Automatic graded warning method, device, electronic device and storage medium

Abstract

The present invention discloses an automatic graded warning method, device, electronic device and storage medium, including: obtaining a graded warning instruction, wherein the graded warning instruction contains a customer identification; obtaining a graded warning identification table according to the customer identification in the graded warning instruction, wherein the graded warning identification table contains parameter information of the customer's financial leasing; performing a risk level assessment on the parameter information in the graded warning identification table according to a preset graded warning rule to obtain a first graded warning result, wherein the preset graded warning rule contains a grade assessment standard for each parameter information. By obtaining a graded warning identification table containing the parameter information of the customer's financial leasing according to the customer identification, and performing a risk level assessment on the parameter information according to the preset graded warning rule, the first graded warning result is automatically obtained, thereby improving the efficiency and accuracy of the warning classification.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of information processing technology, and in particular to an automatic graded warning method, device, electronic device and storage medium. Background Art

[0002] Financial leasing refers to a leasing method that has the dual functions of financing and financing goods, in which the lessor purchases the equipment selected by the lessee and leases the equipment to the lessor for paid use within a certain period of time. In today's big data environment, financial leasing companies have begun to focus on upgrading the monitoring of business risks for early warning management, to issue early warnings to customers with repayment risks, and to take corresponding measures such as collection to ensure the safety of funds.

[0003] However, when conducting risk assessment, financial leasing companies currently only use business personnel to conduct subjective early warning classification of customers based on their understanding of the customers. However, the manual method is highly subjective, and business personnel cannot guarantee that they can fully grasp customer information, which affects the efficiency and accuracy of the early warning classification. Summary of the invention

[0004] The embodiments of the present invention provide an automatic graded warning method, device, equipment and storage medium to realize automatic graded warning for customers based on financial leasing business.

[0005] In a first aspect, an embodiment of the present invention discloses an automatic hierarchical warning method, comprising:

[0006] Obtaining a graded warning instruction, wherein the graded warning instruction includes a customer identifier;

[0007] Obtain a graded warning identification table according to the customer identifier in the graded warning instruction, wherein the graded warning identification table contains parameter information of the customer's financial leasing;

[0008] The risk level of the parameter information in the graded warning identification table is evaluated according to the preset graded warning rules to obtain a first graded warning result, wherein the preset graded warning rules include a grade evaluation standard for each parameter information.

[0009] In a second aspect, an embodiment of the present invention provides an automatic graded warning device, comprising:

[0010] A graded warning instruction acquisition module is used to acquire a graded warning instruction, wherein the graded warning instruction includes a customer identifier;

[0011] A module for obtaining a graded warning identification table is used to obtain a graded warning identification table according to a customer identifier in a graded warning instruction, wherein the graded warning identification table contains the customer's financial leasing parameter information;

[0012] The first graded warning result acquisition module is used to perform risk level assessment on the parameter information in the graded warning identification table according to preset graded warning rules to obtain the first graded warning result, wherein the preset graded warning rules include the grade assessment standard for each parameter information.

[0013] In a third aspect, an embodiment of the present invention further provides an electronic device, the electronic device comprising:

[0014] one or more processors;

[0015] A storage device for storing one or more programs;

[0016] When one or more programs are executed by one or more processors, the one or more processors implement the method of any embodiment of the present invention.

[0017] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a method of any embodiment of the present invention.

[0018] In an embodiment of the present invention, a graded warning identification table containing parameter information of a customer's financial lease is obtained according to a customer identifier, and the risk level of the parameter information is evaluated according to preset graded warning rules to automatically obtain a first graded warning result, thereby improving the efficiency and accuracy of the warning classification. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is a flow chart of the automatic graded warning method provided by the first embodiment of the present invention;

[0020] Figure 2 is a flow chart of an automatic graded warning method provided by Embodiment 2 of the present invention;

[0021] Figure 3 is a schematic diagram of the structure of an automatic graded warning device provided in Embodiment 3 of the present invention;

