CN112419008A - Automatic grading early warning method and device, electronic equipment and storage medium - Google Patents
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Abstract
The invention discloses an automatic grading early warning method, an automatic grading early warning device, electronic equipment and a storage medium, wherein the method comprises the following steps: acquiring a grading early warning instruction, wherein the grading early warning instruction comprises a client identifier; acquiring a grading early warning identification table according to the customer identification in the grading early warning instruction, wherein the grading early warning identification table comprises parameter information of customer financial leasing; and performing risk grade evaluation on the parameter information in the grading early warning identification table according to a preset grading early warning rule to obtain a first grading early warning result, wherein the preset grading early warning rule comprises a grade evaluation standard of each item of parameter information. The method comprises the steps of obtaining a grading early warning identification table containing parameter information of customer financial leasing according to customer identification, carrying out risk grade evaluation on the parameter information according to preset grading early warning rules, and automatically obtaining a first grading early warning result, so that the efficiency and the accuracy of early warning grading are improved.
Description
Technical Field
The embodiment of the invention relates to the technical field of information processing, in particular to an automatic grading early warning method and device, electronic equipment and a storage medium.
Background
The financial leasing is a leasing mode with double functions of financing and article-melting, wherein the leasing mode is that a lessor purchases equipment selected by a lessee and rents the equipment for use for a certain period of time. Under the current big data environment, each financial leasing company is focused on upgrading the monitoring of business risks for early warning management, so as to give early warning prompts to customers with risk of repayment, and corresponding measures such as payment urging and the like are taken to ensure the safety of funds.
However, when the financial leasing company carries out risk assessment at present, the business personnel are only used for carrying out subjective early warning classification on the clients according to the knowledge of the business personnel on the clients, but the manual mode has strong subjectivity, and the business personnel cannot guarantee that the client information can be mastered in an all-around manner, so that the efficiency and the accuracy of early warning classification are influenced.
Disclosure of Invention
The embodiment of the invention provides an automatic grading early warning method, device, equipment and storage medium, which are used for realizing automatic grading early warning on customers based on financial leasing business.
In a first aspect, an embodiment of the present invention discloses an automatic grading early warning method, including:
acquiring a grading early warning instruction, wherein the grading early warning instruction comprises a client identifier;
acquiring a grading early warning identification table according to the customer identification in the grading early warning instruction, wherein the grading early warning identification table comprises parameter information of customer financial leasing;
and performing risk grade evaluation on the parameter information in the grading early warning identification table according to a preset grading early warning rule to obtain a first grading early warning result, wherein the preset grading early warning rule comprises a grade evaluation standard of each item of parameter information.
In a second aspect, an embodiment of the present invention provides an automatic grading early warning apparatus, including:
the grading early warning instruction acquisition module is used for acquiring a grading early warning instruction, wherein the grading early warning instruction comprises a client identifier;
the grading early warning identification table acquisition module is used for acquiring a grading early warning identification table according to the customer identification in the grading early warning instruction, wherein the grading early warning identification table comprises financial lease parameter information of the customer;
and the first grading early warning result acquisition module is used for carrying out risk grade evaluation on the parameter information in the grading early warning identification table according to a preset grading early warning rule to obtain a first grading early warning result, wherein the preset grading early warning rule comprises a grade evaluation standard of each parameter information.
In a third aspect, an embodiment of the present invention further provides an electronic device, where the electronic device includes:
one or more processors;
storage means 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 are caused to implement the methods of any of the embodiments of the present invention.
In a fourth aspect, the embodiments of the present invention also provide a computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the method of any of the embodiments of the present invention.
In the embodiment of the invention, the first grading early warning result is automatically obtained by acquiring the grading early warning identification table containing the parameter information of the financial lease of the customer according to the customer identification and evaluating the risk grade of the parameter information according to the preset grading early warning rule, so that the efficiency and the accuracy of early warning grading are improved.
