CN114169915A - Method and device for determining price reference value of automobile parts in automobile insurance claim settlement industry - Google Patents
Method and device for determining price reference value of automobile parts in automobile insurance claim settlement industry Download PDFInfo
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Abstract
The invention discloses a method and a device for determining a vehicle accessory price reference value in the vehicle insurance claim settlement industry, relates to the technical field of information, and mainly aims to improve the calculation precision of the vehicle accessory industry reference value. The method comprises the following steps: acquiring accessory price data corresponding to auto accessories to be evaluated under a target vehicle brand; determining suspicious data in the accessory price data according to the average value corresponding to the accessory price data; calculating a Grabs check value corresponding to the suspicious data, and judging whether the suspicious data is abnormal data or not based on the Grabs check value; if the suspicious data are the abnormal data, excluding the abnormal data from the accessory price data to obtain excluded accessory price data; and determining an industry reference value corresponding to the automobile part based on the excluded part price data. The method is suitable for determining the price reference value of the automobile parts in the automobile insurance claim settlement industry.
Description
Technical Field
The invention relates to the technical field of information, in particular to a method and a device for determining a price reference value of an automobile part in the automobile insurance claim settlement industry.
Background
Because the industry reference value of the automobile part has important value and guidance function for automobile insurance claim settlement operation, how to accurately determine the industry reference value of the automobile part is a problem to be solved urgently at present.
At present, the industry reference value of the automobile parts is determined by directly utilizing the data of the check loss list of the accident vehicle in the vehicle insurance industry. However, since the standards of claim data of each insurance company are not uniform, and a large amount of junk data is generated in actual claim settlement business operation, the quality of collected loss assessment list data is poor, and if the loss assessment list data is directly utilized to determine the industry reference value of the automobile parts, the accuracy of the determined industry reference value of the automobile parts is low, and the actual reference value is not high.
Disclosure of Invention
The invention provides a method and a device for determining a vehicle part price reference value in the vehicle insurance claim settlement industry, which mainly aim to improve the calculation precision of the vehicle part industry reference value.
According to a first aspect of the invention, there is provided a method for determining a vehicle insurance claim settlement industry auto parts price reference value, comprising:
acquiring accessory price data corresponding to auto accessories to be evaluated under a target vehicle brand;
determining suspicious data in the accessory price data according to the average value corresponding to the accessory price data;
calculating a Grabs check value corresponding to the suspicious data, and judging whether the suspicious data is abnormal data or not based on the Grabs check value;
if the suspicious data are the abnormal data, excluding the abnormal data from the accessory price data to obtain excluded accessory price data;
and determining an industry reference value corresponding to the automobile part based on the excluded part price data.
According to a second aspect of the present invention, there is provided an auto parts price reference value determination apparatus in the auto insurance claim settlement industry, comprising:
the system comprises an acquisition unit, a judgment unit and a display unit, wherein the acquisition unit is used for acquiring accessory price data corresponding to auto accessories to be evaluated under a target vehicle brand;
the first determining unit is used for determining suspicious data in the accessory price data according to the average value corresponding to the accessory price data;
the judging unit is used for calculating a Grabbs check value corresponding to the suspicious data and judging whether the suspicious data is abnormal data or not based on the Grabbs check value;
the excluding unit is used for excluding the abnormal data from the accessory price data to obtain the excluded accessory price data if the suspicious data is the abnormal data;
and the second determining unit is used for determining the industry reference value corresponding to the automobile part based on the excluded part price data.
According to a third aspect of the present invention, there is provided a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of:
acquiring accessory price data corresponding to auto accessories to be evaluated under a target vehicle brand;
determining suspicious data in the accessory price data according to the average value corresponding to the accessory price data;
calculating a Grabs check value corresponding to the suspicious data, and judging whether the suspicious data is abnormal data or not based on the Grabs check value;
if the suspicious data are the abnormal data, excluding the abnormal data from the accessory price data to obtain excluded accessory price data;
and determining an industry reference value corresponding to the automobile part based on the excluded part price data.
According to a fourth aspect of the present invention, there is provided a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the program:
acquiring accessory price data corresponding to auto accessories to be evaluated under a target vehicle brand;
determining suspicious data in the accessory price data according to the average value corresponding to the accessory price data;
calculating a Grabs check value corresponding to the suspicious data, and judging whether the suspicious data is abnormal data or not based on the Grabs check value;
if the suspicious data are the abnormal data, excluding the abnormal data from the accessory price data to obtain excluded accessory price data;
and determining an industry reference value corresponding to the automobile part based on the excluded part price data.
