CN117350866A - Insurance claim fraud risk location identification method and apparatus - Google Patents

Abstract

The embodiment of the disclosure provides an insurance claim fraud risk site identification method and device, comprising the following steps: acquiring the risk position information in the claim settlement policy; determining a target risk area to which the risk position information belongs; according to the risk area of the target of the position information of the danger and the position information of the danger, confirm whether the place that the position information of the danger corresponds to is the place of risk of fraud of insurance claim, rely on the accumulated experience in the work of the salesman of claim, the method can carry on the processing of the claim application of batch fast, can confirm the place that the position information of the danger corresponds to the place of risk of fraud of insurance claim according to the position information of the danger and the target of the position information of the danger in the case of claim, predict and discern the place of risk, raise the recognition efficiency of anti-fraud, reduce the probability of the financial institution to take place and pay fraud.

Description

Insurance claim fraud risk location identification method and apparatus

Technical Field

Embodiments of the present disclosure relate to the field of identifying insurance fraud and related technology, and in particular, to a method and apparatus for identifying a fraud risk location applicable to an insurance claim.

Background

Currently, in the field of financial insurance (e.g., in the field of car insurance), some customers may make insurance with the aim of cheating insurance or provide false claim information (e.g., fictional insurance accident sites, insurance damage sites, and insurance emergence sites) while transacting related insurance claim services.

In order to avoid such risks, enterprises related to financial insurance usually set special claims settlement auditing posts, adopt a manual auditing mode to conduct anti-fraud recognition on the claims settlement application of clients based on professional experience, and have low anti-fraud recognition efficiency, and because professional levels of auditors are different, partial cases may have insufficient recognition strength on hidden risks.

Disclosure of Invention

Embodiments described herein provide a method and apparatus for identifying points of risk of insurance claims fraud that address the problems of the prior art.

In a first aspect, according to the present disclosure, there is provided a method of identifying an insurance claim fraud risk location, comprising:

acquiring the risk position information in the claim settlement policy;

determining a target risk area to which the risk position information belongs;

and determining whether the place corresponding to the dangerous position information is an insurance claim fraud risk place or not according to the dangerous position information and a target risk area to which the dangerous position information belongs.

In some embodiments of the present disclosure, the determining, according to the risk position information and the target risk area to which the risk position information belongs, whether the location corresponding to the risk position information is an insurance claim fraud risk location includes:

acquiring a corresponding relation between a risk area and a risk coefficient;

determining a risk coefficient of the risk position information according to the corresponding relation between the risk area and the risk coefficient;

and determining whether the place corresponding to the dangerous position information is an insurance claim fraud risk place or not according to the dangerous position information and the dangerous risk coefficient of the dangerous position information.

In some embodiments of the present disclosure, the determining, according to the risk coefficient of the risk location information and the risk location information, whether the location corresponding to the risk location information is an insurance claim fraud risk location includes:

encoding the risk exposure location information and risk exposure coefficients of the risk exposure location information, obtaining a risk position vector and a risk coefficient vector, wherein the risk position information comprises risk name information and risk place information;

and inputting the risk position vector and the risk coefficient vector to an identification model, and determining whether the place corresponding to the risk position information is an insurance claim fraud risk place or not based on the identification model.

In some embodiments of the present disclosure, before determining the target risk area to which the risk-out location information belongs, the method further includes:

acquiring a first tag identifier corresponding to the risk position information, wherein the first tag identifier is an identifier of an administrative region in which the risk position is located;

determining a risk area and a risk location included in the risk area, wherein the risk area includes at least one risk location;

acquiring a second tag identifier corresponding to the risk area, wherein the second tag identifiers corresponding to the risk positions included in the same risk area are the same, and the second tag identifiers are identifiers of administrative areas where the risk positions are located in the risk area;

the determining the target risk area to which the risk position information belongs includes:

and determining a target risk area to which the risk position information belongs according to the matching degree of the first label identification corresponding to the risk position information and the second label identification corresponding to the risk area.

In some embodiments of the present disclosure, the determining, according to the matching degree of the first tag identifier corresponding to the risk location information and the second tag identifier corresponding to the risk area, the target risk area to which the risk location information belongs includes:

Sequentially obtaining the matching degree of the tag identification corresponding to the position information and the tag identification corresponding to each risk area;

and selecting a risk area with highest matching degree between the tag identification corresponding to the position information and the tag identification corresponding to the risk area as a target risk area.