Drawings
Fig. 1 is a flowchart of an automatic grading early warning method according to an embodiment of the present invention;
fig. 2 is a flowchart of an automatic grading early warning method according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of an automatic grading early warning device provided by a third embodiment of the present invention;
fig. 4 is a block diagram of an electronic device according to a fourth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Example one
Fig. 1 is a flowchart of an automatic hierarchical early warning method according to an embodiment of the present invention, which is applicable to a case where a financial rental business implements automatic hierarchical early warning on a customer. The method can be executed by the automatic grading early warning device in the embodiment of the invention, the device can be realized in a software and/or hardware mode, and the method in the embodiment of the invention specifically comprises the following steps:
and S101, acquiring a grading early warning instruction, wherein the grading early warning instruction comprises a client identifier.
Specifically, the embodiment mainly aims at automatic grading early warning of signed customers under the financial leasing business scene so as to ensure the safety of lessors, such as leasehold companies. In the embodiment, the grading early warning can be initiated to any client with unsettled contract to determine the risk grade of the client and ensure the normal collection of rent.
The electronic equipment is provided with a human-computer interaction interface, a user can operate and select a designated client needing risk assessment on the human-computer interaction interface, and the electronic equipment obtains a grading early warning instruction according to the user operation, wherein the grading early warning instruction comprises a client identifier. The client identifier may be a name of the client, a label marked when signing a contract, or an identity card number of the client, and the like, and the specific form of the client identifier is not limited in this embodiment, and it is within the scope of the present application as long as the client can be distinguished and identified.
And S102, acquiring a grading early warning identification table according to the customer identification in the grading early warning instruction, wherein the grading early warning identification table comprises parameter information of customer financial leasing.
Optionally, obtaining the classification early warning identification table according to the customer identifier in the classification early warning instruction may include: screening data from a client information base according to the client identification in the grading early warning instruction to acquire parameter information matched with the client identification; and constructing a grading early warning identification table according to the parameter information.
Optionally, the parameter information includes debt repayment information and financial statement information.
Optionally, the debt repayment information includes: the number of overdue days and the number of overdue times within a preset time.
Optionally, the financial statement information includes: sales revenue, net profit, accounts receivable, inventory, debt present, rate of assets liability, operational net cash flow, interest support factor, and number of inventory turnover days.
Specifically, since the relevant information of the signed user is stored in the client information base of the electronic device, after receiving the hierarchical early warning instruction, the data screening is performed from the client information base according to the client identifier, such as the name of the client, included in the instruction, and the name of the client, so as to obtain the parameter information matched with the name of the client, where the parameter information may specifically include debt repayment information and financial statement information, and construct the hierarchical early warning identification table according to the parameter information.
It should be noted that, the ranking early warning identification table includes initial subscription information in addition to various parameter information for ranking, and the initial subscription information includes: customer name, social credit code, region, industry of business code, industry of business category, customer type, business nature, business size, and platform type. Table 1 below shows an example of a classification warning and identification table in this embodiment, where table 1 includes: table 1-1 contains initial contract information and debt repayment information, and table 1-2 contains financial statement information:
TABLE 1-1
Tables 1 to 2
It should be noted that, in the embodiment, the hierarchical warning recognition table is only illustrated, and in practical applications, the content of the hierarchical warning recognition table is to be described in more detail, and the embodiment is exemplified for the sake of space limitation.
And S103, performing risk grade evaluation on the parameter information in the grading early warning identification table according to a preset grading early warning rule to obtain a first grading early warning result, wherein the preset grading early warning rule comprises a grade evaluation standard of each item of parameter information.
Optionally, the risk level assessment is performed on the parameter information in the classification early warning identification table according to the preset classification early warning rule to obtain a first classification early warning result, including: determining an early warning grade corresponding to each item of parameter information in a grading early warning identification table according to a preset grading early warning rule, wherein each item of parameter information corresponds to an early warning grade with the same grade or different grades respectively; and taking the early warning grade with the highest grade corresponding to each parameter information as a first grading early warning result.
