Commercial vehicle tenant credit auditing method and device, electronic equipment and medium

Abstract

The invention relates to the field of commercial vehicle leasing and the technical field of financial science and technology, and discloses a credit auditing method and device for a commercial vehicle lessee, electronic equipment and a medium, and the method comprises the steps: determining a target lessee and a lessee identifier of the target lessee in response to a commercial vehicle leasing request, and receiving lessee information uploaded by the target lessee; under the condition that historical vehicle operation data matched with the tenant identifier is extracted, analyzing the historical vehicle operation data based on currently stored total vehicle operation data of all tenants to obtain an operation analysis result; and adopting the operation analysis result and the tenant information to perform credit auditing on the target tenant to obtain a credit auditing result of the target tenant. The real credit status of the tenant and the risk level of the lease service are comprehensively reflected, and the flexibility is good.

Description

Technical Field

[0001] The present invention relates to the field of commercial vehicle leasing and financial technology, and in particular to a credit review method, device, electronic equipment and medium for a commercial vehicle lessee. Background Art

[0002] In the commercial vehicle leasing industry, commercial vehicles are widely used in the fields of cargo transportation as a means of transportation for profit. Such vehicles usually have the characteristics of high unit value and high selling price, which makes buyers tend to choose to apply for financial leasing services from financial institutions, especially leasing companies, to share the economic pressure when facing high purchase costs. In order to ensure the safety of funds and the sustainable development of leasing business, it has become an industry practice for leasing companies to conduct strict credit checks on lessees of commercial vehicles.

[0003] In the related art, when conducting a credit review on a lessee, it is necessary to calculate the lessee's income flow within a fixed time period, and combine the lessee's loan usage record and other information to assess the loan risk. However, the inventors realize that if the lessee falsifies the flow when submitting the review materials, it will directly lead to the distortion of the credit review results, bringing potential financial risks to the leasing company. In addition, the current credit review method is too dependent on data from the financial feature dimension, lacks an in-depth understanding and integration of the characteristics of the commercial vehicle leasing industry, and causes the credit evaluation conclusion to deviate from the actual situation, and cannot fully and accurately reflect the lessee's true credit status and the risk level of the leasing business, and has obvious limitations. Summary of the invention

[0004] The present invention provides a credit review method, device, electronic device and medium for commercial vehicle lessees, so as to solve the technical problem that the lack of in-depth understanding and integration of the characteristics of the commercial vehicle leasing industry may lead to the credit evaluation conclusion deviating from the actual situation, and failing to fully and accurately reflect the lessee's real credit status and the risk level of the leasing business, and has obvious limitations.

[0005] In a first aspect, a credit review method for a commercial vehicle lessee is provided, comprising:

[0006] In response to a commercial vehicle lease request, determining a target lessee and a lessee identifier of the target lessee, and receiving lessee information uploaded by the target lessee;

[0007] When the historical vehicle operation data matching the lessee identifier is extracted, the historical vehicle operation data is analyzed based on the currently stored total vehicle operation data of all lessees to obtain an operation analysis result;

[0008] The operation analysis result and the tenant information are used to conduct a credit check on the target tenant to obtain a credit check result of the target tenant.

[0009] In a second aspect, a credit review device for a commercial vehicle lessee is provided, comprising:

[0010] A determination module, configured to respond to a commercial vehicle lease request, determine a target lessee and a lessee identifier of the target lessee, and receive lessee information uploaded by the target lessee;

[0011] An analysis module, configured to analyze the historical vehicle operation data based on the currently stored total vehicle operation data of all lessees to obtain an operation analysis result when the historical vehicle operation data matching the lessee identification is extracted;

[0012] The audit module is used to use the operation analysis result and the tenant information to conduct a credit audit on the target tenant and obtain the credit audit result of the target tenant.

[0013] In a third aspect, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned commercial vehicle lessee credit review method when executing the computer program.

[0014] In a fourth aspect, a medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned commercial vehicle lessee credit review method are implemented.

[0015] In the scheme implemented by the above-mentioned commercial vehicle lessee credit review method, device, electronic device and medium, in response to the commercial vehicle lease request, the target lessee and the target lessee's lessee identification are determined, the lessee information uploaded by the target lessee is received, and when the historical vehicle operation data matching the lessee identification is extracted, the historical vehicle operation data is analyzed based on the total vehicle operation data of all currently stored lessees to obtain the operation analysis results, and the operation analysis results and the lessee information are used to conduct a credit review on the target lessee to obtain the credit review results of the target lessee, and the characteristics of the commercial vehicle leasing industry are deeply understood and integrated to form the operation analysis results, and then the operation analysis results and the lessee information are innovatively integrated to conduct a comprehensive credit review on the target lessee, which goes beyond the traditional single-dimensional credit review and more comprehensively reflects the lessee's actual ability and willingness to perform the contract, thereby more accurately predicting its future behavior in the car rental business, and comprehensively reflecting the lessee's actual credit status and the risk level of the leasing business, with good flexibility. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0017] Figure 1 is a schematic diagram of an application environment of a credit review method for a commercial vehicle lessee in one embodiment of the present invention;

[0018] Figure 2A is a flow chart of a credit review method for a commercial vehicle lessee in one embodiment of the present invention;

[0019] Figure 2B is a schematic diagram of the architecture of a vehicle rental system in one embodiment of the present invention;

[0020] Figure 3 is a schematic flow chart of a specific implementation of step S20;

[0021] Figure 4 It is a flowchart for calculating mileage data and driving time data;

