CN111861765A - Intelligent anti-fraud method for vehicle insurance claim settlement - Google Patents
Intelligent anti-fraud method for vehicle insurance claim settlement Download PDFInfo
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- CN111861765A CN111861765A CN202010744161.7A CN202010744161A CN111861765A CN 111861765 A CN111861765 A CN 111861765A CN 202010744161 A CN202010744161 A CN 202010744161A CN 111861765 A CN111861765 A CN 111861765A
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Abstract
The invention relates to an intelligent anti-fraud method for vehicle insurance claim settlement, which comprises the following steps of S1, collecting multidimensional information data related to vehicle insurance business; s2, integrating the multi-dimensional information data to form integrated data of a unified standard interface; s3, substituting the integration data into the multi-dimensional vehicle insurance claim anti-fraud model, and calculating the vehicle insurance claim fraud probability; and S4, judging the fraud behavior according to the fraud probability of the vehicle insurance claim settlement. The invention integrates the multidimensional information data related to the vehicle insurance business to form the integrated data of a unified standard interface, substitutes the integrated data into the multidimensional vehicle insurance claim fraud prevention model, calculates the vehicle insurance claim fraud probability, and judges the fraud behavior according to the vehicle insurance claim fraud probability, can accurately identify the fraud behavior in the vehicle insurance claim settlement process, and solves the problem that the funds of insurance companies are lost due to fraud.
Description
Technical Field
The invention relates to the field of vehicle insurance, in particular to an intelligent anti-fraud method for vehicle insurance claim settlement.
Background
Integrity is the traditional American of Chinese nationality, but at present, people who are not honest and the frequency of dishonest events is higher and higher, which has caused great influence on the life of people, so the establishment of the integrity system of the citizens is urgent. With the increase of the holding amount of automobiles, the density of vehicles on urban roads is higher and higher, and more traffic accidents occur among the vehicles. When a traffic accident occurs, an insurance company is required to make a loss in order to secure insurance. The user driving the vehicle can now take the on-site materials by taking a picture and submit them to the insurance company on line, and the insurance company checks and confirms them remotely. In this case, the insurance company can perform the subsequent car insurance claim settlement processing only depending on the level of consciousness and morality of the user. Therefore, how to prevent the user from cheating insurance funds in the vehicle insurance claim settlement process is always a relatively headache problem for insurance companies.
Disclosure of Invention
The invention aims to provide an intelligent anti-fraud method for vehicle insurance claim settlement, which can identify fraud behaviors in the vehicle insurance claim settlement process and solve the problem that funds of insurance companies are lost due to fraud protection.
The technical scheme for solving the technical problems is as follows: an intelligent anti-fraud method for vehicle insurance claim settlement comprises the following steps,
s1, collecting multidimensional information data related to vehicle insurance business;
s2, integrating the multi-dimensional information data to form integrated data of a unified standard interface;
s3, substituting the integration data into the multi-dimensional vehicle insurance claim anti-fraud model, and calculating the vehicle insurance claim fraud probability;
and S4, judging the fraud behavior according to the fraud probability of the vehicle insurance claim settlement.
On the basis of the technical scheme, the invention can be further improved as follows.
Further, the step S1 is specifically to collect multidimensional information data related to the vehicle insurance business from different data sources; the multidimensional information data related to the vehicle insurance business comprises vehicle information data, accident vehicle owner credit data, accident vehicle owner social relation data and policy information data.
Further, in S2, specifically,
converting the information data into standard data with a standard data format;
checking the integrity and correctness of the standard data, and filtering the standard data which do not meet the requirements;
and (5) persisting the standard data which passes the verification to a database, integrating and storing to obtain integrated data.
Further, before S3, the method further includes the step of constructing a multidimensional vehicle insurance claim anti-fraud model.
Further, the concrete steps for constructing the anti-fraud model of the multi-dimensional vehicle insurance claim settlement are as follows,
filtering non-fraud data related to the normal insurance of the vehicle and fraud data related to the fraud insurance of the vehicle from the historical data to form big data;
constructing an initial multi-dimensional vehicle insurance claim settlement anti-fraud model according to the neural network;
dividing the big data into a training set and a testing set, and training an initial multi-dimensional vehicle insurance claim anti-fraud model through the training set to obtain the multi-dimensional vehicle insurance claim anti-fraud model.
