CN110675268A - Risk client identification method and device and server - Google Patents
Risk client identification method and device and server Download PDFInfo
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Abstract
The embodiment of the invention provides a method, a device and a server for identifying a risk client, and relates to the field of big data, wherein the method comprises the following steps: collecting claim settlement data of a client in a set time period; according to the claim settlement data of the client in a set time period, counting a plurality of risk assessment data of the client; calculating a risk assessment score of the client according to a plurality of risk assessment data; judging whether the risk assessment score of the client is larger than a risk assessment threshold value; and if the risk assessment score of the client is judged to be larger than the risk assessment threshold, determining the client as a risk client. Therefore, the technical scheme provided by the embodiment of the invention greatly reduces the risk of insurance fraud and reduces the cost.
Description
[ technical field ] A method for producing a semiconductor device
The invention relates to the field of big data, in particular to a method, a device and a server for identifying a risk client.
[ background of the invention ]
In the process of claim settlement of flight delay insurance and baggage delay insurance, insurance products of flight delay and baggage delay are easy to be used for earning by illegal customers, and the risk of insurance fraud is high.
Currently, no convenient method is available for claim settlement service personnel to identify the insurance fraud risk of each insurance claim case, so that the insurance fraud risk and the labor cost are high.
[ summary of the invention ]
In view of this, embodiments of the present invention provide a method, an apparatus, and a server for identifying a risk client, so as to solve the problems of high risk of insurance fraud and high labor cost in the prior art.
In one aspect, an embodiment of the present invention provides a method for identifying a risk client, where the method includes:
collecting claim settlement data of a client in a set time period;
according to the claim settlement data of the client in a set time period, counting a plurality of risk assessment data of the client;
calculating a risk assessment score of the client according to a plurality of risk assessment data;
judging whether the risk assessment score of the client is larger than a risk assessment threshold value;
and if the risk assessment score of the client is judged to be larger than the risk assessment threshold, determining the client as a risk client.
Optionally, the calculating a risk assessment score of the client according to the plurality of risk assessment data comprises:
inquiring a score corresponding to each risk assessment data from a preset score corresponding relation;
multiplying the score corresponding to each risk assessment data with the weight corresponding to each risk assessment data to obtain a multiplication result corresponding to each risk assessment data;
and adding the multiplication results corresponding to each risk assessment data to obtain the risk assessment score of the client.
Optionally, when the claim data includes claim data of flight delay insurance, the plurality of risk assessment data includes: the number of times the customer has been offered an insurance premium over a set period of time, the number of policies the customer has been offered a insurance premium over a set period of time, the difference between the date of the offer and the date of the application, the number of times the customer has paid a day, whether the customer is on a black list, the age of the customer, and the number of certificates associated with the customer.
Optionally, whether the weight corresponding to the customer in a blacklist, the weight corresponding to the age of the customer and the weight corresponding to the number of certificates associated with the customer are equal, whether the weight corresponding to the customer in the blacklist is greater than the weight corresponding to the number of policy of the customer in a set time period, the weight corresponding to the number of policy of the customer in the set time period is greater than the weight corresponding to the number of times of risk of the customer in the set time period, the weight corresponding to the number of times of risk of the customer in the set time period is greater than the weight corresponding to the difference between the date of risk and the date of application, and the weight corresponding to the difference between the date of risk and the date of application is greater than the weight corresponding to the number of times of claims of the customer in one day.
Optionally, when the claim data includes claim data of baggage loss risk, the plurality of risk assessment data includes: the number of the reports corresponding to the telephone number and the certificate number of the client, the amount of the claims of the client in the set time period and the number of the insurance times of the client in the set time period.
Optionally, the weight corresponding to the number of times of entry corresponding to the telephone number and the certificate number of the customer is equal to the weight corresponding to the number of times of insurance leaving of the customer within a set time period, and the weight corresponding to the number of times of entry corresponding to the telephone number and the certificate number of the customer is greater than the weight corresponding to the amount of claims of the customer within the set time period.
