CN112785149A - Automatic vehicle claims settlement and damage assessment method and system, computer equipment and storage medium - Google Patents
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Abstract
The application provides a vehicle automatic claims settlement and damage assessment method, a system, computer equipment and a storage medium, wherein vehicle filing information and/or user identity information which needs to be claimed are extracted according to vehicle claim settlement request information of a user; calling a corresponding insurance project according to the vehicle report information, and checking the insurance project; performing claim settlement identity verification according to the user identity information or the vehicle report information; when the insurance project verification and the claim settlement identity verification pass, performing automatic damage assessment condition verification, wherein the automatic damage assessment condition comprises that the user and an insured person of the insurance project are the same person; when the loss assessment condition is checked to pass, obtaining the loss assessment compensation amount through the insurance item information and the loss assessment amount mapping list; otherwise, prompting that the automatic damage assessment fails, and simultaneously pushing vehicle claim settlement request information of the user to a manual damage assessment process to perform manual damage assessment. According to the automatic vehicle claim settlement and loss assessment method, the efficiency of loss assessment operation is greatly improved, and the system directly maps the loss assessment amount according to the loss assessment logic, so that the claim settlement manpower is saved.
Description
Technical Field
The application belongs to the technical field of artificial intelligence, and particularly relates to a method and a system for automatically settling claims and determining damage of a vehicle, computer equipment and a storage medium.
Background
With the increase of vehicles and vehicle insurance products, the claims of the scooter are always puzzled by the claims time-effectiveness and the claims process, a client needs to face a long process and also needs to submit various complex documents and certification documents, time and labor are wasted, the claims can be paid out only after the documents are submitted and the insurance company passes the audit, the scooter can not be settled directly after the vehicle insurance claims are finished, and an insured cannot settle the claims timely through claims, so the timeliness of the claims and the convenience of the claims are very important for the user.
However, at present, the conventional scooter claim settlement is not communicated with the car insurance claim settlement information, so that the flow of the scooter claim settlement is long, the payment time is slow, part of claim data is repeatedly provided, the customer claim settlement experience is poor, if the customer claim settlement experience is not improved, the risk of customer complaints and even loss is faced, otherwise, the investment of claim settlement personnel is increased to meet the customer requirements, and the precious claim settlement manpower resources are largely invested in providing simple, repeated and low-value labor, so that the true value of the claim settlement is difficult to realize.
Therefore, a new automatic damage assessment method for vehicles is urgently needed, which puts through basic claim settlement data, improves case transfer efficiency, and meets the requirement of customers on claim settlement timeliness under the condition of not increasing claim settlement personnel.
Disclosure of Invention
The invention provides a method and a system for automatically settling claims and determining damage of a vehicle, and aims to solve the problems of long claim settling process and slow payment timeliness of the conventional method for settling claims on a scooter.
According to a first aspect of the embodiments of the present application, there is provided a method for automatically settling claims and setting damage of a vehicle, specifically including the following steps:
extracting vehicle report information and/or user identity information which need to be claimed according to vehicle claim settlement request information of a user;
calling a corresponding insurance project according to the vehicle report information, and checking the insurance project; performing claim settlement identity verification according to the user identity information or the vehicle report information;
when the insurance project verification and the claim settlement identity verification pass, performing automatic damage assessment condition verification, wherein the automatic damage assessment condition comprises that the user and an insured person of the insurance project are the same person;
when the loss assessment condition is checked to pass, obtaining the loss assessment compensation amount through the insurance item information and the loss assessment amount mapping list; otherwise, prompting that the automatic damage assessment fails, and simultaneously pushing vehicle claim settlement request information of the user to a manual damage assessment process to perform manual damage assessment.
In some embodiments of the present application, the vehicle registration information includes a license plate number, a vehicle insurance registration number, and/or an electronic version of a paper registration form; the user identity information comprises the identity card number, the account ID and/or the mobile phone number information of the user.
In some embodiments of the present application, the performing a claim identity validation according to the vehicle application information specifically includes:
obtaining a text recognition result through text recognition according to an electronic version paper report form of vehicle report information;
carrying out keyword retrieval according to the text recognition result to acquire the identity information of the insured;
searching an insurance information base according to the identity information of the insured life, and judging whether the insured life has claim rights and interests;
when the insured has the claim right, the identity verification of the claim is passed.
In some embodiments of the present application, the performing a claim identity validation according to the user identity information specifically includes:
searching an insurance staff information base according to the user identity information, and judging whether the user has claim settlement rights and interests;
and when the user has the claim right, the user passes the check of the claim right.
In some embodiments of the present application, the automatic damage assessment condition further includes that the user passes a voice verification, and the voice verification specifically includes the following steps:
acquiring first voice information of a user;
searching an insurance staff information base according to the user identity information to acquire second voice information prestored by the user;
comparing the audio characteristics according to the first voice information and the second voice information;
and if the user is determined to be the safe identity according to the comparison result, the user passes the voice verification.
In some embodiments of the present application, obtaining the indemnity amount by mapping the insurance item information with the indemnity amount mapping list specifically includes:
presetting the insurance policy insurance frequency and the insurance policy accumulated amount, and a mapping list of the loss settlement amount;
calculating the corresponding insurance policy insurance times and the accumulated amount of the insurance policy according to the insurance item information;
and automatically obtaining the loss-rated amount according to the insurance policy insurance number of times and the accumulated amount of the insurance policy corresponding to the mapping list of the loss-rated amount.