In some embodiments of the present disclosure, when acquiring the risk position information in the claim policy, the method further includes:

acquiring the application position information in the claim policy;

the determining whether the location corresponding to the risk position information is an insurance claim fraud risk location according to the risk position information and the target risk area to which the risk position information belongs, includes:

and determining whether a place corresponding to the insurance position information is an insurance claim fraud risk place according to the insurance position information, the insurance position information and a target risk area to which the insurance position information belongs.

In some embodiments of the disclosure, the acquiring the risk location information in the claim policy includes:

performing text recognition on the claim settlement policy to obtain target text content corresponding to the target tag identification;

and preprocessing the target text content corresponding to the target tag identifier to obtain the risk position information.

In some embodiments of the present disclosure, before the acquiring the risk position information in the claim policy, the method further includes

And responding to the target object to submit the claim settlement application, and generating a claim settlement policy corresponding to the claim settlement application.

In some embodiments of the present disclosure, the method further comprises:

and when the place corresponding to the dangerous position information is determined to be the insurance claim fraud risk place, the place corresponding to the dangerous position information is marked in the target risk area.

In a second aspect, according to the present disclosure, there is provided an insurance claim fraud risk location identification device, comprising:

the insurance position information acquisition module is used for acquiring the insurance position information in the claim insurance policy;

the target risk area determining module is used for determining a target risk area to which the risk position information belongs;

and the fraud risk location determining module is used for determining whether the location corresponding to the insurance position information is an insurance claim fraud risk location according to the insurance position information and the target risk area to which the insurance position information belongs.

The method and the device for identifying the insurance claim fraud risk site provided by the embodiment of the disclosure firstly acquire the risk position information in the claim settlement policy; then determining a target risk area to which the risk position information belongs; and finally, determining whether the place corresponding to the risk position information is an insurance claim fraud risk place according to the risk position information and a target risk area to which the risk position information belongs, namely analyzing the risk coefficient of the input risk position information and the target risk area to which the risk position information belongs based on an identification model, and determining whether the place corresponding to the risk position information is the insurance claim fraud risk place, so that batch claim settlement application can be rapidly processed, the anti-fraud identification efficiency is improved, and the probability of the financial institution to generate claim fraud is reduced. The foregoing description is only an overview of the technical solutions of the embodiments of the present application, and may be implemented according to the content of the specification, so that the technical means of the embodiments of the present application can be more clearly understood, and the following detailed description of the present application will be presented in order to make the foregoing and other objects, features and advantages of the embodiments of the present application more understandable.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the following brief description of the drawings of the embodiments will be given, it being understood that the drawings described below relate only to some embodiments of the present disclosure, not to limitations of the present disclosure, in which:

FIG. 1 is a flow diagram of an insurance claim fraud risk location identification method provided by an embodiment of the present disclosure;

FIG. 2 is a flow chart of a method for identifying an alternative insurance claim fraud risk location according to an embodiment of the present disclosure;

FIG. 3 is a flow chart of yet another method for identifying an insurance claim fraud risk location provided by an embodiment of the present disclosure;

FIG. 4 is a schematic diagram of an apparatus for identifying a location of risk of fraud for insurance claims according to an embodiment of the present disclosure;

fig. 5 is a schematic structural diagram of a computer device according to an embodiment of the present disclosure.

In the drawings, the last two digits are identical to the elements. It is noted that the elements in the drawings are schematic and are not drawn to scale.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present disclosure more apparent, the technical solutions of the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings. It will be apparent that the described embodiments are some, but not all, of the embodiments of the present disclosure. All other embodiments, which can be made by those skilled in the art based on the described embodiments of the present disclosure without the need for creative efforts, are also within the scope of the protection of the present disclosure.

Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the presently disclosed subject matter belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the specification and relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein. As used herein, a statement that two or more parts are "connected" or "coupled" together shall mean that the parts are joined together either directly or joined through one or more intermediate parts.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the present application. The appearances of the phrase "an embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.

The term "and/or" is herein merely an association relationship describing an associated object, meaning that there may be three relationships, e.g., a and/or B, may represent: there are three cases, a, B, a and B simultaneously. In addition, the character "/" herein generally indicates that the front and rear associated objects are an "or" relationship.

Furthermore, in all embodiments of the present disclosure, terms such as "first" and "second" are used merely to distinguish one component (or portion of a component) from another component (or another portion of a component).

In the description of the present application, unless otherwise indicated, the meaning of "plurality" means two or more (including two), and similarly, "plural sets" means two or more (including two).

In order to better understand the technical solutions of the present application, the following description will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings.

The insurance claim provided by the embodiment of the disclosure is applied to terminal equipment, and the terminal equipment can be a personal computer, a notebook computer, or an iPad, etc., which is not particularly limited by the embodiment of the disclosure.