[0022] Figure 4 This is a structural block diagram of an electronic device provided in Embodiment 4 of the present invention. DETAILED DESCRIPTION

[0023] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0024] Embodiment 1

[0025] Figure 1This is a flow chart of an automatic graded warning method provided by an embodiment of the present invention. This embodiment is applicable to the case of implementing automatic graded warning for customers based on financial leasing business. The method can be executed by the automatic graded warning device in the embodiment of the present invention, which can be implemented by software and / or hardware. The method in the embodiment of the present invention specifically includes the following steps:

[0026] Step S101, obtaining a graded warning instruction, wherein the graded warning instruction includes a customer identifier.

[0027] Specifically, this implementation mainly targets the automatic graded warning for signed customers in the financial leasing business scenario to ensure the safety of funds of the lessor, such as the leasing company. In this implementation, a graded warning can be initiated for any customer with an unsettled contract to determine the customer's risk level to ensure the normal collection of rent.

[0028] Among them, there is a human-computer interaction interface on the electronic device, and the user can operate on the human-computer interaction interface to select the designated customer who needs to be risk assessed. The electronic device obtains a graded warning instruction according to the user operation, wherein the graded warning instruction includes a customer identifier. The customer identifier can be the customer's name, the number marked when signing the contract, or the customer's ID number, etc. The specific form of the customer identifier is not limited in this implementation. As long as the customer can be distinguished and identified, it is within the scope of protection of this application.

[0029] Step S102, obtaining a graded warning identification table according to the customer identifier in the graded warning instruction, wherein the graded warning identification table contains parameter information of the customer's financial leasing.

[0030] Optionally, obtaining a graded warning recognition table based on a customer identifier in a graded warning instruction may include: filtering data from a customer information database based on the customer identifier in the graded warning instruction to obtain parameter information matching the customer identifier; and constructing a graded warning recognition table based on the parameter information.

[0031] Optionally, the parameter information includes debt repayment information and financial statement information.

[0032] Optionally, the debt repayment information includes: the number of overdue days and the number of overdue times within a preset time.

[0033] Optionally, financial statement information includes: sales revenue, net profit, accounts receivable, inventory, liabilities, debt-to-asset ratio, operating net cash flow, interest coverage ratio and inventory turnover days.

[0034] Specifically, since the relevant information of the contracted users is stored in the customer information database of the electronic device, after receiving the graded warning instruction, the customer identifier contained in the instruction, such as the customer's name, will be used to filter data from the customer information database and obtain parameter information that matches the customer name. The parameter information may specifically include debt repayment information and financial statement information, and a graded warning recognition table will be constructed based on the parameter information.

[0035] It should be noted that, in addition to the various parameter information used for graded assessment, the graded early warning identification table also includes initial contract information, which includes: customer name, social credit code, region, industry code, industry category, customer type, enterprise nature, enterprise scale and platform type. The following Table 1 is an example of the graded early warning identification table in this implementation, wherein Table 1 includes: Table 1-1 includes initial contract information and debt repayment information, and Table 1-2 includes financial statement information:

[0036] Table 1-1

[0037]

[0038] Table 1-2

[0039]

[0040]

[0041] It should be noted that the present embodiment only provides an example of the graded warning identification table. In actual applications, the content of the graded warning identification table should be more detailed. The present embodiment provides an example explanation due to space limitations.

[0042] Step S103, performing risk level assessment on the parameter information in the graded warning identification table according to preset graded warning rules to obtain a first graded warning result, wherein the preset graded warning rules include a grade assessment standard for each parameter information.

[0043] Optionally, a risk level assessment is performed on the parameter information in the graded warning identification table according to preset graded warning rules to obtain a first graded warning result, including: determining the warning level corresponding to each parameter information in the graded warning identification table according to the preset graded warning rules, wherein each parameter information corresponds to the same level or different levels of warning levels; and taking the highest warning level corresponding to each parameter information as the first graded warning result.

[0044] Optionally, there are at least three warning levels, and each warning level corresponds to a different score.