Optionally, the number of the early warning grades is at least three, and each early warning grade corresponds to a different score.
Specifically, in the present embodiment, the rating evaluation criteria of each item of parameter information in the rating pre-warning determination table are set in the preset rating pre-warning rule, for example, for the number of days that is overdue, when the number of days that is overdue exceeds 90 days, the pre-warning rating is three; when the number of overdue days exceeds 30 days and does not exceed 90 days, the early warning level is two levels; when the number of overdue days exceeds 5 days and does not exceed 30 days, the early warning grade is first grade; when the number of overdue days does not exceed 5 days, no early warning is carried out. And the higher the grade is, the greater the risk is, each early warning grade corresponds to different scores respectively, for example, the first grade corresponds to 40 scores, the second grade corresponds to 70 scores, the third grade corresponds to 90 scores, and the higher the corresponding score is, the greater the risk is. Of course, in the embodiment, only the number of overdue days is taken as an example for illustration, and the parameter information of other items has corresponding grade evaluation criteria in the preset grading early warning rule. The electronic equipment automatically carries out risk assessment on each parameter information according to a preset grading early warning rule to determine the early warning grade corresponding to each parameter information, and the early warning grade corresponding to each parameter information can be the same or different, for example, the early warning grade corresponding to the overdue days is two grades, the early warning grade corresponding to the sales income is one grade, and the early warning grade corresponding to the asset liability rate is two grades. However, after each item of parameter information in the classification early warning identification table is evaluated to obtain a corresponding early warning level, the early warning level with the highest level corresponding to each item of parameter information is used as an obtained final result, namely a first classification early warning result. For example, when it is determined that the highest early warning level corresponding to the 12 items of parameter information included in the hierarchical early warning identification table is three levels, it is determined that the first hierarchical early warning result obtained by the electronic device performing the risk assessment is three levels.
In the embodiment of the invention, the first grading early warning result is automatically obtained by acquiring the grading early warning identification table containing the parameter information of the financial lease of the customer according to the customer identification and evaluating the risk grade of the parameter information according to the preset grading early warning rule, so that the efficiency and the accuracy of early warning grading are improved.
Example two
Fig. 2 is a flowchart of an automatic grading early warning method according to a second embodiment of the present invention, where the embodiment is based on the foregoing embodiment, and after performing risk grade assessment on parameter information according to a preset grading early warning rule to obtain a first grading early warning result, the method further includes: and generating an alarm prompt when the first grading early warning result is determined to exceed the preset grade, acquiring a second grading early warning result input by a user through actual investigation, and comprehensively analyzing the first grading result automatically acquired by the electronic equipment and the second grading early warning result determined manually to output a final early warning result.
As shown in fig. 2, the method of the embodiment of the present disclosure specifically includes:
step S201, a grading early warning instruction is obtained, wherein the grading early warning instruction comprises a customer identification.
Step S202, a grading early warning identification table is obtained according to the customer identification in the grading early warning instruction, wherein the grading early warning identification table comprises parameter information of customer financial leasing.
Optionally, obtaining the classification early warning identification table according to the customer identifier in the classification early warning instruction may include: screening data from a client information base according to the client identification in the grading early warning instruction to acquire parameter information matched with the client identification; and constructing a grading early warning identification table according to the parameter information.
Optionally, the parameter information includes debt repayment information and financial statement information.
Optionally, the debt repayment information includes: the number of overdue days and the number of overdue times within a preset time.
Optionally, the financial statement information includes: sales revenue, net profit, accounts receivable, inventory, debt present, rate of assets liability, operational net cash flow, interest support factor, and number of inventory turnover days.
Step S203, performing risk level evaluation on the parameter information in the classification early warning identification table according to a preset classification early warning rule to obtain a first classification early warning result, wherein the preset classification early warning rule comprises a level evaluation standard of each item of parameter information.