Further, the specific step of constructing the anti-fraud model of the multi-dimensional vehicle insurance claim also comprises the step of testing the anti-fraud model of the multi-dimensional vehicle insurance claim according to the test set; if the test result is greater than the preset test threshold value, the anti-fraud model for the multi-dimensional vehicle insurance claim settlement meets the requirement; and if the test result is smaller than the preset test threshold, the anti-fraud model for the multi-dimensional vehicle insurance claim does not meet the requirement, the training set and the test set are re-divided, and the initial anti-fraud model for the multi-dimensional vehicle insurance claim is re-trained according to the re-divided training set.
Further, in S3, specifically,
and performing credit investigation analysis and claim settlement analysis on the integrated data through the multi-dimensional vehicle insurance claim anti-fraud model, and obtaining vehicle insurance claim fraud probability according to credit investigation analysis results and claim settlement analysis results.
Further, the vehicle insurance claim fraud probability obtained according to the credit investigation result and the claim investigation result is specifically,
the vehicle insurance claim fraud probability is calculated using the following formula,
wherein a and b are fixed constants, and a + b is 1, x1To assess the results of the analysis, x2And analyzing the result for the claim.
Further, in S4, specifically,
and if the vehicle insurance claim settlement fraud probability is greater than or equal to 0.8, the fraud behavior exists, otherwise, the fraud behavior does not exist.
The invention has the beneficial effects that: the invention integrates the multidimensional information data related to the vehicle insurance business to form the integrated data of a unified standard interface, substitutes the integrated data into the multidimensional vehicle insurance claim fraud prevention model, calculates the vehicle insurance claim fraud probability, and judges the fraud behavior according to the vehicle insurance claim fraud probability, can accurately identify the fraud behavior in the vehicle insurance claim settlement process, and solves the problem that the funds of insurance companies are lost due to fraud.
Drawings
FIG. 1 is a flow chart of an intelligent anti-fraud method for vehicle insurance claim settlement according to the present invention.
Detailed Description
The principles and features of this invention are described below in conjunction with the following drawings, which are set forth by way of illustration only and are not intended to limit the scope of the invention.
As shown in fig. 1, an intelligent anti-fraud method for vehicle insurance claims includes the following steps,
s1, collecting multidimensional information data related to vehicle insurance business;
s2, integrating the multi-dimensional information data to form integrated data of a unified standard interface;
s3, substituting the integration data into the multi-dimensional vehicle insurance claim anti-fraud model, and calculating the vehicle insurance claim fraud probability;
and S4, judging the fraud behavior according to the fraud probability of the vehicle insurance claim settlement.
In this particular embodiment:
the step S1 is specifically to collect multidimensional information data related to vehicle insurance services from different data sources; the multidimensional information data related to the vehicle insurance business comprises vehicle information data, accident vehicle owner credit data, accident vehicle owner social relation data and policy information data.
The S2 is specifically configured to convert the information data into standard data having a standard data format; checking the integrity and correctness of the standard data, and filtering the standard data which do not meet the requirements; and (5) persisting the standard data which passes the verification to a database, integrating and storing to obtain integrated data.
Before S3, the method further includes the step of constructing a multidimensional vehicle insurance claim anti-fraud model.
The method comprises the specific steps of constructing a multi-dimensional vehicle insurance claim settlement anti-fraud model, filtering non-fraud data related to normal insurance of a vehicle and fraud data related to fraud insurance of the vehicle from historical data to form big data; constructing an initial multi-dimensional vehicle insurance claim settlement anti-fraud model according to the neural network; dividing the big data into a training set and a testing set, and training an initial multi-dimensional vehicle insurance claim anti-fraud model through the training set to obtain the multi-dimensional vehicle insurance claim anti-fraud model.
The specific steps of constructing the anti-fraud model of the multi-dimensional vehicle insurance claim also comprise testing the anti-fraud model of the multi-dimensional vehicle insurance claim according to the test set; if the test result is greater than the preset test threshold value, the anti-fraud model for the multi-dimensional vehicle insurance claim settlement meets the requirement; and if the test result is smaller than the preset test threshold, the anti-fraud model for the multi-dimensional vehicle insurance claim does not meet the requirement, the training set and the test set are re-divided, and the initial anti-fraud model for the multi-dimensional vehicle insurance claim is re-trained according to the re-divided training set.
The S3 is specifically configured to perform credit investigation and claim settlement analysis on the integration data through the multidimensional vehicle insurance claim anti-fraud model, and obtain a vehicle insurance claim fraud probability according to credit investigation results and claim settlement analysis results.
The vehicle insurance claim fraud probability is obtained according to the credit investigation result and the claim investigation result, specifically, the vehicle insurance claim fraud probability is calculated by adopting the following formula,
wherein a and b are fixed constants, and a + b is 1, x1To assess the results of the analysis, x2And analyzing the result for the claim.