In some embodiments of the present application, the mapping relationship of the mapping list of the damage amount is:
when the number of times of insurance policy is greater than the time threshold value, or the accumulated amount of the insurance policy is greater than the first amount threshold value, the loss amount is zero;
when the accumulated amount of the policy is larger than the first amount threshold value and is smaller than or equal to the second amount threshold value, matching the corresponding loss settlement amount according to the vehicle type of the policy; the second amount threshold is greater than the first amount threshold;
and when the accumulated amount of the policy is larger than the second amount threshold, the loss-rated amount is the second amount threshold.
In some embodiments of the present application, after obtaining the indemnity amount, the method further comprises:
adjusting the loss settlement compensation amount according to the damage severity of the vehicle to obtain a final loss settlement compensation amount, which specifically comprises:
extracting an accident vehicle image from the vehicle claim settlement request information, and preprocessing the accident vehicle image;
inputting the preprocessed accident vehicle image into a first neural network model to extract vehicle damage characteristic data;
matching the vehicle damage characteristic data with images in a vehicle damage assessment database to obtain the damage severity of the accident vehicle and the vehicle damage severity coefficient;
and multiplying the loss settlement compensation amount by the vehicle damage severity coefficient to obtain the final loss settlement compensation amount.
According to a second aspect of the embodiments of the present application, there is provided a system for automatically settling claims and setting damage of a vehicle, specifically comprising:
the information extraction module: the system is used for extracting vehicle report information needing claim settlement and/or user identity information according to vehicle claim settlement request information of a user;
identity and project validation module: the system is used for calling corresponding insurance projects according to the vehicle report information and checking the insurance projects; performing claim settlement identity verification according to the user identity information or the vehicle report information;
loss assessment condition verification module: the system is used for carrying out automatic damage assessment condition verification when the insurance item verification and the claim settlement identity verification pass, wherein the automatic damage assessment condition comprises that a user and an insured person of the insurance item are the same person;
automatic loss assessment module: when the loss assessment condition is checked to pass, obtaining the loss assessment compensation amount through the insurance item information and the loss assessment amount mapping list; otherwise, prompting that the automatic damage assessment fails, and simultaneously pushing vehicle claim settlement request information of the user to a manual damage assessment process to perform manual damage assessment.
According to a third aspect of embodiments of the present application, there is provided a computer apparatus, including:
a memory: for storing executable instructions; and
and the processor is connected with the memory to execute the executable instructions so as to complete the automatic vehicle claim settlement and damage assessment method.
According to a fourth aspect of embodiments of the present application, there is provided a computer-readable storage medium having a computer program stored thereon; the computer program is executed by a processor to implement a vehicle automated claims settlement and damage assessment method.
By adopting the automatic vehicle claim settlement and damage assessment method and system, vehicle report information and/or user identity information which need claim settlement are extracted according to vehicle claim settlement request information of a user; calling a corresponding insurance project according to the vehicle report information, and checking the insurance project; performing claim settlement identity verification according to the user identity information or the vehicle report information; when the insurance project verification and the claim settlement identity verification pass, performing automatic damage assessment condition verification, wherein the automatic damage assessment condition comprises that the user and an insured person of the insurance project are the same person; when the loss assessment condition is checked to pass, obtaining the loss assessment compensation amount through the insurance item information and the loss assessment amount mapping list; otherwise, prompting that the automatic damage assessment fails, and simultaneously pushing vehicle claim settlement request information of the user to a manual damage assessment process to perform manual damage assessment. The efficiency of the automatic settlement and loss assessment of the vehicle greatly improves the operation of the loss assessment, and the system directly maps the amount of the loss assessment according to the logic of the loss assessment, so that the manpower of the settlement and the loss assessment is saved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
FIG. 1 is a flow chart illustrating steps of a method for automatically settling claims and setting damage for a vehicle according to an embodiment of the application;
FIG. 2 is a schematic flow chart illustrating an automatic vehicle claims settlement method according to an embodiment of the present application;
FIG. 3 is a flow chart illustrating steps of a method for automatically claiming claims and damage in a vehicle according to another embodiment of the present application;
fig. 4 is a schematic structural diagram of an automatic vehicle claims settlement system according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of the automatic vehicle claim settlement device according to the embodiment of the present application.
Detailed Description
In the process of implementing the application, the inventor finds that the conventional scooter claim settlement is not communicated with the car insurance claim settlement information, so that the flow of the scooter claim settlement is long, the payment time is slow, part of claim data is repeatedly provided, the customer claim settlement experience is poor, if the customer claim settlement experience is not improved, the risk of loss is encountered, otherwise, the investment of claim settlement personnel is increased to meet the customer requirements, and the precious claim settlement human resources are greatly put into the labor for providing simple, repeated and low-value claims, so that the true value of the claim settlement is difficult to realize.
Based on the method and the system for automatically settling the claims and determining the damage of the vehicle, identity verification and project information verification are carried out according to vehicle report information submitted by a client; when the identity check and the project information check are passed, performing damage assessment condition check; when the condition of the damage assessment is checked to pass, automatically assessing the damage of the vehicle to obtain the compensation amount of the damage assessment; otherwise, prompting the failure of automatic damage assessment, and pushing vehicle report information submitted by a client to a manual damage assessment process for manual damage assessment.
The efficiency of the automatic settlement and loss assessment of the vehicle greatly improves the operation of the loss assessment, and the system directly maps the amount of the loss assessment according to the logic of the loss assessment, so that the manpower of the settlement and the loss assessment is saved.
In addition, this application combines together automatic loss assessment and artifical loss assessment, has prevented the omission when automatic loss assessment, has reduced because of the insurant fills in information or uploads the data incorrect, the loss assessment failure rate that the artificial factor caused.
