternative implementation, the server performs structured processing on the acquired feature information and outstanding bill information to generate a unified, machine-readable customer-bill feature vector.

[0077] At the same time, all the rules of installment promotion activities, such as applicable groups, scenario restrictions, amount thresholds, time limits, and discount levels, are transformed into structured activity feature vectors or executable rule sets.

[0078] Next, the server inputs the customer-bill feature vector into the rule engine. The engine's built-in rule matching algorithm can determine whether the hard conditions of the installment discount activity are met based on the characteristics of the customer and the characteristics of the bill to be repaid (such as credit score > 650, consumption amount greater than the minimum activity threshold, merchant type matching, etc.). Then, it outputs multiple candidate installment discount activities that initially meet the conditions.

[0079] For any candidate installment payment offer, the activity feature vector and customer-bill feature vector of the candidate installment payment offer are input into a pre-trained filtering model. The pre-trained filtering model outputs a fit score, which can be between 0 and 1. The higher the score, the more likely the offer is to be the optimal choice for the customer under the current bill. In addition to outputting the fit score, the pre-trained filtering model can also output a recommendation reason, such as: Based on your credit history and the type of this purchase, this interest-free offer has a 92% match rate.

[0080] This application does not limit the specific form of the screening model. For example, the screening model can be a logistic regression model, a gradient boosting tree, a deep neural network, etc.

[0081] Finally, the matching scores of each candidate installment discount activity are sorted, and the one or more candidate installment discount activities with the highest scores are selected as the target installment discount activities.

[0082] Optionally, the consumption information also includes: the consumption area; and, based on characteristic information and outstanding bill information, filtering from multiple installment payment promotions to select the target installment payment promotion, including:

[0083] Obtain the target region where the user is located;

[0084] Target consumption information is extracted from at least one consumption record; the consumption region corresponding to the target consumption information is the target region.

[0085] Multiple installment payment promotions were selected as candidate installment payment promotions, and the regions targeted by these candidate installment payment promotions were the target regions.

[0086] Based on feature information and target consumption information, the target installment discount is selected from multiple alternative installment discount activities.

[0087] The consumption area is used to indicate the geographical location of the user when the consumption occurred.

[0088] Specifically, when a user uses a bank's app, answers outbound calls, or makes a transaction, the server can obtain the user's current geographical coordinates in real time through the mobile device's LBS (Location-Based Services) technology, IP (Internet Protocol) address resolution, or base station positioning.

[0089] Based on the user's current geographic coordinates, the target area is determined through a region-geofencing mapping database. This database can integrate with third-party map API (Application Programming Interface) geofencing services, quickly identifying which predefined consumption area the coordinates fall into. For example, if the user is located at coordinates (116.3, 39.9), the region-geofencing mapping database maps the user's target area to "City A, District B".

[0090] For any given transaction, the transaction information includes the transaction region, which is linked to the region where the transaction occurred via UnionPay data or merchant registration information. The transaction region corresponding to this transaction is compared with the target region. If they match, the transaction is considered the target transaction.

[0091] In the installment discount activity management backend, each activity is marked with its applicable consumption area when it is created. The server can filter out alternative installment discount activities from multiple installment discount activities based on the consumption area used as the target area.

[0092] Then, the server selects the target installment discount activity from multiple alternative installment discount activities based on feature information and target consumption information.

[0093] By linking activities to specific regions (such as cities or business districts), it ensures that recommended activities are real, available, and relevant to the user's geographical location, avoiding unnecessary disturbances to the user and greatly improving the relevance and credibility of the recommended information, thereby directly enhancing the user experience.

[0094] Optionally, based on feature information and target consumption information, a target installment payment offer can be selected from multiple alternative installment payment offers, including:

[0095] The feature information and target consumption information are input into the promotional activity determination model. The promotional activity determination model selects the target installment promotion from multiple candidate installment promotions and outputs the corresponding identification information of the target installment promotion.

[0096] The function of the promotional activity determination model is to evaluate and rank the matching degree between candidate installment promotional activities and the current user and current consumption. This application does not limit the specific form of the promotional activity determination model. For example, the promotional activity determination model can be a logistic regression model, a decision tree model, a gradient boosting decision tree model, a random forest model, a deep neural network model, a deep cross-network model, a sequence model, a multi-task learning model, a reinforcement learning model, or any form of ranking learning model.

[0097] Input the feature information, target consumption information, and features of each alternative installment discount activity into the discount activity determination model, and the discount activity determination model can output the corresponding identification information of the target installment discount activity.

[0098] The training method for determining the promotional activity model is as follows:

[0099] A training sample set is constructed. Each training sample in the set includes: user feature information, historical target consumption information, and features of various historical alternative installment payment promotions. The label corresponding to the training sample is: actual installment payment promotion. The historical target installment payment promotions are determined through manual review.

