Vehicle insurance monitoring and early warning method, device and equipment and storage medium

Abstract

The invention discloses a vehicle insurance monitoring and early warning method, device and equipment and a storage medium, and relates to the field of data analysis, and the method comprises the steps: comparing local vehicle insurance operation and management data with external vehicle insurance operation and management data of a monitoring platform, so as to determine the vehicle insurance operation and management data variation; if the vehicle insurance operation management data variable quantity is greater than a preset variable quantity threshold value, generating an early warning task corresponding to the vehicle insurance operation management data variable quantity, and pushing the early warning task to a task processing end, so that the task processing end generates a corresponding target solution; executing the target solution, and performing data backtracking on the monitoring platform and the vehicle insurance early warning platform to judge whether the current vehicle insurance operation management data variation is greater than a preset variation threshold; and determining whether to carry out vehicle insurance early warning based on the obtained current comparison result. Therefore, by comparing the internal data with the external industry data, the market change can be quickly perceived, corresponding measures are taken, result backtracking is carried out regularly, and timely early warning is carried out.

Description

Technical Field

[0001] The present invention relates to the field of data analysis, and in particular to a vehicle risk monitoring and early warning method, device, equipment and storage medium. Background Art

[0002] With the stable development of the auto insurance market, regulatory authorities usually monitor the key operating indicators of property and casualty insurance companies, make dynamic adjustments, and conduct regular retrospectives to maintain the order of the auto insurance market and ensure the stable and healthy development of the industry. However, the data platforms and analysis systems within the company are generally internal data, lacking external data of the industry as a whole, and unable to monitor and adjust market changes in a timely and effective manner. In addition, the company's internal decision-making and analysis capabilities are weak, and the capabilities of data analysts are uneven, resulting in a time-consuming and labor-intensive analysis process, and it is difficult to find the root cause of the problem. After the institutional analysis is completed, the golden time for market development may have been missed. It can be seen that the traditional insurance auto insurance business monitoring methods often have problems such as incomplete data collection, slow processing speed, lack of external industry data comparison, and inaccurate early warnings, which are difficult to meet the needs of modern auto insurance business management. Summary of the invention

[0003] In view of this, the purpose of the present invention is to provide a method, device, equipment and storage medium for monitoring and warning of automobile insurance, which can quickly perceive market changes by comparing internal data with external industry data, take corresponding measures and regularly trace the results to provide timely warnings. The specific scheme is as follows:

[0004] In a first aspect, the present application discloses a vehicle insurance monitoring and early warning method, which is applied to a vehicle insurance early warning platform, comprising:

[0005] Collecting external auto insurance business management data of the monitoring platform, comparing the local auto insurance business management data with the external auto insurance business management data, and determining the amount of change in the auto insurance business management data based on the comparison results;

[0006] If the change amount of the motor insurance business management data is greater than a preset change amount threshold, a warning task corresponding to the change amount of the motor insurance business management data is generated according to a preset large model, and the warning task is pushed to a task processing end, so that the task processing end generates a target solution corresponding to the warning task based on the warning task;

[0007] Execute the target solution, and perform data backtracking on the monitoring platform and the auto insurance early warning platform, so as to determine whether the change amount of the current auto insurance business management data is greater than the preset change amount threshold according to the obtained current external auto insurance business management data and the current local auto insurance business management data, and obtain the current comparison result;

[0008] Determine whether to issue a vehicle insurance warning based on the current comparison result.

[0009] Optionally, the external auto insurance business management data of the acquisition monitoring platform is compared with the local auto insurance business management data and the external auto insurance business management data, and the change amount of the auto insurance business management data is determined according to the comparison result, including:

[0010] Collecting external auto insurance business management data of the monitoring platform through a local preset large model, and analyzing the external auto insurance business management data to determine target external auto insurance business management data corresponding to preset indicators in the external auto insurance business management data;

[0011] Extract the local auto insurance operation and management data corresponding to the preset indicator in the auto insurance early warning platform, and compare the local auto insurance operation and management data with the target external auto insurance operation and management data to determine the change in auto insurance operation and management data between the local auto insurance operation and management data and the target external auto insurance operation and management data.

