CN112330474B - Nuclear protection wind control monitoring method, device, equipment and storage medium - Google Patents

Nuclear protection wind control monitoring method, device, equipment and storage medium Download PDF

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CN112330474B
CN112330474B CN202011302774.1A CN202011302774A CN112330474B CN 112330474 B CN112330474 B CN 112330474B CN 202011302774 A CN202011302774 A CN 202011302774A CN 112330474 B CN112330474 B CN 112330474B
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CN112330474A (en
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喻芳
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Ping An Property and Casualty Insurance Company of China Ltd
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Abstract

The invention relates to the field of artificial intelligence, and discloses a method, a device, equipment and a storage medium for monitoring nuclear protection wind control, wherein the method comprises the following steps: acquiring a nuclear protection wind control monitoring instruction and a monitored insurance type input by a user, and judging the monitoring type represented by the instruction; if the monitoring type is result monitoring, acquiring a policy corresponding to the insurance type and various policy information, and making a corresponding risk map according to the policy and the policy information, wherein the risk map comprises the risk single quantity and the risk score of each insurance application place; determining high-risk places in the classified insurance places in the geographic area according to the risk single quantity and the risk score, and early warning the high-risk places; if the monitoring type is process monitoring, analyzing the underwriting process of the policy according to the policy information to obtain process monitoring data; the risk map or process monitoring data is sent to the user. In addition, the invention also relates to a blockchain technology, and the risk single quantity can be stored in the blockchain.

Description

Nuclear protection wind control monitoring method, device, equipment and storage medium
Technical Field
The invention relates to the field of artificial intelligence, in particular to a method, a device, equipment and a storage medium for monitoring nuclear protection wind control.
Background
With the increasing awareness of people's insurance, commercial insurance has become an important component in current social security systems. The number of policies for a portion of the insurance organization is on the order of tens of millions based on the referenceable data. After the insurance policy is generated in the insurance system, the insurance policy needs to be checked to determine whether the information in the insurance policy meets the participation requirement, and the existing check mode of the insurance policy is generally performed manually, for example, the insurance policy is checked manually based on a risk control rule and product pricing rules, auxiliary information and the like of different client groups, however, with rapid development of big data mining, more and more data can be referred for check, if the check is performed manually, a great deal of manpower consumption can be caused, and the check efficiency is low.
The existing part of insurance institutions all use a risk prediction model, enter the risk prediction model according to quotation information filled by an applicant, flow various risk application and screening rules, and carry out risk assessment on insurance policies of the applicant, however, due to insufficient risk prediction models, false killing is possible, the situation that the applicant cannot apply insurance occurs, meanwhile, due to the fact that the risk prediction models are used, a manager cannot know the conditions of a check-up concrete rule, various risk type interception single quantity and the like, and further, when the applicant fails to check up the check, the manager cannot find out where a problem, various interception single quantity cannot be counted, gaps exist in data statistics analysis, and follow-up demand analysis is not facilitated.
Disclosure of Invention
The invention mainly aims to solve the technical problem that the existing risk prediction model is lack of monitoring, so that data analysis on the insurance policy misclassification and interception policy quantity is difficult.
The first aspect of the invention provides a nuclear protection wind control monitoring method, which comprises the following steps:
acquiring a nuclear protection wind control monitoring instruction and a monitored insurance type input by a user, and judging the monitoring type represented by the nuclear protection wind control monitoring instruction, wherein the monitoring type comprises result monitoring and process monitoring;
if the monitoring type is result monitoring, acquiring a policy corresponding to the insurance type and various policy information corresponding to the policy, and making a corresponding risk map according to the policy and the policy information, wherein the risk map comprises risk single amounts and risk scores of various insurance applying places divided in a preset geographic area;
determining high-risk places in all the insuring places divided in the geographic area according to the risk single quantity and the risk score, and carrying out early warning on the high-risk places;
if the monitoring type is process monitoring, analyzing the underwriting process of the policy according to the policy information to obtain process monitoring data;
And sending the risk map or the process monitoring data to the user so as to enable the user to conduct nuclear security wind control analysis.
Optionally, in a first implementation manner of the first aspect of the present invention, the obtaining the policy corresponding to the insurance type and each item of policy information corresponding to the policy, and making a corresponding risk map according to the policy and the policy information includes:
acquiring a policy corresponding to the insurance type, various policy information corresponding to the policy and geographic information of the geographic area;
carrying out geographical region classification on the policy according to the geographical information to obtain a geographical region classification result;
respectively inputting the various item of policy information into a preset risk prediction model according to the geographical region classification result to obtain a risk score of a policy corresponding to the geographical region, and judging whether the policy corresponding to the risk score is a risk policy according to whether the policy corresponding to the risk score is a risk policy or not;
counting the number of the risk orders, and calculating regional risk scores of the geographic regions according to the risk scores corresponding to the risk orders;
and displaying the risk list quantity and the regional risk scores on a map according to a preset display mode and the geographic information to obtain a risk map.
