Renting scheme generation method and system and electronic equipment

Abstract

The invention provides a renting scheme generation method and system and electronic equipment, and the method comprises the steps: obtaining an object residual value of a renting object and a user credit value corresponding to a demand user of the renting object when a renting scheme is generated; determining a renting decision result that the renting object can be rented from the demand user based on the object residual value and the user credit value; and generating a renting scheme for the renting object based on the renting decision result.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular, to a rental plan generation method, system, and electronic device. Background Art

[0002] With the development of network technology, shared resources have become commonplace in our daily lives. For example, resource rental platforms optimize the allocation of shared resources and provide rental services to users. Users can rent resources from resource rental platforms online, and they can flexibly choose to rent resources based on short-term needs or cost requirements. However, resource rental carries certain risks, so a reliable rental method is needed to reduce these risks. Summary of the Invention

[0003] The present application provides a leasing plan generation method and system, which can generate a reliable leasing plan when leasing resources and reduce leasing risks.

[0004] In a first aspect, a method for generating a rental plan is provided, the method comprising:

[0005] Obtaining the residual value of the rental object and the user credit value corresponding to the user who requires the rental object, wherein the residual value is used to indicate the remaining usage of the rental object;

[0006] Determining a rental decision result that the rental object can be rented to the user in need based on the object residual value and the user credit value;

[0007] A rental plan for the rental object is generated based on the rental decision result.

[0008] In an optional embodiment, before obtaining the residual value of the rental object and the user credit value corresponding to the user who requires the rental object, the method further includes:

[0009] If a request for a rental object from a user who needs the rental object is detected, obtaining the residual value of the rental object and the user credit value corresponding to the user who needs the rental object is executed; or

[0010] If it is monitored that the remaining rental time of the rental object is less than a preset time threshold, the object residual value of the rental object and the user credit value corresponding to the user who requires the rental object are obtained.

[0011] In an optional embodiment, the determining of the rental decision result that the rental object can be rented to the user in need based on the object residual value and the user credit value includes:

[0012] Obtaining the residual value interval to which the object residual value belongs, and obtaining the credit value interval to which the user credit value belongs;

[0013] The rental decision result that the rental object can be rented to the user in need is determined based on the preset interval matching relationship, the residual value interval, and the credit value interval.

[0014] In an optional embodiment, the determining, based on the preset interval matching relationship, the residual value interval, and the credit value interval, of the rental decision result that the rental object can be rented to the user in need includes:

[0015] Based on the preset interval matching relationship, determining a matching credit value interval corresponding to the residual value interval, and determining that the rental object can be rented to the user in need when the user credit value is greater than or equal to a lower limit of the matching credit value interval;

[0016] Based on the residual value range and the credit value range, rental transaction data of the rental object is determined.

[0017] In an optional embodiment, the determining, based on the preset interval matching relationship, the residual value interval, and the credit value interval, of the rental decision result that the rental object can be rented to the user in need includes:

[0018] Based on the preset interval matching relationship, determining a matching residual value interval corresponding to the credit value interval, and determining that the rental object can be rented to the demanding user when the object residual value is within the matching residual value interval;

[0019] Based on the residual value range and the credit value range, rental transaction data of the rental object is determined.

[0020] In an optional implementation, determining the rental transaction data of the rental object based on the residual value range and the credit value range includes:

[0021] Determining a target rental transaction data table based on the residual value interval, wherein the target rental transaction data table is used to indicate a correspondence between each credit value sub-interval and rental transaction data;

[0022] Determine a target credit value sub-interval to which the user credit value belongs within the credit value interval;

[0023] The rental transaction data of the rental object corresponding to the target credit value sub-interval is determined based on the target rental transaction data table.

[0024] In an optional embodiment, before determining the rental decision result that the rental object can be rented to the user based on the preset interval matching relationship, the residual value interval, and the credit value interval, the further step includes:

[0025] Obtaining the historical residual value of the leased object before a preset time interval;

[0026] Determining a change in the residual value of the leased object based on the residual value of the object and the historical residual value;

[0027] When the residual value change value is greater than or equal to a first preset threshold, the upper limit value and the lower limit value of the credit value interval in the preset interval matching relationship are adjusted according to the residual value change trend.

[0028] In an optional embodiment, the determining of the rental decision result that the rental object can be rented to the user in need based on the object residual value and the user credit value includes:

[0029] Obtaining a residual value evaluation value corresponding to the residual value interval to which the residual value of the object belongs;

[0030] Obtaining a credit rating value corresponding to the credit value interval to which the user's credit value belongs;

[0031] Determining the rentability of the rental object based on the residual value evaluation value and the credit evaluation value;

[0032] If the rentability is greater than or equal to a second preset threshold, it is determined that the rental object can be rented to the user in need.

[0033] In an optional implementation, obtaining the residual value of the leased object includes:

[0034] Obtaining the usage time, maintenance records and current demand information of the rental object;

[0035] and determining the wear rate of the rental object based on the usage time and the maintenance record;

[0036] The object residual value of the rental object is obtained according to the wear rate and the current demand information.

[0037] In a second aspect, a rental service system is further provided, the rental service system comprising:

[0038] An acquiring unit, configured to acquire a residual value of a rental object and a user credit value corresponding to a user who requires the rental object, wherein the residual value indicates the remaining usage of the rental object;

[0039] A determining unit, configured to determine a rental decision result that the rental object can be rented to the user in need based on the residual value of the object and the user credit value;

[0040] A processing unit is configured to generate a rental plan for the rental object based on the rental decision result.

[0041] In a third aspect, an electronic device is further provided, the electronic device comprising:

[0042] a memory for storing executable program code;

[0043] The processor is configured to call and run the executable program code from the memory, so that the electronic device executes the method described in the first direction above.

[0044] In a fourth aspect, a computer program product is provided, comprising: a computer program code, which, when executed on a computer, enables the computer to execute the method in the first aspect or any possible implementation of the first aspect.

[0045] In a fifth aspect, a computer-readable storage medium is provided, which stores a computer program code. When the computer program code runs on a computer, the computer executes the method in the above-mentioned first aspect or any possible implementation of the first aspect.