[0012] Optionally, if the change amount of the motor insurance business management data is greater than a preset change amount threshold, a warning task corresponding to the change amount of the motor insurance business management data is generated according to a preset large model, and the warning task is pushed to a task processing end, so that the task processing end generates a target solution corresponding to the warning task based on the warning task, including:

[0013] Comparing the change amount of the motor vehicle insurance business management data with a stepped preset change amount threshold to determine a warning level corresponding to the change amount of the motor vehicle insurance business management data;

[0014] A warning task corresponding to the warning level is generated according to the preset large model, and the warning task is pushed to the task processing end so that the task processing end can generate a pending review solution corresponding to the warning task, and use the pending review solution as the target solution after receiving the review approval notification corresponding to the pending review solution.

[0015] Optionally, executing the target solution and tracing back data on the monitoring platform and the vehicle insurance warning platform includes:

[0016] Executing the target solution to adjust the local auto insurance business management data;

[0017] If the target solution is executed, the current external auto insurance operation and management data is re-collected from the monitoring platform according to the preset data backtracking frequency, and the current local auto insurance operation and management data corresponding to the preset indicators is obtained.

[0018] Optionally, the step of determining whether the change amount of the current motor insurance operation and management data is greater than the preset change amount threshold according to the obtained current external motor insurance operation and management data and the current local motor insurance operation and management data, and obtaining the current comparison result, includes:

[0019] Extracting current target external auto insurance business management data corresponding to the preset indicator from the current external auto insurance business management data;

[0020] Comparing the current target external motor insurance operation and management data with the current local motor insurance operation and management data to determine a change in the current motor insurance operation and management data;

[0021] Determine whether the change in the current motor insurance business management data is greater than the preset change threshold. If the change in the current motor insurance business management data is greater than the preset change threshold, generate a first current comparison result; if the change in the current motor insurance business management data is not greater than the preset change threshold, generate a second current comparison result.

[0022] Optionally, determining whether to issue a vehicle insurance warning based on the current comparison result includes:

[0023] If the current comparison result is the first current comparison result, jump to the step of executing the target solution and performing data backtracking on the monitoring platform and the vehicle insurance warning platform to perform the next round of data backtracking and record the number of data backtracking;

[0024] If the number of data backtracking is greater than the preset data backtracking threshold, the data backtracking is terminated, and it is determined whether the current motor insurance business management data change is greater than the preset change threshold according to the current comparison result. If the current motor insurance business management data change is greater than the preset change threshold, a motor insurance warning is issued;

[0025] Or, if the current comparison result is the second current comparison result, data backtracking is terminated.

[0026] Optionally, the warning method of the car insurance warning is to generate a car insurance warning email and send the car insurance warning email to a preset mailbox.

[0027] In a second aspect, the present application discloses a vehicle insurance monitoring and early warning device, which is applied to a vehicle insurance early warning platform, comprising:

[0028] A data comparison module is used to collect external auto insurance business management data of the monitoring platform, compare the local auto insurance business management data with the external auto insurance business management data, and determine the change amount of the auto insurance business management data according to the comparison result;

[0029] A solution generation module is used to generate a warning task corresponding to the change amount of the auto insurance business management data according to a preset large model if the change amount of the auto insurance business management data is greater than a preset change amount threshold, and push the warning task to the task processing end so that the task processing end generates a target solution corresponding to the warning task based on the warning task;

[0030] A data backtracking module is used to execute the target solution and perform data backtracking on the monitoring platform and the auto insurance early warning platform, so as to determine whether the change amount of the current auto insurance business management data is greater than the preset change amount threshold according to the obtained current external auto insurance business management data and the current local auto insurance business management data, and obtain the current comparison result;

[0031] The vehicle insurance warning module is used to determine whether to issue a vehicle insurance warning based on the current comparison result.