Based on the problems existing in the prior art, an embodiment of the present disclosure provides a method for identifying an insurance claim fraud risk location, and fig. 1 is a schematic flow chart of the method for identifying an insurance claim fraud risk location provided in the embodiment of the present disclosure, as shown in fig. 1, a specific process of the method for identifying an insurance claim fraud risk location includes:

S110, acquiring the risk position information in the claim policy.

Specifically, the claim settlement policy is generated by the claim settlement system according to claim settlement information filled in by the user when the user applies for the claim settlement on the claim settlement system after the user fills out the claim settlement application on the claim settlement system, and the claim settlement policy comprises the claim settlement case type information, the information of the applicant, the application place, the damage assessment place and the risk emergence place but is not limited to the information.

In a specific embodiment, obtaining the risk location information in the claim policy includes: text recognition is carried out on the claim settlement policy, and target text content corresponding to the target tag identification is obtained; and preprocessing the target text content corresponding to the target tag identifier to obtain the risk position information.

Specifically, after obtaining the claim policy, text recognition is performed on the claim policy by a text recognition method, in the recognition process, text content is associated with a tag, and an exemplary claim policy includes a claim case type tag identifier, an applicant tag identifier and an insurance place identifier, the text content of a text box corresponding to the claim case type tag identifier is "car insurance claim", the text content of a text box corresponding to the applicant tag identifier is "Zhang san", the text content of an insurance place tag identifier is "XX province XX street XX number XX address" of XX area, and after text recognition, the text content of "car insurance claim" is associated with the claim case type tag identifier, the text content of "Zhang san" is associated with the applicant tag identifier, and the text content of "XX area XX street XX number XX address" is associated with the insurance place tag. At this time, if the risk-out position information in the claim policy needs to be obtained, obtaining the risk-out position information by obtaining the text content ' XX address of XX street XX in XX area XX in XX province ' corresponding to the risk-out position label, and preprocessing the text content ' XX address of XX street XX in XX area XX in XX province ' corresponding to the risk-out position label '.

When a user fills in a claim settlement application on a claim settlement system, the format of text content filled in a text box corresponding to a label mark of a place of risk can be in various forms, such as a XX address of a XX street XX in a XX area, namely, lack of part and other information, and a special character is included in the text content, namely, the text content, so that after the target text content corresponding to the target label mark is acquired, the target text content corresponding to the target label mark needs to be preprocessed, and a specific preprocessing process comprises supplementing the information lack in the target text content and eliminating the special character included in the target text content.

In the process of supplementing the information lacking in the target text content, the Chinese character strings in the address field data are firstly segmented by using a jieba equal segmentation word stock, the vocabularies of provinces, cities and regions are extracted from the segmentation result, then the target text information is mapped to administrative division data containing each province, city and region, and finally the information lacking in the target text content is supplemented according to the mapping result.

S130, determining a target risk area to which the risk position information belongs.

After the risk position information is acquired, determining a target risk area to which the risk position information belongs according to the relation between the risk position information and the target risk area, namely, when the risk position information is positioned in a certain risk area, the risk area is the target risk area to which the risk position information belongs.

And S140, determining whether the place corresponding to the risk position information is an insurance claim fraud risk place or not according to the risk position information and the target risk area to which the risk position information belongs.

Specifically, after the risk position information and the target risk area to which the risk position information belongs are determined, since the risk coefficients are corresponding to different risk areas, the risk coefficient corresponding to the risk position information can be determined according to the target risk area to which the risk position information belongs, and then whether the place corresponding to the risk position information is an insurance claim fraud risk place or not is determined according to the risk coefficient corresponding to the risk position and the risk position.

In a specific embodiment, determining whether a location corresponding to the risk position information is an insurance claim fraud risk location according to the risk position information and a target risk area to which the risk position information belongs, includes: acquiring a corresponding relation between a risk area and a risk coefficient; determining a risk coefficient of the risk position information according to the corresponding relation between the risk area and the risk coefficient; and determining whether the place corresponding to the dangerous position information is an insurance claim fraud risk place according to the dangerous position information and the dangerous risk coefficient of the dangerous position information.

The risk coefficient corresponding to the risk area is related to the number of risk positions in the risk area, the number of insurance claim fraud occurring in the risk area and administrative area information corresponding to the risk area, the more the number of risk positions in the risk area, the more the number of insurance claim fraud occurring in the risk area and the administrative area information corresponding to the risk area are in remote administrative areas, the higher the risk coefficient corresponding to the risk area, the fewer the number of risk positions in the risk area, the fewer the insurance claim fraud occurring in the risk area and the lower the risk coefficient corresponding to the risk area are in common administrative areas.