[0046] The rental plan generation method, system, and electronic device provided in one or more embodiments of the present specification, before generating a rental plan, comprehensively determine the decision result that the rental object can be rented to the demanding user based on the object residual value of the rental object and the user credit value of the demanding user. The object residual value can reflect the remaining usage of the rental object, and the user credit score value can reflect the credit level of the demanding user for returning the rental object with the remaining usage. Deciding whether the rental object can be rented or the rental transaction data of the rental object from multiple dimensions can improve the accuracy and reliability of risk identification, reduce rental risks, and improve rental services. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 This is a scenario diagram of a rental plan generation method provided in an embodiment of the present application;

[0048] Figure 2 This is a flowchart of a method for generating a rental plan provided in an embodiment of the present application;

[0049] Figure 3 This is a flowchart of a method for generating a rental plan provided in an embodiment of the present application;

[0050] Figure 4This is a flowchart of a method for generating a rental plan provided in an embodiment of the present application;

[0051] Figure 5 This is a flowchart of a method for generating a rental plan provided in an embodiment of the present application;

[0052] Figure 6 This is a structural diagram of a rental plan generation method provided in an embodiment of the present application;

[0053] Figure 7 This is a structural diagram of a rental plan generation system provided in an embodiment of the present application;

[0054] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0055] The following will clearly and thoroughly describe the technical solutions in one or more embodiments of this specification in conjunction with the accompanying drawings. In the description of one or more embodiments of this specification, unless otherwise specified, " / " means or, for example, A / B can mean A or B: "and / or" in the text is only a description of the association relationship of associated objects, indicating that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of one or more embodiments of this specification, "multiple" means two or more than two.

[0056] In the following, the terms "first" and "second" are used for descriptive purposes only and should not be understood to imply or suggest relative importance or implicitly indicate the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features.

[0057] The technical solutions of one or more embodiments of this specification are described in detail below in conjunction with the embodiments and drawings.

[0058] With the development of network technology, shared resources have become commonplace in our daily lives. For example, resource rental platforms optimize the allocation of shared resources and provide rental services to users. Users can rent resources from resource rental platforms online, and users can choose to rent resources based on short-term needs or cost requirements.

[0059] However, resource rental carries certain risks. For example, users may not return the items on time or may be unable to do so. Therefore, rental platforms need to assess rental risks. For example, when a user rents a resource online from a rental platform, the platform assesses the user's ability to return the item. In particular, after renting out the item, the user may want to renew the lease. If the remaining lease time is less than or equal to a preset time threshold, the platform assesses the user's ability to renew the lease and then prompts the user to choose to renew or return the item.

[0060] In the prior art, rental platforms typically use the credit score of the user requesting the item to determine whether the item can be renewed with the tenant, and then send the user a renewal plan. However, this approach, based on user credit scores, is limited in scope, covers a limited number of scenarios, requires manual review, and offers low accuracy and reliability in identifying rental risks. Therefore, a reliable rental method is needed to generate reliable rental plans and reduce resource rental risks.

[0061] In response to the above technical problems, this specification provides a rental plan generation method and a rental plan generation system that can execute the method. In this method, when renting, the residual value of the rental object and the user credit value corresponding to the user who needs the rental object are combined to comprehensively evaluate whether the rental object can be rented to the user who needs the rental object and the rental decision result of renting it to the user who needs the rental object. In short, the rental risk of the rental object is comprehensively judged from multiple dimensions such as the object residual value and the user credit value, the judgment accuracy is higher, and the rental service is balanced from multiple dimensions such as the object residual value and the user credit value, thereby improving the reliability of the rental decision results.

[0062] It should be noted that in one or more embodiments of this specification, the demanding user refers to the mobile terminal of the user of the target rental object, and the target rental object refers to the rental object rented for use by the user.

[0063] Figure 1 This is a schematic diagram of a rental scenario provided in an embodiment of the present application. The rental scenario may include a cloud 10, a mobile terminal 20 and an edge node 30. The cloud 10 provides a rental platform, and the rental platform provides various types of rental objects 40. For example, the rental object 40 can be a mobile phone, a tablet, a vehicle, a home appliance, etc., or a non-electronic rental object, such as furniture, etc. The type of rental object is not limited.

[0064] The mobile terminal 20 communicates with the cloud 10. The user in need accesses the rental platform of the cloud 10 through the mobile terminal 20, selects the rental object 40 on the rental platform, and rents the rental object 40 from the rental platform. The user in need can use the rental object 40 within the rental period, and choose to return the rental object 40 or continue to rent the rental object 40 after the use period expires. When the user in need accesses the rental platform through the mobile terminal 20, the user in need needs to register the user information of the user in need in the mobile terminal 20, wherein the user information includes the user credit value. The cloud 10 can obtain the user credit value of the user in need through the mobile terminal 20. Alternatively, after the cloud 10 obtains the user information of the user in need through the mobile terminal 20, it can record the user's performance behavior, abnormal behavior and other information, so as to facilitate the retrieval of the user's performance behavior record and abnormal behavior record to determine the user credit value of the user in need. Alternatively, the cloud 10 may obtain the user information of the user in need, and then, based on the third-party platform associated with the user information, obtain information such as the third-party rating record of the user in need, and then determine the user credit value corresponding to the mobile terminal 20 based on information such as the user's fulfillment behavior record, abnormal behavior record, and third-party rating record.

[0065] In some examples, the rental object 40 is equipped with an IoT sensor, which detects data related to the rental object 40, such as usage time, maintenance records, location information, and rental object information. Some smart IoT sensors can communicate with the cloud 10 and upload detected data related to the rental object 30 to the cloud 10, providing data support for the cloud 10 to calculate the residual value of the rental object. Alternatively, some standard IoT sensors can communicate with an edge node 30 (such as a gateway) in the cloud 10. The IoT sensor uploads detected data related to the rental object 40 to the cloud 10 through the edge node 30, providing data support for the cloud 10 to analyze the residual value of the object. The edge node 30 filters and calculates the data collected by the IoT sensor, transmitting data related to the calculated residual value to the cloud while filtering out data unrelated to the rental object's residual value. This reduces data processing on the cloud server and reduces bandwidth usage.

[0066] Based on the above rental scenario, when the user in need accesses the rental platform through a mobile terminal and triggers a rental request for the rental object on the rental platform, the cloud will determine whether the rental object can be rented to the user in need based on the residual value of the rental object and the user credit value of the user in need. If the rental object can be rented to the user in need, the cloud will determine the rental transaction data of the rental object and generate a rental plan based on the rental transaction data.

[0067] Alternatively, while the rental object is being rented, the cloud monitors the remaining usage time of the rental object and, if it detects that the remaining usage time is less than or equal to a preset time threshold, triggers the generation of a renewal plan for the rental object. Specifically, the cloud obtains the residual value of the rental object and the user credit score of the requesting user, and then determines whether the rental object can be renewed with the requesting user based on the residual value and the user credit score of the requesting user. If the rental object can be renewed with the requesting user, the cloud determines the rental transaction data of the rental object and generates a rental plan based on the rental transaction data.

[0068] Figure 2 This is a flow chart of a method for generating a rental plan provided in an embodiment of this specification. Figure 2 As shown, taking the execution subject as a rental plan generation system as an example, the method of the embodiment of the present application includes:

[0069] S202, obtaining the residual value of the rental object and the user credit value corresponding to the user who requires the rental object;

[0070] In this embodiment, the rental plan generation system is used to generate a rental plan. The rental plan generation system triggers the rental plan generation process in at least the following two scenarios:

[0071] For example, in scenario 1, the rental plan generation system provides a rental platform, which offers various types of rental objects. When a user selects a desired rental object for rental based on the rental platform, the rental platform generates a rental plan for the rental object and then reaches a rental agreement with the user.