On the other hand, an embodiment of the present invention provides an identification apparatus for a risk client, including:
the collection unit is used for collecting the claim settlement data of the client in a set time period;
the statistical unit is used for counting a plurality of risk assessment data of the client according to the claim settlement data of the client in a set time period;
the calculation unit is used for calculating the risk assessment score of the client according to a plurality of risk assessment data;
the judging unit is used for judging whether the risk assessment score of the client is larger than a risk assessment threshold value;
and the determining unit is used for determining the client as a risk client if the judging unit judges whether the risk assessment score of the client is greater than the risk assessment threshold.
In another aspect, an embodiment of the present invention provides a server, including: the identification device of the risk client.
In another aspect, an embodiment of the present invention provides a storage medium, where the storage medium includes a stored program, where when the program runs, a device in which the storage medium is located is controlled to execute the method for identifying a risky client.
In another aspect, the present invention provides a computer device comprising a memory for storing information comprising program instructions and a processor for controlling the execution of the program instructions, which program instructions, when loaded and executed by the processor, implement the steps of the above-mentioned method of identifying an at-risk client.
According to the scheme of the embodiment of the invention, a plurality of risk assessment data of a client are counted and the risk assessment score of the client is calculated according to the claim data of the client in a set time period, and whether the client is a risk client is judged according to the risk assessment score and the risk assessment threshold of the client, so that a claim service worker or a claim system can distinguish the insurance fraud risk of each claim case according to the identification result of the risk client in the insurance claim settlement process, thereby greatly reducing the insurance fraud risk and reducing the cost.
[ description of the drawings ]
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive labor.
Fig. 1 is a flowchart of an identification method for a risk client according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an identification apparatus for an at-risk client according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a computer device according to an embodiment of the present invention.
[ detailed description ] embodiments
For better understanding of the technical solutions of the present invention, the following detailed descriptions of the embodiments of the present invention are provided with reference to the accompanying drawings.
It should be understood that the described embodiments are only some embodiments of the invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the examples of the present invention 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 be understood that the term "and/or" as used herein is merely one type of associative relationship that describes an associated object, meaning that three types of relationships may exist, e.g., A and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
Fig. 1 is a flowchart of an identification method for a risk client according to an embodiment of the present invention, as shown in fig. 1, the method includes:
and step S101, collecting the claim settlement data of the client in a set time period.
In this embodiment, the claim settlement data may include customer information, insurance information, and a blacklist, where the customer information includes a customer name, a customer age, an id card/passport/taiwan, australian pass, and a phone number, the insurance information includes insurance application date and insurance application content, the insurance information includes insurance application date and a payment amount, and the blacklist includes customer information of the customer.
And S102, counting a plurality of risk assessment data of the client according to the claim settlement data of the client in a set time period.
In this embodiment, the set time period may be one year. In practical applications, the set time period may be set as required, for example, the set time period may also be three months or half a year.
And step S103, calculating the risk assessment score of the client according to the plurality of risk assessment data.
Step S104, judging whether the risk evaluation score of the client is larger than a risk evaluation threshold value, if so, executing step S105; if not, the process ends.
And step S105, determining the client as a risk client.
According to the scheme of the embodiment of the invention, a plurality of risk assessment data of a client are counted and the risk assessment score of the client is calculated according to the claim data of the client in a set time period, and whether the client is a risk client is judged according to the risk assessment score and the risk assessment threshold of the client, so that a claim service worker or a claim system can distinguish the insurance fraud risk of each claim case according to the identification result of the risk client in the insurance claim settlement process, thereby greatly reducing the insurance fraud risk and reducing the cost.
Optionally, after step S105, the method further includes: the risky clients are added to the blacklist. When a client is determined to be a risky client, the risky client may be blacklisted. In particular, the client information of the at-risk client may be blacklisted. And adding the risk client into the blacklist, so that a claim settlement service personnel or a claim settlement system can acquire the risk client from the blacklist. If the claim settlement process is executed manually, the claim settlement service personnel can acquire risk customers from the blacklist; if the claim settlement process is executed in an automatic claim settlement mode, the claim settlement system can directly acquire the risk client from the blacklist.