Compared with the mode that the industry reference value of the auto part is determined by directly utilizing the check loss list data of the accident vehicle in the vehicle insurance claim settlement industry, the method and the device for determining the price reference value of the auto part in the vehicle insurance claim settlement industry can obtain the price data of the part corresponding to the auto part to be evaluated under the brand of the target vehicle; determining suspicious data in the accessory price data according to the average value corresponding to the accessory price data; meanwhile, calculating a Grabs check value corresponding to the suspicious data, and judging whether the suspicious data is abnormal data or not based on the Grabs check value; if the suspicious data are the abnormal data, excluding the abnormal data from the accessory price data to obtain excluded accessory price data; finally, determining an industry reference value corresponding to the automobile part based on the excluded part price data, judging whether the suspicious data is abnormal data or not by calculating a Grabbs inspection value corresponding to the suspicious data, and excluding the abnormal data from the part price data, so that the quality of the excluded part price data can be improved, and further determining the industry reference value corresponding to the automobile part according to the excluded part price data, so that the calculation precision of the industry reference value of the automobile part can be improved, and the industry reference value has an effective guiding function and a reference value for industry business operation.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
FIG. 1 is a flow chart of a method for determining a price reference value of an automobile accessory in the automobile insurance claim settlement industry according to an embodiment of the invention;
FIG. 2 is a flow chart of another method for determining a price reference value of an automobile accessory in the automobile insurance claim settlement industry according to an embodiment of the invention;
FIG. 3 is a schematic structural diagram of an auto-parts price reference value determination apparatus in the auto insurance claim settlement industry according to an embodiment of the present invention;
FIG. 4 is a schematic structural diagram of another apparatus for determining a price reference value of an auto-parts in the auto insurance claim settlement industry according to an embodiment of the present invention;
fig. 5 shows a physical structure diagram of a computer device according to an embodiment of the present invention.
Detailed Description
The invention will be described in detail hereinafter with reference to the accompanying drawings in conjunction with embodiments. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
At present, if the collected data of the fixed core loss list is directly utilized to determine the industry reference value of the automobile part, the accuracy of the determined industry reference value of the automobile part is low, and the actual reference value is not large.
In order to solve the above problem, an embodiment of the present invention provides a method for determining a price reference value of an automobile part in a vehicle insurance claim settlement industry, as shown in fig. 1, where the method includes:
101. acquiring the accessory price data corresponding to the auto-parts to be evaluated under the target vehicle brand.
The target vehicle brand can be any one of vehicle brands in the vehicle insurance industry, the automobile parts to be evaluated can be any one of automobile parts under the target vehicle brand, such as tires, bumpers and the like of a certain vehicle brand, and the part price data is the part price given by an insurance company in the process of claims and damage assessment. In order to overcome the defect that the industry reference value corresponding to the automobile part is calculated by directly utilizing the part price data with poor quality in the prior art, and further the calculated industry reference value is low in precision, the embodiment of the invention judges whether the suspicious data is abnormal data or not by calculating the Grabs check value corresponding to the suspicious data in the part price data and based on the Grabs check value, can eliminate the abnormal data from the part price data, and further utilizes the eliminated part price data to calculate the industry reference value corresponding to the automobile part, and can improve the calculation precision of the industry reference value of the automobile part. The embodiment of the invention is mainly applied to a scene of determining the reference value of the automobile accessory industry in the automobile insurance claim settlement industry. The execution subject of the embodiment of the invention is a device or equipment capable of determining the reference value of the automobile accessory industry, and the execution subject can be specifically arranged on one side of the server.
For the embodiment of the invention, in order to calculate the industry reference value of a certain auto part under a certain vehicle brand, the vehicle insurance information platform needs to collect the fixed core loss list data of all insurance companies in a certain area aiming at the vehicle insurance accident vehicle in advance, wherein the vehicle insurance information platform can collect the fixed core loss list data of any area, for example, the fixed core loss list data of all insurance companies in a certain province are collected, the fixed core loss list data comprises the information of the auto part replaced by the insurance companies in the vehicle insurance claim settlement process, the price data of the part corresponding to the replaced auto part and the information of the fixed loss vehicle, the information of the auto part can be the code (OE number) of the auto part, and the information of the fixed loss vehicle can be the vehicle brand. After the vehicle insurance information platform collects the data, the vehicle brand name and the original factory code (OE number) of the automobile parts in the original data need to be standardized, specifically, the brand name of the same vehicle brand needs to be unified, the blank space and the symbol in the original factory code need to be removed, and only the letter and the number in the original factory code need to be reserved. Further, after the vehicle brand name and the original factory code of the auto part are standardized, when an industry reference value corresponding to a certain auto part under a certain vehicle brand needs to be calculated, the insurance information platform can obtain the price data of the part corresponding to the auto part under the corresponding vehicle brand from the collected approval loss list data according to the vehicle brand and the OE number corresponding to the auto part, for example, the insurance information platform obtains all the price data of the part corresponding to the auto part b in the vehicle brand a from the collected approval loss list data according to the OE number corresponding to the auto part b in the vehicle brand a, so that the industry reference value corresponding to the auto part b under the vehicle brand a is calculated based on the price data of the part.