[0072] For scenario 1, if the rental plan generation system detects a rental request from a user requesting the rental object, it executes step S202 to obtain the residual value of the rental object and the user credit value corresponding to the user requesting the rental object.

[0073] For example, in scenario 2: when the rental object is rented and used by the user in need, the rental platform will regularly check the remaining rental time of the rental object, and based on the remaining rental time being less than the preset time threshold, the rental platform will generate a rental plan based on whether the lease can be renewed.

[0074] For scenario 2, if the rental plan generation system detects that the remaining rental time of the rental object is less than the preset time threshold, step S202 is executed to obtain the residual value of the rental object and the user credit value corresponding to the user who requires the rental object.

[0075] In an optional implementation, the processor of the rental solution generation system can respond to the rental request and renewal task in the following manner: when the processor receives a rental request from the application layer (the demand user triggers a rental request for the rental object through the application interface), it generates a rental task according to the rental request, and then adds the rental task to the message queue. Alternatively, when the processor detects that the remaining rental time of a rental object is less than a preset time threshold, it generates a renewal rental task for the rental object, and then adds the rental task to the message queue. In this way, when the processor processes the tasks in the message queue, if it obtains a rental task, it determines the rental object and the demand user corresponding to the rental object based on the rental task, and then obtains the object residual value of the rental object and the user credit value corresponding to the demand user of the rental object.

[0076] Optionally, in this step, the residual value of the leased object is used to indicate the remaining usage of the leased object. The residual value of the leased object can be obtained by the following steps A1 to A3:

[0077] A1: Obtain the usage time, maintenance records, and current demand information of the rental object;

[0078] It should be noted that the usage duration and maintenance records of the rental object can be obtained based on the rental object's IoT sensors. Current demand information for the rental object can be captured from other platforms or systems through API interfaces. This current demand information reflects the supply and demand situation of the rental object at the time of rental. For example, current demand information includes a demand index. When the supply of the rental object exceeds the demand at the time of rental, the demand index is low; when the supply of the rental object is low, the demand index is high.

[0079] A2: Determine the wear rate of the rental object based on usage time and maintenance records;

[0080] The wear rate is one of the indices that reflects the remaining usage of the rental object. The longer the usage period, the greater the wear rate of the rental object. The more maintenance records, the greater the wear rate of the rental object. The greater the wear rate of the rental object, the less the remaining usage.

[0081] A3: Obtain the residual value of the leased object based on the wear rate and current demand information.

[0082] In some examples, the wear rate is converted into a physical residual value, the current demand information is converted into a demand residual value, and the object residual value of the leased object is obtained by weighting the physical residual value and the demand residual value.

[0083] Optionally, in this step, the user credit value corresponding to the user who requires the rental object can be obtained in the following way:

[0084] In one optional implementation, the rental plan generation system obtains the user credit score corresponding to the requesting user by accessing a third-party platform. The user credit score is generated by the third-party platform based on all the user's fulfillment behavior records and abnormal behavior records (including the fulfillment behavior records and abnormal behavior records on the rental receipt).

[0085] In an optional implementation method, the rental plan generation system obtains the fulfillment behavior record and abnormal behavior record of the user in need on the rental platform, and obtains the evaluation value of the user in need from the third-party platform, and generates a user credit score value corresponding to the user in need based on the user's fulfillment behavior record, abnormal behavior record and evaluation value.

[0086] S204, determining a rental decision result that the rental object can be rented to the user in need based on the residual value of the object and the user's credit value;

[0087] In the rental decision, the rental decision result includes whether the rental object is available for rental or not. Alternatively, in some scenarios, the rental decision result also includes rental transaction data of the rental object.

[0088] The object residual value is used to indicate the remaining usage of the leased object, and the user credit value is used to indicate the credit level of the requesting user.

[0089] In some applications, a single user credit score is used to decide whether an object can be rented. The decision results are inaccurate and most decisions require human intervention. For example, when a single user credit score is used to decide whether an object can be rented, 40% of the decisions can be completed automatically, but 60% of the decisions require human intervention.

[0090] In one or more embodiments of the present specification, whether the rental object is available for rent may also be related to the residual value of the rental object. The size of the residual value of the object may affect the credit of the user who requests the rental object. For example, when the remaining usage of the rental object is high, there is a possibility that the user who requests the rental object with a high degree of credit will refuse to return the rental object, while the user who requests the rental object with a low degree of credit is more likely to refuse to return the rental object. Alternatively, when the remaining usage of the rental object is low, there is also a possibility that the user who requests the rental object with a high degree of credit will not return the rental object. Alternatively, when the remaining usage of the rental object is low, the user who requests the rental object with a low degree of credit may also return the rental object on time.

[0091] In this embodiment, a comprehensive decision on whether a rental object is available for rent is made based on the object's residual value and the user's credit score. For example, a rental object with a high residual value can only be rented to a user with a high credit score, while a rental object with a low residual value can be rented to a user with a low credit score, but cannot be rented to a user with an extremely low credit score. Alternatively, a user with a low credit score can rent objects with a narrow range of residual values, but cannot rent objects with high residual values; a user with a high credit score can rent objects with a wider range of residual values, but cannot rent objects with very low residual values. Based on this, judging whether a rental object is available for rent to a user based on the object's residual value and the user's credit score can, on the one hand, reduce rental risks, and on the other hand, provide more scenarios for automatic decision-making, thereby reducing manual intervention in decision-making.

[0092] S206: Generate a rental plan for the rental object based on the rental decision result.

[0093] In this step, if the rental decision result includes determining that the rental object can be rented to the user in need, a rental plan for the rental object can be generated based on the preset rental transaction data.

[0094] Alternatively, if the rental decision result includes determining whether the rental object is available for rent and rental transaction data, a rental plan for the rental object may be generated based on the determined rental transaction data.

[0095] In some optional embodiments, if it is determined that the rental object cannot be rented to the user in need based on the residual value of the object and the user's credit value, a manual review instruction is output to prompt that the rental object requires manual review to determine whether it can be rented to the user in need. At the same time, a rental risk prompt for the rental object is output.

[0096] In this embodiment, before generating a rental plan, the object residual value of the rental object and the user credit value of the user in need are used to comprehensively determine the decision result that the rental object can be rented to the user in need. The object residual value can reflect the remaining usage of the rental object, and the user credit score value can reflect the credit level of the user in need for returning the rental object with this remaining usage. Deciding whether the rental object can be rented or the rental transaction data of the rental object from multiple dimensions can improve the accuracy and reliability of risk identification, reduce rental risks, and improve rental services.