In addition, this application still combines together automatic loss assessment rule and actual vehicle damage degree, has increaseed the flexibility of loss assessment, has improved the scientificity of loss assessment to and the satisfaction of insured.
In order to make the technical solutions and advantages of the embodiments of the present application more apparent, the following further detailed description of the exemplary embodiments of the present application with reference to the accompanying drawings makes it clear that the described embodiments are only a part of the embodiments of the present application, and are not exhaustive of all 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.
Example 1
A flow chart of steps of a method for automatically settling claims and setting damage of a vehicle according to an embodiment of the application is shown in fig. 1.
As shown in fig. 1, the method for automatically settling claims and setting damage of a vehicle specifically includes the following steps:
s101: and extracting vehicle report information and/or user identity information which needs to be settled according to the vehicle claim settlement request information of the user.
First, the user submits vehicle claim request information, such as: for example: registration information such as license plate number, payment information, insurance registration number, electronic version paper registration form and the like, or user information of a user.
After the application acquires the claim settlement request information, vehicle report information and/or user identity information which need to be claimed are extracted, and claim settlement identity verification and insurance project verification are carried out.
The vehicle report information comprises a license plate number, a vehicle insurance report number and/or an electronic version paper report sheet; the user identity information comprises the identity card number, the account ID and/or the mobile phone number information of the user.
S102, calling a corresponding insurance project according to the vehicle report information, and checking the insurance project; and performing claim settlement identity verification according to the user identity information or the vehicle report information.
The claim identity verification comprises: and the user identity verification or the insured identity verification is carried out, and when one of the user and the insured verifies that the claim settlement right is in favor, the claim settlement identity verification passes.
Specifically, the following two cases are included:
when the vehicle claim settlement request information comprises user identity information, namely the vehicle claim settlement request information comprises one of identity number, account ID or mobile phone number information of a user of the user:
searching an insurance staff information base according to the user identity information, and judging whether the user has claim right. And if the user has the claim right, the claim identity verification passes.
And (II) if the user information does not contain the user identity information, identifying the identity information of the insured life according to an electronic version paper report form of the vehicle report information. It is determined whether the insured has claim right.
Specifically, the method comprises the following steps:
obtaining a text recognition result through text recognition according to an electronic version paper report form of vehicle report information;
carrying out keyword retrieval according to the text recognition result to acquire the identity information of the insured;
searching an insurance information base according to the identity information of the insured life, and judging whether the insured life has claim rights and interests;
when the insured has the claim right, the identity verification of the claim is passed.
When the user has the claim right or the insured has the claim right, the identity verification is passed; if neither the user nor the insured has the insurance claim right, a prompt message "the user or the insured does not have the claim right" is displayed.
Verification of information about the project:
according to the claim settlement request information, such as the license plate number, the insurance claim number and the electronic version paper claim form, the identity information matched with the insured life and the pre-stored insurance item information are called, and the following verification is carried out.
And when the report information comprises the license plate number and the vehicle insurance report number, searching an insurance item information base according to the license plate number and the vehicle insurance report number, and judging whether a corresponding insurance item exists.
And when the report information does not comprise the license plate number and the insurance report number, identifying the license plate number and the insurance report number according to the electronic version paper report sheet of the vehicle report information.
Specifically, the method comprises the following steps:
according to the electronic edition paper report form, a text recognition result is obtained through ocr text recognition;
carrying out keyword retrieval according to the text recognition result to obtain a license plate number and a vehicle insurance case number;
searching an insurance item information base according to the license plate number and the vehicle insurance report number, and judging whether the license plate number and the vehicle insurance report number have responsive insurance items.
When the corresponding insurance item is retrieved, the item passes the verification; otherwise, displaying a prompt message that the license plate number and the insurance report number do not exist.
Wherein, the vehicle insurance application number exists, but has already used, display "the vehicle insurance application number is wrong". Project verification failed either ".
The check of claim identity and the check of items can be carried out simultaneously, and the prompt information which does not pass can be displayed simultaneously.
S103: and when the insurance item verification and the claim settlement identity verification pass, performing automatic damage assessment condition verification.
The automatic damage assessment condition of the embodiment of the application comprises the following conditions: the user is the same person as the insured life of the insurance project.
Firstly, extracting user identity information according to vehicle claim settlement request information, and judging that the automatic damage assessment condition is not met if the user identity information does not exist, namely the identity card number, the account ID or the mobile phone number information of the user does not exist.
Secondly, determining the identity information of the insured life according to the vehicle report information, for example, identifying the identity information of the insured life according to an electronic version paper report form; and then, comparing the user identity information with the insured identity information, if the user identity information is consistent with the insured identity information, the user and the insured of the insurance project are the same person, and the automatic loss assessment condition is met.
S104: when the loss assessment condition is checked to pass, obtaining the loss assessment compensation amount through the insurance item information and the loss assessment amount mapping list; otherwise, prompting that the automatic damage assessment fails, and simultaneously pushing vehicle claim settlement request information of the user to a manual damage assessment process to perform manual damage assessment.
Step S104 specifically includes: firstly, presetting a mapping list of insurance policy insurance frequency, insurance policy accumulated amount and loss-fixing amount; then, calculating the corresponding insurance policy insurance times and the insurance policy accumulated amount according to the insurance item information; and finally, automatically obtaining the loss-rated amount according to the insurance policy insurance number of times and the accumulated amount of the insurance policy corresponding to the mapping list of the loss-rated amount.