[0022] Figure 5 is a schematic flow chart of a specific implementation of step S24;

[0023] Figure 6 is a schematic flow chart of a specific implementation of step S25;

[0024] Figure 7 is a schematic flow chart of a specific implementation of step S30;

[0025] Figure 8 is another flow chart of a credit review method for a commercial vehicle lessee according to an embodiment of the present invention;

[0026] Fig. 9 is a schematic diagram of a structure of a credit review device for a commercial vehicle lessee in one embodiment of the present invention;

[0027] Fig.10 is a schematic diagram of a structure of a computer device in one embodiment of the present invention;

[0028] Fig.11 It is another structural schematic diagram of a computer device in one embodiment of the present invention. DETAILED DESCRIPTION

[0029] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0030] The credit review of commercial vehicle lessees provided by the embodiment of the present invention is based on artificial intelligence intelligent question-answering processing method, which can be applied in Figure 1 In an application environment, the client communicates with the server through a network. The server can receive a commercial vehicle rental request through the client, determine the target lessee and the lessee identification of the target lessee in response to the commercial vehicle rental request, receive the lessee information uploaded by the target lessee, and analyze the historical vehicle operation data based on the total vehicle operation data of all currently stored lessees to obtain an operation analysis result when the historical vehicle operation data matching the lessee identification is extracted, and use the operation analysis result and the lessee information to conduct a credit review on the target lessee to obtain the credit review result of the target lessee. In the present invention, for the scenario of financial car leasing, combined with the total vehicle operation data of all current lessees, the historical operation behavior of the target lessee is deeply analyzed to obtain the operation analysis result, which not only mines the lessee's operation habits, vehicle maintenance status and other key information, but also reveals its relative credit level in the industry through horizontal comparison, effectively avoiding the risk of information asymmetry. Moreover, on this basis, the present invention also innovatively integrates the operational analysis results with the lessee information, conducts a comprehensive credit review of the target lessee, surpasses the traditional single-dimensional credit review, and more comprehensively reflects the lessee's true ability and willingness to perform the contract, so as to more accurately predict its future behavior in the car rental business. Therefore, the credit review results not only improve the scientificity and accuracy of decision-making, but also reduce the economic losses and credit risks caused by the lessee's default, and bring higher income stability and risk management capabilities to financial car rental institutions. In summary, the present invention not only improves the response speed and customer experience of car rental services through a data-driven credit review process, but also strengthens the risk prevention and control mechanism, ensuring the healthy and sustainable development of the financial car rental business. Among them, the client can be but not limited to various personal computers, laptops, smart phones, tablet computers and portable wearable devices. The server can be implemented with an independent server or a server cluster composed of multiple servers. The present invention is described in detail below through specific embodiments.

[0031] See also Figure 2A As shown, Figure 2AA flow chart of a credit review method for a commercial vehicle lessee provided by an embodiment of the present invention includes the following steps:

[0032] S10: In response to the commercial vehicle lease request, determine the target lessee and the lessee identifier of the target lessee, and receive the lessee information uploaded by the target lessee.

[0033] The credit review method for commercial vehicle lessees provided by the present invention can be applied to vehicle rental systems in various application scenarios. The vehicle rental system is usually implemented through a server, which can receive commercial vehicle rental requests in real time. Figure 2B As shown, the vehicle leasing system includes a rental account subsystem, a commercial vehicle operation analysis subsystem, and a commercial vehicle lessee credit review subsystem: the rental account subsystem maintains the historical rental information of the leasing company's commercial vehicles in the form of data records. Each data record contains fields such as the lessee ID, lessee name, and frame number. The data example is shown in Table 1 below:

[0034] Table 1

[0035] Tenant ID Tenant Name Frame number … 4418821990****339X Zhang San FLV1234 … 91321012MA1XXRM96J XX Company FLV5678 …

[0036] Among them, in Table 1, when the lessee is a natural person, the lessee ID is generally the ID number, and when the lessee is an enterprise, the lessee ID is generally the enterprise's unified credit code.

[0037] The commercial vehicle operation analysis subsystem is used to calculate the vehicle's mileage, driving time, average monthly mileage, average monthly driving time and other operating data as historical vehicle operation data based on the positioning information reported by the GPS device installed on the vehicle. The data example is shown in Table 2 below:

[0038] Table 2

[0039]

[0040] It should be noted that, based on the data in Table 2, the commercial vehicle operation analysis subsystem can also perform further processing and analysis to obtain the vehicle operation analysis results.

[0041] The commercial vehicle lessee credit review subsystem is used to comprehensively evaluate and ultimately determine whether the lessee meets the company's initial lease risk control requirements based on the operational analysis results of the lessee's historical vehicle operation data (if any) and other credit review factors.

[0042] The above content is a detailed description of the vehicle rental system, and each subsystem performs its own functions to complete the technical solution of the present invention. For the sake of convenience, the following description is based on the vehicle rental system as the execution subject.