[0097] Figure 3 This is a flow chart of a method for generating a rental plan provided in an embodiment of this specification. Figure 3 As shown, the execution subject is a rental plan generation system as an example for description. This embodiment is based on the above embodiment and refines the situation where the rental object can be rented to the user in need. Specifically, this embodiment includes S302 and S304:

[0098] S302, obtaining the residual value interval to which the object residual value belongs, and obtaining the credit value interval to which the user credit value belongs;

[0099] This embodiment uses the example of dividing the residual value of an object from 0% to 100% into three residual value intervals. For example, the residual value intervals include a first residual value interval corresponding to 0% to 30%, a second residual value interval corresponding to 30% to 50%, and a third residual value interval corresponding to 50% to 100%. If the residual value of the rental object is 50%, the residual value of the object belongs to the third residual value interval. If the residual value of the rental object is 30%, the residual value of the object belongs to the first residual value interval.

[0100] This embodiment uses the example of dividing a user's credit score into three credit score intervals. For example, the credit score intervals include a first credit score interval corresponding to 650-750, a second credit score interval corresponding to 750-800, and a third credit score interval corresponding to values ​​above 800. If the user's credit score is 700, the credit score interval to which the user's credit score belongs is the first credit score interval. If the user's credit score is 800, the credit score interval to which the user's credit score belongs is the third credit score interval.

[0101] It should be noted that this embodiment is not limited to the three residual value intervals and three credit value intervals listed above. In actual application, more or fewer residual value intervals and credit value intervals can be selected according to specific needs. Moreover, the number of residual value intervals and the number of credit value intervals can be the same or different. For example, three residual value intervals can be divided based on 0-100%, and two or four credit value intervals can be divided based on 650 or above. Moreover, the upper and lower limits of each interval are not limited to the values ​​listed above. The upper and lower limits of each interval can be determined according to needs or according to experimental tests. The ranges listed below are not limiting.

[0102] S304: Based on the preset interval matching relationship, the residual value interval, and the credit value interval, a rental decision result is determined, indicating that the rental object can be rented to the user in need.

[0103] In this embodiment, the rental decision result includes whether the object can be rented or not. When the residual value interval and the credit value interval meet the preset interval matching relationship, it is determined that the rental object can be rented to the user in need.

[0104] A preset interval matching relationship refers to a pre-set pairing relationship between residual value intervals and credit value intervals. The object's residual value within the paired residual value intervals is combined with the user's credit value within the paired credit value intervals to determine whether the rental object is suitable for the user in need, with low rental risk and a balanced risk-benefit ratio. Therefore, the preset interval matching relationship includes pairings between the first residual value interval and the first, second, and third credit value intervals. Alternatively, the third residual value interval, corresponding to 50% to 100%, needs to be matched with a credit value interval of 800 or above, with low rental risk and a balanced risk-benefit ratio. Therefore, the preset interval matching relationship includes pairings between the third residual value interval and the third credit value interval. "Balanced rental risk-benefit ratio" indicates that the rental object has a low rental risk and is suitable for rental.

[0105] If, based on step S301, it is determined that the residual value interval to which the object residual value of the rental object belongs is the first residual value interval, and the credit value interval to which the user credit value of the requesting user belongs is the first credit value interval / the second credit value interval / the third credit value interval, then it is determined that the residual value interval and the credit value interval satisfy a preset interval matching relationship, and the rental object is determined to be available for rental to the requesting user. If, based on step S301, it is determined that the residual value interval to which the object residual value of the rental object belongs is the third residual value interval, and the credit value interval to which the user credit value of the requesting user belongs is the first credit value interval or the second credit value interval, then it is determined that the residual value interval and the credit value interval do not satisfy the preset interval matching relationship; if the credit value interval to which the user credit value of the requesting user belongs is the third credit value interval, then it is determined that the residual value interval and the credit value interval satisfy a preset interval matching relationship, and the rental object is determined to be available for rental to the requesting user.

[0106] In short, based on the preset interval matching relationship, the residual value interval and the credit value interval, the rental transaction data that determines whether the rental object can be rented to the user in need can be determined. Specifically, it can be: judging whether the residual value interval and the credit value interval meet the preset interval matching relationship. If so, it is determined that the rental object can be rented to the user in need. If not, it is determined that the rental object cannot be rented to the user in need.

[0107] In an optional embodiment, the rental decision result includes whether the rental object is available for rent or not, as well as the rental transaction data of the rental object. This embodiment, based on the rental object value and the user's credit value, needs to determine whether the rental object can be rented to the user in need, and the corresponding rental transaction data when it is available. The following two embodiments are listed to explain in detail the method for determining whether the rental object is available for rent and the method for determining the rental transaction data:

[0108] For example, in Example 1, based on the preset interval matching relationship, the residual value interval, and the credit value interval, the rental decision result of determining whether the rental object can be rented to the user in need includes:

[0109] A1: Based on the preset interval matching relationship, a matching credit value interval corresponding to the residual value interval is determined, and when the user's credit value is greater than or equal to the lower limit of the matching credit value interval, the rental object is determined to be available for rental to the user in need;

[0110] For example, if the preset matching relationship includes a first residual value interval matching a first credit value interval, a second credit value interval, and a third credit value interval, then if the residual value interval to which the object residual value of the rental object belongs is the first residual value interval, then the corresponding matching credit value intervals are determined to be the first credit value interval, the second credit value interval, and the third credit value interval. If the user credit value of the requesting user is greater than or equal to the lower limit of the matching credit value interval, such as the lower limit of the first credit value interval, then it is determined that the risk of renting the rental object to the requesting user is low, and the rental object can be rented to the requesting user.

[0111] Alternatively, if the preset matching relationship includes a match between a third residual value interval and a third credit score interval, then if the residual value interval of the rental object falls within the third residual value interval, the corresponding matching credit score interval is determined to be the third credit score interval. If the user credit score of the requesting user is less than the lower limit of the third credit score interval, this indicates that the residual value of the rental object is high, while the user credit score of the requesting user is low. In this case, the rental risk is high, and the rental object is determined not to be rented to the requesting user.

[0112] A2: Based on the residual value range and the credit value range, the rental transaction data of the rental object is determined.

[0113] The rental transaction data includes the rental amount and / or rental period of the rental object.

[0114] In some examples, the rental transaction data of the rental object is set by the rental platform, and the rental transaction data is the same for all users with requirements.

[0115] In some examples, in order to improve the rental efficiency and enhance the rental service experience, the rental transaction data can be adaptively adjusted based on the residual value of the rental object and the user credit value of the demanding user. For example, when the residual value of the rental object corresponds to different user credit values, the corresponding rental transaction data is different. For example, if the residual value of the rental object is in the first residual value interval, if the user credit value of the demanding user is in the first credit value interval, the corresponding rental transaction data is Z1; if the user credit value of the demanding user is in the second credit value interval, the corresponding rental transaction data is Z2; if the user credit value of the demanding user is in the third credit value interval, the corresponding rental transaction data is Z3. For example, Z1>Z2>Z3. For different demanding users, the rental transaction data of the rental object is different, thereby improving the rental service experience.

