CN112434945A - Automobile risk assessment method, device and equipment and computer readable storage medium - Google Patents
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Abstract
The invention discloses an automobile risk assessment method, an automobile risk assessment device, automobile risk assessment equipment and a computer readable storage medium, wherein the automobile risk assessment method comprises the following steps: determining the vehicle brand of a vehicle to be evaluated, determining all negative evaluation indexes based on the negative evaluation dimensionality corresponding to the vehicle brand, and calculating a negative evaluation score corresponding to each negative evaluation index; determining all positive evaluation indexes based on the positive evaluation dimensions corresponding to the vehicle brand, and calculating a positive evaluation score corresponding to each positive evaluation index; and determining the risk level of the vehicle to be evaluated according to the negative evaluation score and the positive evaluation score, and executing a risk strategy corresponding to the risk level. The method improves the accuracy of the automobile risk assessment.
Description
Technical Field
The invention relates to the technical field of science and technology finance (Fintech), in particular to a method, a device and equipment for evaluating automobile risk and a computer readable storage medium.
Background
At present, in the process of examining and approving the automobile financial loan, financial institutions such as banks generally evaluate and analyze data such as the vehicle price of a passenger vehicle, vehicle filing, violation inquiry, vehicle history report and the like in an automobile, but do not evaluate the dimension of an automobile brand, and cannot quantify and monitor the value and the risk degree of the automobile brand in real time. The loan admission to the high-risk automobile brand may cause the rapid depreciation of the automobile and cause the risk of residual value evaluation, i.e. the evaluation result of financial institutions such as banks is distorted, the accuracy of the automobile risk evaluation is reduced, and the risk cannot be effectively avoided.
Disclosure of Invention
The invention mainly aims to provide a method, a device and equipment for evaluating automobile risk and a computer readable storage medium, aiming at solving the technical problem of how to improve the accuracy of automobile risk evaluation.
In order to achieve the above object, the present invention provides an automobile risk assessment method, apparatus, device and computer readable storage medium, wherein the automobile risk assessment method comprises:
determining the vehicle brand of a vehicle to be evaluated, determining all negative evaluation indexes based on the negative evaluation dimensionality corresponding to the vehicle brand, and calculating a negative evaluation score corresponding to each negative evaluation index;
determining all positive evaluation indexes based on the positive evaluation dimensions corresponding to the vehicle brand, and calculating a positive evaluation score corresponding to each positive evaluation index;
and determining the risk level of the vehicle to be evaluated according to the negative evaluation score and the positive evaluation score, and executing a risk strategy corresponding to the risk level.
Optionally, the step of determining all negative evaluation indexes based on the negative evaluation dimension corresponding to the vehicle brand, and calculating a negative evaluation score corresponding to each negative evaluation index includes:
determining all basic operation information of the license plate brand in enterprise information corresponding to the vehicle brand, and taking the basic operation information as a negative evaluation index;
and acquiring negative sub-evaluation scores corresponding to the negative evaluation indexes in a preset evaluation score comparison table, calculating a first sum of the negative sub-evaluation scores, and taking the first sum as the negative evaluation score.
Optionally, the negative assessment indicators include sales capacity, quality consensus, brand management, and vehicle type at risk.
Optionally, the step of determining all positive evaluation indexes based on the positive evaluation dimensions corresponding to the vehicle brand, and calculating the positive evaluation score corresponding to each positive evaluation index includes:
determining enterprise information corresponding to the vehicle brand, determining enterprise qualification information in the enterprise information and vehicle brand quality information associated with the vehicle brand, and taking the enterprise qualification information and the vehicle brand quality information as positive evaluation indexes;
and acquiring the positive sub-evaluation scores corresponding to the positive evaluation indexes in a preset evaluation score comparison table, calculating a second sum of the positive sub-evaluation scores, and taking the second sum as the positive evaluation score.
Optionally, the positive assessment indicators include financial indicators, sales capacity, business quality, user public praise, market position, and quality indicators.
Optionally, the step of determining the risk level of the vehicle to be assessed according to the negative evaluation score and the positive evaluation score includes:
detecting whether the negative evaluation score is larger than a first preset threshold value;
if the negative evaluation score is smaller than or equal to a first preset threshold, detecting whether the positive evaluation score is larger than a second preset threshold;
and if the positive evaluation score is larger than a second preset threshold value, determining that the risk level of the vehicle to be evaluated is a low risk level.
Optionally, the step of detecting whether the negative evaluation score is greater than a first preset threshold includes:
and if the negative evaluation score is larger than a first preset threshold value, determining that the risk level of the vehicle to be evaluated is a high risk level.
In addition, to achieve the above object, the present invention also provides an automobile risk assessment apparatus, including:
the first calculation module is used for determining the vehicle brand of a vehicle to be evaluated, determining all negative evaluation indexes based on the negative evaluation dimensionality corresponding to the vehicle brand, and calculating the negative evaluation score corresponding to each negative evaluation index;
the second calculation module is used for determining all front evaluation indexes based on the front evaluation dimensionality corresponding to the vehicle brand and calculating front evaluation scores corresponding to the front evaluation indexes;
and the execution module is used for determining the risk level of the vehicle to be evaluated according to the negative evaluation score and the positive evaluation score and executing a risk strategy corresponding to the risk level.