Optionally, the risk level assessment is performed on the parameter information in the classification early warning identification table according to the preset classification early warning rule to obtain a first classification early warning result, including: determining an early warning grade corresponding to each item of parameter information in a grading early warning identification table according to a preset grading early warning rule, wherein each item of parameter information corresponds to an early warning grade with the same grade or different grades respectively; and taking the early warning grade with the highest grade corresponding to each parameter information as a first grading early warning result.
Optionally, the number of the early warning grades is at least three, and each early warning grade corresponds to a different score.
And step S204, generating an alarm prompt when the first grading early warning result exceeds the early warning grade.
Specifically, in this embodiment, an alarm prompt is generated when it is determined that the first-level early warning result exceeds the early warning level, where the early warning level may be specifically one level, that is, the alarm prompt may be generated as long as it is determined that the customer has a risk according to the first-level early warning result, and the alarm prompt may be "the customer currently has a risk and asks you to perform risk investigation", and an investigation result input port may also be displayed for the user to input a risk investigation result.
When the first-grade early warning result does not display the risk grade, it indicates that the current client does not have the risk, and at this time, the client risk-free result is directly displayed, specifically, the client risk-free result can be displayed in a text or voice manner, and a specific display manner is not limited in this embodiment.
And step S205, receiving a second grading early warning result input by the user for risk investigation on the client according to the alarm prompt.
Specifically, in order to ensure the accuracy of early warning classification, when determining that a risk exists in a client according to a first classified early warning result, a second classified early warning result input by the user after risk investigation is performed on the client is further received, for example, the first classified early warning result is three-stage due to long overdue time of the client, but the user finds that the current economic condition of the client is good through risk investigation on the client, but the second classified early warning result of the client is determined to be two-stage due to the fact that a responsible person cannot sign for a long time and cannot pay normally due to the fact that the responsible person goes abroad, and the second classified early warning result input by the user is obtained through an input port.
And step S206, obtaining a third grading early warning result according to the first grading early warning result and the second grading early warning result.
Optionally, before obtaining a third grading early warning result according to the first grading early warning result and the second grading early warning result, the method further includes: and acquiring a first weight coefficient corresponding to the first grading early warning result and a second weight coefficient corresponding to the second grading early warning result.
Optionally, obtaining a third grading early warning result according to the first grading early warning result and the second grading early warning result may include: calculating a first product result of the first grading early warning result and the first weight coefficient; calculating a second product result of the second grading early warning result and the second weight coefficient; and determining the addition sum of the first product result and the second product result, and taking the addition sum as a third grading early warning result.
Specifically, in this embodiment, before performing comprehensive analysis according to the first and second grading early warning results to obtain the final early warning result, different weight coefficients need to be allocated to the first and second grading early warning results, for example, the first weight coefficient corresponding to the first grading early warning result is 70%, and the second weight coefficient corresponding to the second grading early warning result is 30%, and of course, the weight coefficients may be specifically adjusted and set according to actual situations, and a specific value of the weight coefficient is not limited in this embodiment.
When the third-level early warning result is determined, the weighted sum of the first-level early warning result and the second-level early warning result may be specifically calculated, for example, it is determined that the first-level early warning result is three-level, the corresponding score is 90, the second-level early warning result is one-level, and the corresponding score is 40, and then the weighted sum calculation results of the first-level early warning result and the second-level early warning result are: 90 × 70% +40 × 30% ═ 75, because each early warning grade in this embodiment corresponds to different scores respectively, the first grade corresponds to 40 points, the second grade corresponds to 70 points, and the third grade corresponds to 90 points, and when the score exceeding the current grade score but not reaching the next higher grade can be set in advance, the early warning grade is determined continuously according to the current grade. Since the third grading pre-warning result is 75, the third grading pre-warning result is more than two grades and reaches three grades, the third grading pre-warning result can be determined to be two grades. In addition, after the third grading early warning result is obtained, the third grading early warning result is displayed on a human-computer interaction interface, so that a user can obtain the final early warning result more intuitively and quickly.