[0116] For example, in Example 2, based on the preset interval matching relationship, residual value interval, and credit value interval, the rental transaction data of the rental object that can be rented to the user in need is determined, including:

[0117] B2: Based on the preset interval matching relationship, determine the matching residual value interval corresponding to the credit value interval, and if the object residual value is within the matching residual value interval, determine that the rental object can be rented to the user in need;

[0118] The difference between Example 2 and Example 1 is that Example 1 uses the residual value interval to determine a matching credit value interval that satisfies a preset interval matching relationship, and then determines whether the rental object is available for rental to the requesting user based on the relationship between the user's credit value and the matching credit value interval. In contrast, Example 2 uses the credit value interval to determine a matching residual value interval that satisfies a preset interval matching relationship, and then determines whether the rental object is available for rental to the requesting user based on the relationship between the object residual value of the rental object and the matching residual value interval.

[0119] Exemplarily, if the preset matching relationship includes a pairing relationship between a first credit value interval and a first residual value interval, a pairing relationship between a second credit value interval and the first residual value interval and the second residual value interval, and a pairing relationship between a third credit value interval and the first residual value interval, the second residual value interval and the third residual value interval. If the credit value interval to which the user credit value of the requesting user belongs is the first credit value interval, the corresponding matching residual value interval is determined to be the first residual value interval. If the object residual value of the rental object is in the first residual value interval, it is determined that the risk of renting the rental object to the requesting user is small, and the rental object can be rented to the requesting user. If the object residual value of the rental object is in the second residual value interval or the third residual value interval, it is determined that the risk of renting the rental object to the requesting user is high, and the rental object cannot be rented to the requesting user.

[0120] B4: Based on the residual value range and the credit value range, determine the rental transaction data of the rental object.

[0121] The rental transaction data includes the rental amount and / or rental period of the rental object.

[0122] In some examples, the rental transaction data of the rental object is set by the rental platform, and the rental transaction data is the same for all users with requirements.

[0123] In some examples, in order to improve the rental efficiency and enhance the rental service experience, the rental transaction data can be adaptively adjusted based on the residual value of the rental object and the user credit value of the demanding user. For example, when the residual value of the rental object corresponds to different user credit values, the corresponding rental transaction data is different. For example, if the residual value of the rental object is in the first residual value interval, if the user credit value of the demanding user is in the first credit value interval, the corresponding rental transaction data is Z1; if the user credit value of the demanding user is in the second credit value interval, the corresponding rental transaction data is Z2; if the user credit value of the demanding user is in the third credit value interval, the corresponding rental transaction data is Z3. For example, Z1>Z2>Z3. For different demanding users, the rental transaction data of the rental object is different, thereby improving the rental service experience.

[0124] In this embodiment, a preset interval matching relationship is set for the residual value interval and the credit value interval. When the residual value interval to which the object residual value belongs and the credit value interval to which the user's credit value belongs meet the matching relationship, a rental plan that can be rented to the user in need is generated, and the balance between rental risk and rental benefit is ensured based on the preset interval matching relationship.

[0125] Figure 4 This is a flow chart of a method for generating a rental plan provided in an embodiment of this specification. Figure 4 As shown, the execution subject is a rental plan generation system as an example for description. Based on the above embodiment, this embodiment refines the process of determining the rental transaction data, specifically including:

[0126] S402: Determine a target rental transaction data table based on the residual value interval. The target rental transaction data table is used to indicate the correspondence between each credit value sub-interval and rental transaction data.

[0127] S404, determining the target credit value sub-interval to which the user's credit value belongs within the credit value interval;

[0128] S406: Determine the rental transaction data of the rental object corresponding to the target credit value sub-interval based on the target rental transaction data table.

[0129] In this embodiment, each residual value interval corresponds to a rental transaction data table. Within each rental transaction data table, the corresponding rental transaction data differs based on the credit value interval. This allows different rental plans to be set based on the rental object and the user who requested the rental. This allows for generating different rental plans based on the residual value of the rental object and the user's credit score. For example, a rental plan can be generated in which rental transaction data varies in a step-by-step manner based on the residual value of the rental object and the user's credit score.

[0130] For example, the residual value interval includes a first residual value interval, a second residual value interval, and a third residual value interval, and the credit value interval includes a first credit value interval, a second credit value interval, and a third credit value interval. The first residual value interval corresponds to a first rental transaction data table. In the first rental transaction data table, the rental transaction data corresponding to the first credit value interval is M1, the rental transaction data corresponding to the second credit value interval is N1, and the rental transaction data corresponding to the third credit value interval is K1. The second residual value interval corresponds to a second rental transaction data table. In the second rental transaction data table, the rental transaction data corresponding to the first credit value interval is M2, the rental transaction data corresponding to the second credit value interval is N2, and the rental transaction data corresponding to the third credit value interval is K2. The third residual value interval corresponds to a third rental transaction data table. In the third rental transaction data table, the rental transaction data corresponding to the first credit value interval is M3, the rental transaction data corresponding to the second credit value interval is N3, and the rental transaction data corresponding to the third credit value interval is K3. Specifically, within the same rental transaction data table, the rental transaction data decreases as the credit value range increases (e.g., M1>N1>K1). That is, for the same rental object, the higher the user's credit value, the lower the rental fee. Users with high credit values ​​receive greater discounts, improving rental services. Within different rental transaction data tables, the rental transaction data for the same credit value range is different. The higher the residual value of the rental object, the higher the rental transaction data (e.g., K1<K2<K3). In other words, the higher the residual value of the object, the higher the remaining usage of the rental object. Based on the balance between benefits and risks, the higher the rental transaction data.

[0131] In an optional embodiment, at least two sub-intervals are divided in the first credit value interval, the second credit value interval and the third credit value interval, and different sub-intervals in the same credit value interval correspond to different rental transaction data, thereby realizing a more refined step-by-step rental plan.

[0132] For example, in the first rental transaction data table corresponding to the first residual value interval, the first credit value interval includes three credit value sub-intervals, the second credit value interval includes three credit value sub-intervals, and the third credit value interval includes three credit value sub-intervals. Different credit value sub-intervals correspond to different rental transaction data. The larger the credit value sub-interval, the smaller the rental transaction data.

[0133] If the residual value interval of the rental object's residual value falls within the first residual value interval, the matching credit value intervals corresponding to the first residual value interval include the first credit value interval, the second credit value interval, and the third credit value interval. The user credit value of the user requesting to rent the rental object is determined, and the credit value interval to which the user credit value falls is determined. If the credit value interval falls within the first credit value interval, rental transaction data for the rental of the rental object by the requesting user is determined based on the target credit value sub-interval to which the user credit value falls within the first credit value interval. If the user credit value interval falls within the second credit value interval, rental transaction data for the rental of the rental object by the requesting user is determined based on the target credit value sub-interval to which the user credit value falls within the second credit value interval.