[0032] In a third aspect, the present application discloses an electronic device, comprising:

[0033] Memory, used to store computer programs;

[0034] The processor is used to execute the computer program to implement the aforementioned vehicle insurance monitoring and early warning method.

[0035] In a fourth aspect, the present application discloses a computer-readable storage medium for storing a computer program, wherein the computer program, when executed by a processor, implements the aforementioned vehicle risk monitoring and early warning method.

[0036] In the present application, firstly, the external auto insurance operation and management data of the monitoring platform is collected, and the local auto insurance operation and management data and the external auto insurance operation and management data are compared, and the change amount of the auto insurance operation and management data is determined according to the comparison result. If the change amount of the auto insurance operation and management data is greater than the preset change amount threshold, a warning task corresponding to the change amount of the auto insurance operation and management data is generated according to the preset large model, and the warning task is pushed to the task processing end, so that the task processing end generates a target solution corresponding to the warning task based on the warning task, and then executes the target solution, and performs data backtracking on the monitoring platform and the auto insurance warning platform, so as to judge whether the change amount of the current auto insurance operation and management data is greater than the preset change amount threshold according to the current external auto insurance operation and management data and the current local auto insurance operation and management data, and obtain the current comparison result, and finally determine whether to issue an auto insurance warning based on the current comparison result. It can be seen that through the method of this application, the local auto insurance business management data and the external auto insurance business management data of the monitoring platform can be compared to determine the change in the auto insurance business management data. If the change in the auto insurance business management data is greater than the preset change threshold, an early warning task corresponding to the change in the auto insurance business management data is generated and pushed to the task processing end, so that the task processing end can generate the corresponding target solution, execute the target solution, and perform data backtracking on the monitoring platform and the auto insurance early warning platform to determine whether the current change in the auto insurance business management data is greater than the preset change threshold. Finally, it can be determined whether to issue an auto insurance early warning based on the current comparison results. In this way, by comparing internal data with external industry data, it is possible to quickly perceive market changes, take corresponding measures and regularly trace back the results to monitor key indicators and issue timely early warnings. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0038] Figure 1 A flow chart of a vehicle insurance monitoring and early warning method disclosed in this application;

[0039] Figure 2 A timing diagram of a vehicle insurance monitoring and early warning method disclosed in this application;

[0040] Figure 3 This is a structural schematic diagram of a vehicle insurance monitoring and warning device disclosed in this application;

[0041] Figure 4This is a structural diagram of an electronic device disclosed in this application. DETAILED DESCRIPTION

[0042] 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 only 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.

[0043] In the existing technology, traditional insurance auto insurance business monitoring methods often have problems such as incomplete data collection, slow processing speed, lack of external industry data comparison, inaccurate early warning, etc., which are difficult to meet the needs of modern auto insurance business management.

[0044] In order to overcome the above-mentioned technical problems, the present application discloses a motor vehicle insurance monitoring and early warning method, device, equipment and storage medium, which can quickly perceive market changes by comparing internal data with external industry data, take corresponding measures and regularly trace back the results to provide timely early warnings.

[0045] See also Figure 1 As shown, the embodiment of the present invention discloses a vehicle insurance monitoring and early warning method, which is applied to a vehicle insurance early warning platform, comprising:

[0046] Step S11, collecting external auto insurance business management data of the monitoring platform, comparing the local auto insurance business management data with the external auto insurance business management data, and determining the change amount of the auto insurance business management data according to the comparison result.

[0047] In this embodiment, it is necessary to collect external auto insurance business management data of the monitoring platform, among which the various sections of the monitoring platform are mainly monitored, such as the development section, the cost section, etc. The monitored external auto insurance business management data mainly include industry benchmarking index, new energy, household car autonomy coefficient, policy cost rate, expected claim rate, sales expense rate and other data, and the external auto insurance business management data of the monitoring platform can be collected through a local preset large model, and the collected external auto insurance business management data can be analyzed to determine the target external auto insurance business management data corresponding to the preset indicators in the external auto insurance business management data according to the analysis results obtained by the analysis. It should be noted that the preset indicators are the key indicators among several types of monitoring data set by the user, which can be set by the user according to the needs of the user and are not specifically limited in this application. Therefore, the target external auto insurance business management data corresponding to the preset indicators can be extracted from the external auto insurance business management data.