Specifically, in S4, if the fraud probability of the vehicle insurance claim is greater than or equal to 0.8, there is a fraud, otherwise, there is no fraud.
The invention integrates the multidimensional information data related to the vehicle insurance business to form the integrated data of a unified standard interface, substitutes the integrated data into the multidimensional vehicle insurance claim fraud prevention model, calculates the vehicle insurance claim fraud probability, and judges the fraud behavior according to the vehicle insurance claim fraud probability, can accurately identify the fraud behavior in the vehicle insurance claim settlement process, and solves the problem that the funds of insurance companies are lost due to fraud.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (9)
1. An intelligent anti-fraud method for vehicle insurance claims is characterized in that: comprises the following steps of (a) carrying out,
s1, collecting multidimensional information data related to vehicle insurance business;
s2, integrating the multi-dimensional information data to form integrated data of a unified standard interface;
s3, substituting the integration data into the multi-dimensional vehicle insurance claim anti-fraud model, and calculating the vehicle insurance claim fraud probability;
and S4, judging the fraud behavior according to the fraud probability of the vehicle insurance claim settlement.
2. The vehicle insurance claim settlement intelligent anti-fraud method of claim 1, characterized in that: the step S1 is specifically to collect multidimensional information data related to vehicle insurance services from different data sources; the multidimensional information data related to the vehicle insurance business comprises vehicle information data, accident vehicle owner credit data, accident vehicle owner social relation data and policy information data.
3. The vehicle insurance claim settlement intelligent anti-fraud method of claim 1, characterized in that: specifically, the step S2 is,
converting the information data into standard data with a standard data format;
checking the integrity and correctness of the standard data, and filtering the standard data which do not meet the requirements;
and (5) persisting the standard data which passes the verification to a database, integrating and storing to obtain integrated data.
4. The vehicle insurance claim settlement intelligent anti-fraud method according to any one of claims 1 to 3, characterized in that: before S3, the method further includes the step of constructing a multidimensional vehicle insurance claim anti-fraud model.
5. The vehicle insurance claim settlement intelligent anti-fraud method of claim 4, characterized in that: the specific steps for constructing the anti-fraud model of the multi-dimensional vehicle insurance claim are as follows,
filtering non-fraud data related to the normal insurance of the vehicle and fraud data related to the fraud insurance of the vehicle from the historical data to form big data;
constructing an initial multi-dimensional vehicle insurance claim settlement anti-fraud model according to the neural network;
dividing the big data into a training set and a testing set, and training an initial multi-dimensional vehicle insurance claim anti-fraud model through the training set to obtain the multi-dimensional vehicle insurance claim anti-fraud model.
6. The vehicle insurance claim settlement intelligent anti-fraud method of claim 5, characterized in that: the specific steps of constructing the anti-fraud model of the multi-dimensional vehicle insurance claim also comprise testing the anti-fraud model of the multi-dimensional vehicle insurance claim according to the test set; if the test result is greater than the preset test threshold value, the anti-fraud model for the multi-dimensional vehicle insurance claim settlement meets the requirement; and if the test result is smaller than the preset test threshold, the anti-fraud model for the multi-dimensional vehicle insurance claim does not meet the requirement, the training set and the test set are re-divided, and the initial anti-fraud model for the multi-dimensional vehicle insurance claim is re-trained according to the re-divided training set.
7. The vehicle insurance claim settlement intelligent anti-fraud method according to any one of claims 1 to 3, characterized in that: specifically, the step S3 is,
and performing credit investigation analysis and claim settlement analysis on the integrated data through the multi-dimensional vehicle insurance claim anti-fraud model, and obtaining vehicle insurance claim fraud probability according to credit investigation analysis results and claim settlement analysis results.
8. The vehicle insurance claim settlement intelligent anti-fraud method of claim 7, characterized in that: specifically, the vehicle insurance claim fraud probability obtained according to the credit investigation result and the claim investigation result is,
the vehicle insurance claim fraud probability is calculated using the following formula,
wherein a and b are fixed constants, and a + b is 1, x1To assess the results of the analysis, x2And analyzing the result for the claim.
9. The vehicle insurance claim settlement intelligent anti-fraud method of claim 8, characterized in that: specifically, the step S4 is,
and if the vehicle insurance claim settlement fraud probability is greater than or equal to 0.8, the fraud behavior exists, otherwise, the fraud behavior does not exist.
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