In the embodiment of the present invention, step S102 may specifically include:
step S1021, inquiring the score corresponding to each risk assessment data from a preset score corresponding relation.
The score corresponding relation comprises corresponding relation between the risk assessment data and the score.
Step S1022, multiplying the score corresponding to each risk assessment data by the weight corresponding to each risk assessment data, to obtain a multiplication result corresponding to each risk assessment data.
And S1023, adding the multiplication results corresponding to each risk evaluation data to obtain the risk evaluation score of the client.
In the embodiment of the invention, the claim data comprises the claim data of flight delay insurance and/or the claim data of baggage loss insurance.
The following specifically describes two cases, namely, the claim data is the claim data of flight delay insurance and the claim data is the claim data of baggage loss insurance.
In the first case: when the claim data comprises claim data of flight delay insurance, the risk assessment data comprises: the number of times the customer has been offered an insurance premium over a set period of time, the number of policies the customer has been offered a insurance premium over a set period of time, the difference between the date of the offer and the date of the application, the number of times the customer has paid a day, whether the customer is on a black list, the age of the customer, and the number of certificates associated with the customer.
And when the obtained difference value between the insurance leaving date and the insurance application date is multiple, the difference value between the insurance leaving date and the insurance application date is the average value of the difference values between the insurance leaving date and the insurance application date. In practical applications, the difference between the insurance offering date and the insurance application date may also take other values, for example, the difference between the insurance offering date and the insurance application date is the maximum value of the differences between the insurance offering date and the insurance application date.
When the number of times of claims of the clients in each single day in a plurality of single days is counted, that is, the number of times of claims of the clients in one day is counted, the number of times of claims of the clients in one day may be an average value of the number of times of claims of the clients in one day. In practical applications, the number of payments made by a customer during a day may be the maximum number of payments made by a plurality of customers during a day.
In this case, the weights corresponding to the risk assessment data are ranked as follows:
whether the weight corresponding to the customer in a blacklist, the weight corresponding to the age of the customer and the weight corresponding to the number of certificates associated with the customer are equal, whether the weight corresponding to the customer in the blacklist is larger than the weight corresponding to the number of insurance policies of the customer in a set time period, the weight corresponding to the number of insurance policies of the customer in the set time period is larger than the weight corresponding to the number of risks of the customer in the set time period, the weight corresponding to the number of insurance risks of the customer in the set time period is larger than the weight corresponding to the difference between the insurance date and the insurance application date, and the weight corresponding to the difference between the insurance application date and the insurance application date is larger than the weight corresponding to the number of claims of the customer in one day.
For example: whether the weight of the client corresponds to 100% in the blacklist, the weight of the client corresponds to 100% in age, the weight of the number of certificates associated with the client corresponds to 100%, the weight of the number of the policy of the client in a set time period corresponds to 30%, the weight of the number of times of the client for taking out insurance in the set time period corresponds to 25%, the weight of the difference value between the date of taking out insurance and the date of insuring corresponds to 20%, and the weight of the number of times of the client for paying in a day corresponds to 10%.