In addition, in order to achieve the purpose, the invention also provides automobile risk assessment equipment;
the automobile risk assessment device includes: a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein:
the computer program, when executed by the processor, implements the steps of the automotive risk assessment method as described above.
In addition, to achieve the above object, the present invention also provides a computer-readable storage medium;
the computer-readable storage medium has stored thereon a computer program which, when being executed by a processor, carries out the steps of the automobile risk assessment method as described above.
According to the method, the vehicle brand of a vehicle to be evaluated is determined, all negative evaluation indexes are determined based on the negative evaluation dimension corresponding to the vehicle brand, and the negative evaluation score corresponding to each negative evaluation index is calculated; determining all positive evaluation indexes based on the positive evaluation dimensions corresponding to the vehicle brand, and calculating a positive evaluation score corresponding to each positive evaluation index; and determining the risk level of the vehicle to be evaluated according to the negative evaluation score and the positive evaluation score, and executing a risk strategy corresponding to the risk level. The method comprises the steps of determining all negative evaluation indexes and positive evaluation indexes of vehicle evaluation of a vehicle to be evaluated, determining the risk level of the vehicle to be evaluated according to the negative evaluation scores corresponding to the negative evaluation indexes and the positive evaluation scores corresponding to the positive evaluation indexes, and executing a risk strategy corresponding to the risk level, so that the phenomena that the accuracy of the vehicle risk evaluation is reduced and the risk cannot be effectively avoided due to the fact that the vehicle risk evaluation cannot be carried out according to the vehicle brand in the prior art are avoided, the accuracy of the vehicle risk evaluation is improved, and the safety of data related to the vehicle to be evaluated is guaranteed.
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FIG. 1 is a schematic diagram of an automobile risk assessment device of a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart illustrating a first embodiment of the risk assessment method for a vehicle according to the present invention;
FIG. 3 is a schematic diagram of the device module of the risk assessment device for a vehicle according to the present invention;
FIG. 4 is a schematic flow chart illustrating the negative evaluation scores in the automobile risk evaluation method according to the present invention;
FIG. 5 is a schematic flow chart of positive evaluation scores in the automobile risk evaluation method of the present invention.
The objects, features and advantages of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 1, fig. 1 is a schematic diagram of an automobile risk assessment device of a hardware operating environment according to an embodiment of the present invention.
The terminal of the embodiment of the invention is automobile risk assessment equipment.
As shown in fig. 1, the terminal may include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, a communication bus 1002. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high-speed RAM memory or a non-volatile memory (e.g., a magnetic disk memory). The memory 1005 may alternatively be a storage device separate from the processor 1001.
Optionally, the terminal may further include a camera, a Radio Frequency (RF) circuit, a sensor, an audio circuit, a WiFi module, and the like. Such as light sensors, motion sensors, and other sensors. Specifically, the light sensor may include an ambient light sensor that adjusts the brightness of the display screen according to the brightness of ambient light, and a proximity sensor that turns off the display screen and/or the backlight when the terminal device is moved to the ear. Of course, the terminal device may also be configured with other sensors such as a gyroscope, a barometer, a hygrometer, a thermometer, and an infrared sensor, which are not described herein again.
Those skilled in the art will appreciate that the terminal structure shown in fig. 1 is not intended to be limiting and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
As shown in fig. 1, a memory 1005, which is a kind of computer storage medium, may include therein an operating system, a network communication module, a user interface module, and an automobile risk assessment program.
In the terminal shown in fig. 1, the network interface 1004 is mainly used for connecting to a backend server and performing data communication with the backend server; the user interface 1003 is mainly used for connecting a client (user side) and performing data communication with the client; and the processor 1001 may be configured to invoke the car risk assessment program stored in the memory 1005 and perform the following operations:
determining the vehicle brand of a vehicle to be evaluated, determining all negative evaluation indexes based on the negative evaluation dimensionality corresponding to the vehicle brand, and calculating a negative evaluation score corresponding to each negative evaluation index;
determining all positive evaluation indexes based on the positive evaluation dimensions corresponding to the vehicle brand, and calculating a positive evaluation score corresponding to each positive evaluation index;
and determining the risk level of the vehicle to be evaluated according to the negative evaluation score and the positive evaluation score, and executing a risk strategy corresponding to the risk level.
The invention provides an automobile risk assessment method, in a first embodiment of the automobile risk assessment method, referring to fig. 2, the automobile risk assessment method comprises the following steps:
step S10, determining the vehicle brand of the vehicle to be evaluated, determining all negative evaluation indexes based on the negative evaluation dimensionality corresponding to the vehicle brand, and calculating the negative evaluation score corresponding to each negative evaluation index;
the embodiment of the invention can be applied to a terminal or a server, and in the embodiment, the vehicle to be evaluated can be any one of a sedan, a passenger car, a truck, an off-road vehicle, a tractor, a dump truck, a special vehicle and a semitrailer. And the vehicle brand can be various automobile brands which are common at present, such as modern, Chevrolet, Buick, Toyota, Nissan and great wall.