Optionally, in a second implementation manner of the first aspect of the present invention, the inputting the various policy information into a preset risk prediction model according to the geographical area classification result, to obtain a risk score of a policy corresponding to the geographical area, and determining whether the policy corresponding to the risk score is a risk policy according to whether the risk score is a risk policy includes:
respectively inputting the various item of policy information into a preset risk prediction model according to the geographical region classification result to obtain corresponding risk coefficients of the various item of policy information;
acquiring a single-item adjustment coefficient corresponding to each item of policy information;
the corresponding risk coefficients are adjusted through the single item adjustment coefficients, and single item risk scoring values of various item of policy information are obtained;
and judging whether the policy corresponding to the single grading value of each item of policy information is a risk policy or not according to the policy.
Optionally, in a third implementation manner of the first aspect of the present invention, whether the policy corresponding to the single item grading value of the policy information is a risk policy includes:
obtaining the scoring weight of each item of policy information;
weighting and summing all the single scoring values according to the corresponding scoring weights to obtain risk scores;
Judging whether the risk score is larger than a preset risk score threshold value or not;
if yes, determining the policy corresponding to the risk score as a risk policy.
Optionally, in a fourth implementation manner of the first aspect of the present invention, determining a high-risk location in the insurance coverage locations divided in the geographic area according to the risk single quantity and the risk score, and early warning the high-risk location includes:
acquiring an insuring place name input by a user, and inquiring corresponding historical scoring data according to the insuring place name;
and drawing a risk score trend graph corresponding to the insuring place name according to the risk score and the historical score data.
Optionally, in a fifth implementation manner of the first aspect of the present invention, the policy information includes quotation data, application data and wholesale data according to the underwriting process, and the analyzing the underwriting process of the policy according to the policy information includes:
inputting the quotation data in the policy data into the risk prediction model, judging whether the quotation data which does not pass through the risk prediction model is determined to be in accordance with the fusion rule, and counting the quantity of the quotation data which does not meet the fusion rule;
The quotation data conforming to the fusion rule and the insurance data of the insurance policy data corresponding to the quotation data determined to pass through by the risk prediction model are input into the risk prediction model, whether the insurance data determined to not pass through by the risk prediction model conforms to the fusion rule or not is judged, and the quantity of the insurance data not conforming to the fusion rule is counted;
inputting the insurance data conforming to the fusing rules and the batch bill data of the insurance policy data corresponding to the insurance data determined by the risk prediction model as passing insurance data into the risk prediction model, judging whether the batch bill data determined by the risk prediction model as not passing batch bill data conforms to the fusing rules, and counting the quantity of batch bill data not conforming to the fusing rules;
and outputting the quotation data, the application data and the wholesale data which do not accord with the fusion rule as process monitoring data.
Optionally, in a sixth implementation manner of the first aspect of the present invention, the inputting the bid data in the policy data into the risk prediction model, and determining whether the bid data that is determined to not pass by the risk prediction model meets a fusion rule, and counting the number of bid data that does not meet the fusion rule includes:
Inputting the quotation data into the risk prediction model to obtain a single risk scoring value of the quotation data;
if the single risk score value is larger than a preset single risk score threshold value, determining that the corresponding quotation data does not pass;
judging whether the quotation data which do not pass through the risk prediction model is in accordance with a fusion rule or not;
the number of quotation data in which the convergence rule is not met is counted.
The second aspect of the invention provides a nuclear protection wind control monitoring device, comprising:
the system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring a nuclear protection wind control monitoring instruction and a monitored insurance type input by a user and judging the monitoring type represented by the nuclear protection wind control monitoring instruction, wherein the monitoring type comprises result monitoring and process monitoring;
the map generation module is used for acquiring a policy corresponding to the insurance type and various policy information corresponding to the policy when the monitoring type is result monitoring, and making a corresponding risk map according to the policy and the policy information, wherein the risk map comprises risk single amounts and risk scores of various insurance applying places divided in a preset geographic area;
the early warning module is used for determining high-risk places in all the insurance applying places divided in the geographic area according to the risk single quantity and the risk score and carrying out early warning on the high-risk places;
The analysis module is used for analyzing the underwriting process of the policy according to the policy information to obtain process monitoring data when the monitoring type is process monitoring;
and the sending module is used for sending the risk map or the process monitoring data to the user so as to enable the user to carry out the nuclear security wind control analysis.