102. And determining suspicious data in the accessory price data according to the average value corresponding to the accessory price data.
The suspicious data is data which may have an exception. For the embodiment of the invention, as the data standards of various insurance companies are not uniform, and a large amount of junk data is generated in actual claim settlement business operation, the quality of the collected check loss list data is not high, that is, abnormal data may exist in the acquired accessory price data corresponding to a certain automobile accessory under a certain vehicle brand, in order to ensure the calculation accuracy of the automobile accessory industry reference value, the abnormal data needs to be eliminated from the collected accessory price data, so that the automobile accessory industry reference value is calculated based on the eliminated accessory price data, in the process of eliminating the abnormal data, firstly suspicious data in the automobile accessory price data needs to be determined, then whether the suspicious data is real abnormal data is judged, and if the suspicious data is abnormal data, the suspicious data is eliminated.
Specifically, in order to determine suspicious data in the accessory price data corresponding to a certain auto-accessory under a certain vehicle brand, it is required to calculate an average value corresponding to the accessory price data, and determine a maximum price data and a minimum price data in the accessory price data, then determine a first deviation value of the maximum price data from the average value and a second deviation value of the minimum price data from the average value, respectively, and determine a suspicious data from the maximum price data and the minimum price data based on the first deviation value and the second deviation value, and see steps 202 and 203 for a specific determination process of the suspicious data.
103. And calculating a Grabs check value corresponding to the suspicious data, and judging whether the suspicious data is abnormal data or not based on the Grabs check value.
For the embodiment of the present invention, in order to further determine whether the suspicious data is abnormal data, a preset grassbs check algorithm is used to calculate a grassbs check value corresponding to the suspicious data, a specific calculation process for the grassbs check value is shown in step 204, meanwhile, a preset grassbs table is queried according to the preset check level and the number corresponding to the accessory price data, a critical value corresponding to the automobile accessory is determined, further, the grassbs check value corresponding to the suspicious data is compared with the critical value corresponding to the automobile accessory, a comparison result is used to determine whether the suspicious data is abnormal data, and a specific process for determining whether the suspicious data is abnormal data by using the grassbs check value and the critical value is shown in step 204.
104. And if the suspicious data are the abnormal data, excluding the abnormal data from the accessory price data to obtain the excluded accessory price data.
For the embodiment of the invention, if certain suspicious data is determined to be abnormal data, the abnormal data is excluded from n accessory price data to obtain the rest n-1 accessory price data, and then the process of determining the suspicious data and the abnormal data is repeated in the n-1 accessory price data until the corresponding Grabas check value of certain suspicious data is smaller than the corresponding critical value of the automobile accessory, the process is stopped, and finally excluded accessory price data is obtained. For example, m pieces of abnormal data are excluded from n pieces of accessory price data, and an industry reference value corresponding to an automobile accessory can be calculated based on n-m pieces of excluded accessory price data.
105. And determining an industry reference value corresponding to the automobile part based on the excluded part price data.
The industry reference value comprises an industry average value, an industry maximum value, an industry minimum value, an industry confidence coefficient and the like corresponding to the automobile part. For the embodiment of the invention, after the excluded part price data is obtained, the excluded part price data is utilized to respectively calculate the industry average value, the industry maximum value, the industry minimum value and the industry confidence degree corresponding to the automobile part, and the specific calculation process for the industry average value, the industry maximum value, the industry minimum value and the industry confidence interval is shown in step 206.
In a specific application scenario, an industry reference data table corresponding to the automobile part may be generated according to the calculation result, as shown in table 1.