Therefore, in this embodiment, after the vehicle to be evaluated, which needs to be subjected to risk evaluation, is determined, the vehicle brand of the vehicle to be evaluated is identified first, and the identification mode may be that characters input by a user are directly identified, or a computer performs image identification on an icon of the vehicle brand input by the user, and then the vehicle brand of the vehicle to be evaluated is determined according to an identification result.
After the vehicle brand is determined, the negative dimension of the vehicle brand needs to be evaluated, namely enterprise information of vehicles of the vehicle brand type is determined according to the vehicle brand, and negative evaluation indexes are determined in the enterprise information. The negative evaluation indexes comprise sales capacity, quality public sentiment, brand management and risk vehicle type. And the negative evaluation index is selected only by considering whether the vehicle brand can maintain basic normal operation, so that the basic operation information (namely the negative evaluation index) of the vehicle brand operation is only required to be acquired.
In the present embodiment, the sales capacity includes a train sales amount, which is the amount of the train sales in the previous year, and if the brand of vehicle is a vehicle for sale, the train sales amount is replaced with the amount of the train sales in the previous year, and if the brand of vehicle is an imported vehicle, the train sales amount is replaced with the global sales amount. In the present embodiment, the train sales amount is divided into five stages, and all of them are set in the evaluation score look-up table set in advance by the user. Namely the train sales is 1 point above 100000, 2 points above 50000-100000, 3 points above 20000-50000, 4 points above 10000-20000 and 5 points above 0-10000; and then comparing the acquired vehicle affiliation sales of the vehicle brand with the evaluation score comparison table to determine the score of the vehicle affiliation sales, namely the negative sub-evaluation score.
And the evaluation score comparison table further comprises quality public sentiments, and the quality public sentiments comprise vehicle series: the complaint amount of the website is in proportion; average website complaint amount of the same brand; 5-year value retention rate and quality evaluation. Vehicle system: the ratio of the complaint amount of the website to the complaint amount/sales amount in a preset time interval on the network can be divided into five grades: the ratio is 0-0.1% to obtain 1 point, 0.1-0.2% to obtain 2 points, 0.2-0.3% to obtain 3 points, 0.3-0.4% to obtain 4 points, and more than 0.4% to obtain 5 points. The average website complaint amount of the same brand of automobile department is the average value of the website complaint amounts of other automobile departments of the same brand of automobile. The 5-year value retention rate and quality evaluation are divided into 5 grades: the value retention rate is more than 50 percent and is divided into 1 point, 45 percent to 50 percent and is divided into 2 points, 40 percent to 45 percent and is divided into 3 points, 30 percent to 40 percent and is divided into 4 points, and 0 percent to 30 percent and is divided into 5 points. The quality evaluation is the number of hundred vehicle faults in the congestion period of 2-12 months, and the indexes are divided into 5 grades: the failure number is 100 to 1, 100 to 200 to 2, 200 to 300 to 3, 300 to 400 to 4, and 400 to 5.
And the evaluation score comparison table further comprises a brand operation, wherein the brand operation comprises the recent negative public sentiments and the negative public sentiments within half a year, such as: high management and departure, judges, legal disputes and the like, and each major negative public opinion is divided into 5 points; other risks are actual automobile quality or significant operational risks, such as risk warning announcements issued by quality control bureaus, and additional deductions for automobile recalls from manufacturers.
And the evaluation score comparison table also comprises a risk vehicle type, the risk vehicle type is from a risk vehicle type list, the data is from a client (calling sample size is 20 thousands) of assets in the gamma wind control system credit monitoring stock, and the ranking is carried out by combining repayment conditions after the brand, the vehicle system and the vehicle type are analyzed according to the assets in the monitoring. The index is divided into 5 grades, the score is 1 out of the risk vehicle type, the score is 2 out of 50-100, the score is 3 out of 20-50, the score is 4 out of 10-20, and the score is 5 out of 0-10.
In this embodiment, all negative evaluation indexes of the vehicle brand are compared with the evaluation score comparison table to determine negative sub-evaluation scores corresponding to the respective negative evaluation indexes, and then a sum of the respective negative sub-evaluation scores is calculated and used as the negative evaluation score. In addition, in this embodiment, in order to obtain a more accurate negative score (i.e., a negative evaluation score), different weights may be set for each negative evaluation index, as shown in fig. 4, the weight of the negative score is set to 100%, the weight of the sales capacity is set to 25% (including the weight of the sales volume of the train is 25%), the weight of the quality consensus is set to 45% (including the weight of the ratio of the complaints of the website of the train to 15%, the weight of the average complaint of the website of the same-brand train to 5%, the weight of the 5-year warranty rate to 20%, the weight of the quality evaluation to 5%), the weight of the brand operation is set to 20%, and the weight of the risk vehicle type is set to 10%. Then the negative assessment score 25% sales yields a negative sub-assessment score + 45% quality consensus negative sub-assessment score + 20% brand management negative sub-assessment score + 10% risk vehicle type negative sub-assessment score.