Specifically, through constructing the corresponding relation between the risk areas and the risk coefficients, after determining the risk area to which the risk position information belongs, the risk coefficient corresponding to the risk area to which the risk position information belongs is obtained, the risk coefficient of the risk position information is determined, and whether the place corresponding to the risk position information is an insurance claim fraud risk place or not is determined according to the risk position information and the risk coefficient of the risk position information.

As a specific embodiment, determining whether a location corresponding to the risk position information is an insurance claim fraud risk location according to the risk position information and the risk coefficient of the risk position information, including:

encoding the risk coefficient of the risk position information and the risk position information to obtain a risk position vector and a risk coefficient vector, wherein the risk position information comprises risk name information and risk place information; and inputting the risk position vector and the risk coefficient vector to an identification model, and determining whether the place corresponding to the risk position information is an insurance claim fraud risk place or not based on the identification model.

Specifically, the risk of the danger location information and the risk coefficient of the danger location information are encoded, the danger location vector and the risk coefficient of the danger are obtained, then the encoded danger location vector and the encoded risk coefficient of the danger are input to the recognition model, the input danger location vector and the input risk coefficient of the danger are analyzed based on the recognition model, whether the place corresponding to the danger location information is a fraud risk place of an insurance claim or not is determined, wherein the input danger location vector and the input risk coefficient of the danger are analyzed based on the recognition model, whether the place corresponding to the danger location information is the fraud risk place of the insurance claim or not is determined, the result output by the recognition model comprises two risks and no risks, when the result output by the recognition model is no risks, the place corresponding to the danger location information is characterized as the fraud risk place of the insurance claim, the place corresponding to the danger location information can be verified in a mode of manually checking the insurance claim by communicating with an insurance policy on a communication line, for example, and the place corresponding to an insurance policy can be checked by a user on a communication line, and the place corresponding to the insurance policy can be accurately carried out by a user on the insurance policy, and further, and the necessary situation can be improved.

The recognition model may employ a Xgboost, catBoost, lightGBM, wide & Deep model, which is not specifically limited by the embodiments of the present disclosure.

The method for identifying the insurance claim fraud risk location provided by the embodiment of the disclosure comprises the steps of firstly obtaining the risk position information in a claim settlement policy; then determining a target risk area to which the risk position information belongs; and finally, determining whether the place corresponding to the insurance position information is an insurance claim fraud risk place according to the insurance position information and a target risk area to which the insurance position information belongs, namely analyzing the insurance risk coefficient of the input insurance position information and the target risk area to which the insurance position information belongs based on an identification model to determine whether the place corresponding to the insurance position information is the insurance claim fraud risk place.

Fig. 2 is a schematic flow chart of another method for identifying an insurance claim fraud risk location according to an embodiment of the present disclosure, where the method is based on the above embodiment, as shown in fig. 2, and further includes, before executing step S130:

s120, acquiring a first tag identification corresponding to the risk position information.

The first label is an identifier of an administrative area where the danger-giving position is located.

After the dangerous position information is obtained, the dangerous position information can be split, and the split dangerous position information is marked with a corresponding label. For example, the danger-escaping location information is "XX address of XX street XX number in XX area of XX province", and the danger-escaping location information is split to obtain the following phrases "XX province", "XX city", "XX area", "XX street", "XX number" and "XX address", wherein the first label corresponding to the "XX province" is identified as 11, the first label corresponding to the "XX city" is identified as 12, the first label corresponding to the "XX area" is identified as 13, the first label corresponding to the "XX street" is identified as 14, the first label corresponding to the "XX number" is identified as 15, and the first label corresponding to the "XX address" is identified as 16.

S121, determining a risk area and a risk position included in the risk area.

Wherein the risk area comprises at least one risk location.

S122, acquiring a second label identification corresponding to the risk area.

The second label identification corresponding to the risk position included in the same risk area is the same, and the second label identification is the identification of the administrative area where the risk position is located in the risk area.

The risk location is a location corresponding to the risk position information with the risk of insurance claim fraud mapped in the geographic space based on the historical data, and the risk area is an area obtained by clustering the risk locations within the same area range, and at least comprises one risk location.