When the customer is in the blacklist, the corresponding score is 20; when the customer is not in the blacklist, the corresponding score is 0. When the age of the client is over 70 years old, the corresponding score is 5 points; when the client is less than 70 years of age, the corresponding score is 0. When the number of the certificates associated with the client is more than 3, the corresponding score is 10; and when the number of the certificates associated with the client is less than 3, the corresponding score is 0. When the number of the risk taking times of the client in the set time period is 3-6 times, the corresponding score is 25 points; when the number of the risk taking times of the client in the set time period is 7-9 times, the corresponding score is 50 points; when the number of the risk taking times of the client in the set time period is 10-12 times, the corresponding score is 75 points; when the number of the insurance taking times of the client in the set time period is more than 13, the corresponding score is 100. When the number of the policy of the client in a set time period is 3 to 5, the corresponding score is 20; when the number of the policy of the customer in the set time period is 6 to 7, the corresponding score is 40; when the number of the policy of the client in the set time period is 8 to 9, the corresponding score is 60; when the number of the policy of the customer in the set time period is 10 to 11, the corresponding score is 80; when the number of the policy of the client in the set time period is more than 12, the corresponding score is 100. When the difference value between the insurance date and the insurance date is 0-3 days, the corresponding score is 100; when the difference value between the insurance date and the insurance date is 4 to 6 days, the corresponding score is 80 points; when the difference value between the insurance date and the insurance date is 7 to 9 days, the corresponding score is 60 points; when the difference value between the insurance date and the insurance date is 10 to 12 days, the corresponding score is 40 points; when the difference value between the insurance-taking date and the insurance-applying date is more than 13 days, the corresponding score is 20. When the number of times of the customer's claims in one day is less than 2, the corresponding score is 30; when the number of times of the client's reimbursement in one day is more than 3, the corresponding score is 60.
The risk assessment threshold value may range from 60 to 80, for example, a risk assessment threshold value of 72.
In the second case: when the claim data comprises claim data of baggage loss risk, the plurality of risk assessment data comprises: the number of the reports corresponding to the telephone number and the certificate number of the client, the amount of the claims of the client in the set time period and the number of the insurance times of the client in the set time period.
In this case, the weights corresponding to the risk assessment data are ranked as follows:
the weight corresponding to the number of the reports corresponding to the telephone number and the certificate number of the client is equal to the weight corresponding to the number of the risks of the client in the set time period, and the weight corresponding to the number of the reports corresponding to the telephone number and the certificate number of the client is greater than the weight corresponding to the amount of the claims of the client in the set time period.
For example: the weight corresponding to the number of the reports corresponding to the telephone number and the certificate number of the client is 40%, the weight corresponding to the number of the risks of the client in the set time period is 40%, and the weight corresponding to the amount of the claims of the client in the set time period is 20%.
When the number of times of the corresponding reports of the telephone number and the certificate number of the client is less than 2 times, the corresponding score is 10 points; when the number of the corresponding reports of the telephone number and the certificate number of the client is 3-10, the corresponding score is 50; when the number of times of the reports corresponding to the telephone number and the certificate number of the client is more than 11, the corresponding score is 100. When the number of the risk taking times of the client in the set time period is less than 2 times, the corresponding score is 10 points; when the number of the risk taking times of the client in the set time period is 3-5 times, the corresponding score is 50 points; when the number of the insurance taking times of the client in the set time period is more than 6, the corresponding score is 100. When the claim settlement amount of a client in a set time period is below 1750 yuan, the corresponding score is 10; when the claim settlement amount of a client in a set time period is greater than 1750 yuan and less than or equal to 5000 yuan, the corresponding score is 50 points; when the claim amount of the client in the set time period is larger than 5000 yuan, the corresponding score is 100.
The risk assessment threshold value may range from 30 to 40, for example, 36.
In the embodiment of the invention, the risk assessment score of the client is calculated through the score corresponding to the risk assessment data and the corresponding weight, so that the obtained risk assessment score is more accurate, and the calculation method is simple and easy to realize.
Optionally, after step S105, the method further includes: and classifying the customers into different grades of customers according to the risk assessment scores of the customers.
Specifically, according to the risk assessment score of the client, a client grade corresponding to the risk assessment score of the client is inquired from the preset corresponding relation between the risk assessment score and the client grade.
For example: when the inquired client is higher in grade, the client is indicated to have higher insurance fraud risk degree; when the searched client is in a lower grade, the risk degree of insurance fraud of the client is indicated to be lower.
In this embodiment, the risk degree of insurance fraud of the risk client can be further identified by the claim settlement service personnel or the claim settlement system according to the client grade, so that the service claim settlement personnel or the claim settlement system can more accurately identify the risk of each claim case.