[0048] Furthermore, it is also necessary to extract local auto insurance business management data corresponding to preset indicators from the auto insurance early warning platform. For example, if the preset indicators are average compensation per case, accident rate, and average premium per policy, it is necessary to extract local auto insurance business management data corresponding to the preset indicators from the local area, and then compare the local auto insurance business management data with the target external auto insurance business management data, and determine the change in auto insurance business management data corresponding to the preset indicators between the local auto insurance business management data and the target external auto insurance business management data based on the comparison results. In this way, preset indicators can be set according to the data that users need to monitor, so that the final monitoring and early warning results are consistent with user needs, and the operation status and market dynamics of the auto insurance business can be accurately reflected based on the collection, processing, analysis and mining of massive data, ensuring a quick and accurate grasp of the business status.

[0049] Step S12: If the change in the motor insurance business management data is greater than a preset change threshold, a warning task corresponding to the change in the motor insurance business management data is generated according to a preset large model, and the warning task is pushed to the task processing end so that the task processing end generates a target solution corresponding to the warning task based on the warning task.

[0050] In this embodiment, it is necessary to compare the change amount of the auto insurance business management data with the stepped preset change amount threshold to determine the warning level corresponding to the change amount of the auto insurance business management data, such as Figure 2 As shown, if the change amount of the auto insurance business management data is greater than the first preset change amount threshold, the warning level is characterized as a general warning. If the change amount of the auto insurance business management data is greater than the second preset change amount threshold, the warning level is characterized as a general warning. If the change amount of the auto insurance business management data is greater than the third preset change amount threshold, the warning level is characterized as a serious warning. Then, it is necessary to generate a warning task corresponding to the warning level according to the preset large model, and push the warning task to the task processing end, so that the task processing end can formulate a solution to be reviewed corresponding to the warning task after receiving the warning task, and then review the solution to be reviewed. If the review fails, the warning level of the current warning task may not be consistent with the warning task itself, and it needs to be returned to the stage of generating the warning task. If the review passes, it is necessary to use the solution to be reviewed as the target solution, or conduct a secondary review of the warning task, so that the solution to be reviewed can be used as the target solution after the secondary review passes. In this way, the corresponding warning task can be generated according to the warning level corresponding to the change amount of the auto insurance business management data, and the corresponding solution can be generated according to the warning task to ensure the accuracy of the warning.

[0051] Step S13, execute the target solution, and perform data backtracking on the monitoring platform and the auto insurance early warning platform to determine whether the change in the current auto insurance business management data is greater than the preset change threshold based on the current external auto insurance business management data and the current local auto insurance business management data, and obtain the current comparison result.

[0052] In this embodiment, it is necessary to execute the target solution to adjust the local auto insurance business management data. It should be noted that the target solution is a solution for adjusting the local auto insurance business management data. Therefore, after executing the target solution, the local auto insurance business management data may change. If the target solution is executed, data backtracking can be performed according to the preset data backtracking frequency to re-collect the current external auto insurance business management data from the monitoring platform according to the preset data backtracking frequency, and obtain the current local auto insurance business management data corresponding to the preset indicators. It should be further noted that backtracking can be automatically performed according to the preset data backtracking frequency set by the auditor, such as backtracking at a frequency of days, weeks, months, etc., to re-collect the current external auto insurance business management data of the monitoring platform and the local current local auto insurance business management data corresponding to the preset indicators.

[0053] Furthermore, it is necessary to extract the current target external auto insurance management data corresponding to the preset index from the current external auto insurance management data, and then compare the current target external auto insurance management data and the current local auto insurance management data to determine the change in the current auto insurance management data, and then determine whether the change in the current auto insurance management data is greater than the preset change threshold. If the change in the current auto insurance management data is greater than the preset change threshold, it indicates that the effect after executing the target solution is not obvious, and then a first current comparison result is generated. If the change in the current auto insurance management data is not greater than the preset change threshold, it indicates that the effect after executing the target solution is effective, and then a second current comparison result is generated. It should be noted that after a data backtracking, the current comparison result obtained can be added to the warning task, so that when the next warning task is generated, the warning level can be increased to generate a warning task that matches the warning level, and then the task status can be changed to backtracking monitoring, so that the corresponding responsible person can see the backtracking information of the task.