Optionally, in a first implementation manner of the second aspect of the present invention, the map generating module includes:
the data acquisition unit is used for acquiring the insurance policy corresponding to the insurance type, various insurance policy information corresponding to the insurance policy and geographic information of the geographic area;
the classification unit is used for classifying the geographic areas of the policy according to the geographic information to obtain a geographic area classification result;
the model input unit is used for respectively inputting the various item of policy information into a preset risk prediction model according to the geographical region classification result to obtain the risk score of the policy corresponding to the geographical region, and judging whether the policy corresponding to the risk score is a risk policy according to whether the policy corresponding to the risk score is a risk policy or not;
the statistics unit is used for counting the number of the risk orders and calculating regional risk scores of the geographic regions according to the risk scores corresponding to the risk orders;
And the map display unit is used for displaying the risk list number and the regional risk score on a map according to a preset display mode and the geographic information to obtain a risk map.
Optionally, in a second implementation manner of the second aspect of the present invention, the model input unit includes:
the risk coefficient subunit is used for respectively inputting the various item of policy information into a preset risk prediction model according to the geographical region classification result to obtain the corresponding coefficient of the various item of policy information;
the adjustment coefficient subunit is used for acquiring a single adjustment coefficient corresponding to each item of policy information;
the adjustment subunit is used for adjusting the corresponding risk coefficient through the single item adjustment coefficient to obtain a single item risk scoring value of each item of policy information;
and the risk judging subunit is used for judging whether the policy corresponding to the single item grading value of each item of policy information is a risk policy or not.
Optionally, in a third implementation manner of the second aspect of the present invention, the risk judging subunit is specifically configured to:
obtaining the scoring weight of each item of policy information;
weighting and summing all the single scoring values according to the corresponding scoring weights to obtain risk scores;
Judging whether the risk score is larger than a preset risk score threshold value or not;
if yes, determining the policy corresponding to the risk score as a risk policy.
Optionally, in a fourth implementation manner of the second aspect of the present invention, the core protection wind control monitoring device further includes a trend graph module, where the trend graph module is specifically configured to:
acquiring an insuring place name input by a user, and inquiring corresponding historical scoring data according to the insuring place name;
and drawing a risk score trend graph corresponding to the insuring place name according to the risk score and the historical score data.
Optionally, in a fifth implementation manner of the second aspect of the present invention, the analysis module is specifically configured to:
inputting the quotation data in the policy data into the risk prediction model, judging whether the quotation data which does not pass through the risk prediction model is determined to be in accordance with the fusion rule, and counting the quantity of the quotation data which does not meet the fusion rule;
the quotation data conforming to the fusion rule and the insurance data of the insurance policy data corresponding to the quotation data determined to pass through by the risk prediction model are input into the risk prediction model, whether the insurance data determined to not pass through by the risk prediction model conforms to the fusion rule or not is judged, and the quantity of the insurance data not conforming to the fusion rule is counted;
Inputting the insurance data conforming to the fusing rules and the batch bill data of the insurance policy data corresponding to the insurance data determined by the risk prediction model as passing insurance data into the risk prediction model, judging whether the batch bill data determined by the risk prediction model as not passing batch bill data conforms to the fusing rules, and counting the quantity of batch bill data not conforming to the fusing rules;
and outputting the quotation data, the application data and the wholesale data which do not accord with the fusion rule as process monitoring data.
Optionally, in a sixth implementation manner of the second aspect of the present invention, the analysis module is specifically further configured to:
inputting the quotation data into the risk prediction model to obtain a single risk scoring value of the quotation data;
if the single risk score value is larger than a preset single risk score threshold value, determining that the corresponding quotation data does not pass;
judging whether the quotation data which do not pass through the risk prediction model is in accordance with a fusion rule or not;
the number of quotation data in which the convergence rule is not met is counted.
A third aspect of the present invention provides a nuclear protection wind control monitoring device, including: a memory and at least one processor, the memory having instructions stored therein, the memory and the at least one processor being interconnected by a line; and the at least one processor calls the instruction in the memory so that the nuclear protection wind control monitoring equipment executes the nuclear protection wind control monitoring method.
A fourth aspect of the present invention provides a computer readable storage medium having instructions stored therein that, when executed on a computer, cause the computer to perform the above-described method of nuclear security wind control monitoring.