TABLE 1
Further, the generated industry reference data table can be used for monitoring the claim payment standards of insurance companies in each region, so as to generate a supervision report for the insurance companies, and the supervision report is provided for the bank insurance department, so that the bank insurance department governs various problems occurring in the claim payment process of the insurance companies based on the supervision report, and based on the supervision report, the method comprises the following steps: acquiring approved price checking data provided by a business object aiming at the automobile parts; and generating claim settlement monitoring information corresponding to the business object based on the audited pricing data and the industry confidence interval. The business object can be an insurance company, and the approved pricing data provides the reimbursement standard for the insurance company.
For example, if the approved pricing data provided by an insurance company is not in the corresponding confidence interval of the automobile parts, the insurance company is likely to pay the inferior automobile parts, and therefore a supervision report for the insurance company can be generated and provided to a bank guard.
In addition, the generated industry reference data sheet can be used by insurance companies and host factories, the insurance companies can correct their own indemnity standards by using the industry reference data sheet, and the host factories can supervise the repair amount of accessories of their distributors by using the industry reference data sheet.
Compared with the mode that the industry reference value of the auto part is determined by directly utilizing the check loss list data of the accident vehicle in the vehicle insurance claim industry, the method for determining the price reference value of the auto part in the vehicle insurance claim industry can obtain the price data of the part corresponding to the auto part to be evaluated under the brand of the target vehicle; determining suspicious data in the accessory price data according to the average value corresponding to the accessory price data; meanwhile, calculating a Grabs check value corresponding to the suspicious data, and judging whether the suspicious data is abnormal data or not based on the Grabs check value; if the suspicious data are the abnormal data, excluding the abnormal data from the accessory price data to obtain excluded accessory price data; finally, determining an industry reference value corresponding to the automobile part based on the excluded part price data, judging whether the suspicious data is abnormal data or not by calculating a Grabbs inspection value corresponding to the suspicious data, and excluding the abnormal data from the part price data, so that the quality of the excluded part price data can be improved, and further determining the industry reference value corresponding to the automobile part according to the excluded part price data, so that the calculation precision of the industry reference value of the automobile part can be improved, and the industry reference value has an effective guiding function and a reference value for industry business operation.
Further, in order to better explain the above process for determining the auto parts industry reference value, as a refinement and an extension to the above embodiment, an embodiment of the present invention provides another method for determining a price reference value of an auto parts industry auto parts in an automobile insurance claim settlement industry, as shown in fig. 2, where the method includes:
201. acquiring the accessory price data corresponding to the auto-parts to be evaluated under the target vehicle brand.
For the embodiment of the present invention, in order to calculate the industry reference value corresponding to a certain auto part under a certain vehicle brand, the price data of the part corresponding to the auto part needs to be collected in advance, and the specific process for acquiring the interval data of the part is completely the same as that in step 101, and is not described herein again.
202. Determining maximum price data and minimum price data in the accessory price data, and respectively calculating a first deviation value corresponding to the maximum price data and a second deviation value corresponding to the minimum price data based on the maximum price data, the minimum price data and the average value.
For the embodiment of the invention, in the process of determining the suspicious data, since the maximum price data and the minimum price data in the accessory price data are data which are relatively far away from the data center and are probably suspicious data, the maximum price data and the minimum price data in the accessory price data are determined firstly, and the average value corresponding to the accessory price data is calculated at the same time
Wherein x isnRepresenting the price data of the accessories, and n represents the quantity corresponding to the price data of the accessories.
Further, a first deviation value of the maximum price data from the average value and a second deviation value of the minimum price data from the average value are respectively calculated, and the specific formula is as follows:
wherein the content of the first and second substances,
is the mean value, X, corresponding to the price data of the accessorymaxIs the maximum price data, XminIs the minimum price data, D1Is a first deviation value, D2Is a second deviation value, whereby a first deviation value corresponding to the maximum price data and a second deviation value corresponding to the minimum price data can be calculated according to the above formula, so that the suspicious data can be screened from the maximum price data and the minimum price data based on the first deviation value and the second deviation value.
203. And comparing the first deviation value with the second deviation value, and determining suspicious data from the maximum price data and the minimum price data according to a comparison result.
For the embodiment of the present invention, in order to determine suspicious data from the maximum price data and the minimum price data, step 203 specifically includes: if the first deviation value is larger than the second deviation value, determining the maximum price data as suspicious data; if the first deviation value is smaller than the second deviation value, determining the minimum price data as suspicious data; and if the first deviation value is equal to the second deviation value, determining that the maximum price data and the minimum price data are suspicious data.