Specifically, the risk area includes a risk area 1, a risk area 2 and a risk area 3, the risk area 1 includes a risk position 11, a risk position 12 and a risk position 13, wherein the position information corresponding to the risk position 11 is "YY street YY address in YY area YY of XX province", the position information corresponding to the risk position 12 is "ZZ street ZZ address in ZZ area ZZ of YY area of XX province", the position information corresponding to the risk position 13 is "FF street FF address in FF area of YY area of XX province", and therefore, the second tag identifier corresponding to the risk area 1 includes an identifier 21, an identifier 22 and an identifier 23, the identifier 21 is "XX province", the identifier 22 is "YY area" and the identifier 23 is "YY area"; the risk area 2 comprises a risk position 21 and a risk position 22, the position information corresponding to the risk position 21 is 'XX-province XX-region YY street YY number YY address', the position information corresponding to the risk position 22 is 'XX-province XX-region ZZ street ZZ number ZZ address', and therefore, the second tag identification corresponding to the risk area 2 comprises an identification 31, an identification 32 and an identification 33, the identification 31 is 'XX-province', the identification 32 is 'XX-city' and the identification 33 is 'XX-region'; the risk area 3 includes the risk location 31, and the location information corresponding to the risk location 31 is "XX city YY area YY street YY number YY address", so that the second tag identifier corresponding to the risk area 3 includes an identifier 41, an identifier 42 and an identifier 43, the identifier 41 is "XX province", the identifier 42 is "XX city" and the identifier 43 is "YY area".

When the insurance claim fraud risk location identification method includes steps S120, S121, and S122, a specific implementation manner of step S130 includes:

s131, determining a target risk area to which the risk position information belongs according to the matching degree of the first label identification corresponding to the risk position information and the second label identification corresponding to the risk area.

In a specific embodiment, determining, according to the matching degree of the first tag identifier corresponding to the risk location information and the second tag identifier corresponding to the risk area, a target risk area to which the risk location information belongs includes:

sequentially acquiring the matching degree of the tag identifications corresponding to the position information and the tag identifications corresponding to the risk areas; and selecting a risk area with highest matching degree between the label identification corresponding to the position information and the label identification corresponding to the risk area as a target risk area.

The target risk area to which the risk position information belongs is determined by sequentially matching the matching degree of the first label identification corresponding to the risk position information and the second label identification of the risk area 1, the matching degree of the first label identification corresponding to the risk position information and the second label identification of the risk area 2 and the matching degree of the first label identification corresponding to the risk position information and the second label identification of the risk area 3.

In the above embodiment, the matching degree between the first tag identifier corresponding to the risk position information and the second tag identifier of the risk area 2 is the highest, so the risk area 2 is the target risk area to which the risk position information belongs.

As an implementation manner, fig. 3 is a schematic flow chart of another method for identifying an insurance claim fraud risk location according to an embodiment of the present disclosure, where, on the basis of the foregoing embodiment, as shown in fig. 3, when executing step S110, the method further includes:

s111, acquiring the application position information in the claim policy.

When the insurance claim fraud risk location identification method includes step S111, a specific implementation manner of step S140 includes:

s141, determining whether a place corresponding to the insurance position information is an insurance claim fraud risk place according to the insurance position information, the insurance position information and a target risk area to which the insurance position information belongs.

In a specific embodiment, the claim policy includes information such as claim case type information, information of an applicant, an application location, a damage assessment location, an insurance emergence location, and the like, and by acquiring the application location information in the claim policy, in determining whether a location corresponding to the insurance location information is an insurance claim fraud risk location based on the insurance emergence location information and a target risk area to which the insurance emergence location information belongs, by adding the application location information, accuracy of determining whether the location corresponding to the insurance emergence location information is an insurance claim fraud risk location is improved.

Specifically, when the insurance application location information and the insurance emergence location information are located in two different administrative areas, the greater the probability that the location corresponding to the insurance emergence location information is an insurance claim fraud risk location, the smaller the probability that the location corresponding to the insurance emergence location information is an insurance claim fraud risk location when the insurance application location information and the insurance emergence location information are the same administrative area (the administrative area at least includes provinces and cities).

On the basis of the foregoing embodiments, the method for identifying an insurance claim fraud risk location according to the embodiment of the present disclosure further includes: and when the place corresponding to the risk position information is determined to be the insurance claim fraud risk place, the place corresponding to the risk position information is marked in the target risk area.

And when the result output by the identification model is that the risk is not found, the place corresponding to the risk position information is not the risk place of insurance claim fraud, and when the result output by the identification model is that the risk exists, the place corresponding to the risk position information is likely to be the risk place of insurance claim fraud, and the risk position information is mapped into the geographic space through the identification of the risk position information, namely the place corresponding to the risk position information is marked in the target risk area to which the risk position information belongs, so that the accuracy of the identification result of the subsequent risk places is improved.