In the embodiment of the invention, the first grading early warning result is automatically obtained by acquiring the grading early warning identification table containing the parameter information of the financial lease of the customer according to the customer identification and evaluating the risk grade of the parameter information according to the preset grading early warning rule, so that the efficiency and the accuracy of early warning grading are improved. After the first grading early warning result is automatically obtained through the electronic equipment, a second grading early warning result obtained through actual investigation of a user is obtained under the condition that the early warning risk exists, and the final early warning grading result is obtained by combining the sum of the two results, so that the accuracy of early warning grading is further improved.
EXAMPLE III
Fig. 3 is a schematic structural diagram of an automatic grading early warning device provided in an embodiment of the present invention, which specifically includes: a grading early warning instruction obtaining module 310, a grading early warning identification table obtaining module 320 and a first grading early warning result obtaining module 330.
The hierarchical early warning instruction acquisition module 310 is configured to acquire a hierarchical early warning instruction, where the hierarchical early warning instruction includes a client identifier;
a grading early warning identification table obtaining module 320, configured to obtain a grading early warning identification table according to a customer identifier in the grading early warning instruction, where the grading early warning identification table includes financial lease parameter information of the customer;
the first grading early warning result obtaining module 330 is configured to perform risk grade evaluation on the parameter information in the grading early warning identification table according to a preset grading early warning rule to obtain a first grading early warning result, where the preset grading early warning rule includes a grade evaluation standard of each parameter information.
Optionally, the classification early warning identification table obtaining module is configured to perform data screening from a client information base according to a client identifier in the classification early warning instruction, and obtain parameter information matched with the client identifier;
and constructing a grading early warning identification table according to the parameter information.
Optionally, the first grading early warning result obtaining module is configured to determine, according to a preset grading early warning rule, an early warning grade corresponding to each item of parameter information in a grading early warning identification table, where each item of parameter information corresponds to an early warning grade of the same grade or different grades;
and taking the early warning grade with the highest grade corresponding to each parameter information as a first grading early warning result.
Optionally, the parameter information includes debt repayment information and financial statement information.
Optionally, the debt repayment information includes: the number of overdue days and the number of overdue times within a preset time.
Optionally, the financial statement information includes: sales revenue, net profit, accounts receivable, inventory, liability status, rate of assets liability, operational net cash flow, interest support factor, and number of inventory turnover days.
Optionally, the hierarchical early warning subscription table further includes initial subscription information,
the initial subscription information includes: customer name, social credit code, region, industry of business code, industry of business category, customer type, business nature, business size, and platform type.
Optionally, the device further includes a third grading early warning result obtaining module, configured to generate an alarm prompt when it is determined that the first grading early warning result exceeds the preset grade;
receiving a second grading early warning result input by the user for risk investigation on the client according to the alarm prompt;
and obtaining a third grading early warning result according to the first grading early warning result and the second grading early warning result.
Optionally, the apparatus further includes a weight coefficient obtaining module, configured to obtain a first weight coefficient corresponding to the first hierarchical warning result and a second weight coefficient corresponding to the second hierarchical warning result.
Optionally, the third grading early warning result obtaining module is further configured to calculate a first product result of the first grading early warning result and the first weight coefficient;
calculating a second product result of the second grading early warning result and the second weight coefficient;
and determining the addition sum of the first product result and the second product result, and taking the addition sum as a third grading early warning result.
Optionally, the number of the early warning grades is at least three, and each early warning grade corresponds to a different score.
Optionally, the device further includes a display module, configured to display the third grading early warning result.
The device can execute the automatic grading early warning method provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method. For technical details not described in detail in this embodiment, reference may be made to the method provided in any embodiment of the present invention.
Example four
Fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention. FIG. 4 illustrates a block diagram of an exemplary electronic device 412 suitable for use in implementing embodiments of the present invention. The electronic device 412 shown in fig. 4 is only an example and should not bring any limitations to the functionality and scope of use of the embodiments of the present invention.