[0045] Specifically, in the preset graded warning rules, the level assessment standards for each parameter information in the graded warning identification table are set in the present embodiment. For example, for the number of overdue days, when the number of overdue days exceeds 90 days, the warning level is level three; when the number of overdue days exceeds 30 days but does not exceed 90 days, the warning level is level two; when the number of overdue days exceeds 5 days but does not exceed 30 days, the warning level is level one; when the number of overdue days does not exceed 5 days, no warning is issued. And the higher the level, the greater the risk. Each warning level corresponds to a different score. For example, level one corresponds to 40 points, level two corresponds to 70 points, and level three corresponds to 90 points. The higher the corresponding score, the greater the risk. Of course, in the present embodiment, only the number of overdue days is used as an example for illustration. For the parameter information of other items, there are corresponding level assessment standards in the preset graded warning rules. The electronic device automatically conducts risk assessment on each parameter information according to the preset graded warning rules, and determines the warning level corresponding to each parameter information. The warning level corresponding to each parameter information can be the same or different. For example, the warning level corresponding to the number of overdue days is level 2, the warning level corresponding to the sales revenue is level 1, and the warning level corresponding to the asset-liability ratio is level 2. However, after evaluating each parameter information in the graded warning recognition table to obtain the corresponding warning level, the highest warning level corresponding to each parameter information will be used as the final result obtained, that is, the first graded warning result. For example, when it is determined that the highest warning level corresponding to the 12 parameter information contained in the graded warning recognition table is level 3, it is determined that the first graded warning result obtained by the risk assessment of the electronic device is level 3.

[0046] In an embodiment of the present invention, a graded warning identification table containing parameter information of a customer's financial lease is obtained according to a customer identifier, and the risk level of the parameter information is evaluated according to preset graded warning rules to automatically obtain a first graded warning result, thereby improving the efficiency and accuracy of the warning classification.

[0047] Embodiment 2

[0048] Figure 2 It is a flow chart of an automatic graded warning method provided in Example 2 of the present invention. This embodiment is based on the above embodiment. After the risk level of the parameter information is evaluated according to the preset graded warning rules to obtain the first graded warning result, it also includes: generating an alarm prompt when it is determined that the first graded warning result exceeds the preset level, and obtaining the second graded warning result input by the user after actual investigation, and comprehensively analyzing the first graded result automatically obtained by the electronic device and the second graded warning result determined manually to output the final warning result.

[0049] like Figure 2 As shown, the method of the embodiment of the present disclosure specifically includes:

[0050] Step S201, obtaining a graded warning instruction, wherein the graded warning instruction includes a customer identifier.

[0051] Step S202, obtaining a graded warning identification table according to the customer identifier in the graded warning instruction, wherein the graded warning identification table contains parameter information of the customer's financial leasing.

[0052] Optionally, obtaining a graded warning recognition table based on a customer identifier in a graded warning instruction may include: filtering data from a customer information database based on the customer identifier in the graded warning instruction to obtain parameter information matching the customer identifier; and constructing a graded warning recognition table based on the parameter information.

[0053] Optionally, the parameter information includes debt repayment information and financial statement information.

[0054] Optionally, the debt repayment information includes: the number of overdue days and the number of overdue times within a preset time.

[0055] Optionally, financial statement information includes: sales revenue, net profit, accounts receivable, inventory, liabilities, debt-to-asset ratio, operating net cash flow, interest coverage ratio and inventory turnover days.

[0056] Step S203, performing risk level assessment on the parameter information in the graded warning identification table according to preset graded warning rules to obtain a first graded warning result, wherein the preset graded warning rules include a grade assessment standard for each parameter information.

[0057] Optionally, a risk level assessment is performed on the parameter information in the graded warning identification table according to preset graded warning rules to obtain a first graded warning result, including: determining the warning level corresponding to each parameter information in the graded warning identification table according to the preset graded warning rules, wherein each parameter information corresponds to the same level or different levels of warning levels; and taking the highest warning level corresponding to each parameter information as the first graded warning result.