On the basis of the above embodiments, fig. 4 is a schematic structural diagram of an apparatus for identifying an insurance claim fraud risk site according to an embodiment of the present disclosure, where, as shown in fig. 4, the apparatus for identifying an insurance claim fraud risk site includes:

a risk-out position information obtaining module 410, configured to obtain risk-out position information in the claim policy;

the target risk area determining module 420 is configured to determine a target risk area to which the risk position information belongs;

the fraud risk location determining module 430 is configured to determine, according to the risk location information and the target risk area to which the risk location information belongs, whether the location corresponding to the risk location information is an insurance claim fraud risk location.

The insurance claim fraud risk location recognition device provided by the embodiment of the disclosure firstly obtains the information of the position of the risk in the claim settlement policy; then determining a target risk area to which the risk position information belongs; and finally, determining whether the place corresponding to the risk position information is an insurance claim fraud risk place according to the risk position information and a target risk area to which the risk position information belongs, namely analyzing the risk coefficient of the input risk position information and the target risk area to which the risk position information belongs based on an identification model, and determining whether the place corresponding to the risk position information is the insurance claim fraud risk place, so that batch claim settlement application can be rapidly processed, the anti-fraud identification efficiency is improved, and the probability of the financial institution to generate claim fraud is reduced.

In a specific embodiment, the fraud risk location determining module includes a correspondence determining unit, a risk coefficient determining unit, and a fraud risk location determining unit;

the corresponding relation determining unit is used for obtaining the corresponding relation between the risk area and the risk coefficient;

the risk coefficient determination unit is used for determining risk coefficients of the risk position information according to the corresponding relation between the risk areas and the risk coefficients;

the fraud risk location determining unit is used for determining whether the location corresponding to the risk location information is an insurance claim fraud risk location according to the risk location information and the risk coefficient of the risk location information.

In a specific embodiment, the specific implementation procedure of the fraud risk location determining unit includes:

encoding the risk coefficient of the risk position information and the risk position information to obtain a risk position vector and a risk coefficient vector, wherein the risk position information comprises risk name information and risk place information;

and inputting the risk position vector and the risk coefficient vector to an identification model, and determining whether the place corresponding to the risk position information is an insurance claim fraud risk place or not based on the identification model.

In a specific embodiment, the insurance claim fraud risk location identification device further includes: the risk position determining system comprises a first tag identification acquisition module, a risk position determining module and a second tag identification acquisition module;

the first tag identification acquisition module is used for acquiring a first tag identification corresponding to the dangerous position information, wherein the first tag identification is an identification of an administrative region where the dangerous position is located;

a risk location determining module configured to determine a risk location included in a risk area and a risk area, where the risk area includes at least one risk location;

the risk management system comprises a risk area, a first label identification acquisition module, a second label identification acquisition module and a management module, wherein the risk area comprises a risk position and a risk identification, the risk position comprises a risk position and a risk position, and the risk position comprises a risk position and a risk position;

at this time, the specific implementation manner of the target risk area determining module is as follows: and determining a target risk area to which the risk position information belongs according to the matching degree of the first label identification corresponding to the risk position information and the second label identification corresponding to the risk area.

In a specific embodiment, determining, according to the matching degree of the first tag identifier corresponding to the risk location information and the second tag identifier corresponding to the risk area, a target risk area to which the risk location information belongs includes:

Sequentially acquiring the matching degree of the tag identifications corresponding to the position information and the tag identifications corresponding to the risk areas; and selecting a risk area with highest matching degree between the label identification corresponding to the position information and the label identification corresponding to the risk area as a target risk area.

In a specific embodiment, the insurance claim fraud risk location identification device further includes: an application position information acquisition module;

the application position information acquisition module is used for acquiring application position information in the claim insurance policy;

at this time, the implementation process of the fraud risk location determination module includes: and determining whether the place corresponding to the insurance position information is an insurance claim fraud risk place or not according to the insurance position information, the insurance position information and the target risk area to which the insurance position information belongs.

In a specific embodiment, the risk position information acquisition module comprises a target text content acquisition unit and a risk position information acquisition unit;

the target text content acquisition unit is used for carrying out text recognition on the claim settlement policy and acquiring target text content corresponding to the target tag identification;

the risk-out position information acquisition unit is used for preprocessing the target text content corresponding to the target tag identifier to obtain risk-out position information.

In a specific embodiment, the insurance claim fraud risk location identification device further includes: a claim policy generation module;

and the claim settlement policy generation module is used for responding to the target object to submit the claim settlement application and generating the claim settlement policy corresponding to the claim settlement application.