Step S20, determining all positive evaluation indexes based on the positive evaluation dimensions corresponding to the vehicle brand, and calculating the positive evaluation scores corresponding to the positive evaluation indexes;
in this embodiment, in addition to calculating the negative evaluation score of the vehicle brand, it is also necessary to calculate the positive evaluation score of the vehicle brand, that is, to evaluate the positive dimension of the vehicle brand, determine the enterprise information of the vehicle selling the vehicle of the vehicle brand type according to the vehicle brand, and obtain each positive evaluation index including financial index, sales capacity, enterprise quality, user public praise, market status and quality index from the enterprise information. And the financial indicators include net profit; the compound growth rate of three years; registered capital and capital strength. The sales capacity includes the train sales volume. The user public praise comprises a train: a user public praise score and a co-branded department rating score. Market positions include vehicle series indices. The quality index includes 5-year value-keeping rate and quality evaluation.
And each positive evaluation index is arranged in the evaluation score comparison table, and a positive sub-evaluation score corresponding to each positive evaluation index is arranged in the evaluation score comparison table. If the net profit in the financial index is the net profit of the previous year, the method is divided into five grades: net profit is 0-10 billion to 1, 10-50 billion to 2, 50-100 billion to 3, 100-1000 billion to 4, and more than 1000 billion to 5. The compound growth rate in the last three years is the compound growth rate of business income in the last three years, if no data in the last three years exists, the longest available data is taken, and the compound growth rate in the last three years is divided into five grades: the compound growth rate in the last three years is 1 point from 0 percent, 2 points from 0 percent to 5 percent, 3 points from 5 percent to 10 percent, 4 points from 10 percent to 20 percent and 5 points from 20 percent. The registered capital is divided into five grades: the registered capital is in the range of 0-10 billion 1, 10-50 billion 2, 50-100 billion 3, 100-1000 billion 4, and more than 1000 billion 5, and the capital strength index is given double weight when it is not available. The capital strength is the maximum value of the total assets, the net asset scale and the accumulated financing, and is divided into five grades: the capital strength is 0-100 billion 1 points, 100-500 billion 2 points, 500-1000 billion 3 points, 1000-10000 billion 4 points, and more than 10000 billion 5 points, and when the registered capital index is not available, the index is given double weight.
And the evaluation score comparison table is also provided with sales capacity and capacity of a positive evaluation dimension, the sales capacity and capacity comprise vehicle sales volume, the vehicle sales volume is the vehicle sales volume in the previous year, if the brand of vehicle is the parking fee, the vehicle sales volume is replaced by the vehicle sales volume in the previous year, and if the brand of vehicle is the import vehicle, the vehicle sales volume is replaced by the global sales volume. In this embodiment, the vehicle train sales amount is divided into five grades, the vehicle train sales amount is 0-10000 to 1 point, 10000 to 20000 to 2 points, 20000 to 50000 to 3 points, 50000 to 100000 to 4 points, and 100000 to 5 points.
And the evaluation score comparison table is also provided with the enterprise quality, namely if the enterprise is 500 points strong 4 in the world, 500 points strong 2 in the country, and if the enterprise is on the market, 1 point is added.
And the evaluation score comparison table is also provided with user public praise, which comprises the following vehicle systems: the user public praise score is a weighted average of user public praise scores of a vehicle network, such as a vehicle quality network, a home of a vehicle and a vehicle-easy network, wherein the vehicle is as follows: the user public praise score is divided into five grades: score <4 score 1 score, 4-4.2 score 2 score, 4.2-4.4 score 3 score, 4.4-4.6 score 4 score >4.6 score 5 score. Also includes the rating score of the same brand automobile series, namely the average value of the public praise scores of other automobile series users of the brand.
And the evaluation score comparison table is also provided with market positions which comprise a vehicle system index (the total annual sales volume of the vehicle system/the total annual sales volume of the enterprise to which the vehicle system belongs) × (the total annual sales volume of the vehicle system/the total annual sales volume of the subdivision type to which the vehicle system belongs), and the vehicle system index is 1 point obtained from 0 to 3 percent, 2 points obtained from 3 to 5 percent, 3 points obtained from 5 to 10 percent, 4 points obtained from 10 to 20 percent and 5 points obtained from 20 percent.
And the evaluation score comparison table is also provided with quality indexes comprising 5-year value-keeping rate, wherein the 5-year value-keeping rate is 1 score when the 5-year value-keeping rate is 0-30%, 2 score when the 5-year value-keeping rate is 30-40%, 3 score when the 40-year value-keeping rate is 40-45%, 4 score when the 5-year value-keeping rate is 45-50%, and 5 score when the 5-year value-keeping rate is more than 50%; the method also comprises quality evaluation, wherein the quality evaluation is the number of hundreds of vehicle faults in a vehicle congestion period of 2-12 months, and the index is divided into 5 grades: the failure number is 100 to 1, 100 to 200 to 2, 200 to 300 to 3, 300 to 400 to 4, and 400 to 5.