[0100] The training samples are input into the initial promotional activity determination model to obtain the predicted installment promotional activities corresponding to each training sample. For each training sample, the loss value is calculated through the loss function based on the actual installment promotional activity and the predicted installment promotional activity corresponding to that training sample. The initial promotional activity determination model is then adjusted based on the loss value to obtain the trained risk determination model.

[0101] In this way, the model can learn online or be retrained periodically to incorporate the latest user feedback data, thereby dynamically adjusting its recommendation strategy and automatically adapting to market changes, user preference shifts, and new activity types. This gives the system the ability to self-optimize without the need for frequent manual adjustments to complex rules.

[0102] Step 203: Based on the feature information and outstanding bill information, determine at least one installment plan through the target installment promotion.

[0103] Among them, the target installment discount activity includes the core parameters of the activity rules, such as the applicable period range, preferential interest rate / handling fee rate, whether it is interest-free, whether there is a handling fee discount or cap rule, whether a fixed installment amount is required, etc.

[0104] In one alternative implementation, the server first reads the allowed installment periods defined in the rules of the target installment promotion. It then filters the available installment periods based on user characteristics such as credit score and risk level, inputting a list of possible installment periods for the user. For example, a user with a low credit score may not be able to choose a longer term such as 24 installments.

[0105] For each installment period, the applicable interest rate and its discount relative to the original installment rate are determined. The original installment rate is the regional benchmark rate, which is updated regularly at a fixed time each day. Then, based on the user's total outstanding amount or single payment amount, and the interest rate for that installment period, the service area determines the total handling fee, the payment amount for each period, the total payment amount, and so on.

[0106] For each installment period, the corresponding installment plan may include: the number of installments, the amount due in each period, the total handling fee, the total repayment amount, and the actual annualized interest rate, etc.

[0107] The server can then sort the generated installment plans based on the user's historical installment records (e.g., the user's most frequently chosen installment period in the past), prioritizing the plan with the historically preferred number of installments. Alternatively, it can prioritize the plan with the "lowest total cost" or "lowest monthly repayment pressure." Finally, the user enters at least one, usually around three, installment plans, with the plan having the lowest interest rate highlighted.

[0108] Optionally, the installment plan includes: the target installment period, the target installment interest rate, and the discount information of the target installment interest rate relative to the original installment interest rate.

[0109] The original installment interest rate is the regional benchmark interest rate, which can be updated at a fixed time every day.

[0110] The discount information, by comparing the target installment interest rate with the original installment interest rate, intuitively and quantitatively reveals the extent of the discount offered in this recommendation, further improving users' decision-making efficiency and enhancing user satisfaction.

[0111] Optionally, the method for determining the phased implementation plan provided in this application embodiment further includes:

[0112] Get the user's set "Do Not Disturb" time period;

[0113] Determine the target time based on the Do Not Disturb period, where the target time is not located within the Do Not Disturb period;

[0114] At the target time, push at least one installment plan to the user.

[0115] The push notification methods include, but are not limited to, the following: push notifications via mobile applications; sending SMS messages; outbound calls by customer service personnel; display on the user's online banking or mobile banking interface; sending messages through associated social media accounts or instant messaging tools; and prompts on the interface of bank branch self-service equipment, etc.

[0116] By giving users some control over when to send push notifications, they can proactively avoid being disturbed during rest periods, meetings, or at night. This greatly reduces user resentment and resistance caused by receiving push notifications at inappropriate times, fundamentally improving the customer experience.

[0117] The installment plan determination method provided in this application can obtain user characteristic information and user outstanding bill information; the outstanding bill information includes at least one consumption information; the consumption information includes: consumption amount; based on the characteristic information and outstanding bill information, a target installment promotion is selected from multiple installment promotion activities; based on the characteristic information and outstanding bill information, at least one installment plan is determined through the target installment promotion activity. In this way, through automated screening and matching, users are freed from massive, scattered, and complex promotion activities, eliminating the need for manual information collection and comparison, significantly shortening decision-making time, reducing selection costs, and by simultaneously considering user characteristic information and real-time bill information, the recommended results are more in line with the user's actual needs and repayment ability, improving the applicability of the plan and helping users choose an installment method with lower costs, more flexible terms, or more matching benefits.

[0118] Corresponding to the above-described method for determining the phased implementation plan, this application also provides a device for determining the phased implementation plan. Figure 3 This is a schematic diagram of a phased scheme determination device provided in an embodiment of this application, as shown below. Figure 3 As shown in the figure, this embodiment provides a phased scheme determination device, which includes:

[0119] The acquisition module 301 is used to acquire the user's characteristic information and the user's outstanding bill information; the outstanding bill information includes at least one consumption record; the consumption information includes: the consumption amount;

[0120] The filtering module 302 is used to filter out the target installment discount activity from multiple installment discount activities based on feature information and outstanding bill information;

[0121] The determination module 303 is used to determine at least one installment plan based on feature information and outstanding bill information, through the target installment promotion.