In a specific embodiment, the insurance claim fraud risk location identification device further includes: a labeling module;

and the marking module is used for marking the place corresponding to the risk position information in the target risk area when the place corresponding to the risk position information is determined to be the place of the risk of the insurance claim fraud.

The embodiment of the application also provides a computer device, referring specifically to fig. 5, and fig. 5 is a basic structural block diagram of the computer device of the embodiment.

The computer device includes a memory 510 and a processor 520 communicatively coupled to each other via a system bus. It should be noted that only computer devices having components 510-520 are shown in the figures, but it should be understood that not all of the illustrated components are required to be implemented and that more or fewer components may be implemented instead. It will be appreciated by those skilled in the art that the computer device herein is a device capable of automatically performing numerical calculations and/or information processing in accordance with predetermined or stored instructions, the hardware of which includes, but is not limited to, microprocessors, application specific integrated circuits (Application Specific Integrated Circuit, ASICs), programmable gate arrays (fields-Programmable Gate Array, FPGAs), digital processors (Digital Signal Processor, DSPs), embedded devices, etc.

The computer device may be a desktop computer, a notebook computer, a palm computer, a cloud server, or the like. The computer device can perform man-machine interaction with a user through a keyboard, a mouse, a remote controller, a touch pad or voice control equipment and the like.

The memory 510 includes at least one type of readable storage medium including non-volatile memory (non-volatile memory) or volatile memory, such as flash memory (flash memory), hard disk, multimedia card, card memory (e.g., SD or DX memory, etc.), random access memory (random access memory, RAM), read-only memory (ROM), erasable programmable read-only memory (erasable programmable read-only memory, EPROM), electrically erasable programmable read-only memory (electrically erasable programmable read-only memory, EEPROM), programmable read-only memory (programmable read-only memory, PROM), magnetic memory, magnetic disk, optical disk, etc., which may include static RAM or dynamic RAM. In some embodiments, the memory 510 may be an internal storage unit of a computer device, such as a hard disk or memory of the computer device. In other embodiments, the memory 510 may also be an external storage device of a computer device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, or a Flash Card (Flash Card) provided on the computer device. Of course, memory 510 may also include both internal storage units for computer devices and external storage devices. In this embodiment, the memory 510 is typically used to store an operating system installed on a computer device and various types of application software, such as program codes of the above-described methods. In addition, the memory 510 may also be used to temporarily store various types of data that have been output or are to be output.

Processor 520 is typically used to perform the overall operations of the computer device. In this embodiment, the memory 510 is configured to store program codes or instructions, the program codes include computer operation instructions, and the processor 520 is configured to execute the program codes or instructions stored in the memory 510 or process data, such as the program codes for executing the above-mentioned method.

Herein, the bus may be an Industry standard architecture (StandardArchitecture, ISA) bus, a peripheral component interconnect (Peripheral Component Interconnect, PCI) bus, or an extended Industry standard architecture (Extended Industry Standard Architecture, EISA) bus, among others. The bus system may be classified as an address bus, a data bus, a control bus, etc. For ease of illustration, the figures are shown with only one bold line, but not with only one bus or one type of bus.

Another embodiment of the present application also provides a computer-readable medium, which may be a computer-readable signal medium or a computer-readable medium. A processor in a computer reads computer readable program code stored in a computer readable medium, such that the processor is capable of performing the functional actions specified in each step or combination of steps in the above-described method; a means for generating a functional action specified in each block of the block diagram or a combination of blocks.

The computer readable medium includes, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared memory or semiconductor system, apparatus or device, or any suitable combination of the foregoing, the memory storing program code or instructions, the program code including computer operating instructions, and the processor executing the program code or instructions of the above-described methods stored by the memory.

The definition of memory and processor may refer to the description of the embodiments of the computer device described above, and will not be repeated here.

In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of modules or units is merely a logical functional division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.

The functional units or modules in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be embodied essentially or in part or all or part of the technical solution contributing to the prior art or in the form of a software product stored in a storage medium, including several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor (processor) to perform all or part of the steps of the methods of the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

As used herein and in the appended claims, the singular forms of words include the plural and vice versa, unless the context clearly dictates otherwise. Thus, when referring to the singular, the plural of the corresponding term is generally included. Similarly, the terms "comprising" and "including" are to be construed as being inclusive rather than exclusive. Likewise, the terms "comprising" and "or" should be interpreted as inclusive, unless such an interpretation is expressly prohibited herein. Where the term "example" is used herein, particularly when it follows a set of terms, the "example" is merely exemplary and illustrative and should not be considered exclusive or broad.