[0043] A commercial vehicle rental request refers to a formal application submitted by a potential lessee (such as an enterprise or an individual) through the vehicle rental system interface or application, hoping to rent a commercial vehicle to meet its transportation needs. The commercial vehicle rental request usually contains key information such as the type, quantity, and rental period of the rental vehicle. In response to the commercial vehicle rental request, the vehicle rental system will identify and lock the specific lessee according to the information in the rental request, that is, the individual or enterprise that proposes the rental demand, to ensure that the subsequent process can be carried out for the correct lessee. The lessee identification is a unique identification code or information used to uniquely identify the target lessee in the vehicle rental system. It can be the lessee's ID number, enterprise registration number, or the exclusive ID assigned by the system to each lessee. The lessee identification ensures the accuracy and traceability of the lessee information. The present invention does not limit the specific content of the lessee identification. The lessee information refers to the detailed information of the individual or enterprise that the vehicle rental system allows the lessee to submit by uploading files, filling out forms, etc., including but not limited to identity proof, business license, financial status proof, etc. The lessee information is an important basis for subsequent credit review and risk assessment.

[0044] In this way, by automatically identifying and receiving lessee information, the vehicle leasing system can quickly respond to commercial vehicle leasing requests, reduce manual intervention, improve processing efficiency, and provide comprehensive and accurate data support for subsequent credit reviews and risk assessments, helping leasing companies make more informed decisions and reduce potential risks and losses.

[0045] For example, in the field of financial car leasing, a lessee who needs to rent a car can submit a commercial vehicle rental request through the client of the vehicle leasing system and specify the required model, lease term and other detailed information. The vehicle leasing system will immediately respond to this request and start the credit review process. The vehicle leasing system will first identify the logistics company as the target lessee and obtain its lessee identification (such as company registration number, unified social credit code, etc.). Subsequently, the vehicle leasing system will require the logistics company to upload the lessee information, including but not limited to company qualification certificate, legal representative identity certificate, past business conditions, etc., so as to conduct a subsequent credit review of the logistics company.

[0046] S20: When the historical vehicle operation data matching the lessee identification is extracted, the historical vehicle operation data is analyzed based on the currently stored total vehicle operation data of all lessees to obtain an operation analysis result.

[0047] Among them, historical vehicle operation data covers multi-dimensional information such as the target lessee's past mileage, maintenance records, accident conditions, and violation records when renting vehicles. It is an important basis for evaluating their operating habits and sense of responsibility. The historical vehicle operation data can be obtained based on the positioning information uploaded by the GPS device installed on the vehicle. When the historical vehicle operation data matching the lessee's ID is extracted, the vehicle rental system will analyze the historical vehicle operation data based on the total vehicle operation data of all the lessees currently stored to obtain the operation analysis results. The total vehicle operation data of all lessees actually constitutes a huge database, which records the vehicle use behavior of all lessees and provides a benchmark for comparative analysis. Through analysis, the vehicle rental system can dig out the target lessee's operating characteristics, potential risk points, and performance level compared with other lessees to form an operation analysis result. The operation analysis result reveals the historical behavior pattern of the target lessee and provides data support for predicting its future behavior. Compared with traditional experience judgment or simple inquiry, it can more accurately reflect the target lessee's real operation ability and credit status, which helps to reduce the risks caused by information asymmetry.

[0048] For example, a logistics company applies to lease a commercial vehicle. The vehicle leasing system extracts the vehicle operation data of the past year through the lessee's ID, and analyzes the vehicle operation data to determine the company's vehicles' average mileage, total mileage, average driving time, total driving time and other data, and determines whether these data are better or worse than other lessees in the industry, thereby forming an operational analysis result, so that the subsequent leasing company can formulate a more personalized leasing plan for the lessee based on the operational analysis results, which not only meets customer needs but also effectively controls risks.

[0049] Among them, Figure 3 As shown, in step S20, that is, based on the total vehicle operation data of all lessees currently stored, the historical vehicle operation data is analyzed to obtain the operation analysis results, including the following steps S21 to S26:

[0050] S21: Determine a plurality of designated lessees from among all lessees based on historical vehicle operation data.

[0051] Among them, multiple designated lessees are lessees who are in the same industry and / or rent the same vehicle model and / or are in the same region as the target lessee. When determining multiple designated lessees, the vehicle rental system will extract the lessee's basic information and vehicle use records from the historical vehicle operation database, including but not limited to the lessee's industry classification, the rented vehicle model, and the lessee's geographical location. Then, through the matching algorithm, based on the historical vehicle operation data of the target lessee, the lessee with the same or similar characteristics (such as the same industry, renting the same vehicle model, and being in the same region) as the target lessee is selected as the designated lessee. Historical vehicle operation data refers to the record of the target lessee's use of the vehicle in the past period of time, including mileage, duration, location and other information. In fact, not only the target lessee, but each lessee has corresponding historical vehicle operation data. Designated lessees refer to a group of lessees with similar characteristics as the target lessee selected according to specific conditions. By comparing with lessees with similar characteristics, the operation of the target lessee can be more accurately evaluated.

[0052] For example, if the target lessee is a logistics company and requests to rent a truck, the designated lessees may be other lessees that are also engaged in the logistics industry, who also rent trucks or similar vehicles and are located in a similar geographical area; or, if the target lessee is a courier company that rents a batch of electric tricycles for urban delivery, other lessees that are also engaged in courier business, who also rent electric tricycles and are located in the same city or surrounding cities may be found in the database, and these lessees are identified as designated lessees.

[0053] S22: Calculate the target mileage data and target driving duration data of the target lessee based on the historical vehicle operation data.

[0054] In order to analyze the operating status of the target lessee, the vehicle rental system will extract the driving records of all vehicles of the target lessee from the historical vehicle operation data, and calculate the mileage and driving time of all vehicles to obtain the target mileage data and target driving time data. The target mileage data refers to the data related to the cumulative mileage of all vehicles of the target lessee within a period of time, which may include total mileage, average mileage, etc.; the target driving time data refers to the data related to the cumulative driving time of these vehicles within the same period of time, which may include total time, average time, etc.