According to the technical scheme, a nuclear protection wind control monitoring instruction input by a user and a monitored insurance type are obtained, and a monitoring type represented by the nuclear protection wind control monitoring instruction is judged, wherein the monitoring type comprises result monitoring and process monitoring; if the monitoring type is result monitoring, acquiring a policy corresponding to the insurance type and various policy information corresponding to the policy, and making a corresponding risk map according to the policy and the policy information, wherein the risk map comprises risk single amounts and risk scores of various insurance applying places divided in a preset geographic area; determining high-risk places in all the insuring places divided in the geographic area according to the risk single quantity and the risk score, and carrying out early warning on the high-risk places; if the monitoring type is process monitoring, analyzing the underwriting process of the policy according to the policy information to obtain process monitoring data; and sending the risk map or the process monitoring data to the user so as to enable the user to conduct nuclear security wind control analysis. According to the invention, different nuclear protection wind control monitoring methods are provided through different nuclear protection wind control monitoring instructions sent by a user, the nuclear protection wind control monitoring is carried out on the nuclear protection result and the nuclear protection process of the nuclear protection data, and a manager is helped to know information such as the nuclear protection rule, the risk type interception amount and the like through the result monitoring and the process monitoring, so that the follow-up data statistical analysis and the optimization of the risk prediction model are facilitated. In addition, the invention also relates to a blockchain technology, and the risk single quantity can be stored in the blockchain.
Drawings
FIG. 1 is a schematic diagram of a first embodiment of a method for monitoring a nuclear protection wind control according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a second embodiment of a method for monitoring a nuclear protection wind control according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a third embodiment of a method for monitoring a nuclear protection wind control according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a fourth embodiment of a method for monitoring a nuclear protection wind control according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of an embodiment of a device for monitoring and controlling a nuclear protection wind in an embodiment of the present invention;
FIG. 6 is a schematic diagram of another embodiment of a device for monitoring and controlling a nuclear protection wind in an embodiment of the present invention;
fig. 7 is a schematic diagram of an embodiment of a nuclear protection wind control monitoring device according to an embodiment of the present invention.
Detailed Description
According to the technical scheme, a nuclear protection wind control monitoring instruction input by a user and a monitored insurance type are obtained, and a monitoring type represented by the nuclear protection wind control monitoring instruction is judged, wherein the monitoring type comprises result monitoring and process monitoring; if the monitoring type is result monitoring, acquiring a policy corresponding to the insurance type and various policy information corresponding to the policy, and making a corresponding risk map according to the policy and the policy information, wherein the risk map comprises risk single amounts and risk scores of various insurance applying places divided in a preset geographic area; determining high-risk places in all the insuring places divided in the geographic area according to the risk single quantity and the risk score, and carrying out early warning on the high-risk places; if the monitoring type is process monitoring, analyzing the underwriting process of the policy according to the policy information to obtain process monitoring data; and sending the risk map or the process monitoring data to the user so as to enable the user to conduct nuclear security wind control analysis. According to the invention, different nuclear protection wind control monitoring methods are provided through different nuclear protection wind control monitoring instructions sent by a user, the nuclear protection wind control monitoring is carried out on the nuclear protection result and the nuclear protection process of the nuclear protection data, and a manager is helped to know information such as the nuclear protection rule, the risk type interception amount and the like through the result monitoring and the process monitoring, so that the follow-up data statistical analysis and the optimization of the risk prediction model are facilitated. In addition, the invention also relates to a blockchain technology, and the risk single quantity can be stored in the blockchain.
The terms "first," "second," "third," "fourth" and the like in the description and in the claims and in the above drawings, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments described herein may be implemented in other sequences than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or apparatus.
For easy understanding, the following describes a specific flow of an embodiment of the present invention, referring to fig. 1, and a first embodiment of a method for monitoring a nuclear protection wind control in the embodiment of the present invention includes:
101. acquiring a nuclear protection wind control monitoring instruction and a monitored insurance type input by a user, and judging the monitoring type represented by the nuclear protection wind control monitoring instruction;
It can be understood that the execution body of the invention may be a core protection wind control monitoring device, and may also be a terminal or a server, which is not limited herein. The embodiment of the invention is described by taking a server as an execution main body as an example.
It is emphasized that to ensure privacy and security of data, the policy and corresponding items of policy information may be stored in nodes of a blockchain.
In this embodiment, the monitoring of the security risk control mainly includes two types of result monitoring and process monitoring, where the result monitoring mainly includes obtaining existing policy data, counting and calculating risk policies in all policies, and generating different monitoring products for a manager to check and analyze through different requirements after counting and calculating.