Fig. 2 is a schematic structural diagram of an identification apparatus for a risk client according to an embodiment of the present invention, the apparatus is configured to execute the identification method for a risk client, as shown in fig. 2, the apparatus includes: the device comprises a collecting unit 11, a counting unit 12, a calculating unit 13, a judging unit 14 and a determining unit 15.
The collecting unit 11 is used for collecting the claim settlement data of the client in a set time period;
the statistical unit 12 is configured to perform statistics on a plurality of risk assessment data of the client according to the claim settlement data of the client in a set time period;
the calculating unit 13 is configured to calculate a risk assessment score of the client according to a plurality of risk assessment data;
the judging unit 14 is used for judging whether the risk assessment score of the client is larger than a risk assessment threshold value;
the determining unit 15 is configured to determine the client as a risk client if the determining unit 14 determines whether the risk assessment score of the client is greater than the risk assessment threshold.
In the embodiment of the present invention, the calculation module 13 includes a query submodule 131, a first calculation submodule 132, and a second calculation submodule 133.
The query submodule 131 is configured to query a score corresponding to each risk assessment data from a preset score correspondence;
the first calculating sub-module 132 is configured to multiply the score corresponding to each of the risk assessment data and the weight corresponding to each of the risk assessment data to obtain a multiplication result corresponding to each of the risk assessment data;
the second calculating submodule 133 is configured to add the multiplication results corresponding to each risk assessment data to obtain a risk assessment score of the client.
According to the scheme of the embodiment of the invention, a plurality of risk assessment data of a client are counted and the risk assessment score of the client is calculated according to the claim data of the client in a set time period, and whether the client is a risk client is judged according to the risk assessment score and the risk assessment threshold of the client, so that a claim service worker or a claim system can distinguish the insurance fraud risk of each claim case according to the identification result of the risk client in the insurance claim settlement process, thereby greatly reducing the insurance fraud risk and reducing the cost.
The embodiment of the invention provides a server which comprises the face recognition device.
The invention provides a storage medium, which comprises a stored program, wherein when the program runs, a device where the storage medium is located is controlled to execute the following steps: collecting claim settlement data of a client in a set time period; according to the claim settlement data of the client in a set time period, counting a plurality of risk assessment data of the client; calculating a risk assessment score of the client according to a plurality of risk assessment data; judging whether the risk assessment score of the client is larger than a risk assessment threshold value; and if the risk assessment score of the client is judged to be larger than the risk assessment threshold, determining the client as a risk client.
Optionally, the apparatus for controlling the storage medium when the program runs further performs the following steps: inquiring a score corresponding to each risk assessment data from a preset score corresponding relation;
multiplying the score corresponding to each risk assessment data with the weight corresponding to each risk assessment data to obtain a multiplication result corresponding to each risk assessment data;
and adding the multiplication results corresponding to each risk assessment data to obtain the risk assessment score of the client.
When the claim data comprises claim data of flight delay insurance, the risk assessment data comprises: the number of times the customer has been offered an insurance premium over a set period of time, the number of policies the customer has been offered a insurance premium over a set period of time, the difference between the date of the offer and the date of the application, the number of times the customer has paid a day, whether the customer is on a black list, the age of the customer, and the number of certificates associated with the customer.
The weight corresponding to whether the customer is in a blacklist, the weight corresponding to the age of the customer and the weight corresponding to the number of certificates associated with the customer are equal, the weight corresponding to whether the customer is in the blacklist is larger than the weight corresponding to the number of insurance policies of the customer in a set time period, the weight corresponding to the number of insurance policies of the customer in the set time period is larger than the weight corresponding to the number of risks of the customer in the set time period, the weight corresponding to the number of risks of the customer in the set time period is larger than the weight corresponding to the difference between the insurance date and the insurance application date, and the weight corresponding to the difference between the insurance application date and the insurance application date is larger than the weight corresponding to the number of benefits of the customer in one day.
Wherein when the claim data comprises claim data of baggage loss risk, the plurality of risk assessment data comprises: the number of the reports corresponding to the telephone number and the certificate number of the client, the amount of the claims of the client in the set time period and the number of the insurance times of the client in the set time period.