Specifically, the mapping relationship of the mapping list of the loss assessment amount is as follows:
when the number of times of insurance policy is greater than the time threshold value, or the accumulated amount of the insurance policy is greater than the first amount threshold value, the loss amount is zero;
when the accumulated amount of the policy is larger than the first amount threshold value and is smaller than or equal to the second amount threshold value, matching the corresponding loss settlement amount according to the vehicle type of the policy; the second amount threshold is greater than the first amount threshold;
and when the accumulated amount of the policy is larger than the second amount threshold, the loss-rated amount is the second amount threshold.
Specifically, when the corresponding loss assessment amount is matched according to the vehicle type of the policy:
firstly, matching vehicle grades according to the vehicle types of policy-keeping vehicles; and then, according to the vehicle grade, performing vehicle loss matching to obtain the loss assessment amount of the corresponding vehicle.
The vehicle grade table and the vehicle damage assessment table can be calibrated and modified.
In step S104, if the damage assessment condition check fails, a prompt is made to push the information to the manual damage assessment process.
And when the verification fails, converting the damage assessment process into conventional manual damage assessment, and performing detailed manual verification and damage assessment by related personnel.
The omission of automatic damage assessment is prevented, and the damage assessment failure rate caused by artificial factors such as incorrect information filling or data uploading of the insured is reduced.
In other embodiments, the number of policy offers and the cumulative amount of the policy need to be determined before the comparison of the number of policy offers and the cumulative amount of the policy is performed in step S104.
Two approaches are involved:
the first way is to directly call the accumulated insurance record of the insured, and accumulate and calculate the number of the insurances and the amount of the insurance policy to obtain the number of the insurances of the insured vehicle and the accumulated amount of the insurance policy.
The second approach: and if the insurance policy is uploaded by the insurer, performing image recognition to obtain the total insurance policy insurance times and the accumulated amount of the insurance policy.
The specific process of identifying the image text is as follows:
1) and acquiring an image to be identified.
2) Inputting an image to be recognized into an image compression righting network to rotate so as to enable a text in the image to be recognized to be in a horizontal position;
the image compression normal position network is obtained by training through a machine learning method and has an image rotation function.
3) The image output from the image compression righting network device identifies text.
When the text image is identified, the method has the advantages that the mode of combining the self-encoder with the convolutional neural network is adopted, so that the user does not need to pre-process the original image, convenience is provided for the user, and meanwhile, higher character identification precision is maintained; the complicated steps of the existing character recognition are simplified, and the character recognition can be completed in the same network system.
Specifically, the convolutional self-encoder includes an encoder composed of a plurality of convolutional layers and pooling layers, and a decoder composed of an anti-pooling layer and an anti-convolutional layer. The convolution layer comprises a plurality of convolution kernels, and feature extraction is carried out on the input image to obtain a feature map; the pooling layer performs a de-noising sampling operation on the feature map to reduce the computational complexity of the convolution operation. The deconvolution operation convolves and sums each feature map with the transpose of its corresponding convolution kernel.
The method and the device have the advantages that the convolution self-encoder is used for carrying out rotation transformation on the input text image, so that the arrangement direction of the output image text is horizontal, and the character segmentation accuracy is improved.
The image compression normal position network compresses the image to be identified while rotating the image to be identified; cutting the compressed and rotated image to be identified line by line and word by word according to the mark points; and inputting the cut image to be recognized into a text recognition neural network for text recognition, wherein the text recognition neural network is obtained by training through a machine learning method and has a text recognition function.
According to the automatic vehicle claim settlement and damage assessment method, vehicle report information and/or user identity information which need claim settlement are extracted according to vehicle claim settlement request information of a user; calling a corresponding insurance project according to the vehicle report information, and checking the insurance project; performing claim settlement identity verification according to the user identity information or the vehicle report information; when the insurance project verification and the claim settlement identity verification pass, performing automatic damage assessment condition verification, wherein the automatic damage assessment condition comprises that the user and an insured person of the insurance project are the same person; when the loss assessment condition is checked to pass, obtaining the loss assessment compensation amount through the insurance item information and the loss assessment amount mapping list; otherwise, prompting that the automatic damage assessment fails, and simultaneously pushing vehicle claim settlement request information of the user to a manual damage assessment process to perform manual damage assessment.
The efficiency of the automatic settlement and loss assessment of the vehicle greatly improves the operation of the loss assessment, and the system directly maps the amount of the loss assessment according to the logic of the loss assessment, so that the manpower of the settlement and the loss assessment is saved.
In addition, this application combines together automatic loss assessment and artifical loss assessment, has prevented the omission when automatic loss assessment, has reduced because of the insurant fills in information or uploads the data incorrect, the loss assessment failure rate that the artificial factor caused. In addition, this application still combines together automatic loss assessment rule and actual vehicle damage degree, has increaseed the flexibility of loss assessment, has improved the scientificity of loss assessment to and the satisfaction of insured.
Example 2
In the automatic vehicle claims settlement method of embodiment 2, based on the automatic vehicle claims settlement method of embodiment 1, the automatic damage assessment conditions of step S103 further include a second condition: and the user passes the voice verification, namely the voice information of the user is obtained, voice recognition is carried out, the voice recognition is compared with the reserved voice information, and the identity of the user is verified.
Firstly, a security identity library is constructed, wherein the security identity library comprises voice data reserved during user registration.
Then, when a client logs in, voice information needs to be input, and the voice information to be verified is obtained after processing;
and finally, performing voice verification on the two sections of voice data.
The specific voice verification process comprises the following steps:
acquiring first voice information of a user; searching an insurance staff information base according to the user identity information to acquire second voice information prestored by the user; comparing the audio characteristics according to the first voice information and the second voice information; and if the user is determined to be the safe identity according to the comparison result, the user passes the voice verification.