Specifically, if the first deviation value is greater than the second deviation value, it indicates that the maximum price data is further deviated from the average value relative to the minimum price data, and thus the maximum price data is determined to be suspicious data; if the first deviation value is smaller than the second deviation value, the minimum price data is more far from the average value relative to the maximum price data, and therefore the minimum price data is determined to be suspicious data; if the first deviation value is equal to the second deviation value, it is indicated that the maximum price data and the minimum price data have equal deviation values from the average value, and thus both the maximum price data and the minimum price data are determined to be suspicious data.
204. And calculating a Grabs check value corresponding to the suspicious data, and judging whether the suspicious data is abnormal data or not based on the Grabs check value.
For the embodiment of the present invention, after determining suspicious data in the accessory price data, in order to further determine whether the suspicious data is abnormal data, a preset grassbs test method is required to calculate a grassbs test value corresponding to the suspicious data, and the grassbs test value is compared with a critical value, and it is determined whether the suspicious data is abnormal data according to a comparison result, based on this, step 204 specifically includes: calculating a standard deviation corresponding to the accessory price data, and calculating a Grabbs check value corresponding to the suspicious data based on the standard deviation, the average value and the suspicious data; inquiring a preset Labs table according to a preset check level and the quantity corresponding to the accessory price data, and determining a critical value corresponding to the automobile accessory; if the Grabbs check value is larger than the critical value, determining the suspicious data as abnormal data; and if the Grabbs check value is smaller than or equal to the critical value, determining the suspicious data as valid data.
Specifically, first, a standard deviation corresponding to the accessory price data is calculated, and a specific calculation formula of the standard deviation is as follows:
wherein x isiRepresenting any one of the accessory price data,
the standard deviation corresponding to the accessory price data can be calculated according to the formula by taking the average value corresponding to the accessory price data as n represents the quantity corresponding to the accessory price data.
Further, according to the standard deviation, the average value and the size of the suspicious data corresponding to the accessory price data, calculating a corresponding Grabbs check value of the suspicious data, wherein a specific calculation formula of the Grabbs check value is as follows:
wherein G isiRepresenting corresponding Grabbs test values, x, of suspect dataiOn behalf of the data that is suspect,
the mean value corresponding to the part price data and S the standard deviation corresponding to the part price data, and thus the grassbris check value corresponding to the suspect data can be calculated according to the above formula.
Further, the number corresponding to the preset check level and the accessory price data is obtained, a preset Labs table is inquired based on the preset check level and the number, and the critical value corresponding to the automobile accessory is determined. For example, the preset check level is 0.05, the p value is 0.95, the preset Labs table is inquired according to the p value and the number n, and the critical value G corresponding to the automobile part is obtained at the intersection of the horizontal axis and the vertical axis0.95(n) of (a). Further, after determining the granbus test value and the critical value, if the granbus test value is greater than the critical value, the suspicious data is abnormal data; if the Labs test value is less than or equal to the threshold value, the suspicious data is valid data.
205. And if the suspicious data are the abnormal data, excluding the abnormal data from the accessory price data to obtain the excluded accessory price data.
For the embodiment of the present invention, after determining that the suspicious data is abnormal data, it needs to be excluded from the automobile accessory data, and based on this, step 205 specifically includes: and repeating the process of determining and eliminating the abnormal data sum in the accessory price data until the corresponding Grabbs check value of any suspicious data is less than or equal to the critical value, so as to obtain the finally eliminated accessory price data.
Specifically, after the first abnormal data is eliminated from the accessory price data, suspicious data needs to be determined from n-1 data, the process of calculating the corresponding grassplot inspection value of the suspicious data needs to be repeated, if the corresponding grassplot inspection value of the suspicious data is larger than the critical value, the suspicious data is also abnormal data, the abnormal data needs to be eliminated from n-1 data, the above processes of determining and eliminating the abnormal data are repeated until the corresponding grassplot inspection value of the suspicious data in a certain round of calculation process is smaller than or equal to the critical value, the calculation is stopped, and finally eliminated accessory price data is obtained.
206. And determining an industry reference value corresponding to the automobile part based on the excluded part price data.
For the embodiment of the present invention, in order to calculate the industry reference value corresponding to the automobile part according to the excluded part price data, step 206 specifically includes: respectively calculating an industry average value, an industry maximum value, an industry minimum value and an industry confidence interval corresponding to the excluded accessory price data; and determining the industry average value, the industry maximum value, the industry minimum value and the industry confidence interval as the industry reference value corresponding to the automobile part.