[0054] Step S14: Determine whether to issue a vehicle insurance warning based on the current comparison result.

[0055] In this embodiment, it can be determined whether to issue a car insurance warning based on the current comparison result. Specifically, if the current comparison result is the first current comparison result, it indicates that the effect of the target solution is not obvious, and it is necessary to jump to the step of executing the target solution and tracing back the data of the monitoring platform and the car insurance warning platform to perform the next round of data tracing back and record the number of data tracing back. If the number of tracing back is greater than the preset data tracing back threshold, the data tracing back can be ended. It should be noted that the preset data tracing back threshold can be set according to user needs. In this embodiment, it is set to three times to determine whether the current car insurance business management data change is greater than the preset change threshold based on the current comparison result obtained after the data is traced back three times. If the current car insurance business management data change is still greater than the preset change threshold, it indicates that the solutions generated by the three data tracing backs are invalid and a car insurance warning is required. In another case, if the current comparison result is the second current comparison result, it indicates that the target solution generated by the first data tracing back is effective, and there is no need to perform the next data tracing back.

[0056] It can be seen that in this embodiment, the local auto insurance business management data and the external auto insurance business management data of the monitoring platform can be compared to determine the change in the auto insurance business management data. If the change in the auto insurance business management data is greater than the preset change threshold, a warning task corresponding to the change in the auto insurance business management data is generated and pushed to the task processing end, so that the task processing end can generate the corresponding target solution, execute the target solution, and perform data backtracking on the monitoring platform and the auto insurance warning platform to determine whether the current change in the auto insurance business management data is greater than the preset change threshold. Finally, it can be determined whether to issue an auto insurance warning based on the current comparison result. In this way, on the one hand, the operating status and market dynamics of the auto insurance business can be accurately reflected based on the collection, processing, analysis and mining of massive data, ensuring a quick and accurate grasp of the business status; on the other hand, corresponding warning tasks can be generated according to the warning levels corresponding to the changes in the auto insurance business management data, and corresponding solutions can be generated based on the warning tasks to ensure the accuracy of the warnings; on the other hand, the results can be traced back according to the traceability frequency set by the auditors, and the comparison between the traceability results and the expected targets can be recorded to detect the execution effect of the formulated plan. For tasks that have failed to achieve the expected targets for many times, the warning task level can be upgraded to attract the attention and intervention of higher levels, effectively ensuring the accuracy of the warnings.

[0057] See also Figure 3 As shown, the embodiment of the present invention discloses a vehicle insurance monitoring and early warning device, which is applied to a vehicle insurance early warning platform, including:

[0058] The data comparison module 11 is used to collect the external auto insurance business management data of the monitoring platform, compare the local auto insurance business management data with the external auto insurance business management data, and determine the change amount of the auto insurance business management data according to the comparison result;

[0059] A solution generation module 12 is used to generate a warning task corresponding to the change amount of the auto insurance business management data according to a preset large model if the change amount of the auto insurance business management data is greater than a preset change amount threshold, and push the warning task to the task processing end so that the task processing end generates a target solution corresponding to the warning task based on the warning task;

[0060] The data backtracking module 13 is used to execute the target solution and perform data backtracking on the monitoring platform and the auto insurance early warning platform, so as to determine whether the change amount of the current auto insurance business management data is greater than the preset change amount threshold value according to the obtained current external auto insurance business management data and the current local auto insurance business management data, and obtain the current comparison result;

[0061] The vehicle risk warning module 14 is used to determine whether to issue a vehicle risk warning based on the current comparison result.