In the concrete implementation process, the method comprises the following steps of,
respectively extracting the characteristics of the first voice information and the second voice information, namely the audio to be verified input by a user and the pre-stored audio to obtain respective corresponding audio vectors;
calculating the similarity of the two audio vectors by using a cosine similarity formula, and recording the similarity as a first similarity;
judging whether the first similarity is higher than a first preset threshold value, if so, judging that the current user is a safe identity, otherwise, executing the next step;
constructing a sound similarity calculation model based on deep learning; the specific process comprises the following steps:
extracting the voice audio of the client A from the registry, and performing characteristic extraction on the audio to obtain a corresponding audio vector which is recorded as an audio characteristic a;
extracting the voice audio of each user in the verification library to obtain corresponding audio vectors which are respectively recorded as audio features b1,b2,…,bnForming an audio feature set B; n is the number of voice audios in the validation library.
Randomly extracting a plurality of audio features from the audio feature set B, wherein each audio feature and the audio feature a form a sample to form a training sample set;
inputting the training sample set into an LSTM neural network for training to generate a sound similarity calculation model; inputting the audio vector of the voice audio input by the current user and the audio feature corresponding to the user in the audio feature set B into the sound similarity calculation model, and outputting the similarity of the audio vector and the audio feature to be recorded as a second similarity;
and judging whether the second similarity is higher than a second preset threshold, if so, judging that the current user is a safe identity, otherwise, judging that the current user is an unsafe identity.
Here, the first preset threshold and the second preset threshold are preferably set to 80% and 50%, respectively.
In other embodiments, the method further includes performing speech preprocessing on the speech of the user, where pre-emphasis, framing, and windowing are required to be performed on the original speech to obtain the standard speech.
The specific process of obtaining the standard voice is as follows:
firstly, the pre-emphasis processing formula is adopted to perform the pre-emphasis processing on the original voice so as to eliminate the influence of vocal cords and lips of a speaker on the voice of the speaker and improve the high-frequency resolution of the voice of the speaker.
The formula of the pre-emphasis processing is as follows:
S′n＝Sn-a*Sn-1；
wherein S' n is the speech signal amplitude at n moments after pre-emphasis processing, SnAmplitude of speech signal at time n, Sn-1Is the speech signal amplitude at the moment n-1 and a is the pre-emphasis coefficient.
Then, the pre-emphasized original speech is subjected to framing processing, and when framing is performed, discontinuous places appear at the starting point and the end point of each frame of speech, and the more framing, the larger the error with the original speech.
Finally, windowing is also required to maintain the frequency characteristics of each frame of speech.
The formula for the windowing process is:
S″n＝Wn*S′n；
wherein, WnIs a Hamming window at N moments, N is the Hamming window length, and S' N is the signal amplitude in the time domain after the windowing at N moments.
The original voice is preprocessed through the steps to obtain the standard voice, and an effective data source is provided for the subsequent endpoint detection processing of the standard voice.
And finally, after voice comparison, determining that the user is a safe identity, and then, the user passes the voice verification.
Example 3
The method for automatically settling and fixing loss for a vehicle according to embodiment 3 is based on the method for automatically settling and fixing loss for a vehicle according to embodiment 1 or embodiment 2, as shown in fig. 3, when the condition for fixing loss is verified in step 104, the method for automatically settling loss for a vehicle is performed to obtain the compensation amount for fixing loss, and further includes step 105: and adjusting the loss settlement compensation amount according to the damage severity of the vehicle to obtain the final loss settlement compensation amount.
Step 105 specifically includes:
firstly, extracting an accident vehicle image from vehicle claim settlement request information and preprocessing the accident vehicle image;
secondly, inputting the preprocessed accident vehicle image into a first neural network model to extract vehicle damage characteristic data;
then, carrying out image matching on the vehicle damage characteristic data and the images in the vehicle damage assessment database to obtain the damage severity degree of the accident vehicle and the vehicle damage severity coefficient;
and finally, multiplying the loss settlement compensation amount by the vehicle damage severity coefficient to obtain the final loss settlement compensation amount.
Wherein the severity coefficient is an integer or decimal between 1-10.
The application combines together automatic loss assessment rule and actual vehicle damage degree, has increaseed the flexibility of loss assessment, has improved the scientificity of loss assessment to and the satisfaction of insured.
Example 4
For details that are not disclosed in the automatic vehicle claim settlement and damage assessment system of this embodiment, please refer to implementation contents of the automatic vehicle claim settlement and damage assessment method in other embodiments.
A schematic structural diagram of the automatic vehicle claim settlement and damage assessment system according to the embodiment of the present application is shown in fig. 4.
As shown in fig. 4, the automatic vehicle claim settlement and damage assessment system of the present application includes an information extraction module 10, an identity and project verification module 20, a damage condition verification module 30, and an automatic damage assessment module 40.
In particular, the method comprises the following steps of,
the information extraction module 10: the system is used for extracting vehicle report information needing claim settlement and/or user identity information according to vehicle claim settlement request information of a user;
first, the user submits vehicle claim request information, such as: for example: registration information such as license plate number, payment information, insurance registration number, electronic version paper registration form and the like, or user information of a user.
After the application acquires the claim settlement request information, vehicle report information and/or user identity information which need to be claimed are extracted, and claim settlement identity verification and insurance project verification are carried out.
The vehicle report information comprises a license plate number, a vehicle insurance report number and/or an electronic version paper report sheet; the user identity information comprises the identity card number, the account ID and/or the mobile phone number information of the user.