[0058] Optionally, there are at least three warning levels, and each warning level corresponds to a different score.

[0059] Step S204: generating an alarm prompt when it is determined that the first graded warning result exceeds the warning level.

[0060] Specifically, in this implementation, an alarm prompt will be generated when it is determined that the first-level warning result exceeds the warning level, where the warning level can be specifically level one, that is, as long as it is determined that the customer is at risk based on the first-level warning result, an alarm prompt will be generated. The alarm prompt can be "The current customer is at risk, please conduct a risk investigation", and the investigation result input port will also be displayed for the user to input the risk investigation results.

[0061] Among them, when the first-level warning result does not display the risk level, it means that there is no risk for the current customer. At this time, the result that the customer has no risk is directly displayed, which can be displayed in the form of text or voice. The specific display method is not limited in this implementation.

[0062] Step S205, receiving a second graded warning result input by the user for conducting a risk investigation on the customer according to the alarm prompt.

[0063] Specifically, in order to ensure the accuracy of the warning classification, when it is determined that the customer is at risk based on the first-level warning result, the second-level warning result entered by the user after a risk investigation on the customer will be further received. For example, the first-level warning result is level three due to a long overdue period of the customer. However, through a risk investigation on the customer, the user finds that the customer’s current financial situation is good, but the person in charge is unable to repay the loan normally because he has been abroad for a long time and failed to sign in time. In this case, the second-level warning result of the customer will be determined to be level two, and the second-level warning result entered by the user will be obtained through the input port.

[0064] Step S206, obtaining a third graded warning result according to the first graded warning result and the second graded warning result.

[0065] Optionally, before obtaining the third level warning result according to the first level warning result and the second level warning result, it also includes: obtaining a first weight coefficient corresponding to the first level warning result, and a second weight coefficient corresponding to the second level warning result.

[0066] Optionally, obtaining a third graded warning result based on the first graded warning result and the second graded warning result may include: calculating a first product result of the first graded warning result and a first weight coefficient; calculating a second product result of the second graded warning result and a second weight coefficient; determining the sum of the first product result and the second product result, and using the sum as the third graded warning result.

[0067] Specifically, in this implementation, before a comprehensive analysis is performed based on the first level warning results and the second level warning results to obtain the final warning result, it is necessary to assign different weight coefficients to the first level warning results and the second level warning results respectively. For example, the first weight coefficient corresponding to the first level warning result is 70%, and the second weight coefficient corresponding to the second level warning result is 30%. Of course, the weight coefficient can be adjusted and set according to actual conditions, and the specific value of the weight coefficient is not limited in this implementation.

[0068] Among them, when determining the third grade warning result, the weighted sum of the first grade warning result and the second grade warning result can be calculated. For example, the first grade warning result is determined to be level three, and the corresponding score is 90, and the second grade warning result is level one, and the corresponding score is 40, then the weighted sum calculation result of the two is: 90*70%+40*30%=75. Since each warning level in this embodiment corresponds to a different score, level one corresponds to 40 points, level two corresponds to 70 points, and level three corresponds to 90 points, and it can be set in advance that when the score exceeds the current level but does not reach the next higher level, the warning level is determined according to the current level. Since the third grade warning result is 75, it exceeds level two and reaches level three, so it can be determined that the third grade warning result is level two. And after obtaining the third grade warning result, this embodiment will also display the third grade warning result on the human-computer interaction interface, so that the user can obtain the final warning result more intuitively and quickly.

[0069] In the embodiment of the present invention, by obtaining a graded warning identification table containing parameter information of the customer's financial lease according to the customer identification, and performing a risk level assessment on the parameter information according to the preset graded warning rules, the first graded warning result is automatically obtained, thereby improving the efficiency and accuracy of the warning classification. After the first graded warning result is automatically obtained through the electronic device, when there is a warning risk, the second graded warning result is obtained through the actual investigation of the user, and the final warning classification result is obtained by combining the sum of the two results, thereby further improving the accuracy of the warning classification.