[0055] By calculating the target mileage data and target driving time data of the target lessee, a benchmark data is provided for subsequent comparative analysis, which intuitively reflects the target lessee's operating efficiency and vehicle usage. Among them, for the target lessee and each of the multiple designated lessees, the mileage data and driving time data need to be calculated. The following takes a certain lessee as an example to explain the specific process of calculating the mileage data and driving time data. Figure 4 As shown, it includes the following steps S221 to S223:

[0056] S221: For the target lessee and each of the multiple designated lessees, the total mileage and total duration are counted according to the historical vehicle operation data corresponding to the lessee.

[0057] The vehicle rental system will first traverse the lessee's historical vehicle operation data. Historical vehicle operation data refers to the driving records of all vehicles of the lessee in the past period of time, including the mileage and duration of each trip, and specifically includes each driving record of each vehicle, such as the start time, end time, mileage, etc. The vehicle rental system will accumulate these records to obtain the total mileage and total duration of all vehicles of the lessee during the statistical period. The total mileage refers to the total distance traveled by all vehicles during the statistical period, and the total duration refers to the total time all vehicles travel. In this way, by counting the total mileage and total duration, the vehicle rental system can obtain the overall situation of the lessee's vehicle use and provide basic data for subsequent analysis.

[0058] For example, a lessee operates 10 vehicles in a month, and each vehicle has a driving record every day. The vehicle rental system will calculate the total mileage and total time of these 10 vehicles in a month based on these records, such as the total mileage is 100,000 kilometers and the total time is 3,000 hours.

[0059] S222: Determine a preset time dimension, and calculate the average value of the total mileage and the total duration according to the preset time dimension to obtain the average mileage and the average duration under the preset time dimension.

[0060] The vehicle rental system will calculate the average value of the total mileage and total duration obtained in step S221 according to a preset time dimension (such as day, week, month, etc.). Specifically, the total mileage and total duration can be divided by the corresponding number of time units (such as days, weeks, months, etc.) to obtain the average mileage and average driving duration in each time unit, thereby ensuring the comparability of the data and enabling effective comparative analysis of data in different time periods.

[0061] The preset time dimension refers to the time unit used by the vehicle rental system when performing data analysis, such as day, week, month, etc. Average mileage refers to the average driving distance of each vehicle under the preset time dimension; average duration refers to the average driving time of each vehicle under the preset time dimension. By calculating the average mileage and average duration, the vehicle rental system can more accurately evaluate the operating efficiency of the lessee in different time periods, which helps to discover fluctuations and trends in the lessee's operations.

[0062] For example, assuming that the preset time dimension is month, the vehicle rental system will calculate the monthly average mileage and monthly average driving time of each vehicle of the target lessee based on the total mileage and total driving time obtained in step S221, such as the monthly average mileage is 10,000 kilometers / month and the monthly average driving time is 300 hours / month.

[0063] S223: The total mileage and the average mileage are used as the driving mileage data of the lessee, and the total duration and the average duration are used as the driving duration data of the lessee.

[0064] The vehicle rental system will organize the total mileage, average mileage, total duration and average duration obtained in step S221 and step S222 to form the lessee's mileage data and driving duration data. These data will serve as the basis for subsequent analysis and comparison to evaluate the lessee's operating efficiency, vehicle utilization efficiency, etc.

[0065] S23: Calculating designated driving mileage data and designated driving duration data of each designated lessee based on the historical vehicle operation data corresponding to each designated lessee in the total vehicle operation data.

[0066] The vehicle rental system will perform calculations for each designated lessee, summarize all vehicle driving records of each designated lessee, and obtain the designated driving mileage data and designated driving duration data of each designated lessee. Specifically, the calculation of the designated driving mileage data and the designated driving duration data is consistent with the calculation process of the driving mileage data and the driving duration data described in the above steps S221 to S223, and will not be repeated here.

[0067] S24: Compare the target mileage data with the designated mileage data of multiple designated lessees to obtain mileage ranking data.

[0068] The vehicle leasing system will compare the target lessee's target mileage data with the designated mileage data of each designated lessee, sort them by value, and obtain the target lessee's mileage ranking data among all designated lessees, thereby intuitively reflecting the target lessee's operating efficiency level in the industry and facilitating subsequent accurate credit review of the target lessee. Specifically, Figure 5As shown, in step S24, the target mileage data is compared with the designated mileage data of multiple designated lessees to obtain mileage ranking data, including the following steps S241 to S242:

[0069] S241: Compare the target total mileage in the target mileage data with the specified total mileage in the specified mileage data of each specified lessee to obtain a total mileage comparison result, and compare the target average mileage in the target mileage data with the specified average mileage in the specified mileage data of each specified lessee to obtain an average mileage comparison result.

[0070] The vehicle rental system first compares the target total mileage in the target mileage data with the designated total mileage in the designated mileage data of multiple designated lessees one by one, and through comparison, understands the level of the target lessee's total mileage relative to other lessees. At the same time, the vehicle rental system also compares the target average mileage in the target mileage data with the designated average mileage of each designated lessee to obtain the average mileage comparison result, so as to fully and accurately grasp the mileage of the target lessee and provide basic data for subsequent analysis.

[0071] S242: Count the first proportion threshold to which the target lessee's ranking in the total mileage comparison result belongs, and count the second proportion threshold to which the target lessee's ranking in the average mileage comparison result belongs, and use the first proportion threshold and the second proportion threshold as the target lessee's mileage ranking data.