[0134] In a rental object renewal scenario, if the residual value of the rental object during the previous rental period was within the second residual value range and the user's credit score was within the second credit value range, then based on the rental transaction data table corresponding to the second residual value range, the rental transaction data corresponding to the second credit value range is determined to be N2, or the rental transaction data corresponding to the target credit value subrange within which the user's credit score falls is determined to be N22. If the remaining rental time of the rental object is less than a preset duration threshold, and the current residual value of the rental object is determined to be within the first residual value range and the user's credit score is still within the second credit value range, then based on the rental transaction data table corresponding to the first residual value range, the rental transaction data corresponding to the second credit value range is determined to be N1, or the rental transaction data corresponding to the target credit value subrange within which the user's credit score falls is determined to be N11, where N1 < N2 or N11 < N22. In a renewal scenario, if the user's credit score remains unchanged or changes slightly, and the residual value of the rental object decreases, the number of rental transaction data is reduced, thereby increasing the renewal success rate and minimizing the renewal risk.

[0135] Alternatively, if the residual value of the rental object of the requesting user during the previous rental period was within the second residual value range and the user's user credit score was within the third credit value range, then based on the rental transaction data table corresponding to the second residual value range, the rental transaction data corresponding to the third credit value range is determined to be K2, or the rental transaction data corresponding to the target credit value subrange within which the user's credit score falls is determined to be K22. If the remaining rental time of the rental object is less than a preset time threshold, and the current residual value of the rental object is determined to be within the third residual value range, and the user's credit score is still within the third credit value range, then based on the rental transaction data table corresponding to the third residual value range, the rental transaction data corresponding to the third credit value range is determined to be K3, or the rental transaction data corresponding to the target credit value subrange within which the user's credit score falls is determined to be K33, where K3>K2 or K33<K22. In the renewal scenario, if the user's user credit score remains unchanged or changes slightly, and the residual value of the rental object increases, additional rental transaction data is added to ensure the rental efficiency of the rental platform while reducing the rental risk of the rental object.

[0136] In this embodiment, different rental transaction data tables are set up based on different residual value intervals. In the rental transaction data table, the rental transaction data corresponding to different credit sub-intervals are different. According to the residual value of the object and the user's credit value, different rental transaction data rental plans can be generated to enrich the rental plans and improve the rental service.

[0137] Figure 5 This is a flow chart of a method for generating a rental plan provided in an embodiment of this specification. Figure 5 As shown, taking the execution subject as a rental plan generation system as an example for explanation, the rental plan generation method provided in this embodiment includes:

[0138] S502, obtaining the residual value of the rental object and the user credit value corresponding to the user who requires the rental object;

[0139] S504, obtaining the residual value interval to which the object residual value belongs, and obtaining the credit value interval to which the user credit value belongs;

[0140] The specific implementation principles and processes of step S502 and step S504 are the same as those in the aforementioned embodiment, and reference may be made to the aforementioned embodiment, which will not be described in detail here.

[0141] S506, obtaining the historical residual value of the leased object before a preset time interval;

[0142] S508, determining a residual value change of the leased object based on the residual value of the object and the historical residual value;

[0143] S510: When the residual value change value is greater than or equal to a first preset threshold, adjust the upper limit and lower limit of the credit value interval in the preset interval matching relationship according to the residual value change trend.

[0144] It should be noted that the rental platform regularly checks the residual value of the rental object to analyze the trend of the residual value. The trend of the residual value change can include a decrease in the residual value or an increase in the residual value. For example, if the residual value decreases from 40% to 30%, the trend of the residual value change is defined as a decrease; if the residual value increases from 40% to 50%, the trend of the residual value change is defined as an increase.

[0145] It should be noted that, in general, the residual value of a rental object will gradually decrease as the rental object is used for a longer period (rental period), and the residual value decreases at a certain curvature, so the residual value change of a rental object is within a certain range. However, in some scenarios, the residual value change of a rental object is abnormal, for example, the residual value of the rental object increases, or the residual value of the rental object drops sharply. In these scenarios, the change in the residual value of the rental object is abnormal. When generating a rental plan, it is necessary to adaptively adjust the matching relationship between the residual value interval and the credit value interval, such as adjusting the upper and lower limits of the matching credit value interval corresponding to the residual value interval, so that the matching relationship between the residual value interval and the credit value interval is adaptively adjusted based on the changing trend of the rental object. Then, based on the adjusted preset interval matching relationship, a rental plan that is more suitable for the current scenario can be generated, so that the rental platform can adjust the appropriate rental plan based on the changing trend of the residual value of the rental object in abnormal circumstances, thereby improving the rental service.

[0146] Optionally, in this embodiment, before generating a lease plan for a leased object, all historical residual values ​​of the leased object prior to a preset time interval are obtained, and a residual value change value for the leased object is determined based on a comparison of all these historical residual values ​​with the currently collected residual value of the object. A first preset threshold is preset as a critical value for determining whether the leased object is abnormal. If the residual value change value is greater than or equal to the first preset threshold, the residual value change of the leased object is determined to be abnormal. In this case, the upper and lower limits of the credit value interval corresponding to the residual value interval in the preset interval matching relationship need to be adjusted based on the residual value change trend of the leased object to accommodate the automatic generation of a lease plan in the event of abnormal residual value change.

[0147] S512: Based on the preset interval matching relationship, the residual value interval, and the credit value interval, a rental decision result is determined, indicating that the rental object can be rented to the user in need.

[0148] S514: Generate a rental plan for the rental object based on the rental decision result.

[0149] The specific implementation principles and processes of step S512 and step S514 are the same as those in the aforementioned embodiment, and reference may be made to the aforementioned embodiment, which will not be repeated here.

[0150] For example, in a scenario where the residual value of an object fluctuates normally, the preset third residual value range corresponds to a third credit value range. If the third residual value range is 50% to 100%, the corresponding third credit value range is a range where the credit value reaches 800 or above. In this scenario, if the residual value of the rental object is 55% and the user credit value of the requesting user is 820, the rental object is determined to be available for rental to the requesting user, and the rental transaction data for the rental object is determined based on the third credit value range.