Identity and item validation module 20: the system is used for calling corresponding insurance projects according to the vehicle report information and checking the insurance projects; performing claim settlement identity verification according to the user identity information or the vehicle report information;
the claim identity verification comprises: and the user identity verification or the insured identity verification is carried out, and when one of the user and the insured verifies that the claim settlement right is in favor, the claim settlement identity verification passes.
Specifically, the following two cases are included:
when the vehicle claim settlement request information comprises user identity information, namely the vehicle claim settlement request information comprises one of identity number, account ID or mobile phone number information of a user of the user:
searching an insurance staff information base according to the user identity information, and judging whether the user has claim right. And if the user has the claim right, the claim identity verification passes.
And (II) if the user information does not contain the user identity information, identifying the identity information of the insured life according to an electronic version paper report form of the vehicle report information. It is determined whether the insured has claim right.
Specifically, the method comprises the following steps:
obtaining a text recognition result through text recognition according to an electronic version paper report form of vehicle report information;
carrying out keyword retrieval according to the text recognition result to acquire the identity information of the insured;
searching an insurance information base according to the identity information of the insured life, and judging whether the insured life has claim rights and interests;
when the insured has the claim right, the identity verification of the claim is passed.
When the user has the claim right or the insured has the claim right, the identity verification is passed; if neither the user nor the insured has the insurance claim right, a prompt message "the user or the insured does not have the claim right" is displayed.
Verification of information about the project:
according to the claim settlement request information, such as the license plate number, the insurance claim number and the electronic version paper claim form, the identity information matched with the insured life and the pre-stored insurance item information are called, and the following verification is carried out.
And when the report information comprises the license plate number and the vehicle insurance report number, searching an insurance item information base according to the license plate number and the vehicle insurance report number, and judging whether a corresponding insurance item exists.
And when the report information does not comprise the license plate number and the insurance report number, identifying the license plate number and the insurance report number according to the electronic version paper report sheet of the vehicle report information.
Specifically, the method comprises the following steps:
according to the electronic edition paper report form, a text recognition result is obtained through ocr text recognition;
carrying out keyword retrieval according to the text recognition result to obtain a license plate number and a vehicle insurance case number;
searching an insurance item information base according to the license plate number and the vehicle insurance report number, and judging whether the license plate number and the vehicle insurance report number have responsive insurance items.
When the corresponding insurance item is retrieved, the item passes the verification; otherwise, displaying a prompt message that the license plate number and the insurance report number do not exist.
Wherein, the vehicle insurance application number exists, but has already used, display "the vehicle insurance application number is wrong". Project verification failed either ".
The check of claim identity and the check of items can be carried out simultaneously, and the prompt information which does not pass can be displayed simultaneously.
Loss assessment condition verification module 30: the system is used for carrying out automatic damage assessment condition verification when the insurance item verification and the claim settlement identity verification pass, wherein the automatic damage assessment condition comprises that a user and an insured person of the insurance item are the same person;
the automatic damage assessment condition of the embodiment of the application comprises the following conditions: the user is the same person as the insured life of the insurance project.
Firstly, extracting user identity information according to vehicle claim settlement request information, and judging that the automatic damage assessment condition is not met if the user identity information does not exist, namely the identity card number, the account ID or the mobile phone number information of the user does not exist.
Secondly, determining the identity information of the insured life according to the vehicle report information, for example, identifying the identity information of the insured life according to an electronic version paper report form; and then, comparing the user identity information with the insured identity information, if the user identity information is consistent with the insured identity information, the user and the insured of the insurance project are the same person, and the automatic loss assessment condition is met.
Automatic damage assessment module 40: when the loss assessment condition is checked to pass, obtaining the loss assessment compensation amount through the insurance item information and the loss assessment amount mapping list; otherwise, prompting that the automatic damage assessment fails, and simultaneously pushing vehicle claim settlement request information of the user to a manual damage assessment process to perform manual damage assessment.
The method specifically comprises the following steps: firstly, presetting a mapping list of insurance policy insurance frequency, insurance policy accumulated amount and loss-fixing amount; then, calculating the corresponding insurance policy insurance times and the insurance policy accumulated amount according to the insurance item information; and finally, automatically obtaining the loss-rated amount according to the insurance policy insurance number of times and the accumulated amount of the insurance policy corresponding to the mapping list of the loss-rated amount.
Specifically, the mapping relationship of the mapping list of the loss assessment amount is as follows:
when the number of times of insurance policy is greater than the time threshold value, or the accumulated amount of the insurance policy is greater than the first amount threshold value, the loss amount is zero;
when the accumulated amount of the policy is larger than the first amount threshold value and is smaller than or equal to the second amount threshold value, matching the corresponding loss settlement amount according to the vehicle type of the policy; the second amount threshold is greater than the first amount threshold;
and when the accumulated amount of the policy is larger than the second amount threshold, the loss-rated amount is the second amount threshold.
Specifically, when the corresponding loss assessment amount is matched according to the vehicle type of the policy:
firstly, matching vehicle grades according to the vehicle types of policy-keeping vehicles; and then, according to the vehicle grade, performing vehicle loss matching to obtain the loss assessment amount of the corresponding vehicle.
The vehicle grade table and the vehicle damage assessment table can be calibrated and modified.
In the automatic damage assessment module 40, if the damage assessment condition check fails, a prompt is made to push the information to the manual damage assessment process.
And when the verification fails, converting the damage assessment process into conventional manual damage assessment, and performing detailed manual verification and damage assessment by related personnel.
The omission of automatic damage assessment is prevented, and the damage assessment failure rate caused by artificial factors such as incorrect information filling or data uploading of the insured is reduced.