[0072] The vehicle rental system will count the target lessee's position in the two rankings based on the total mileage comparison results and the average mileage comparison results obtained in step S241, and determine the first ratio threshold and the second ratio threshold to which it belongs respectively. The first ratio threshold refers to the percentage position of the target lessee in the total mileage ranking (e.g., the top 20% means that the target lessee's total mileage is higher than 80% of the lessees), and the second ratio threshold refers to its percentage position in the average mileage ranking. These two ratio thresholds together constitute the target lessee's mileage ranking data.

[0073] Through the above process, the vehicle leasing system converts complex mileage data into intuitive ranking information, which makes it easier for leasing companies to quickly understand the mileage of target lessees and provide a basis for subsequent credit review. For example, if A's total mileage ranks in the top 20% and the average mileage ranks in the top 50%, then A's first ratio threshold is 20% and the second ratio threshold is 50%.

[0074] S25: Compare the target driving time data with the designated driving time data of multiple designated lessees to obtain driving time ranking data.

[0075] Similar to the above step S24, the vehicle rental system will continue to compare the target driving time data with the designated driving time data of multiple designated lessees to obtain driving time ranking data. Figure 6 As shown, step S25, that is, comparing the target driving time data with the designated driving time data of multiple designated lessees to obtain driving time ranking data, includes the following steps S251 to S252:

[0076] S251: Compare the target total duration in the target driving duration data with the specified total duration in the specified driving duration data of each specified lessee to obtain a total duration comparison result, and compare the target average duration in the target driving mileage data with the specified average duration in the specified driving mileage data of each specified lessee to obtain an average duration comparison result.

[0077] S252: Count the third proportion threshold to which the target lessee's ranking in the total duration comparison result belongs, and count the fourth proportion threshold to which the target lessee's ranking in the average duration comparison result belongs, and use the third proportion threshold and the fourth proportion threshold as the target lessee's driving duration ranking data.

[0078] Among them, the implementation process of step S251 to step S252 is similar to the implementation process of the above-mentioned step S241 to step S242, except that step S251 to step S252 is a ranking operation performed on the driving time data, which converts the complex driving time data into intuitive ranking information, so that the leasing company can quickly understand the driving time of the target lessee, and the specific implementation process will not be repeated here.

[0079] S26: The target mileage data, the target driving time data, the mileage ranking data, and the driving time ranking data are used as operation analysis results.

[0080] The vehicle rental system will integrate all the data obtained from the above calculations and analyses to form an operational analysis result, which includes the target lessee's basic operational data (mileage and duration) and relative position in the industry (ranking data), thereby ensuring that the leasing company can accurately understand the target lessee's operational status and assist in the credit review process and methods.

[0081] S30: Using the operation analysis results and the lessee information, a credit review is performed on the target lessee to obtain a credit review result of the target lessee.

[0082] Among them, the vehicle leasing system will use the operational analysis results and lessee information to conduct a credit assessment on the target lessee through preset audit rules, combining data-driven analysis methods and established business logic to achieve a comprehensive and accurate evaluation of the lessee's credit status. The operational analysis results are the analysis results obtained in the above process based on vehicle operation data (such as driving time, mileage, etc.) and operating conditions (such as comparisons of the same industry, the same model, and the same region). These results reflect the performance of the target lessee in actual operations.

[0083] Tenant information refers to the relevant data used to assess the credit status of the tenant. For natural person tenants, this information usually includes their personal identity information (such as name, gender, age, ID number, contact information, etc.), occupational information (such as work unit, position, income status, etc.), financial information (such as bank flow, asset proof, debt status, etc.) and other personal background information that may affect their credit evaluation. For corporate tenants, tenant information covers the company's basic information (such as company name, registered address, legal representative, unified social credit code, business scope, etc.), business information (such as annual operating income, profit status, industry status, etc.), financial information (such as company bank account flow, balance sheet, income statement and other financial statements) and the company's credit record (such as historical defaults, court judgment records, etc.). This information together forms the basis for the tenant's credit review and is used to comprehensively and accurately assess the tenant's credit status and performance ability.

[0084] In this way, by comprehensively considering operational data and lessee information, it is possible to more comprehensively assess the credit status of target lessees, improve the accuracy and reliability of credit review, help identify potential high-risk lessees, and reduce the operational risks of leasing companies. Figure 7 The step S30, i.e., using the operation analysis result and the lessee information to conduct a credit review on the target lessee to obtain the credit review result of the target lessee, includes the following steps S31 to S32:

[0085] S31: Acquire multiple preset audit rules, and extract a target preset audit rule that matches the operation analysis result from the multiple preset audit rules.

[0086] The vehicle rental system will extract the target preset audit rules that match the operational analysis results from multiple preset audit rules. Multiple preset audit rules are formulated based on historical data and business experience to guide the specific operations of credit audit, including pre-set credit audit standards and conditions. Through matching operations, it can ensure that the credit audit process follows the established business logic and audit standards, improve the consistency and standardization of the audit, and help quickly locate the audit rules applicable to specific lessees and improve audit efficiency.