In this embodiment, all the positive evaluation indexes of the vehicle brand are compared with the evaluation score comparison table to determine the positive sub-evaluation scores corresponding to the respective positive evaluation indexes, and then the sum of the respective positive sub-evaluation scores is calculated and used as the positive evaluation score. And in the embodiment, in order to improve the more accurate positive score (i.e. positive evaluation score), different weights can be set for each positive evaluation index, as shown in fig. 5, the weight of the positive score is 100%, and the weight of the financial index is 20% (including the net profit 5% weight; the three-year composite growth rate 5% weight; the registered capital 5% weight and the capital strength 5% weight); weight of sales energy 35% (including vehicle sales 35% weight); the weight of the enterprise quality is 5%; a 15% weight of user public praise (including car family: 10% weight of user public praise rating score; 5% weight of same brand car family rating score); the weight of market status is 10% (including the weight of train system index is 10%) and the weight of quality index is 15% (including the weight of 5-year-keeping rate is 10% and the weight of quality evaluation is 5%). Namely, the positive evaluation score is 20% of the positive sub-evaluation score corresponding to the financial index + 35% of the positive sub-evaluation score corresponding to the sales capacity and + 5% of the business quality + 15% of the positive sub-evaluation score corresponding to the user public praise + 10% of the positive sub-evaluation score corresponding to the market status + 15% of the positive sub-evaluation score corresponding to the quality index.
And step S30, determining the risk level of the vehicle to be evaluated according to the negative evaluation score and the positive evaluation score, and executing a risk strategy corresponding to the risk level.
After the negative evaluation score and the positive evaluation score of the vehicle brand are obtained, whether the negative evaluation score is larger than a first preset threshold (namely an easy threshold set by a user in advance) or not can be judged, and if the negative evaluation score is larger than the first preset threshold, the risk level of the vehicle to be evaluated is determined to be a high risk level; if the negative evaluation score is smaller than or equal to a first preset threshold, detecting whether the positive evaluation score is larger than a second preset threshold, and if the positive evaluation score is larger than the second preset threshold, determining the risk level of the vehicle to be evaluated as a low risk level; and if the positive evaluation score is less than or equal to a second preset threshold, determining the risk grade of the vehicle to be evaluated as an intermediate risk grade. And if the risk level is a high risk level, suspending all loan operations related to the vehicle to be evaluated, namely executing a risk strategy corresponding to the high risk level. And if the risk grade is the middle risk grade, outputting corresponding prompt information, namely executing a risk strategy corresponding to the middle risk grade. And if the risk level is a low risk level, allowing all loan operations related to the vehicle to be evaluated, namely executing a risk strategy corresponding to the low risk level.
In the embodiment, by determining the vehicle brand of a vehicle to be evaluated, determining all negative evaluation indexes based on the negative evaluation dimensions corresponding to the vehicle brand, and calculating the negative evaluation score corresponding to each negative evaluation index; determining all positive evaluation indexes based on the positive evaluation dimensions corresponding to the vehicle brand, and calculating a positive evaluation score corresponding to each positive evaluation index; and determining the risk level of the vehicle to be evaluated according to the negative evaluation score and the positive evaluation score, and executing a risk strategy corresponding to the risk level. The method comprises the steps of determining all negative evaluation indexes and positive evaluation indexes of vehicle evaluation of a vehicle to be evaluated, determining the risk level of the vehicle to be evaluated according to the negative evaluation scores corresponding to the negative evaluation indexes and the positive evaluation scores corresponding to the positive evaluation indexes, and executing a risk strategy corresponding to the risk level, so that the phenomena that the accuracy of the vehicle risk evaluation is reduced and the risk cannot be effectively avoided due to the fact that the vehicle risk evaluation cannot be carried out according to the vehicle brand in the prior art are avoided, the accuracy of the vehicle risk evaluation is improved, and the safety of data related to the vehicle to be evaluated is guaranteed.
Further, on the basis of the first embodiment of the present invention, a second embodiment of the automobile risk assessment method is provided, where this embodiment is step S10 of the first embodiment of the present invention, the method includes the following steps of determining all negative assessment indexes based on the negative assessment dimensions corresponding to the vehicle brand, and calculating negative assessment scores corresponding to the negative assessment indexes, where the method includes:
step a, determining all basic operation information of the license plate brand in enterprise information corresponding to the vehicle brand, and taking the basic operation information as a negative evaluation index;
in this embodiment, after the license plate of the vehicle is determined, the enterprise information for selling the license plate type of the vehicle can be determined according to the brand of the vehicle, all basic operation information of the license plate number can be obtained from the enterprise information, and the basic operation information can be used as the negative evaluation index.
Specifically, the negative evaluation indexes include sales capacity, quality opinion, brand management, and vehicle type at risk. And the sales capacity includes the train sales. Quality public opinions include vehicle systems: the complaint amount of the website is in proportion; average website complaint amount of the same brand; 5-year value retention rate and quality evaluation. Brand management includes recent negative public opinion and other risks.
And b, acquiring negative sub-evaluation scores corresponding to the negative evaluation indexes in a preset evaluation score comparison table, calculating a first sum of the negative sub-evaluation scores, and taking the first sum as the negative evaluation score.