In the automatic vehicle claim settlement and damage assessment system of the embodiment of the application, the information extraction module 10 extracts vehicle report information and/or user identity information which needs to be claimed according to vehicle claim settlement request information of a user; the identity and project verification module 20 calls a corresponding insurance project according to the vehicle report information and checks the insurance project; performing claim settlement identity verification according to the user identity information or the vehicle report information; the loss assessment condition verification module 30 performs automatic loss assessment condition verification when the insurance item verification and the claim settlement identity verification both pass, wherein the automatic loss assessment condition includes that the user and an insured person of the insurance item are the same person; when the damage condition is checked to pass, the automatic damage assessment module 40 obtains the damage assessment compensation amount through the insurance item information and the damage assessment amount mapping list; otherwise, prompting that the automatic damage assessment fails, and simultaneously pushing vehicle claim settlement request information of the user to a manual damage assessment process to perform manual damage assessment.
The efficiency of the automatic settlement and loss assessment of the vehicle greatly improves the operation of the loss assessment, and the system directly maps the amount of the loss assessment according to the logic of the loss assessment, so that the manpower of the settlement and the loss assessment is saved.
In addition, this application combines together automatic loss assessment and artifical loss assessment, has prevented the omission when automatic loss assessment, has reduced because of the insurant fills in information or uploads the data incorrect, the loss assessment failure rate that the artificial factor caused. In addition, this application still combines together automatic loss assessment rule and actual vehicle damage degree, has increaseed the flexibility of loss assessment, has improved the scientificity of loss assessment to and the satisfaction of insured.
Example 5
For details that are not disclosed in the automatic vehicle claim settlement and damage assessment apparatus of this embodiment, please refer to specific implementation contents of the automatic vehicle claim settlement and damage assessment method or system in other embodiments.
A schematic structural diagram of the automatic vehicle claim settlement and damage assessment apparatus 400 according to the embodiment of the present application is shown in fig. 5.
As shown in fig. 5, the automatic vehicle claims settlement 400 includes:
the memory 402: for storing executable instructions; and
and the processor 401 is connected with the memory 402 to execute the executable instructions so as to complete the automatic vehicle claim settlement method.
Those skilled in the art will appreciate that the schematic diagram 5 is merely an example of the vehicle automatic claims settlement device 400 and does not constitute a limitation of the vehicle automatic claims settlement device 400, and may include more or less components than those shown, or some components in combination, or different components, for example, the vehicle automatic claims settlement device 400 may further include input and output devices, network access devices, buses, etc.
The Processor 401 (CPU) may be other general-purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, a discrete hardware component, or the like. The general purpose processor may be a microprocessor or the processor 401 may be any conventional processor or the like, and the processor 401 is the control center of the vehicle automated claims damage review apparatus 400, and various interfaces and lines are used to connect the various parts of the entire vehicle automated claims damage review apparatus 400.
The memory 402 may be used to store the computer readable instructions, and the processor 401 may implement the various functions of the vehicle automatic claims settlement and damage device 400 by executing or executing the computer readable instructions or modules stored in the memory 402 and invoking the data stored in the memory 402. The memory 402 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data created according to the use of the vehicle automatic claims settlement apparatus 400, and the like. In addition, the Memory 402 may include a hard disk, a Memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash Memory Card (Flash Card), at least one disk storage device, a Flash Memory device, a Read-Only Memory (ROM), a Random Access Memory (RAM), or other non-volatile/volatile storage devices.
The modules integrated by the automatic claims settlement and damage assessment apparatus 400 may be stored in a computer-readable storage medium if they are implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, all or part of the flow of the method according to the above embodiments may be implemented by hardware that is configured to be instructed by computer readable instructions, which may be stored in a computer readable storage medium, and when the computer readable instructions are executed by a processor, the steps of the method embodiments may be implemented.
Example 5
The present embodiment provides a computer-readable storage medium having stored thereon a computer program; the computer program is executed by the processor to implement the automatic vehicle claims settlement and damage assessment method in other embodiments.
By adopting the automatic vehicle claim settlement and damage assessment equipment and the storage medium in the embodiment of the application, vehicle report information and/or user identity information needing claim settlement are extracted according to vehicle claim settlement request information of a user; calling a corresponding insurance project according to the vehicle report information, and checking the insurance project; performing claim settlement identity verification according to the user identity information or the vehicle report information; when the insurance project verification and the claim settlement identity verification pass, performing automatic damage assessment condition verification, wherein the automatic damage assessment condition comprises that the user and an insured person of the insurance project are the same person; when the loss assessment condition is checked to pass, obtaining the loss assessment compensation amount through the insurance item information and the loss assessment amount mapping list; otherwise, prompting that the automatic damage assessment fails, and simultaneously pushing vehicle claim settlement request information of the user to a manual damage assessment process to perform manual damage assessment.
The efficiency of the automatic settlement and loss assessment of the vehicle greatly improves the operation of the loss assessment, and the system directly maps the amount of the loss assessment according to the logic of the loss assessment, so that the manpower of the settlement and the loss assessment is saved.
In addition, this application combines together automatic loss assessment and artifical loss assessment, has prevented the omission when automatic loss assessment, has reduced because of the insurant fills in information or uploads the data incorrect, the loss assessment failure rate that the artificial factor caused. In addition, this application still combines together automatic loss assessment rule and actual vehicle damage degree, has increaseed the flexibility of loss assessment, has improved the scientificity of loss assessment to and the satisfaction of insured.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this specification and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It is to be understood that although the terms first, second, third, etc. may be used herein to describe various information, these information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the present invention. The word "if" as used herein may be interpreted as "at … …" or "when … …" or "in response to a determination", depending on the context.