Further aspects and scope of applicability will become apparent from the description provided herein. It should be understood that various aspects of the present application may be implemented alone or in combination with one or more other aspects. It should also be understood that the description and specific examples are intended for purposes of illustration only and are not intended to limit the scope of the present disclosure.

While several embodiments of the present disclosure have been described in detail, it will be apparent to those skilled in the art that various modifications and variations can be made to the embodiments of the present disclosure without departing from the spirit and scope of the disclosure. The scope of the present disclosure is defined by the appended claims.

Claims (10)

1. A method of identifying a fraud risk location for an insurance claim, comprising:

acquiring the risk position information in the claim settlement policy;

determining a target risk area to which the risk position information belongs;

and determining whether the place corresponding to the dangerous position information is an insurance claim fraud risk place or not according to the dangerous position information and a target risk area to which the dangerous position information belongs.

2. The method according to claim 1, wherein determining whether the location corresponding to the risky location information is an insurance claim fraud risk location according to the risky location information and a target risk area to which the risky location information belongs includes:

acquiring a corresponding relation between a risk area and a risk coefficient;

determining a risk coefficient of the risk position information according to the corresponding relation between the risk area and the risk coefficient;

and determining whether the place corresponding to the dangerous position information is an insurance claim fraud risk place or not according to the dangerous position information and the dangerous risk coefficient of the dangerous position information.

3. The method according to claim 2, wherein determining whether the location corresponding to the risk position information is an insurance claim fraud risk location according to the risk position information and the risk coefficient of the risk position information, comprises:

Encoding the risk exposure location information and risk exposure coefficients of the risk exposure location information, obtaining a risk position vector and a risk coefficient vector, wherein the risk position information comprises risk name information and risk place information;

and inputting the risk position vector and the risk coefficient vector to an identification model, and determining whether the place corresponding to the risk position information is an insurance claim fraud risk place or not based on the identification model.

4. A method according to any one of claims 1-3, wherein prior to said determining a target risk area to which said risk-of-occurrence location information pertains, further comprising:

acquiring a first tag identifier corresponding to the risk position information, wherein the first tag identifier is an identifier of an administrative region in which the risk position is located;

determining a risk area and a risk location included in the risk area, wherein the risk area includes at least one risk location;

acquiring a second tag identifier corresponding to the risk area, wherein the second tag identifiers corresponding to the risk positions included in the same risk area are the same, and the second tag identifiers are identifiers of administrative areas where the risk positions are located in the risk area;

The determining the target risk area to which the risk position information belongs includes:

and determining a target risk area to which the risk position information belongs according to the matching degree of the first label identification corresponding to the risk position information and the second label identification corresponding to the risk area.

5. The method of claim 4, wherein the determining the target risk area to which the risk position information belongs according to the matching degree of the first tag identifier corresponding to the risk position information and the second tag identifier corresponding to the risk area comprises:

sequentially obtaining the matching degree of the tag identification corresponding to the position information and the tag identification corresponding to each risk area;

and selecting a risk area with highest matching degree between the tag identification corresponding to the position information and the tag identification corresponding to the risk area as a target risk area.

6. The method of claim 1, wherein the acquiring the risk location information in the claim policy further comprises:

acquiring the application position information in the claim policy;

the determining whether the location corresponding to the risk position information is an insurance claim fraud risk location according to the risk position information and the target risk area to which the risk position information belongs, includes:

And determining whether a place corresponding to the insurance position information is an insurance claim fraud risk place according to the insurance position information, the insurance position information and a target risk area to which the insurance position information belongs.

7. The method of claim 1, wherein the obtaining the risk location information in the claim policy comprises:

performing text recognition on the claim settlement policy to obtain target text content corresponding to the target tag identification;

and preprocessing the target text content corresponding to the target tag identifier to obtain the risk position information.

8. The method of claim 1, further comprising, prior to the acquiring the risk location information in the claim policy

And responding to the target object to submit the claim settlement application, and generating a claim settlement policy corresponding to the claim settlement application.

9. The method according to claim 2, wherein the method further comprises:

and when the place corresponding to the dangerous position information is determined to be the insurance claim fraud risk place, the place corresponding to the dangerous position information is marked in the target risk area.

10. An insurance claim fraud risk location identification device, comprising:

The insurance position information acquisition module is used for acquiring the insurance position information in the claim insurance policy;

the target risk area determining module is used for determining a target risk area to which the risk position information belongs;

and the fraud risk location determining module is used for determining whether the location corresponding to the insurance position information is an insurance claim fraud risk location according to the insurance position information and the target risk area to which the insurance position information belongs.