[0062] In this embodiment, the external auto insurance business management data of the monitoring platform is first collected, the local auto insurance business management data and the external auto insurance business management data are compared, and the change in the auto insurance business management data is determined based on the comparison result. If the change in the auto insurance business management data is greater than a preset change threshold, a warning task corresponding to the change in the auto insurance business management data is generated according to a preset large model, and the warning task is pushed to the task processing end, so that the task processing end generates a target solution corresponding to the warning task based on the warning task, and then executes the target solution, and performs data backtracking on the monitoring platform and the auto insurance warning platform to determine whether the change in the current auto insurance business management data is greater than the preset change threshold based on the current external auto insurance business management data and the current local auto insurance business management data, and obtain the current comparison result, and finally determine whether to issue an auto insurance warning based on the current comparison result. It can be seen that through the method of this application, the local auto insurance business management data and the external auto insurance business management data of the monitoring platform can be compared to determine the change in the auto insurance business management data. If the change in the auto insurance business management data is greater than the preset change threshold, an early warning task corresponding to the change in the auto insurance business management data is generated and pushed to the task processing end, so that the task processing end can generate the corresponding target solution, execute the target solution, and perform data backtracking on the monitoring platform and the auto insurance early warning platform to determine whether the current change in the auto insurance business management data is greater than the preset change threshold. Finally, it can be determined whether to issue an auto insurance early warning based on the current comparison results. In this way, by comparing internal data with external industry data, it is possible to quickly perceive market changes, take corresponding measures and regularly trace back the results to monitor key indicators and issue timely early warnings.

[0063] In some embodiments, the data comparison module 11 may specifically include:

[0064] A data analysis unit, used to collect external auto insurance business management data of the monitoring platform through a local preset large model, and analyze the external auto insurance business management data to determine target external auto insurance business management data corresponding to preset indicators in the external auto insurance business management data;

[0065] A data comparison unit is used to extract local auto insurance operation and management data corresponding to the preset indicators in the auto insurance early warning platform, and compare the local auto insurance operation and management data with the target external auto insurance operation and management data to determine the change in auto insurance operation and management data between the local auto insurance operation and management data and the target external auto insurance operation and management data.

[0066] In some embodiments, the solution generation module 12 may specifically include:

[0067] An early warning level determination unit, used to compare the change amount of the motor vehicle insurance business management data with a stepped preset change amount threshold to determine the early warning level corresponding to the change amount of the motor vehicle insurance business management data;

[0068] A solution generation unit is used to generate a warning task corresponding to the warning level according to the preset large model, and push the warning task to the task processing end so that the task processing end can generate a pending review solution corresponding to the warning task, and use the pending review solution as the target solution after receiving the review approval notification corresponding to the pending review solution.

[0069] In some embodiments, the data backtracking module 13 may specifically include:

[0070] A solution execution unit, used for executing the target solution to adjust the local auto insurance business management data;

[0071] The data backtracking unit is used to re-collect the current external motor insurance operation and management data from the monitoring platform according to the preset data backtracking frequency if the target solution is executed, and obtain the current local motor insurance operation and management data corresponding to the preset indicators.

[0072] In some embodiments, the data backtracking module 13 may specifically include:

[0073] A data extraction unit, used to extract current target external auto insurance business management data corresponding to the preset index from the current external auto insurance business management data;

[0074] A data comparison unit, used to compare the current target external motor insurance business management data and the current local motor insurance business management data to determine the change amount of the current motor insurance business management data;

[0075] The comparison and judgment unit is used to judge whether the change in the current motor insurance business management data is greater than the preset change threshold. If the change in the current motor insurance business management data is greater than the preset change threshold, a first current comparison result is generated; if the change in the current motor insurance business management data is not greater than the preset change threshold, a second current comparison result is generated.