[0087] In the actual application process, feasible preset audit rules combined with vehicle operation data and operation analysis results are exemplified as follows:

[0088] 1. For operating data, the bank statement requirements for lessees with an average monthly driving time of more than 240 hours can be lowered, while for those with an average monthly driving time of less than 40 hours, the bank statement requirements will be increased;

[0089] 2. Regarding operating conditions, for lessees in the same industry, with the same vehicle model and in the same region, whose monthly average mileage ranks in the top 80% or above, or whose monthly average driving time ranks in the top 70% or above, the requirements for their bank statements can be lowered. For lessees whose mileage ranks in the bottom 20% or whose driving time ranks in the bottom 30%, the requirements for their bank statements will be raised.

[0090] In short, for tenants with good operating data and operating conditions, the credit rating will be appropriately increased or the thresholds of other credit review factors will be lowered. Conversely, the credit rating will be appropriately lowered, the thresholds of other credit review factors will be increased, and the leasing risks will be assessed more prudently.

[0091] S32: According to the preset audit rules of the target, the lessee information is audited to obtain the credit audit result.

[0092] The vehicle leasing system will review the target lessee's information one by one according to the extracted target preset review rules to determine their credit status and whether they meet the credit requirements. In this way, through a strict review process, it can ensure that the lessee's credit status is accurately assessed, providing a reliable basis for the leasing company's decision-making, helping to improve the leasing company's risk control capabilities and reduce losses caused by lessee default.

[0093] For example, if the operational analysis results of lessee A meet the conditions of "average monthly driving time exceeding 240 hours" and "average monthly mileage in the top 80% of the same industry, same model, and same region", then the preset audit rule that matches it may be "lower bank flow requirements"; further, if lessee A's bank flow and other financial information still meet the credit standards of the leasing company after the requirements are lowered, then the credit audit result may be "passed", indicating that A has a good credit status and can lease the vehicle. Conversely, if A's financial information still does not meet the requirements after the requirements are lowered, then the credit audit result may be "failed", indicating that A's credit status is not good and it is necessary to more carefully assess its rental risk.

[0094] In the actual application process, for the first-time lessee, since the historical vehicle operation data has not been accumulated, the vehicle rental system cannot extract the historical vehicle operation data that matches the lessee's ID. In the case that the historical vehicle operation data that matches the lessee's ID is not extracted, the vehicle rental system will automatically obtain the default review rules, review the lessee's information according to the default review rules, and use the obtained results as the credit review results of the target lessee. The default review rules are formulated based on the general standards of the leasing industry and the risk management experience of the leasing company, covering multiple dimensions such as the lessee's personal identity information, financial information, and professional background. The vehicle rental system will review the information submitted by the target lessee one by one according to these rules, and the final review results will be used as the credit review results of the target lessee, ensuring that even in the absence of historical vehicle operation data, the credit status of the target lessee can be relatively accurately and comprehensively evaluated, providing a decision-making basis for the leasing company, while reducing the credit review risk caused by missing information.

[0095] In summary, the logical process of the technical solution of the present invention is summarized as follows: Figure 8 In response to the commercial vehicle rental request, the vehicle rental system determines the target lessee and the lessee identifier of the target lessee. The vehicle rental system inquires whether the target lessee has historical vehicle operation data. If so, the historical vehicle operation data is obtained, the historical vehicle operation data is analyzed, and the operation analysis results are input into the commercial vehicle lessee credit review subsystem in the vehicle rental system, so that the commercial vehicle lessee credit review subsystem combines the operation analysis results with the lessee information of the target lessee to conduct a credit review and output the credit review result; if not, the commercial vehicle lessee credit review subsystem only uses the lessee information to conduct a credit review and outputs the credit review result.

[0096] It can be seen that in the above scheme, in response to the commercial vehicle lease request, the target lessee and the lessee identification of the target lessee are determined, the lessee information uploaded by the target lessee is received, and when the historical vehicle operation data matching the lessee identification is extracted, the historical vehicle operation data is analyzed based on the total vehicle operation data of all currently stored lessees to obtain the operation analysis results, and the operation analysis results and the lessee information are used to conduct a credit review on the target lessee to obtain the credit review results of the target lessee, and the characteristics of the commercial vehicle leasing industry are deeply understood and integrated to form the operation analysis results, and then the operation analysis results and the lessee information are innovatively integrated to conduct a comprehensive credit review on the target lessee, which goes beyond the traditional single-dimensional credit review and more comprehensively reflects the lessee's actual ability and willingness to perform the contract, thereby more accurately predicting its future behavior in the car rental business, and comprehensively reflecting the lessee's actual credit status and the risk level of the leasing business, with good flexibility.

[0097] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0098] In one embodiment, a credit review device for a commercial vehicle lessee is provided, and the credit review device for a commercial vehicle lessee corresponds one-to-one to the credit review method for a commercial vehicle lessee in the above embodiment. Fig. 9 As shown, the credit review device for commercial vehicle lessees includes a determination module 101, an analysis module 102, and a review module 103. The detailed description of each functional module is as follows:

[0099] The determination module 101 is used to determine the target lessee and the lessee identifier of the target lessee in response to the commercial vehicle lease request, and receive the lessee information uploaded by the target lessee;

[0100] The analysis module 102 is used to analyze the historical vehicle operation data based on the currently stored total vehicle operation data of all lessees to obtain an operation analysis result when the historical vehicle operation data matching the lessee identification is extracted;

[0101] The review module 103 is used to use the operation analysis result and the tenant information to conduct a credit review on the target tenant and obtain a credit review result of the target tenant.