[0070] Embodiment 3

[0071] Figure 3 It is a structural diagram of an automatic graded warning device provided by an embodiment of the present invention, which specifically includes: a graded warning instruction acquisition module 310, a graded warning recognition table acquisition module 320 and a first graded warning result acquisition module 330.

[0072] The hierarchical warning instruction acquisition module 310 is used to acquire the hierarchical warning instruction, wherein the hierarchical warning instruction includes the customer identifier;

[0073] The graded warning identification table acquisition module 320 is used to acquire the graded warning identification table according to the customer identifier in the graded warning instruction, wherein the graded warning identification table contains the customer's financial leasing parameter information;

[0074] The first graded warning result acquisition module 330 is used to perform risk level assessment on the parameter information in the graded warning identification table according to preset graded warning rules to obtain a first graded warning result, wherein the preset graded warning rules include a grade assessment standard for each parameter information.

[0075] Optionally, a hierarchical warning identification table acquisition module is used to filter data from a customer information database according to the customer identifier in the hierarchical warning instruction, and obtain parameter information matching the customer identifier;

[0076] Construct a graded warning identification table based on parameter information.

[0077] Optionally, a first graded warning result acquisition module is used to determine the warning level corresponding to each parameter information in the graded warning identification table according to a preset graded warning rule, wherein each parameter information corresponds to the same level or different levels of warning levels;

[0078] The highest warning level corresponding to each parameter information is used as the first graded warning result.

[0079] Optionally, the parameter information includes debt repayment information and financial statement information.

[0080] Optionally, the debt repayment information includes: the number of overdue days and the number of overdue times within a preset time.

[0081] Optionally, financial statement information includes: sales revenue, net profit, accounts receivable, inventory, debt status, debt-to-asset ratio, operating net cash flow, interest coverage ratio and inventory turnover days.

[0082] Optionally, the graded warning identification table also includes initial contract information.

[0083] The initial signing information includes: customer name, social credit code, region, industry code, industry category, customer type, nature of the enterprise, enterprise size and platform type.

[0084] Optionally, the device further includes a third graded warning result acquisition module, which is used to generate an alarm prompt when it is determined that the first graded warning result exceeds a preset level;

[0085] Receive the second-level warning result input by the user for risk investigation on the customer according to the alarm prompt;

[0086] The third level warning result is obtained based on the first level warning result and the second level warning result.

[0087] Optionally, the device also includes a weight coefficient acquisition module, which is used to obtain a first weight coefficient corresponding to the first grade warning result and a second weight coefficient corresponding to the second grade warning result.

[0088] Optionally, the third graded warning result acquisition module is further used to calculate a first product result of the first graded warning result and the first weight coefficient;

[0089] Calculate a second product result of the second graded warning result and the second weight coefficient;

[0090] Determine the sum of the first product result and the second product result, and use the sum as the third graded warning result.

[0091] Optionally, there are at least three warning levels, and each warning level corresponds to a different score.

[0092] Optionally, the device also includes a display module for displaying the third grade warning result.

[0093] The above device can execute the automatic graded warning method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method. For technical details not described in detail in this embodiment, please refer to the method provided by any embodiment of the present invention.

[0094] Embodiment 4

[0095] Figure 4 It is a structural schematic diagram of an electronic device provided by an embodiment of the present invention. Figure 4 A block diagram of an exemplary electronic device 412 suitable for use in implementing embodiments of the present invention is shown. Figure 4 The electronic device 412 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0096] like Figure 4 As shown, the electronic device 412 appears in the form of a general-purpose computing device. The components of the electronic device 412 may include, but are not limited to: one or more processors 412, a memory 428, and a bus 418 connecting different system components (including the memory 428 and the processor 416).

[0097] Bus 418 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. By way of example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0098] The electronic device 412 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the electronic device 412, including volatile and non-volatile media, removable and non-removable media.