As shown in fig. 4, the electronic device 412 is 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 that couples the various system components (including the memory 428 and the processor 416).
The memory 428 is used to store instructions. Memory 428 can 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/nonvolatile computer system storage media. By way of example only, storage system 434 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 4, commonly referred to as a "hard drive"). Although not shown in FIG. 4, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 418 by one or more data media interfaces. Memory 428 can include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 440 having a set (at least one) of program modules 442 may be stored, for instance, 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 examples or some combination thereof may comprise an implementation of a network environment. The program modules 442 generally perform the functions and/or methodologies of the described embodiments of the invention.
The electronic device 412 may also communicate with one or more external devices 414 (e.g., keyboard, pointing device, display 424, etc.), with one or more devices that enable a user to interact with the electronic device 412, and/or with any devices (e.g., network card, modem, etc.) that enable the electronic device 412 to communicate with one or more other computing devices. Such communication may occur via input/output (I/O) interfaces 422. Also, the electronic device 412 may 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) through the network adapter 420. As shown, network adapter 420 communicates with the other modules of electronic device 412 over bus 418. It should be appreciated that although not shown in FIG. 4, other hardware and/or software modules may be used in conjunction with the 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, among others.
The processor 416 performs various functional applications and data processing by executing instructions stored in the memory 428, such as performing the following: acquiring a grading early warning instruction, wherein the grading early warning instruction comprises a client identifier; acquiring a grading early warning identification table according to the customer identification in the grading early warning instruction, wherein the grading early warning identification table comprises parameter information of customer financial leasing; and performing risk grade evaluation on the parameter information in the grading early warning identification table according to a preset grading early warning rule to obtain a first grading early warning result, wherein the preset grading early warning rule comprises a grade evaluation standard of each item of parameter information.
EXAMPLE five
An embodiment of the present invention further provides a storage medium containing computer-executable instructions, which when executed by a computer processor, are configured to perform an automatic hierarchical warning method, including:
acquiring a grading early warning instruction, wherein the grading early warning instruction comprises a client identifier; acquiring a grading early warning identification table according to the customer identification in the grading early warning instruction, wherein the grading early warning identification table comprises parameter information of customer financial leasing; and performing risk grade evaluation on the parameter information in the grading early warning identification table according to a preset grading early warning rule to obtain a first grading early warning result, wherein the preset grading early warning rule comprises a grade evaluation standard of each item of parameter information.
Of course, the storage medium provided by the embodiment of the present invention contains computer-executable instructions, and the computer-executable instructions are not limited to the above method operations, and may also perform related operations in the automatic grading early warning method provided by any embodiment of the present invention.
From the above description of the embodiments, it is obvious for those skilled in the art that the present invention can be implemented by software and necessary general hardware, and certainly, can also be implemented by hardware, but the former is a better embodiment in many cases. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which may be stored in a computer-readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a FLASH Memory (FLASH), a hard disk, or an optical disk of a computer, and includes several instructions to enable an electronic device (which may be a personal computer, a server, or a network device) to execute the cross-platform job transition method according to the embodiments of the present invention.
It should be noted that, the units and modules included in the above embodiments are merely divided according to functional logic, but are not limited to the above division as long as the corresponding functions can be implemented; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments illustrated herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (15)
1. An automatic grading early warning method is characterized by comprising the following steps:
acquiring a grading early warning instruction, wherein the grading early warning instruction comprises a client identifier;
acquiring a graded early warning identification table according to the customer identification in the graded early warning instruction, wherein the graded early warning identification table comprises parameter information of the customer financial lease;
and performing risk grade evaluation on the parameter information in the grading early warning identification table according to a preset grading early warning rule to obtain a first grading early warning result, wherein the preset grading early warning rule comprises a grade evaluation standard of each item of parameter information.