After determining each negative evaluation index of the vehicle to be evaluated, all negative evaluation indexes may be compared with the evaluation score comparison table to determine a negative sub-evaluation score corresponding to each negative evaluation index, and then a sum (i.e., a first sum) of each negative sub-evaluation score is calculated as a negative evaluation score. In addition, in this embodiment, in order to obtain a more accurate negative score (i.e., a negative evaluation score), different weights may be set for each negative evaluation index, as shown in fig. 4, the weight of the negative score is set to 100%, the weight of the sales capacity is set to 25% (including the weight of the sales volume of the train is 25%), the weight of the quality consensus is set to 45% (including the weight of the ratio of the complaints of the website of the train to 15%, the weight of the average complaint of the website of the same-brand train to 5%, the weight of the 5-year warranty rate to 20%, the weight of the quality evaluation to 5%), the weight of the brand operation is set to 20%, and the weight of the risk vehicle type is set to 10%. Then the negative assessment score 25% sales yields a negative sub-assessment score + 45% quality consensus negative sub-assessment score + 20% brand management negative sub-assessment score + 10% risk vehicle type negative sub-assessment score.
In this embodiment, all basic operation information in the enterprise information corresponding to the vehicle brand is determined and used as the negative evaluation index, each negative sub-evaluation score is determined according to the evaluation score comparison table, and the sum of the negative sub-evaluation scores is used as the negative evaluation score, so that the accuracy of the obtained negative evaluation score is guaranteed.
Further, the step of determining all positive evaluation indexes based on the positive evaluation dimensions corresponding to the vehicle brand and calculating the positive evaluation score corresponding to each positive evaluation index includes:
step c, determining enterprise information corresponding to the vehicle brand, determining enterprise qualification information in the enterprise information and vehicle brand quality information related to the vehicle brand, and taking the enterprise qualification information and the vehicle brand quality information as positive evaluation indexes;
in this embodiment, after determining the brand of the vehicle, the enterprise information for selling the brand type of the vehicle may be determined according to the brand of the vehicle, and the enterprise qualification information (such as financial index, sales capacity, enterprise quality, etc. of the enterprise) may be obtained from the enterprise information, and the vehicle brand quality information associated with the brand of the vehicle may also need to be obtained, such as user public praise, market status, quality index, etc. And the obtained enterprise qualification information and the vehicle brand quality information are used as positive evaluation indexes.
Specifically, the positive evaluation indexes include financial indexes, sales and productivity, enterprise quality, user public praise, market status and quality indexes. Wherein the financial indicators include net profits; the compound growth rate of three years; registered capital and capital strength. The sales capacity includes the train sales volume. The user public praise comprises a train: a user public praise score and a co-branded department rating score. Market positions include vehicle series indices. The quality index includes 5-year value-keeping rate and quality evaluation.
And d, acquiring the front sub-evaluation scores corresponding to the front evaluation indexes in a preset evaluation score comparison table, calculating a second sum of the front sub-evaluation scores, and taking the second sum as the front evaluation score.
After each positive evaluation index of the vehicle to be evaluated is determined, all the positive evaluation indexes can be compared with the evaluation score comparison table to determine the positive sub-evaluation scores corresponding to each positive evaluation index, and then the sum value (i.e., the second sum value) of each positive sub-evaluation score is calculated and used as the positive evaluation score. And in the embodiment, in order to improve the more accurate positive score (i.e. positive evaluation score), different weights can be set for each positive evaluation index, as shown in fig. 5, the weight of the positive score is 100%, and the weight of the financial index is 20% (including the net profit 5% weight; the three-year composite growth rate 5% weight; the registered capital 5% weight and the capital strength 5% weight); weight of sales energy 35% (including vehicle sales 35% weight); the weight of the enterprise quality is 5%; a 15% weight of user public praise (including car family: 10% weight of user public praise rating score; 5% weight of same brand car family rating score); the weight of market status is 10% (including the weight of train system index is 10%) and the weight of quality index is 15% (including the weight of 5-year-keeping rate is 10% and the weight of quality evaluation is 5%). Namely, the positive evaluation score is 20% of the positive sub-evaluation score corresponding to the financial index + 35% of the positive sub-evaluation score corresponding to the sales capacity and + 5% of the business quality + 15% of the positive sub-evaluation score corresponding to the user public praise + 10% of the positive sub-evaluation score corresponding to the market status + 15% of the positive sub-evaluation score corresponding to the quality index.
In this embodiment, the accuracy of the obtained positive evaluation score is ensured by determining all enterprise qualification information and vehicle brand quality information in the enterprise information corresponding to the vehicle brand, taking the enterprise qualification information and the vehicle brand quality information as negative evaluation indexes, determining each positive sub-evaluation score according to the evaluation score comparison table, and taking the sum of each positive sub-evaluation score as the positive evaluation score.