[0102] In one embodiment, the analysis module 102 is specifically configured to:

[0103] Determine a plurality of designated lessees from among all the lessees according to the historical vehicle operation data, wherein the plurality of designated lessees are lessees in the same industry and / or leasing the same vehicle model and / or in the same region as the target lessee;

[0104] Calculating target mileage data and target driving duration data of the target lessee based on the historical vehicle operation data;

[0105] Calculating the designated driving mileage data and designated driving duration data of each designated lessee based on the historical vehicle operation data corresponding to each designated lessee in the total vehicle operation data;

[0106] Comparing the target mileage data with the designated mileage data of the plurality of designated lessees to obtain mileage ranking data;

[0107] Comparing the target driving time data with the designated driving time data of the plurality of designated lessees to obtain driving time ranking data;

[0108] The target driving mileage data, the target driving duration data, the driving mileage ranking data, and the driving duration ranking data are used as the operation analysis result.

[0109] In one embodiment, the analysis module 102 is specifically configured to:

[0110] For each of the target lessee and the plurality of designated lessees, the total mileage and total duration are counted according to the historical vehicle operation data corresponding to the lessee;

[0111] Determine a preset time dimension, and calculate the average value of the total mileage and the total duration according to the preset time dimension to obtain the average mileage and the average duration under the preset time dimension;

[0112] The total mileage and the average mileage are used as the driving mileage data of the lessee, and the total duration and the average duration are used as the driving duration data of the lessee.

[0113] In one embodiment, the analysis module 102 is specifically configured to:

[0114] Comparing the target total mileage in the target mileage data with the designated total mileage in the designated mileage data of each designated lessee to obtain a total mileage comparison result, and comparing the target average mileage in the target mileage data with the designated average mileage in the designated mileage data of each designated lessee to obtain an average mileage comparison result;

[0115] A first proportion threshold to which the target lessee's ranking in the total mileage comparison result belongs is counted, and a second proportion threshold to which the target lessee's ranking in the average mileage comparison result belongs is counted, and the first proportion threshold and the second proportion threshold are used as the mileage ranking data of the target lessee.

[0116] In one embodiment, the analysis module 102 is specifically configured to:

[0117] Comparing the target total duration in the target driving duration data with the designated total duration in the designated driving duration data of each designated lessee to obtain a total duration comparison result, and comparing the target average duration in the target driving mileage data with the designated average duration in the designated driving mileage data of each designated lessee to obtain an average duration comparison result;

[0118] The third proportion threshold to which the target lessee's ranking in the total duration comparison result belongs is counted, and the fourth proportion threshold to which the target lessee's ranking in the average duration comparison result belongs is counted, and the third proportion threshold and the fourth proportion threshold are used as the driving duration ranking data of the target lessee.

[0119] In one embodiment, the audit module 103 is specifically configured to:

[0120] Acquire multiple preset audit rules, and extract a target preset audit rule matching the operation analysis result from the multiple preset audit rules;

[0121] According to the preset audit rules of the target, the lessee information is audited to obtain the credit audit result.

[0122] In one embodiment, the audit module 103 is further configured to:

[0123] If no historical vehicle operation data matching the lessee identifier is extracted, obtaining a default audit rule;

[0124] According to the default audit rules, the lessee information is audited, and the obtained result is used as the credit audit result of the target lessee.

[0125] The present invention provides a credit review device for a lessee of a commercial vehicle. In response to a request for starting a lease of a commercial vehicle, a target lessee and a lessee identification of the target lessee are determined, lessee information uploaded by the target lessee is received, and when historical vehicle operation data matching the lessee identification is extracted, the historical vehicle operation data is analyzed based on the total vehicle operation data of all currently stored lessees to obtain an operation analysis result, and a credit review is conducted on the target lessee using the operation analysis result and the lessee information to obtain a credit review result of the target lessee, and an in-depth understanding and integration of the characteristics of the commercial vehicle leasing industry is performed to form an operation analysis result, and then the operation analysis result is innovatively integrated with the lessee information to conduct a comprehensive credit review on the target lessee, which goes beyond the traditional single-dimensional credit review and more comprehensively reflects the lessee's actual ability and willingness to perform the contract, thereby more accurately predicting its future behavior in the car rental business, and comprehensively reflecting the lessee's actual credit status and the risk level of the leasing business, with good flexibility.

[0126] For the specific definition of the credit review device for commercial vehicle lessees, please refer to the definition of the credit review method for commercial vehicle lessees mentioned above, which will not be repeated here. Each module in the above-mentioned credit review device for commercial vehicle lessees can be implemented in whole or in part through software, hardware and their combination. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0127] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Fig.10 As shown. The computer device includes a processor, a memory, a network interface and a database connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile and / or volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external client via a network connection. When the computer program is executed by the processor, it implements the functions or steps on the service side of a credit review method for commercial vehicle lessees.

[0128] In one embodiment, a computer device is provided. The computer device may be a client, and its internal structure diagram may be as follows: Fig.11 As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external server via a network connection. When the computer program is executed by the processor, it implements the functions or steps on the client side of a credit review method for commercial vehicle lessees

[0129] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program:

[0130] In response to a commercial vehicle lease request, determining a target lessee and a lessee identifier of the target lessee, and receiving lessee information uploaded by the target lessee;

[0131] When the historical vehicle operation data matching the lessee identifier is extracted, the historical vehicle operation data is analyzed based on the currently stored total vehicle operation data of all lessees to obtain an operation analysis result;

[0132] The operation analysis result and the tenant information are used to conduct a credit check on the target tenant to obtain a credit check result of the target tenant.