2. The method of claim 1, wherein obtaining a rating pre-warning identification form according to the customer identification in the rating pre-warning instruction comprises:
performing data screening from a customer information base according to the customer identification in the grading early warning instruction to acquire parameter information matched with the customer identification;
and constructing the grading early warning identification table according to the parameter information.
3. The method of claim 2, wherein the performing risk level assessment on the parameter information in the classification early warning identification table according to a preset classification early warning rule to obtain a first classification early warning result comprises:
determining an early warning grade corresponding to each item of parameter information in the grading early warning identification table according to the preset grading early warning rule, wherein each item of parameter information corresponds to an early warning grade with the same grade or different grades respectively;
and taking the early warning grade with the highest grade corresponding to each parameter information as the first grade early warning result.
4. The method of claim 1, wherein the parameter information includes debt repayment information and financial statement information.
5. The method of claim 4, wherein the debt repayment information comprises: the number of overdue days and the number of overdue times within a preset time.
6. The method of claim 4, wherein the financial reporting information comprises: sales revenue, net profit, accounts receivable, inventory, liability status, rate of assets liability, operational net cash flow, interest support factor, and number of inventory turnover days.
7. The method of claim 1, wherein the hierarchical early warning subscription table further comprises initial subscription information,
the initial subscription information includes: customer name, social credit code, region, industry of business code, industry of business category, customer type, business nature, business size, and platform type.
8. The method of claim 1, wherein after the risk level assessment is performed on the parameter information in the classification early warning identification table according to a preset classification early warning rule to obtain a first classification early warning result, the method further comprises:
generating an alarm prompt when the first grading early warning result is determined to exceed a preset grade;
receiving a second grading early warning result input by a user for risk investigation on the client according to an alarm prompt;
and obtaining a third grading early warning result according to the first grading early warning result and the second grading early warning result.
9. The method of claim 8, wherein before obtaining a third grading pre-warning result according to the first grading pre-warning result and the second grading pre-warning result, the method further comprises:
and acquiring a first weight coefficient corresponding to the first grading early warning result and a second weight coefficient corresponding to the second grading early warning result.
10. The method of claim 9, wherein obtaining a third grading pre-warning result according to the first grading pre-warning result and the second grading pre-warning result comprises:
calculating a first product result of the first grading early warning result and the first weight coefficient;
calculating a second product result of the second grading early warning result and the second weight coefficient;
and determining the addition sum of the first product result and the second product result, and taking the addition sum as the third grading early warning result.
11. The method of claim 3, wherein the number of the early warning levels is at least three, and each early warning level corresponds to a different score.
12. The method of claim 8, wherein after obtaining a third grading pre-warning result according to the first grading pre-warning result and the second grading pre-warning result, the method further comprises:
and displaying the third grading early warning result.
13. An automatic grading early warning device, characterized in that the device comprises:
the grading early warning instruction acquisition module is used for acquiring a grading early warning instruction, wherein the grading early warning instruction comprises a client identifier;
the grading early warning identification table acquisition module is used for acquiring a grading early warning identification table according to the customer identification in the grading early warning instruction, wherein the grading early warning identification table comprises financial lease parameter information of the customer;
and the first grading early warning result acquisition module is used for performing risk grade evaluation on the parameter information in the grading early warning identification table according to a preset grading early warning rule to obtain a first grading early warning result, wherein the preset grading early warning rule comprises a grade evaluation standard of each parameter information.
14. An electronic device, characterized in that the electronic device comprises:
one or more processors;
storage means for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-12.
15. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-12.
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Effective date of registration: 20220913 Address after: 12 / F, 15 / F, 99 Yincheng Road, China (Shanghai) pilot Free Trade Zone, Pudong New Area, Shanghai, 200120 Applicant after: Jianxin Financial Science and Technology Co.,Ltd. Applicant after: CCB Financial Leasing Co.,Ltd. Address before: 25 Financial Street, Xicheng District, Beijing 100033 Applicant before: CHINA CONSTRUCTION BANK Corp. |