Specifically, an industry average value corresponding to the excluded accessory price data is calculated, and a specific formula is as follows:
wherein the content of the first and second substances,
in the embodiment of the invention, the abnormal data are eliminated in the process of calculating the industry average value, so that the industry average value corresponding to the automobile parts is calculated by using the effective data after elimination, and the calculation precision of the industry average value can be improved.
Further, after calculating the industry average value corresponding to the automobile part, an industry confidence interval corresponding to the industry average value may also be calculated, and a specific calculation formula of the confidence interval is as follows:
wherein the content of the first and second substances,
if the part price data is regarded as obeying normal distribution, the high-frequency confidence interval of the part price data at 60% is (the industry average value is-0.845 standard deviation S, and the industry average value is +0.845 standard deviation S). Meanwhile, the maximum price data and the minimum price data in the excluded accessory price data are respectively determined as an industry maximum value and an industry minimum value, and an industry reference data table corresponding to the automobile accessory is generated according to the industry average value, the industry maximum value, the industry minimum value and the industry confidence interval.
Compared with the mode that the industry reference value of the auto part is determined by directly utilizing the check loss list data of the accident vehicle in the vehicle insurance industry, the method for determining the price reference value of the auto part in the vehicle insurance claim settlement industry can obtain the price data of the part corresponding to the auto part to be evaluated under the brand of the target vehicle; determining suspicious data in the accessory price data according to the average value corresponding to the accessory price data; meanwhile, calculating a Grabs check value corresponding to the suspicious data, and judging whether the suspicious data is abnormal data or not based on the Grabs check value; if the suspicious data are the abnormal data, excluding the abnormal data from the accessory price data to obtain excluded accessory price data; finally, determining an industry reference value corresponding to the automobile part based on the excluded part price data, judging whether the suspicious data is abnormal data or not by calculating a Grabbs inspection value corresponding to the suspicious data, and excluding the abnormal data from the part price data, so that the quality of the excluded part price data can be improved, and further determining the industry reference value corresponding to the automobile part according to the excluded part price data, so that the calculation precision of the industry reference value of the automobile part can be improved, and the industry reference value has an effective guiding function and a reference value for industry business operation.
Further, as a specific implementation of fig. 1, an embodiment of the present invention provides an apparatus for determining a price reference value of an automobile accessory in the automobile insurance claim settlement industry, as shown in fig. 3, where the apparatus includes: an acquisition unit 31, a first determination unit 32, a determination unit 33, an exclusion unit 34, and a second determination unit 35.
The obtaining unit 31 may be configured to obtain accessory price data corresponding to an auto accessory to be evaluated under a target vehicle brand.
The first determining unit 32 may be configured to determine suspicious data in the accessory price data according to an average value corresponding to the accessory price data.
The determining unit 33 may be configured to calculate a grassbs check value corresponding to the suspicious data, and determine whether the suspicious data is abnormal data based on the grassbs check value.
The excluding unit 34 may be configured to, if the suspicious data is the abnormal data, exclude the abnormal data from the accessory price data to obtain excluded accessory price data.
The second determining unit 35 may be configured to determine an industry reference value corresponding to the automobile part based on the excluded part price data.
In a specific application scenario, in order to determine suspicious data in the accessory price data, the first determining unit 32, as shown in fig. 4, includes: a first determination module 321, a first calculation module 322, and a comparison module 323.
The first determining module 321 may be configured to determine maximum price data and minimum price data in the accessory price data.
The first calculating module 322 may be configured to calculate a first deviation value corresponding to the maximum price data and a second deviation value corresponding to the minimum price data based on the maximum price data, the minimum price data and the average value, respectively.
The comparing module 323 may be configured to compare the first deviation value with the second deviation value, and determine suspicious data from the maximum price data and the minimum price data according to a comparison result.
Further, in order to determine suspicious data from the maximum price data and the minimum price data according to a comparison result, the comparison module 323 may be specifically configured to determine that the maximum price data is suspicious data if the first deviation value is greater than the second deviation value; if the first deviation value is smaller than the second deviation value, determining the minimum price data as suspicious data; and if the first deviation value is equal to the second deviation value, determining that the maximum price data and the minimum price data are suspicious data.
In a specific application scenario, in order to determine whether suspicious data is abnormal data, the determining unit 33 includes: a second calculation module 331 and a second determination module 332.
The second calculating module 331 may be configured to calculate a standard deviation corresponding to the accessory price data, and calculate a grubbs check value corresponding to the suspicious data based on the standard deviation, the average value, and the suspicious data.