Further, the step of determining the risk level of the vehicle to be assessed according to the negative assessment score and the positive assessment score comprises:
step e, detecting whether the negative evaluation score is larger than a first preset threshold value;
step f, if the negative evaluation score is smaller than or equal to a first preset threshold, detecting whether the positive evaluation score is larger than a second preset threshold;
in this embodiment, after the positive evaluation score and the negative evaluation score of the vehicle to be evaluated are obtained, it is required to detect whether the negative evaluation score is greater than a first preset threshold (any threshold set by the user in advance, for example, 20), and if the negative evaluation score is less than or equal to the first preset threshold, it is required to detect whether the positive evaluation score is greater than a second preset threshold (any threshold set by the user in advance, which may be the same as or different from the first preset threshold), and different operations are performed according to different detection results.
And g, if the positive evaluation score is larger than a second preset threshold, determining the risk level of the vehicle to be evaluated as a low risk level.
And when the positive evaluation score is judged to be larger than the second preset threshold value, determining the risk level of the vehicle to be evaluated as a low risk level, and executing a risk strategy corresponding to the low risk level, such as allowing all loan operations related to the vehicle to be evaluated. And if the positive evaluation score is less than or equal to a second preset threshold, determining the risk grade of the vehicle to be evaluated as an intermediate risk grade, and executing a risk strategy corresponding to the intermediate risk grade, such as outputting corresponding prompt information.
In this embodiment, when it is determined that the negative evaluation score is less than or equal to the first preset threshold and the positive evaluation score is greater than the second preset threshold, the risk level of the vehicle to be evaluated is determined to be a low risk level, so that the accuracy of the determined risk level of the vehicle to be evaluated is guaranteed.
Specifically, the step of detecting whether the negative evaluation score is greater than a first preset threshold value includes:
and h, if the negative evaluation score is larger than a first preset threshold value, determining the risk level of the vehicle to be evaluated as a high risk level.
And when the negative evaluation score is larger than the first preset threshold value through judgment, directly determining the risk grade of the vehicle to be evaluated as a high risk grade without evaluating the positive evaluation score, and executing a risk strategy corresponding to the high risk grade, such as suspending all loan operations related to the vehicle to be evaluated.
In the embodiment, when the negative evaluation score is determined to be larger than the first preset threshold, the risk level of the vehicle to be evaluated is determined to be a high risk level, so that the accuracy of the determined risk level of the vehicle to be evaluated is guaranteed.
In addition, referring to fig. 3, an embodiment of the present invention further provides an automobile risk assessment apparatus, where the automobile risk assessment apparatus includes:
the first calculation module A10 is used for determining the vehicle brand of a vehicle to be evaluated, determining all negative evaluation indexes based on the negative evaluation dimensions corresponding to the vehicle brand, and calculating the negative evaluation score corresponding to each negative evaluation index;
the second calculation module A20 is used for determining all positive evaluation indexes based on the positive evaluation dimensions corresponding to the vehicle brand and calculating the positive evaluation scores corresponding to the positive evaluation indexes;
and the execution module A30 is used for determining the risk level of the vehicle to be evaluated according to the negative evaluation score and the positive evaluation score and executing a risk strategy corresponding to the risk level.
Optionally, the first calculating module a10 is configured to:
determining all basic operation information of the license plate brand in enterprise information corresponding to the vehicle brand, and taking the basic operation information as a negative evaluation index;
and acquiring negative sub-evaluation scores corresponding to the negative evaluation indexes in a preset evaluation score comparison table, calculating a first sum of the negative sub-evaluation scores, and taking the first sum as the negative evaluation score.
Optionally, the first calculating module a10 is configured to:
negative assessment indicators include sales, productivity, quality consensus, brand management, and vehicle type at risk.
Optionally, the second calculating module a20 is configured to:
determining enterprise information corresponding to the vehicle brand, determining enterprise qualification information in the enterprise information and vehicle brand quality information associated with the vehicle brand, and taking the enterprise qualification information and the vehicle brand quality information as positive evaluation indexes;
and acquiring the positive sub-evaluation scores corresponding to the positive evaluation indexes in a preset evaluation score comparison table, calculating a second sum of the positive sub-evaluation scores, and taking the second sum as the positive evaluation score.
Optionally, the second calculating module a20 is configured to:
the positive evaluation indexes comprise financial indexes, sales volume and productivity, enterprise quality, user public praise, market position and quality indexes.
Optionally, a module a30 is executed for:
detecting whether the negative evaluation score is larger than a first preset threshold value;
if the negative evaluation score is smaller than or equal to a first preset threshold, detecting whether the positive evaluation score is larger than a second preset threshold;
and if the positive evaluation score is larger than a second preset threshold value, determining that the risk level of the vehicle to be evaluated is a low risk level.
Optionally, a module a30 is executed for:
and if the negative evaluation score is larger than a first preset threshold value, determining that the risk level of the vehicle to be evaluated is a high risk level.
The steps implemented by each functional module of the automobile risk assessment device can refer to each embodiment of the automobile risk assessment method, and are not described herein again.
The invention also provides an automobile risk assessment device, and the terminal comprises: a memory, a processor, a communication bus, and an automobile risk assessment program stored on the memory:
the communication bus is used for realizing connection communication between the processor and the memory;
the processor is used for executing the automobile risk assessment program to realize the steps of the automobile risk assessment method.
The present invention also provides a computer readable storage medium storing one or more programs, which are further executable by one or more processors for implementing the steps of the embodiments of the above-described automobile risk assessment method.