While the preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all alterations and modifications as fall within the scope of the application.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.
Claims (10)
1. A method for automatically settling claims and determining damage of a vehicle is characterized by comprising the following steps:
extracting vehicle report information and/or user identity information which need to be claimed according to vehicle claim settlement request information of a user;
calling a corresponding insurance project according to the vehicle report information, and checking the insurance project; performing claim settlement identity verification according to the user identity information or the vehicle report information;
when the insurance project verification and the claim settlement identity verification pass, performing automatic damage assessment condition verification, wherein the automatic damage assessment condition comprises that a user and an insured person of the insurance project are the same person;
when the loss assessment condition is checked to pass, obtaining the loss assessment compensation amount through the insurance item information and the loss assessment amount mapping list; otherwise, prompting that the automatic damage assessment fails, and simultaneously pushing vehicle claim settlement request information of the user to a manual damage assessment process to perform manual damage assessment.
2. The method for automatically claims settlement and damage assessment according to claim 1, wherein the vehicle report information comprises a license plate number, a vehicle insurance report number and/or an electronic version paper report form; the user identity information comprises an identity card number, an account ID and/or mobile phone number information of the user;
the check of claim settlement identity is carried out according to the vehicle report information, and the check specifically comprises the following steps:
obtaining a text recognition result through text recognition according to the electronic version paper report form of the vehicle report information;
carrying out keyword retrieval according to the text recognition result to acquire the identity information of the insured;
searching an insurance information base according to the identity information of the insured life, and judging whether the insured life has claim rights and interests;
and when the insured has the claim right, passing the claim identity verification.
3. The method for automatically claims settlement and damage assessment for vehicles according to claim 1, wherein the verification of claim settlement identity according to the user identity information specifically comprises:
searching an insurance staff information base according to the user identity information, and judging whether the user has claim settlement rights and interests;
and when the user has the claim right, the user passes the check of the claim right.
4. The method for automatically claims settlement and damage assessment for vehicles according to claim 1, wherein the automatic damage assessment condition further comprises the user passing a voice check, and the voice check comprises the following specific steps:
acquiring first voice information of a user;
searching an insurance staff information base according to the user identity information, and acquiring second voice information prestored by the user;
comparing audio features according to the first voice information and the second voice information;
and if the user is determined to be the safe identity according to the comparison result, the user passes the voice verification.
5. The method according to claim 1, wherein the obtaining of the indemnity amount through the mapping list of the insurance item information and the indemnity amount comprises:
presetting the insurance policy insurance frequency and the insurance policy accumulated amount, and a mapping list of the loss settlement amount;
calculating the corresponding insurance policy insurance times and the accumulated amount of the insurance policy according to the insurance item information;
and automatically obtaining the loss-rated amount corresponding to the mapping list of the loss-rated amount according to the insurance policy number of times and the accumulated amount of the insurance policy.
6. The automatic vehicle claims and loss assessment method according to claim 1, wherein the mapping relationship of the mapping list of loss assessment amounts is as follows:
when the number of times of insurance policy is greater than the time threshold value, or the accumulated amount of the insurance policy is greater than the first amount threshold value, the loss amount is zero;
when the accumulated amount of the policy is larger than the first amount threshold value and is smaller than or equal to the second amount threshold value, matching the corresponding loss settlement amount according to the vehicle type of the policy; the second amount threshold is greater than the first amount threshold;
and when the accumulated amount of the policy is larger than the second amount threshold, the loss-rated amount is the second amount threshold.
7. The method for automatically claiming and setting forth a claim 1, wherein said obtaining a set of compensation amounts further comprises:
adjusting the indemnity amount according to the damage severity of the vehicle to obtain a final indemnity amount, which specifically comprises:
extracting an accident vehicle image from the vehicle claim settlement request information, and preprocessing the accident vehicle image;
inputting the preprocessed accident vehicle image into a first neural network model to extract vehicle damage characteristic data;
matching the vehicle damage characteristic data with images in a vehicle damage assessment database to obtain the damage severity of the accident vehicle and a vehicle damage severity coefficient;
and multiplying the loss settlement compensation amount by the vehicle damage severity coefficient to obtain a final loss settlement compensation amount.
8. The utility model provides a vehicle automatic claims settlement loss assessment system which specifically includes:
the information extraction module: the system is used for extracting vehicle report information needing claim settlement and/or user identity information according to vehicle claim settlement request information of a user;
identity and project validation module: the system is used for calling a corresponding insurance project according to the vehicle report information and checking the insurance project; performing claim settlement identity verification according to the user identity information or the vehicle report information;
loss assessment condition verification module: the system is used for carrying out automatic damage assessment condition verification when the insurance item verification and the claim settlement identity verification pass, wherein the automatic damage assessment condition comprises that a user and an insured person of the insurance item are the same person;
automatic loss assessment module: the system is used for obtaining the loss settlement compensation amount through the insurance item information and the loss settlement amount mapping list when the loss settlement condition is checked to pass; otherwise, prompting that the automatic damage assessment fails, and simultaneously pushing vehicle claim settlement request information of the user to a manual damage assessment process to perform manual damage assessment.
9. A computer device, comprising:
a memory: for storing executable instructions; and
a processor for interfacing with the memory to execute the executable instructions to perform the method of automatically claims 1-7.
10. A computer-readable storage medium, having stored thereon a computer program; the computer program is executed by a processor to implement the vehicle automatic claims settlement and damage assessment method according to any one of claims 1 to 7.
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Application publication date: 20210511 |