[0076] In some embodiments, the vehicle risk warning module 14 may specifically include:

[0077] A data backtracking unit, configured to jump to the step of executing the target solution and performing data backtracking on the monitoring platform and the vehicle insurance warning platform if the current comparison result is the first current comparison result, so as to perform the next round of data backtracking and record the number of data backtracking;

[0078] an early warning unit, configured to terminate data backtracking if the number of data backtracking times is greater than a preset data backtracking threshold, and determine whether the change amount of the current motor insurance business management data is greater than the preset change amount threshold according to the current comparison result, and issue a motor insurance early warning if the change amount of the current motor insurance business management data is greater than the preset change amount threshold;

[0079] The backtracking ending unit is used to end data backtracking if the current comparison result is the second current comparison result.

[0080] Furthermore, the present application also discloses an electronic device. Figure 4 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content in the diagram cannot be regarded as any limitation on the scope of use of the present application.

[0081] Figure 4 The present invention provides a schematic diagram of the structure of an electronic device 20 provided in an embodiment of the present application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 is used to store a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the vehicle risk monitoring and early warning method disclosed in any of the aforementioned embodiments. In addition, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0082] In this embodiment, the power supply 23 is used to provide working voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and the external device, and the communication protocol it follows is any communication protocol that can be applied to the technical solution of the present application, and is not specifically limited here; the input and output interface 25 is used to obtain external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs and is not specifically limited here.

[0083] In addition, the memory 22 as a carrier for resource storage may be a read-only memory, a random access memory, a disk or an optical disk, etc. The resources stored thereon may include an operating system 221, a computer program 222, etc., and the storage method may be temporary storage or permanent storage.

[0084] The operating system 221 is used to manage and control the hardware devices and computer programs 222 on the electronic device 20, and can be Windows Server, Netware, Unix, Linux, etc. In addition to the computer program that can be used to complete the vehicle insurance monitoring and early warning method performed by the electronic device 20 disclosed in any of the aforementioned embodiments, the computer program 222 can further include computer programs that can be used to complete other specific tasks.

[0085] Furthermore, the present application also discloses a computer-readable storage medium for storing a computer program; wherein the computer program, when executed by a processor, implements the aforementioned disclosed vehicle insurance monitoring and early warning method. The specific steps of the method can refer to the corresponding contents disclosed in the aforementioned embodiments, and will not be repeated here.

[0086] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0087] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0088] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0089] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0090] The technical solution provided by the present application is introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea. At the same time, for general technicians in this field, according to the idea of ​​the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A vehicle insurance monitoring and early warning method, characterized in that: Applied to the auto insurance early warning platform, including: Collecting external auto insurance business management data of the monitoring platform, comparing the local auto insurance business management data with the external auto insurance business management data, and determining the amount of change in the auto insurance business management data based on the comparison results; If the change amount of the motor insurance business management data is greater than a preset change amount threshold, a warning task corresponding to the change amount of the motor insurance business management data is generated according to a preset large model, and the warning task is pushed to a task processing end, so that the task processing end generates a target solution corresponding to the warning task based on the warning task; Execute the target solution, and perform data backtracking on the monitoring platform and the auto insurance early warning platform, so as to determine whether the change amount of the current auto insurance business management data is greater than the preset change amount threshold according to the obtained current external auto insurance business management data and the current local auto insurance business management data, and obtain the current comparison result; Determine whether to issue a vehicle insurance warning based on the current comparison result.

2. The vehicle risk monitoring and early warning method according to claim 1 is characterized in that: The external auto insurance business management data of the acquisition monitoring platform is compared with the local auto insurance business management data and the external auto insurance business management data, and the change amount of the auto insurance business management data is determined according to the comparison result, including: Collecting external auto insurance business management data of the monitoring platform through a local preset large model, and analyzing the external auto insurance business management data to determine target external auto insurance business management data corresponding to preset indicators in the external auto insurance business management data; Extract the local auto insurance operation and management data corresponding to the preset indicator in the auto insurance early warning platform, and compare the local auto insurance operation and management data with the target external auto insurance operation and management data to determine the change in auto insurance operation and management data between the local auto insurance operation and management data and the target external auto insurance operation and management data.