The specific implementation manner of the computer-readable storage medium of the present invention is substantially the same as that of the embodiments of the vehicle risk assessment method described above, and is not described herein again.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) as described above and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. An automobile risk assessment method, characterized in that the automobile risk assessment method comprises:
determining the vehicle brand of a vehicle to be evaluated, determining all negative evaluation indexes based on the negative evaluation dimensionality corresponding to the vehicle brand, and calculating a negative evaluation score corresponding to each negative evaluation index;
determining all positive evaluation indexes based on the positive evaluation dimensions corresponding to the vehicle brand, and calculating a positive evaluation score corresponding to each positive evaluation index;
and determining the risk level of the vehicle to be evaluated according to the negative evaluation score and the positive evaluation score, and executing a risk strategy corresponding to the risk level.
2. The automobile risk assessment method according to claim 1, wherein the step of determining all negative assessment indicators based on the negative assessment dimensions corresponding to the vehicle brand, and calculating a negative assessment score corresponding to each negative assessment indicator comprises:
determining all basic operation information of the license plate brand in enterprise information corresponding to the vehicle brand, and taking the basic operation information as a negative evaluation index;
and acquiring negative sub-evaluation scores corresponding to the negative evaluation indexes in a preset evaluation score comparison table, calculating a first sum of the negative sub-evaluation scores, and taking the first sum as the negative evaluation score.
3. The method according to any one of claims 1-2, wherein the negative evaluation indicators include sales capacity, quality consensus, brand management, and vehicle type at risk.
4. The automobile risk assessment method according to claim 1, wherein the step of determining all positive assessment indicators based on the positive assessment dimensions corresponding to the brand of the vehicle and calculating the positive assessment score corresponding to each positive assessment indicator comprises:
determining enterprise information corresponding to the vehicle brand, determining enterprise qualification information in the enterprise information and vehicle brand quality information associated with the vehicle brand, and taking the enterprise qualification information and the vehicle brand quality information as positive evaluation indexes;
and acquiring the positive sub-evaluation scores corresponding to the positive evaluation indexes in a preset evaluation score comparison table, calculating a second sum of the positive sub-evaluation scores, and taking the second sum as the positive evaluation score.
5. The automobile risk assessment method according to claim 4, wherein said positive assessment indicators include financial indicators, sales capacity, business quality, user public praise, market status and quality indicators.
6. The automotive risk assessment method according to claim 1, wherein said step of determining a risk level of said vehicle to be assessed based on said negative assessment score and said positive assessment score comprises:
detecting whether the negative evaluation score is larger than a first preset threshold value;
if the negative evaluation score is smaller than or equal to a first preset threshold, detecting whether the positive evaluation score is larger than a second preset threshold;
and if the positive evaluation score is larger than a second preset threshold value, determining that the risk level of the vehicle to be evaluated is a low risk level.
7. The automotive risk assessment method according to claim 6, wherein said step of detecting whether said negative assessment score is greater than a first preset threshold value, is followed by:
and if the negative evaluation score is larger than a first preset threshold value, determining that the risk level of the vehicle to be evaluated is a high risk level.
8. An automotive risk assessment device, characterized in that it comprises:
the first calculation module is used for determining the vehicle brand of a vehicle to be evaluated, determining all negative evaluation indexes based on the negative evaluation dimensionality corresponding to the vehicle brand, and calculating the negative evaluation score corresponding to each negative evaluation index;
the second calculation module is used for determining all front evaluation indexes based on the front evaluation dimensionality corresponding to the vehicle brand and calculating front evaluation scores corresponding to the front evaluation indexes;
and the execution module is used for determining the risk level of the vehicle to be evaluated according to the negative evaluation score and the positive evaluation score and executing a risk strategy corresponding to the risk level.
9. An automobile risk assessment device, characterized in that it comprises: a memory, a processor and a vehicle risk assessment program stored on the memory and executable on the processor, the vehicle risk assessment program when executed by the processor implementing the steps of the vehicle risk assessment method according to any one of claims 1 to 7.
10. A computer-readable storage medium, wherein a vehicle risk assessment program is stored on the computer-readable storage medium, which when executed by a processor implements the steps of the vehicle risk assessment method according to any one of claims 1 to 7.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113119789A (en) * | 2021-04-19 | 2021-07-16 | 国网智慧能源交通技术创新中心(苏州)有限公司 | Method for ensuring charging safety through video recognition of vehicle type |
| CN116932921A (en) * | 2023-09-18 | 2023-10-24 | 湘江实验室 | Personalized recommendation method and related equipment for automobiles |
-
2020
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113119789A (en) * | 2021-04-19 | 2021-07-16 | 国网智慧能源交通技术创新中心(苏州)有限公司 | Method for ensuring charging safety through video recognition of vehicle type |
| CN116932921A (en) * | 2023-09-18 | 2023-10-24 | 湘江实验室 | Personalized recommendation method and related equipment for automobiles |
| CN116932921B (en) * | 2023-09-18 | 2023-12-12 | 湘江实验室 | Personalized recommendation method and related equipment for automobiles |
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