[0099] The memory 428 is used to store instructions. The memory 428 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 430 and / or cache memory 432. The electronic device 412 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 434 may be used to read and write non-removable, non-volatile magnetic media ( Figure 4 not shown, usually called a "hard drive"). Although Figure 4 Not shown in the figure, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 418 via one or more data medium interfaces. The memory 428 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present invention.

[0100] A program / utility 440 having a set (at least one) of program modules 442 may be stored, for example, in memory 428, such program modules 442 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. Program modules 442 generally perform the functions and / or methods of the embodiments described herein.

[0101] The electronic device 412 may also communicate with one or more external devices 414 (e.g., keyboards, pointing devices, displays 424, etc.), may communicate with one or more devices that enable a user to interact with the electronic device 412, and / or may communicate with any device that enables the electronic device 412 to communicate with one or more other computing devices (e.g., a network card, a modem, etc.). Such communication may be performed via an input / output (I / O) interface 422. Furthermore, the electronic device 412 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 420. As shown, the network adapter 420 communicates with other modules of the electronic device 412 via a bus 418. It should be understood that although Figure 4 Not shown, other hardware and / or software modules may be used in conjunction with electronic device 412, including but not limited to microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0102] The processor 416 executes various functional applications and data processing by running instructions stored in the memory 428, such as performing the following operations: obtaining a graded warning instruction, wherein the graded warning instruction includes a customer identifier; obtaining a graded warning identification table based on the customer identifier in the graded warning instruction, wherein the graded warning identification table includes parameter information of the customer's financial leasing; performing a risk level assessment on the parameter information in the graded warning identification table based on preset graded warning rules to obtain a first graded warning result, wherein the preset graded warning rules include a level assessment standard for each parameter information.

[0103] Embodiment 5

[0104] Embodiment 5 of the present invention further provides a storage medium including computer executable instructions, and when the computer executable instructions are executed by a computer processor, the computer executable instructions are used to execute an automatic graded warning method, the method comprising:

[0105] Obtain a graded warning instruction, wherein the graded warning instruction includes a customer identifier; obtain a graded warning identification table based on the customer identifier in the graded warning instruction, wherein the graded warning identification table includes parameter information of the customer's financial leasing; perform a risk level assessment on the parameter information in the graded warning identification table based on preset graded warning rules to obtain a first graded warning result, wherein the preset graded warning rules include a level assessment standard for each parameter information.

[0106] Of course, the storage medium containing computer executable instructions provided in an embodiment of the present invention is not limited to the above method operations, and the computer executable instructions can also execute related operations in the automatic graded warning method provided in any embodiment of the present invention.

[0107] Through the above description of the implementation method, the technicians in the relevant field can clearly understand that the present invention can be implemented by means of software and necessary general hardware, and of course it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for an electronic device (which can be a personal computer, a server, or a network device, etc.) to execute the cross-platform job conversion method of each embodiment of the present invention.