[0122] Optionally, the consumption information also includes: consumption area; the filtering module 302 is specifically used for:

[0123] Obtain the target region where the user is located;

[0124] Target consumption information is extracted from at least one consumption record; the consumption region corresponding to the target consumption information is the target region.

[0125] Multiple installment payment promotions were selected as candidate installment payment promotions, and the regions targeted by these candidate installment payment promotions were the target regions.

[0126] Based on feature information and target consumption information, the target installment discount is selected from multiple alternative installment discount activities.

[0127] Optionally, when the filtering module 302 filters out the target installment discount activity from multiple candidate installment discount activities based on feature information and target consumption information, it is specifically used for:

[0128] The feature information and target consumption information are input into the promotional activity determination model. The promotional activity determination model selects the target installment promotion from multiple candidate installment promotions and outputs the corresponding identification information of the target installment promotion.

[0129] Optionally, the installment plan includes: the target installment period, the target installment interest rate, and the discount information of the target installment interest rate relative to the original installment interest rate.

[0130] Optionally, module 303 is also used for:

[0131] Get the user's set "Do Not Disturb" time period;

[0132] Determine the target time based on the Do Not Disturb period, where the target time is not located within the Do Not Disturb period;

[0133] At the target time, push at least one installment plan to the user.

[0134] Optionally, the feature information may include at least one of the following: basic information, credit rating, historical installment records, consumption frequency during preset time periods, and merchant category.

[0135] The phased scheme determination device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0136] Figure 4 A schematic diagram of the structure of the electronic device provided in this application. Figure 4 As shown, the electronic device 40 provided in this embodiment includes at least one processor 401 and a memory 402. Optionally, the device 40 further includes a communication component 403. The processor 401, memory 402, and communication component 403 are connected via a bus 404.

[0137] In a specific implementation, at least one processor 401 executes computer execution instructions stored in memory 402, causing at least one processor 401 to perform the above-described method.

[0138] The specific implementation process of processor 401 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0139] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0140] The memory may include high-speed memory (Random Access Memory, RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0141] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0142] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0143] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0144] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0145] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in application-specific integrated circuits (ASICs). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0146] The division of units is merely a logical functional division; 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 indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0147] 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.

[0148] In addition, the functional units in the various embodiments of the present invention 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.

[0149] If a function 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 invention, or the part that contributes to the prior art, or a 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 invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0150] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0151] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A method for determining a phased implementation plan, characterized in that, The method includes: Obtain user characteristic information and the user's outstanding bill information; the outstanding bill information includes at least one transaction; the transaction information includes: the transaction amount; Based on the feature information and the outstanding bill information, a target installment discount activity is selected from multiple installment discount activities; Based on the aforementioned feature information and the outstanding bill information, at least one installment plan is determined through the target installment promotion.

2. The method according to claim 1, characterized in that, The consumption information also includes: the consumption area; based on the feature information and the outstanding bill information, a target installment discount activity is selected from multiple installment discount activities, including: Obtain the target region where the user is located; Target consumption information is selected from at least one consumption record; the consumption region corresponding to the target consumption information is the target region. The candidate installment payment offers are selected from multiple installment payment offers, and the target region is the region targeted by the candidate installment payment offers. Based on the aforementioned feature information and target consumption information, a target installment discount activity is selected from multiple alternative installment discount activities.

3. The method according to claim 2, characterized in that, Based on the aforementioned feature information and target consumption information, a target installment payment promotion is selected from multiple alternative installment payment promotions, including: The feature information and target consumption information are input into the promotional activity determination model. The promotional activity determination model selects the target installment promotional activity from multiple candidate installment promotional activities and outputs the corresponding identification information of the target installment promotional activity.

4. The method according to claim 1, characterized in that, The installment plan includes: the target installment period, the target installment interest rate, and the discount information of the target installment interest rate relative to the original installment interest rate.

5. The method according to claim 1, characterized in that, The method further includes: Get the user's set "Do Not Disturb" time period; Based on the Do Not Disturb period, a target time is determined, wherein the target time is not located within the Do Not Disturb period; At the target time, at least one installment plan will be pushed to the user.

6. The method according to any one of claims 1-5, characterized in that, The feature information includes at least one of the following: basic information, credit rating, historical installment records, consumption frequency during a preset period, and merchant category.

7. A device for determining a phased plan, characterized in that, The device includes: The acquisition module is used to acquire the user's characteristic information and the user's outstanding bill information; the outstanding bill information includes at least one transaction; the transaction information includes: the transaction amount; The filtering module is used to filter out the target installment discount activity from multiple installment discount activities based on the feature information and the bill information to be repaid; The determining module is used to determine at least one installment plan based on the feature information and the outstanding bill information, through the target installment promotion.

8. An electronic device, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-6.

10. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method described in any one of claims 1-6.

Images