The second determining module 332 may be configured to query a preset labus table according to a preset check level and a quantity corresponding to the accessory price data, and determine a critical value corresponding to the automobile accessory.
The second determining module 332 may be further configured to determine that the suspicious data is abnormal data if the grubbs test value is greater than the critical value.
The second determining module 332 may be further configured to determine that the suspicious data is valid data if the grubbs test value is smaller than or equal to the critical value.
In a specific application scenario, in order to exclude the abnormal data from the accessory price data, the excluding unit 34 may be configured to repeat the process of determining and excluding the abnormal data sum in the accessory price data until the grubbs check value corresponding to any suspicious data is less than or equal to the critical value, so as to obtain the finally excluded accessory price data.
In a specific application scenario, in order to determine an industry reference value corresponding to an automobile part, the second determining unit 35 includes: a third calculation module 351 and a third determination module 352.
The third calculating module 351 may be configured to calculate an industry average value, an industry maximum value, an industry minimum value, and an industry confidence interval corresponding to the excluded accessory price data, respectively.
The third determining module 352 may be configured to determine the industry average, the industry maximum, the industry minimum, and the industry confidence interval as industry reference values corresponding to the automobile parts.
Further, in order to generate the claim administration information corresponding to the business object, the apparatus further includes a generating unit 36.
The obtaining unit 31 may be further configured to obtain approved pricing data provided by the business object for the automobile parts.
The generating unit 36 may be configured to generate claim settlement monitoring information corresponding to the business object based on the audited pricing data and the industry confidence interval.
It should be noted that other corresponding descriptions of the functional modules related to the industry reference value determination device for the automobile parts provided in the embodiment of the present invention may refer to the corresponding descriptions of the method shown in fig. 1, and are not described herein again.
Based on the method shown in fig. 1, correspondingly, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the following steps: acquiring accessory price data corresponding to auto accessories to be evaluated under a target vehicle brand; determining suspicious data in the accessory price data according to the average value corresponding to the accessory price data; calculating a Grabs check value corresponding to the suspicious data, and judging whether the suspicious data is abnormal data or not based on the Grabs check value; if the suspicious data are the abnormal data, excluding the abnormal data from the accessory price data to obtain excluded accessory price data; and determining an industry reference value corresponding to the automobile part based on the excluded part price data.
Based on the above embodiments of the method shown in fig. 1 and the apparatus shown in fig. 3, an embodiment of the present invention further provides an entity structure diagram of a computer device, as shown in fig. 5, where the computer device includes: a processor 41, a memory 42, and a computer program stored on the memory 42 and executable on the processor, wherein the memory 42 and the processor 41 are both arranged on a bus 43 such that when the processor 41 executes the program, the following steps are performed: acquiring accessory price data corresponding to auto accessories to be evaluated under a target vehicle brand; determining suspicious data in the accessory price data according to the average value corresponding to the accessory price data; calculating a Grabs check value corresponding to the suspicious data, and judging whether the suspicious data is abnormal data or not based on the Grabs check value; if the suspicious data are the abnormal data, excluding the abnormal data from the accessory price data to obtain excluded accessory price data; and determining an industry reference value corresponding to the automobile part based on the excluded part price data.
According to the technical scheme, the method can obtain the accessory price data corresponding to the auto-parts to be evaluated under the target vehicle brand; determining suspicious data in the accessory price data according to the average value corresponding to the accessory price data; meanwhile, calculating a Grabs check value corresponding to the suspicious data, and judging whether the suspicious data is abnormal data or not based on the Grabs check value; if the suspicious data are the abnormal data, excluding the abnormal data from the accessory price data to obtain excluded accessory price data; finally, determining an industry reference value corresponding to the automobile part based on the excluded part price data, judging whether the suspicious data is abnormal data or not by calculating a Grabbs inspection value corresponding to the suspicious data, and excluding the abnormal data from the part price data, so that the quality of the excluded part price data can be improved, and further determining the industry reference value corresponding to the automobile part according to the excluded part price data, so that the calculation precision of the industry reference value of the automobile part can be improved, and the industry reference value has an effective guiding function and a reference value for industry business operation.
It will be apparent to those skilled in the art that the modules or steps of the present invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and alternatively, they may be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into individual integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method for determining a price reference value of an automobile part in the automobile insurance claim settlement industry is characterized by comprising the following steps:
acquiring accessory price data corresponding to auto accessories to be evaluated under a target vehicle brand;
determining suspicious data in the accessory price data according to the average value corresponding to the accessory price data;
calculating a Grabs check value corresponding to the suspicious data, and judging whether the suspicious data is abnormal data or not based on the Grabs check value;
if the suspicious data are the abnormal data, excluding the abnormal data from the accessory price data to obtain excluded accessory price data;
and determining an industry reference value corresponding to the automobile part based on the excluded part price data.