[0108] It is worth noting that the various units and modules included in the above embodiments are only divided according to functional logic, but are not limited to the above divisions, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0109] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. An automatic graded warning method, characterized in that: include: Obtaining a graded warning instruction, wherein the graded warning instruction includes a customer identifier; Obtaining a graded warning identification table according to the customer identifier in the graded warning instruction, wherein the graded warning identification table contains parameter information of the customer's financial leasing, and the parameter information includes debt repayment information and financial statement information; Performing a risk level assessment on the parameter information in the graded warning identification table according to a preset graded warning rule to obtain a first graded warning result, wherein the preset graded warning rule includes a grade assessment standard for each parameter information; The step of performing risk level assessment on the parameter information in the graded warning identification table according to the preset graded warning rules to obtain the first graded warning result includes: determining the warning level corresponding to each parameter information in the graded warning identification table according to the preset graded warning rules, wherein each parameter information corresponds to the same level or different levels of warning levels; The highest warning level corresponding to each parameter information is used as the first graded warning result; The step of obtaining the graded warning identification table according to the customer identifier in the graded warning instruction comprises: screening data from a customer information database according to the customer identifier in the graded warning instruction to obtain parameter information matching the customer identifier; and constructing the graded warning identification table according to the parameter information; After the risk level assessment of the parameter information in the graded warning identification table is performed according to the preset graded warning rules to obtain the first graded warning result, it also includes: generating an alarm prompt when it is determined that the first graded warning result exceeds the preset level; Receiving a second grade warning result input by the user for conducting a risk investigation on the customer according to the alarm prompt; Obtaining a third graded warning result according to the first graded warning result and the second graded warning result; Before obtaining a third graded warning result according to the first graded warning result and the second graded warning result, the method further includes: obtaining a first weight coefficient corresponding to the first graded warning result and a second weight coefficient corresponding to the second graded warning result; The method of obtaining the third graded warning result based on the first graded warning result and the second graded warning result includes: calculating a first product result of the first graded warning result and the first weight coefficient; calculating a second product result of the second graded warning result and the second weight coefficient; determining the sum of the first product result and the second product result, and using the sum as the third graded warning result.

2. The method according to claim 1, characterized in that The debt repayment information includes: the number of overdue days and the number of overdue times within a preset time.

3. The method according to claim 1, characterized in that The financial statement information includes: sales revenue, net profit, accounts receivable, inventory, debt status, debt-to-asset ratio, operating net cash flow, interest coverage ratio and inventory turnover days.

4. The method according to claim 1, characterized in that The graded warning identification table also includes initial contract information. The initial signing information includes: customer name, social credit code, region, industry code, industry category, customer type, nature of the enterprise, enterprise scale and platform type.

5. The method according to claim 1, characterized in that The warning levels include at least three, and each warning level corresponds to a different score.

6. The method according to claim 1, characterized in that After obtaining a third graded warning result according to the first graded warning result and the second graded warning result, the method further includes: The third grade warning result is displayed.

7. An automatic graded warning device, characterized in that: The device comprises: A graded warning instruction acquisition module is used to acquire a graded warning instruction, wherein the graded warning instruction includes a customer identifier; A hierarchical warning recognition table acquisition module is used to acquire a hierarchical warning recognition table according to the customer identifier in the hierarchical warning instruction, wherein the hierarchical warning recognition table contains the financial leasing parameter information of the customer, and the parameter information includes debt repayment information and financial statement information; A first graded warning result acquisition module, used to perform risk level assessment on the parameter information in the graded warning identification table according to a preset graded warning rule to obtain a first graded warning result, wherein the preset graded warning rule includes a grade assessment standard for each parameter information; The first graded warning result acquisition module is used to determine the warning level corresponding to each parameter information in the graded warning identification table according to the preset graded warning rule, wherein each parameter information corresponds to the same level or different levels of warning levels; The highest warning level corresponding to each parameter information is used as the first graded warning result; A hierarchical warning recognition table acquisition module is used to screen data from a customer information database according to the customer identifier in the hierarchical warning instruction, and obtain parameter information matching the customer identifier; and construct the hierarchical warning recognition table according to the parameter information; The device also includes a third graded warning result acquisition module, which is used to generate an alarm prompt when it is determined that the first graded warning result exceeds a preset level; Receiving a second grade warning result input by the user for conducting a risk investigation on the customer according to the alarm prompt; Obtaining a third graded warning result according to the first graded warning result and the second graded warning result; Before obtaining a third graded warning result according to the first graded warning result and the second graded warning result, the method further includes: obtaining a first weight coefficient corresponding to the first graded warning result and a second weight coefficient corresponding to the second graded warning result; The method of obtaining the third graded warning result based on the first graded warning result and the second graded warning result includes: calculating a first product result of the first graded warning result and the first weight coefficient; calculating a second product result of the second graded warning result and the second weight coefficient; determining the sum of the first product result and the second product result, and using the sum as the third graded warning result.

8. An electronic device, characterized in that: The electronic device comprises: one or more processors; A storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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