[0151] In the scenario where the residual value of the object changes abnormally (the residual value change value is greater than or equal to the first preset threshold), the third residual value interval corresponds to the matching third credit value interval (the lower limit is 800). If the trend of the change in the residual value of the object is an abnormal decrease in the residual value, the lower limit of the third credit value interval is lowered (for example, adjusted to 700 or 750). At this time, if the user's credit value is above 700 or 750, the rental object can be rented. That is, when the residual value of the rental object drops abnormally, it means that the rental rate of the residual value of the rental object may drop. At this time, the lower limit of the third credit value interval can correspond to lowering the requirements for the user credit value of the user in need, compensating for the risk brought about by the abnormal decrease in the residual value of the object. And by determining the rental transaction data based on 700 or 750, the rental transaction data can also be adaptively adjusted to increase the rental rate and enhance the rental service. Conversely, if the trend in the object's residual value shows an abnormal increase, the lower limit of the third credit value interval will be adjusted upward (for example, to 850 or 900). In this case, the user's credit value is abnormally high at 850 or 900, and the rental object can be rented. In other words, when the residual value of a rental object increases abnormally, it indicates that the demand for the rental object exceeds the supply, and the probability of non-return of the rental object increases. In this case, the lower limit of the third credit value interval is adjusted upward to increase the demand for users with demand, reduce the rental risk of the rental object, and at the same time ensure the rental efficiency.

[0152] It can be understood that in some examples, by setting a first preset interval matching relationship corresponding to an abnormal increase in the residual value under abnormal circumstances, and a second preset interval matching relationship corresponding to an abnormal decrease in the residual value, the first preset interval matching relationship or the second preset interval matching relationship can be selected based on the residual value change trend under abnormal circumstances to determine the matching credit value interval of the residual value interval object, thereby achieving adjustment of the lower limit or upper limit of the credit value interval relative to normal circumstances.

[0153] Alternatively, in some examples, the adjustment size of the upper and lower limits of the credit value range can be set. In actual applications, based on the residual value change trend and the adjustment size, the upper and lower limits of the credit value range are adjusted accordingly, and then the rental decision result of whether the rental object can be rented to the user in need is determined based on the adjusted credit value range.

[0154] In this embodiment, the upper and lower limits of the credit value interval in the preset interval matching relationship are adaptively adjusted based on the residual value change, and then the rental decision result is determined and the rental plan is generated based on the residual value interval and the adjusted credit value interval, so as to dynamically adjust the rental plan according to the dynamic changes of the actual application scenario and improve the success rate of the rental decision.

[0155] Figure 6 This is a flow chart of a method for generating a rental plan provided in an embodiment of this specification. Figure 6 As shown, the execution subject is a rental plan generation system as an example for description. This embodiment is based on the above embodiment and refines the situation where the rental object can be rented to the user in need. Specifically, this embodiment includes S602 to S608:

[0156] S602, obtaining a residual value evaluation value corresponding to the residual value interval to which the object residual value belongs;

[0157] S604, obtaining a credit rating value corresponding to the credit value interval to which the user's credit value belongs;

[0158] In this embodiment, similar to the previous embodiment, the residual value of the object is divided into multiple residual value intervals from 0 to 100%, and the user's credit value is correspondingly divided into multiple credit value intervals. Each residual value interval is assigned at least one residual value evaluation value, which is used to reflect the risk-benefit balance of the residual value interval. Each credit value interval is assigned at least one credit evaluation value, which is used to reflect the risk-benefit balance of the credit value interval. In an optional embodiment, a correlation matrix is ​​set. After the residual value interval is quantified by the correlation matrix, a residual value evaluation value can be obtained. Correspondingly, after the credit value interval is quantified by the correlation matrix, a credit evaluation value can be obtained. The correlation matrix can be set based on testing or experimentation.

[0159] For example, the first residual value range corresponding to 0% to 30% is A1, the second residual value range corresponding to 30% to 50% is A2, and the third residual value range corresponding to 50% to 100% is A3, where A1 < A2 < A3. A higher residual value value indicates a higher rentability of the rental object.

[0160] For example, the credit evaluation value of the first credit value range corresponding to 650-750 is B1, the credit evaluation value of the second credit value range corresponding to 750-800 is B2, and the credit evaluation value of the third credit value range corresponding to 800 and above is B3, where B1<B2<B3, and the higher the credit evaluation value, the higher the rentability for the user in need.

[0161] S606, determining the rentability of the rental object based on the residual value evaluation value and the credit evaluation value;

[0162] In an optional implementation, the rentability of the rental object may be obtained based on a weighted average of the residual value evaluation value and the credit evaluation value.

[0163] For example, the weight of the residual value evaluation value is q1, the weight of the credit evaluation value is q2, and the sum of q1 and q2 is 1. If the residual value interval of the object residual value of the rental object belongs to the first residual value interval, then the residual value evaluation value is A3; if the credit value interval of the user credit value of the demanding user belongs to the second credit value interval, then the credit evaluation value is B2, then the rentability M = A3*q1+B2*q2.

[0164] In some examples, the weight q1 of the residual value evaluation value can be different based on different residual value ranges. For example, the larger the residual value range, the smaller the weight q1 of the residual value evaluation value, so that the rentability is more inclined to the user's credit value, to ensure that the higher the residual value of the rental object, the higher the user credit value requirement, to avoid the risk of not returning the rental.

[0165] S608: If the rentability is greater than or equal to the second preset threshold, obtain rental transaction data indicating that the rental object can be rented to the user in need.

[0166] The second preset threshold is a pre-set critical value used to indicate that the rental object is rentable. In this example, if the rentability is greater than or equal to the second preset threshold, it means that the risk of renting the rental object to the user is low, or the risk-benefit ratio is balanced. If the rentability is less than the second preset threshold, it means that there is a risk of renting the rental object to the user, or the risk-benefit ratio is unbalanced, and the rental object cannot be rented to the user.

[0167] Optionally, the rental transaction data is used to indicate the rent and lease term of the rental object.

[0168] In this embodiment, the object residual value and the user credit value are quantified into corresponding risks through a preset correlation matrix, so that the object residual value and the user credit value are combined to identify the rental risk of the rental object, thereby improving the accuracy and reliability of rental risk identification.

[0169] based on Figure 1 The following is a schematic diagram of the scene. Figure 7 , the rental service system provided by the embodiment of this application is introduced in detail. It should be noted that, Figure 7 The rental service system in this application is used to execute Figure 2-Figure 6 For the convenience of explanation, only the part related to the embodiment of the present application is shown. For the specific technical details not disclosed, please refer to the present application. Figure 2-Figure 6 Specifically, the rental service system 70 includes:

[0170] An acquiring unit 701 is configured to acquire a residual value of a rental object and a user credit value corresponding to a user who requires the rental object. The residual value of the object is used to indicate the remaining usage of the rental object.

[0171] A determining unit 703 is configured to determine a rental decision result indicating that the rental object can be rented to a user in need based on the residual value of the object and the user's credit value;

[0172] The processing unit 705 is configured to generate a rental plan for the rental object based on the rental decision result.

[0173] See Figure 8 , is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 8 As shown, the electronic device 80 includes a processor 801 and a memory 802. The processor 801 is electrically connected to the memory 802.