The weight corresponding to the number of the reports corresponding to the telephone number and the certificate number of the client is equal to the weight corresponding to the number of the risks of the client in the set time period, and the weight corresponding to the number of the reports corresponding to the telephone number and the certificate number of the client is greater than the weight corresponding to the amount of the claims of the client in the set time period.
Optionally, the apparatus for controlling the storage medium when the program runs further performs the following steps: the risky clients are added to the blacklist.
Optionally, the apparatus for controlling the storage medium when the program runs further performs the following steps: and classifying the customers into different grades of customers according to the risk assessment scores of the customers.
An embodiment of the present invention provides a computer device, including a memory and a processor, where the memory is used to store information including program instructions, and the processor is used to control execution of the program instructions, and the program instructions are loaded and executed by the processor to implement the following steps: collecting claim settlement data of a client in a set time period; according to the claim settlement data of the client in a set time period, counting a plurality of risk assessment data of the client; calculating a risk assessment score of the client according to a plurality of risk assessment data; judging whether the risk assessment score of the client is larger than a risk assessment threshold value; and if the risk assessment score of the client is judged to be larger than the risk assessment threshold, determining the client as a risk client.
Optionally, the apparatus for controlling the storage medium when the program runs further performs the following steps: inquiring a score corresponding to each risk assessment data from a preset score corresponding relation;
multiplying the score corresponding to each risk assessment data with the weight corresponding to each risk assessment data to obtain a multiplication result corresponding to each risk assessment data;
and adding the multiplication results corresponding to each risk assessment data to obtain the risk assessment score of the client.
When the claim data comprises claim data of flight delay insurance, the risk assessment data comprises: the number of times the customer has been offered an insurance premium over a set period of time, the number of policies the customer has been offered a insurance premium over a set period of time, the difference between the date of the offer and the date of the application, the number of times the customer has paid a day, whether the customer is on a black list, the age of the customer, and the number of certificates associated with the customer.
The weight corresponding to whether the customer is in a blacklist, the weight corresponding to the age of the customer and the weight corresponding to the number of certificates associated with the customer are equal, the weight corresponding to whether the customer is in the blacklist is larger than the weight corresponding to the number of insurance policies of the customer in a set time period, the weight corresponding to the number of insurance policies of the customer in the set time period is larger than the weight corresponding to the number of risks of the customer in the set time period, the weight corresponding to the number of risks of the customer in the set time period is larger than the weight corresponding to the difference between the insurance date and the insurance application date, and the weight corresponding to the difference between the insurance application date and the insurance application date is larger than the weight corresponding to the number of benefits of the customer in one day.
Wherein when the claim data comprises claim data of baggage loss risk, the plurality of risk assessment data comprises: the number of the reports corresponding to the telephone number and the certificate number of the client, the amount of the claims of the client in the set time period and the number of the insurance times of the client in the set time period.
The weight corresponding to the number of the reports corresponding to the telephone number and the certificate number of the client is equal to the weight corresponding to the number of the risks of the client in the set time period, and the weight corresponding to the number of the reports corresponding to the telephone number and the certificate number of the client is greater than the weight corresponding to the amount of the claims of the client in the set time period.
Optionally, the apparatus for controlling the storage medium when the program runs further performs the following steps: the risky clients are added to the blacklist.
Optionally, the apparatus for controlling the storage medium when the program runs further performs the following steps: and classifying the customers into different grades of customers according to the risk assessment scores of the customers.
Fig. 3 is a schematic diagram of a computer device according to an embodiment of the present invention. As shown in fig. 3, the computer device 20 of this embodiment includes: the processor 21, the memory 22, and the computer program 23 stored in the memory 22 and capable of running on the processor 21, where the computer program 23 is executed by the processor 21 to implement the face recognition method applied to the robot in the embodiment, and in order to avoid repetition, details are not repeated herein. Alternatively, the computer program is executed by the processor 21 to implement the functions of each model/unit in the face recognition apparatus applied to the robot in the embodiment, and in order to avoid repetition, the description is omitted here.