3. The vehicle risk monitoring and early warning method according to claim 1, characterized in that: If the change amount of the motor insurance business management data is greater than a preset change amount threshold, a warning task corresponding to the change amount of the motor insurance business management data is generated according to a preset large model, and the warning task is pushed to a task processing end so that the task processing end generates a target solution corresponding to the warning task based on the warning task, including: Comparing the change amount of the motor vehicle insurance business management data with a stepped preset change amount threshold to determine a warning level corresponding to the change amount of the motor vehicle insurance business management data; A warning task corresponding to the warning level is generated according to the preset large model, and the warning task is pushed to the task processing end so that the task processing end can generate a pending review solution corresponding to the warning task, and use the pending review solution as the target solution after receiving the review approval notification corresponding to the pending review solution.

4. The vehicle risk monitoring and early warning method according to claim 2 is characterized in that: The executing the target solution and tracing back the data of the monitoring platform and the vehicle insurance warning platform include: Executing the target solution to adjust the local auto insurance business management data; If the target solution is executed, the current external auto insurance operation and management data is re-collected from the monitoring platform according to the preset data backtracking frequency, and the current local auto insurance operation and management data corresponding to the preset indicators is obtained.

5. The vehicle risk monitoring and early warning method according to claim 4 is characterized in that: The step of determining whether the change amount of the current motor insurance operation and management data is greater than the preset change amount threshold according to the obtained current external motor insurance operation and management data and the current local motor insurance operation and management data, and obtaining the current comparison result, includes: Extracting current target external auto insurance business management data corresponding to the preset indicator from the current external auto insurance business management data; Comparing the current target external motor insurance operation and management data with the current local motor insurance operation and management data to determine a change in the current motor insurance operation and management data; Determine whether the change in the current motor insurance business management data is greater than the preset change threshold. If the change in the current motor insurance business management data is greater than the preset change threshold, generate a first current comparison result; if the change in the current motor insurance business management data is not greater than the preset change threshold, generate a second current comparison result.

6. The vehicle risk monitoring and early warning method according to claim 5, characterized in that: The determining whether to issue a vehicle insurance warning based on the current comparison result includes: If the current comparison result is the first current comparison result, jump to the step of executing the target solution and performing data backtracking on the monitoring platform and the vehicle insurance warning platform to perform the next round of data backtracking and record the number of data backtracking; If the number of data backtracking is greater than the preset data backtracking threshold, the data backtracking is terminated, and it is determined whether the current motor insurance business management data change is greater than the preset change threshold according to the current comparison result. If the current motor insurance business management data change is greater than the preset change threshold, a motor insurance warning is issued; Or, if the current comparison result is the second current comparison result, data backtracking is terminated.

7. The vehicle risk monitoring and early warning method according to any one of claims 1 to 6, characterized in that: The warning method of the car insurance warning is to generate a car insurance warning email and send the car insurance warning email to a preset mailbox.

8. A vehicle insurance monitoring and warning device, characterized in that: Applied to the auto insurance early warning platform, including: A data comparison module is used to collect external auto insurance business management data of the monitoring platform, compare the local auto insurance business management data with the external auto insurance business management data, and determine the change amount of the auto insurance business management data according to the comparison result; A solution generation module is used to generate a warning task corresponding to the change amount of the auto insurance business management data according to a preset large model if the change amount of the auto insurance business management data is greater than a preset change amount threshold, and push the warning task to the task processing end so that the task processing end generates a target solution corresponding to the warning task based on the warning task; A data backtracking module is used to execute the target solution and perform data backtracking on the monitoring platform and the auto insurance early warning platform, so as to determine whether the change amount of the current auto insurance business management data is greater than the preset change amount threshold according to the obtained current external auto insurance business management data and the current local auto insurance business management data, and obtain the current comparison result; The vehicle insurance warning module is used to determine whether to issue a vehicle insurance warning based on the current comparison result.

9. An electronic device, characterized in that: include: Memory, used to store computer programs; A processor is used to execute the computer program to implement the vehicle risk monitoring and early warning method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: Used to store a computer program, wherein when the computer program is executed by a processor, the vehicle risk monitoring and early warning method as described in any one of claims 1 to 7 is implemented.

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