[0174] The processor 801 is the control center of the electronic device 80 and may include one or more processing cores. The processor 801 connects the various parts of the entire electronic device 500 using various interfaces and lines. By running or calling computer programs stored in the memory 802, and calling data stored in the memory 802, it executes various functions of the electronic device 80 and processes data, thereby controlling the electronic device 80 as a whole. Optionally, the processor 801 may be implemented in the form of at least one hardware of a digital signal processing (DSP), a field programmable gate array (FPGA), or a programmable logic array (PLA). The processor 801 may integrate one or a combination of a CPU, a graphics processing unit (GPU), and a modem. The CPU primarily processes the operating system, user pages, and applications; the GPU is responsible for rendering and drawing display content; and the modem is used to handle wireless communications. It is understandable that the modem may not be integrated into the processor 801 and may be implemented separately through a communication chip.

[0175] The memory 802 can be used to store software programs and modules. The processor 801 executes various functional applications and data processing by running the computer programs and modules stored in the memory 802. The memory 802 can mainly include a program storage area and a data storage area. The program storage area can store an operating system, computer programs required for at least one function, etc.; the data storage area can store data generated based on the use of the electronic device 80.

[0176] In addition, the memory 802 may include a high-speed random access memory and a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage device. Accordingly, the memory 802 may also include a memory controller to provide the processor 501 with access to the memory 802.

[0177] It should be understood that the electronic device provided in the embodiment of the present application is used to execute the above-mentioned rental plan generation method, and thus can achieve the same effect as the above-mentioned implementation method.

[0178] In addition, the electronic device provided in the embodiment of the present application can specifically be a chip, component or module, and the chip may include a connected processor and memory; wherein the memory is used to store instructions, and when the processor calls and executes the instructions, the chip can execute the method provided in the above embodiment.

[0179] An embodiment of the present application also provides a computer-readable storage medium, which stores computer program code. When the computer program code runs on a computer, the computer executes the above-mentioned related method steps to implement the method provided in the above embodiment.

[0180] This embodiment further provides a computer program product. When the computer program product is run on a computer, it enables the computer to execute the above-mentioned related steps to implement the method provided in the above embodiment.

[0181] Among them, the system, electronic device, computer-readable storage medium, computer program product or chip provided in this embodiment are all used to execute the corresponding methods provided above. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding methods provided above, and will not be repeated here.

[0182] The above description is based on specific embodiments of the present disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that described in the embodiments and still achieve the desired results.

[0183] Additionally, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results.In certain implementations, multitasking and parallel processing are also possible or may be advantageous.

[0184] The various embodiments in this specification are described in a progressive manner. Similar parts between the various embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences between the other embodiments. In particular, the system embodiments are generally similar to the method embodiments, so the description is relatively simple. For relevant parts, refer to the description of the method embodiments.

[0185] The above content is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A method for generating a rental plan, the method comprising: Obtaining the residual value of the rental object and the user credit value corresponding to the user who requires the rental object, wherein the residual value is used to indicate the remaining usage of the rental object; Determining a rental decision result that the rental object can be rented to the user in need based on the object residual value and the user credit value; A rental plan for the rental object is generated based on the rental decision result.

2. The method according to claim 1, before obtaining the residual value of the rental object and the user credit value corresponding to the user who requested the rental object, further comprising: If a request for a rental object from a user is detected, obtaining the residual value of the rental object and the user credit value corresponding to the user who requested the rental object; or, If it is monitored that the remaining rental time of the rental object is less than a preset time threshold, the object residual value of the rental object and the user credit value corresponding to the user who requires the rental object are obtained.

3. The method according to claim 1, wherein determining the rental decision result that the rental object can be rented to the user in need based on the residual value of the object and the user's credit value comprises: Obtaining the residual value interval to which the object residual value belongs, and obtaining the credit value interval to which the user credit value belongs; The rental decision result that the rental object can be rented to the user in need is determined based on the preset interval matching relationship, the residual value interval, and the credit value interval.

4. The method according to claim 3, wherein determining the rental decision result that the rental object can be rented to the user in need based on the preset interval matching relationship, the residual value interval, and the credit value interval comprises: Based on the preset interval matching relationship, determining a matching credit value interval corresponding to the residual value interval, and determining that the rental object can be rented to the user in need when the user credit value is greater than or equal to a lower limit of the matching credit value interval; Based on the residual value range and the credit value range, rental transaction data of the rental object is determined.

5. The method according to claim 3, wherein determining the rental decision result that the rental object can be rented to the user in need based on the preset interval matching relationship, the residual value interval, and the credit value interval comprises: Based on the preset interval matching relationship, determining a matching residual value interval corresponding to the credit value interval, and determining that the rental object can be rented to the demanding user when the object residual value is within the matching residual value interval; Based on the residual value range and the credit value range, rental transaction data of the rental object is determined.

6. The method according to claim 4 or 5, wherein determining the rental transaction data of the rental object based on the residual value range and the credit value range comprises: Determining a target rental transaction data table based on the residual value interval, wherein the target rental transaction data table is used to indicate a correspondence between each credit value sub-interval and rental transaction data; Determine a target credit value sub-interval to which the user credit value belongs within the credit value interval; The rental transaction data of the rental object corresponding to the target credit value sub-interval is determined based on the target rental transaction data table.

7. The method according to any one of claims 3 to 5, before determining the rental decision result that the rental object can be rented to the user based on the preset interval matching relationship, the residual value interval, and the credit value interval, further comprising: Obtaining the historical residual value of the leased object before a preset time interval; Determining a change in the residual value of the leased object based on the residual value of the object and the historical residual value; When the residual value change value is greater than or equal to a first preset threshold, the upper limit value and the lower limit value of the credit value interval in the preset interval matching relationship are adjusted according to the residual value change trend.

8. The method according to claim 1, wherein determining the rental decision result that the rental object can be rented to the user in need based on the residual value of the object and the user's credit value comprises: Obtaining a residual value evaluation value corresponding to the residual value interval to which the residual value of the object belongs; Obtaining a credit rating value corresponding to the credit value interval to which the user's credit value belongs; Determining the rentability of the rental object based on the residual value evaluation value and the credit evaluation value; If the rentability is greater than or equal to a second preset threshold, it is determined that the rental object can be rented to the user in need.

9. The method according to claim 1, wherein obtaining the residual value of the leased object comprises: Obtaining the usage time, maintenance records and current demand information of the rental object; and determining the wear rate of the rental object based on the usage time and the maintenance record; The object residual value of the rental object is obtained according to the wear rate and the current demand information.

10. A rental service system, comprising: An acquiring unit, configured to acquire a residual value of a rental object and a user credit value corresponding to a user who requires the rental object, wherein the residual value indicates the remaining usage of the rental object; A determining unit, configured to determine a rental decision result that the rental object can be rented to the user in need based on the residual value of the object and the user credit value; A processing unit is configured to generate a rental plan for the rental object based on the rental decision result.

11. An electronic device, comprising: a memory for storing executable program code; A processor is configured to call and run the executable program code from the memory, so that the electronic device executes the method according to any one of claims 1 to 9.

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