The computing device 20 may be a desktop computer, a notebook, a palm top computer, a cloud server, or other computing device. The computer device may include, but is not limited to, a processor 21, a memory 22. Those skilled in the art will appreciate that fig. 3 is merely an example of a computer device 20 and is not intended to limit the computer device 20 and that it may include more or fewer components than shown, or some of the components may be combined, or different components, e.g., the computer device may also include input output devices, network access devices, buses, etc.
The Processor 21 may be a Central Processing Unit (CPU), 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, discrete Gate or transistor logic device, discrete hardware component, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 22 may be an internal storage unit of the computer device 20, such as a hard disk or a memory of the computer device 20. The memory 22 may also be an external storage device of the computer device 20, such as a plug-in hard disk provided on the computer device 20, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like. Further, the memory 22 may also include both internal storage units of the computer device 20 and external storage devices. The memory 22 is used for storing computer programs and other programs and data required by the computer device. The memory 22 may also be used to temporarily store data that has been output or is to be output.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the embodiments provided in the present invention, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions in actual implementation, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) or a Processor (Processor) to execute some steps of the methods according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. A method for identifying an at-risk client, the method comprising:
collecting claim settlement data of a client in a set time period;
according to the claim settlement data of the client in a set time period, counting a plurality of risk assessment data of the client;
calculating a risk assessment score of the client according to a plurality of risk assessment data;
judging whether the risk assessment score of the client is larger than a risk assessment threshold value;
and if the risk assessment score of the client is judged to be larger than the risk assessment threshold, determining the client as a risk client.
2. The method of claim 1, wherein calculating a risk assessment score for the client based on the plurality of risk assessment data comprises:
inquiring a score corresponding to each risk assessment data from a preset score corresponding relation;
multiplying the score corresponding to each risk assessment data with the weight corresponding to each risk assessment data to obtain a multiplication result corresponding to each risk assessment data;
and adding the multiplication results corresponding to each risk assessment data to obtain the risk assessment score of the client.
3. The method for identifying a risk client according to claim 2, wherein when the claim data includes claim data of flight delay insurance, the plurality of risk assessment data includes: the number of times the customer has been offered an insurance premium over a set period of time, the number of policies the customer has been offered a insurance premium over a set period of time, the difference between the date of the offer and the date of the application, the number of times the customer has paid a day, whether the customer is on a black list, the age of the customer, and the number of certificates associated with the customer.
4. The method of claim 3, wherein the weight of the client corresponding to the blacklist, the weight of the client corresponding to the age, and the weight of the number of certificates associated with the client are equal, the weight of the client corresponding to the blacklist is greater than the weight of the client corresponding to the number of policy in the set time period, the weight of the client corresponding to the policy in the set time period is greater than the weight of the client corresponding to the number of times of insurance in the set time period, the weight of the client corresponding to the number of times of insurance in the set time period is greater than the weight of the client corresponding to the difference between the date of insurance and the date of insurance, and the weight of the client corresponding to the difference between the date of insurance and the date of insurance is greater than the weight of the client corresponding to the number of times of payment in one day.
5. The method for identifying a risk client according to claim 2, wherein when the claim data includes claim data of baggage loss risk, the plurality of risk assessment data includes: the number of the reports corresponding to the telephone number and the certificate number of the client, the amount of the claims of the client in the set time period and the number of the insurance times of the client in the set time period.
6. The method for identifying a risky customer according to claim 5, wherein the weight corresponding to the number of times of entry corresponding to the customer's telephone number and certificate number is equal to the weight corresponding to the number of times of risk of the customer within a set time period, and the weight corresponding to the number of times of entry corresponding to the customer's telephone number and certificate number is greater than the weight corresponding to the amount of claims of the customer within the set time period.