[0133] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0134] In response to a commercial vehicle lease request, determining a target lessee and a lessee identifier of the target lessee, and receiving lessee information uploaded by the target lessee;

[0135] When the historical vehicle operation data matching the lessee identifier is extracted, the historical vehicle operation data is analyzed based on the currently stored total vehicle operation data of all lessees to obtain an operation analysis result;

[0136] The operation analysis result and the tenant information are used to conduct a credit check on the target tenant to obtain a credit check result of the target tenant.

[0137] It should be noted that the above functions or steps that can be implemented by the computer-readable storage medium or computer device can refer to the relevant descriptions on the server side and the client side in the aforementioned method embodiment. To avoid repetition, they will not be described one by one here.

[0138] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0139] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0140] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A credit review method for a commercial vehicle lessee, characterized in that: include: In response to a commercial vehicle lease request, determining a target lessee and a lessee identifier of the target lessee, and receiving lessee information uploaded by the target lessee; When the historical vehicle operation data matching the lessee identifier is extracted, the historical vehicle operation data is analyzed based on the currently stored total vehicle operation data of all lessees to obtain an operation analysis result; The operation analysis result and the tenant information are used to conduct a credit check on the target tenant to obtain a credit check result of the target tenant.

2. The method according to claim 1, characterized in that The historical vehicle operation data is analyzed based on the currently stored total vehicle operation data of all lessees to obtain the operation analysis results, including: Determine a plurality of designated lessees from among all the lessees according to the historical vehicle operation data, wherein the plurality of designated lessees are lessees in the same industry and / or leasing the same vehicle model and / or in the same region as the target lessee; Calculating target mileage data and target driving duration data of the target lessee based on the historical vehicle operation data; Calculating the designated driving mileage data and designated driving duration data of each designated lessee based on the historical vehicle operation data corresponding to each designated lessee in the total vehicle operation data; Comparing the target mileage data with the designated mileage data of the plurality of designated lessees to obtain mileage ranking data; Comparing the target driving time data with the designated driving time data of the plurality of designated lessees to obtain driving time ranking data; The target driving mileage data, the target driving duration data, the driving mileage ranking data, and the driving duration ranking data are used as the operation analysis result.

3. The method according to claim 2, characterized in that When calculating the lessee's driving mileage data and driving duration data, the method includes: For each of the target lessee and the plurality of designated lessees, the total mileage and total duration are counted according to the historical vehicle operation data corresponding to the lessee; Determine a preset time dimension, and calculate the average value of the total mileage and the total duration according to the preset time dimension to obtain the average mileage and the average duration under the preset time dimension; The total mileage and the average mileage are used as the driving mileage data of the lessee, and the total duration and the average duration are used as the driving duration data of the lessee.

4. The method according to claim 3, characterized in that: The step of comparing the target mileage data with the designated mileage data of the plurality of designated lessees to obtain mileage ranking data includes: Comparing the target total mileage in the target mileage data with the designated total mileage in the designated mileage data of each designated lessee to obtain a total mileage comparison result, and comparing the target average mileage in the target mileage data with the designated average mileage in the designated mileage data of each designated lessee to obtain an average mileage comparison result; A first proportion threshold to which the target lessee's ranking in the total mileage comparison result belongs is counted, and a second proportion threshold to which the target lessee's ranking in the average mileage comparison result belongs is counted, and the first proportion threshold and the second proportion threshold are used as the mileage ranking data of the target lessee.

5. The method according to claim 3, characterized in that: The step of comparing the target driving time data with the designated driving time data of the plurality of designated lessees to obtain driving time ranking data includes: Comparing the target total duration in the target driving duration data with the designated total duration in the designated driving duration data of each designated lessee to obtain a total duration comparison result, and comparing the target average duration in the target driving mileage data with the designated average duration in the designated driving mileage data of each designated lessee to obtain an average duration comparison result; The third proportion threshold to which the target lessee's ranking in the total duration comparison result belongs is counted, and the fourth proportion threshold to which the target lessee's ranking in the average duration comparison result belongs is counted, and the third proportion threshold and the fourth proportion threshold are used as the driving duration ranking data of the target lessee.

6. The method according to claim 1, characterized in that The step of using the operation analysis result and the tenant information to conduct a credit review on the target tenant to obtain a credit review result of the target tenant includes: Acquire multiple preset audit rules, and extract a target preset audit rule matching the operation analysis result from the multiple preset audit rules; According to the preset audit rules of the target, the lessee information is audited to obtain the credit audit result.

7. The method according to claim 1, characterized in that The method further comprises: If no historical vehicle operation data matching the lessee identifier is extracted, obtaining a default audit rule; According to the default audit rules, the lessee information is audited, and the obtained result is used as the credit audit result of the target lessee.

8. A credit review device for commercial vehicle lessees, characterized in that: include: A determination module, configured to respond to a commercial vehicle lease request, determine a target lessee and a lessee identifier of the target lessee, and receive lessee information uploaded by the target lessee; An analysis module, configured to analyze the historical vehicle operation data based on the currently stored total vehicle operation data of all lessees to obtain an operation analysis result when the historical vehicle operation data matching the lessee identification is extracted; The audit module is used to use the operation analysis result and the tenant information to conduct a credit audit on the target tenant and obtain the credit audit result of the target tenant.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the credit review method for a commercial vehicle lessee as claimed in any one of claims 1 to 7 are implemented.

10. A medium, wherein the computer-readable storage medium stores a computer program, characterized in that: When the computer program is executed by a processor, the steps of the credit review method for a commercial vehicle lessee as claimed in any one of claims 1 to 7 are implemented.

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