2. The method of claim 1, wherein determining suspect data in the parts price data from the corresponding average of the parts price data comprises:
determining maximum price data and minimum price data in the accessory price data;
respectively calculating a first deviation value corresponding to the maximum price data and a second deviation value corresponding to the minimum price data based on the maximum price data, the minimum price data and the average value;
and comparing the first deviation value with the second deviation value, and determining suspicious data from the maximum price data and the minimum price data according to a comparison result.
3. The method of claim 2, wherein comparing the first deviation value to the second deviation value and determining suspect data from the maximum price data and the minimum price data based on the comparison comprises:
if the first deviation value is larger than the second deviation value, determining the maximum price data as suspicious data;
if the first deviation value is smaller than the second deviation value, determining the minimum price data as suspicious data;
and if the first deviation value is equal to the second deviation value, determining that the maximum price data and the minimum price data are suspicious data.
4. The method according to any one of claims 1-3, wherein the calculating a Grabby check value corresponding to the suspicious data and determining whether the suspicious data is abnormal data based on the Grabby check value comprises:
calculating a standard deviation corresponding to the accessory price data, and calculating a Grabbs check value corresponding to the suspicious data based on the standard deviation, the average value and the suspicious data;
inquiring a preset Labs table according to a preset check level and the quantity corresponding to the accessory price data, and determining a critical value corresponding to the automobile accessory;
if the Grabbs check value is larger than the critical value, determining the suspicious data as abnormal data;
and if the Grabbs check value is smaller than or equal to the critical value, determining the suspicious data as valid data.
5. The method of claim 4, wherein said excluding the anomaly data from the part price data resulting in excluded part price data comprises:
and repeating the process of determining and eliminating the abnormal data sum in the accessory price data until the corresponding Grabbs check value of any suspicious data is less than or equal to the critical value, so as to obtain the finally eliminated accessory price data.
6. The method of any one of claims 1-3, 5, wherein determining the industry reference value for the auto part based on the excluded part price data comprises:
respectively calculating an industry average value, an industry maximum value, an industry minimum value and an industry confidence interval corresponding to the excluded accessory price data;
and determining the industry average value, the industry maximum value, the industry minimum value and the industry confidence interval as the industry reference value corresponding to the automobile part.
7. The method of claim 6, further comprising:
acquiring approved price checking data provided by a business object aiming at the automobile parts;
and generating claim settlement monitoring information corresponding to the business object based on the audited pricing data and the industry confidence interval.
8. An auto-parts price reference value determination device in the vehicle insurance claim settlement industry, comprising:
the system comprises an acquisition unit, a judgment unit and a display unit, wherein the acquisition unit is used for acquiring accessory price data corresponding to auto accessories to be evaluated under a target vehicle brand;
the first determining unit is used for determining suspicious data in the accessory price data according to the average value corresponding to the accessory price data;
the judging unit is used for calculating a Grabbs check value corresponding to the suspicious data and judging whether the suspicious data is abnormal data or not based on the Grabbs check value;
the excluding unit is used for excluding the abnormal data from the accessory price data to obtain the excluded accessory price data if the suspicious data is the abnormal data;
and the second determining unit is used for determining the industry reference value corresponding to the automobile part based on the excluded part price data.
9. A computer arrangement comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the computer program realizes the steps of the method of any one of claims 1 to 7 when executed by the processor.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
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| CN202111360537.5A CN114169915A (en) | 2021-11-17 | 2021-11-17 | Method and device for determining price reference value of automobile parts in automobile insurance claim settlement industry |
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| CN202111360537.5A CN114169915A (en) | 2021-11-17 | 2021-11-17 | Method and device for determining price reference value of automobile parts in automobile insurance claim settlement industry |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117235677A (en) * | 2023-11-10 | 2023-12-15 | 邦邦汽车销售服务(北京)有限公司 | Automobile accessory price anomaly identification detection method |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117235677A (en) * | 2023-11-10 | 2023-12-15 | 邦邦汽车销售服务(北京)有限公司 | Automobile accessory price anomaly identification detection method |
| CN117235677B (en) * | 2023-11-10 | 2024-02-20 | 邦邦汽车销售服务(北京)有限公司 | Automobile accessory price anomaly identification detection method |
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