7. An apparatus for identifying an at-risk client, comprising:
the collection unit is used for collecting the claim settlement data of the client in a set time period;
the statistical unit is used for counting a plurality of risk assessment data of the client according to the claim settlement data of the client in a set time period;
the calculation unit is used for calculating the risk assessment score of the client according to a plurality of risk assessment data;
the judging unit is used for judging whether the risk assessment score of the client is larger than a risk assessment threshold value;
and the determining unit is used for determining the client as a risk client if the judging unit judges whether the risk assessment score of the client is greater than the risk assessment threshold.
8. A server, comprising: an identification device of an at risk client as claimed in claim 7.
9. A storage medium, characterized in that the storage medium comprises a stored program, wherein when the program runs, a device in which the storage medium is located is controlled to execute the method for identifying a risky client according to any one of claims 1 to 6.
10. A computer device comprising a memory for storing information including program instructions and a processor for controlling the execution of the program instructions, characterized in that the program instructions are loaded and executed by the processor to implement the steps of the method for identification of a risky client according to any one of claims 1 to 6.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112330468A (en) * | 2020-11-03 | 2021-02-05 | 中国平安财产保险股份有限公司 | Method, device, equipment and storage medium for identifying risk client |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107169869A (en) * | 2017-04-06 | 2017-09-15 | 平安科技（深圳）有限公司 | Information processing method and information processor |
| CN107657047A (en) * | 2017-10-10 | 2018-02-02 | 民太安财产保险公估股份有限公司 | Insurance Fraud method for detecting and system |
| CN107871285A (en) * | 2017-12-06 | 2018-04-03 | 和金在线（北京）科技有限公司 | A kind of health insurance pays for the method for detecting and system of fraud and abuse |
| CN108734591A (en) * | 2018-04-09 | 2018-11-02 | 中国平安人寿保险股份有限公司 | Cheat appraisal procedure, device, storage medium and the terminal of case |
| CN109472706A (en) * | 2018-09-26 | 2019-03-15 | 平安健康保险股份有限公司 | Claims Resolution air control method, apparatus, computer equipment and storage medium |
| CN109658256A (en) * | 2018-10-11 | 2019-04-19 | 平安科技（深圳）有限公司 | Risk control method, device, equipment and readable storage medium storing program for executing |
| CN109859059A (en) * | 2019-01-17 | 2019-06-07 | 深圳壹账通智能科技有限公司 | Settlement of insurance claim method, apparatus, computer equipment and storage medium |
-
2019
- 2019-08-14 CN CN201910750175.7A patent/CN110675268A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107169869A (en) * | 2017-04-06 | 2017-09-15 | 平安科技（深圳）有限公司 | Information processing method and information processor |
| CN107657047A (en) * | 2017-10-10 | 2018-02-02 | 民太安财产保险公估股份有限公司 | Insurance Fraud method for detecting and system |
| CN107871285A (en) * | 2017-12-06 | 2018-04-03 | 和金在线（北京）科技有限公司 | A kind of health insurance pays for the method for detecting and system of fraud and abuse |
| CN108734591A (en) * | 2018-04-09 | 2018-11-02 | 中国平安人寿保险股份有限公司 | Cheat appraisal procedure, device, storage medium and the terminal of case |
| CN109472706A (en) * | 2018-09-26 | 2019-03-15 | 平安健康保险股份有限公司 | Claims Resolution air control method, apparatus, computer equipment and storage medium |
| CN109658256A (en) * | 2018-10-11 | 2019-04-19 | 平安科技（深圳）有限公司 | Risk control method, device, equipment and readable storage medium storing program for executing |
| CN109859059A (en) * | 2019-01-17 | 2019-06-07 | 深圳壹账通智能科技有限公司 | Settlement of insurance claim method, apparatus, computer equipment and storage medium |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112330468A (en) * | 2020-11-03 | 2021-02-05 | 中国平安财产保险股份有限公司 | Method, device, equipment and storage medium for identifying risk client |
| CN112330468B (en) * | 2020-11-03 | 2023-10-27 | 中国平安财产保险股份有限公司 | Method, device, equipment and storage medium for identifying risk clients |
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