In practical applications, the result monitoring can be achieved in several ways: 1. displaying the existing risk single quantity and risk score ranking of each region of the existing policy through a risk map, directly clicking a mechanism with higher risk, giving early warning, grasping the risk dynamic situation in time, and checking the risk score and the risk single quantity for single risk so as to analyze the control situation of the single risk; 2. the total risk score and the influence degree of each risk affecting the score can be analyzed for a certain insurance agency needing to be checked to generate a radar chart, so that the insurance agency can adjust the operation policy in time and control the risk; 3. the risk trends are checked through scoring trends, the risk management and control capability of each institution can be scored by the early-warning risk management and control force of each institution, the benign competition of wind control among the institutions is promoted, and the risk management and control force can be used as a reference of performance judgment indexes; 4. the mechanism and even a salesman can check the unmodified proportion and ranking through a risk list board, link and extract corresponding lists to carry out risk modification, and check whether a risk prediction model needs to be optimized or not through list extraction without interception of a single quantity, so that the service quality of clients is improved; 5. for the special cases of the risk types which cannot be rectified, the risk types need to be subdivided, excluded to be non-risk, and the like.
102. If the monitoring type is result monitoring, acquiring a policy corresponding to the insurance type and various policy information corresponding to the policy, and making a corresponding risk map according to the policy and the policy information, wherein the risk map comprises risk single amounts and risk scores of various insurance applying places divided in a preset geographic area;
in this embodiment, when the received monitoring type is monitored as a result, the manufactured monitoring product is taken as a risk map as an example, after the monitoring type represented by the monitoring instruction for the security risk is received and the monitoring type represented by the monitoring instruction for the security wind control is determined to be monitored as a result, the server obtains the corresponding policy according to the security type, and obtains the policy data according to the security type mainly for facilitating the security risk analysis of each security type, wherein the security types are generally classified into four categories of property insurance, personal insurance, liability insurance and credit insurance according to the respective requirements, the applicant inputs the corresponding policy data according to the different security types, and the risk prediction model performs the risk assessment according to the policy data.
In this embodiment, a risk map is made by using policy data, where the risk map mainly includes location information of all the insurance places where the user needs to perform monitoring analysis, the policy data includes names of the insurance places where the applicant performs insurance, the number of insurance policies of each insurance place can be obtained by counting according to the names of the insurance places, and then the number of risk policies in the insurance policies is determined, so that the existing risk policy quantity of each insurance place can be obtained by counting the number of the insurance policies, where the risk policies can be obtained by inputting the insurance policies into a preset risk prediction model, judging and determining the risk policies in the obtained insurance policies, or can be the insurance policies of claims in all the check insurance policies. In this embodiment, the risk score may be a risk score obtained by inputting all the data of the underwriting policy into a preset risk score model for risk assessment according to the proportion of the underwriting policy in all the underwriting policy, and obtaining a risk score of the application place by taking a representative number such as an average value or a median value.
103. Determining high-risk places in the classified insurance places in the geographic area according to the risk single quantity and the risk score, and early warning the high-risk places;
in this embodiment, when the existing risk single quantity and the risk score are obtained, the existing risk single quantity and/or the risk score of a certain application location may be determined to be greater than a preset threshold, if yes, the application location is determined to be a high risk location, or ranking all application locations in the geographic area from large to small according to the existing risk single quantity and/or the risk score, the application locations ranked in the preset ranking number are determined to be high risk locations, the application location determined to be the high risk location is determined to timely grasp the risk dynamic situation according to the existing risk single quantity and the risk score, analyze the nuclear protection risk in time, adjust the operating policy in time, and control the risk occurrence.
104. If the monitoring type is process monitoring, analyzing the underwriting process of the policy according to the policy information to obtain process monitoring data;
in this embodiment, the process monitoring mainly monitors the underwriting process such as quotation, insurance application, correction, and the like in an omnibearing manner, and can reflect the risk list of each stage, the interception quantity of the risk prediction model for each stage, and the data of the conditions such as passing through and passing through failure after the interception of the insurance list in each stage, by analyzing the change of the data, the underwriting process is monitored.
105. And sending the risk map or the process monitoring data to a user for the user to perform the verification and wind control analysis.
In this embodiment, after acquiring the risk map or the process monitoring data, the user may analyze the risk map or the process monitoring data, adjust the operation policy of the application place according to the risk map, control the risk, and simultaneously, also continuously perfect the wind control model according to the process monitoring data, continuously increase the risk types, match the appropriate risk model for different people, help to provide more references for the manager to control the risk, prevent the occurrence of large-area risk, and meanwhile, through the process monitoring data, the manager is convenient to learn the conditions of the rules of the nuclear insurance concrete and the interception of various risk types, and the like, and make up the gap in the statistical analysis of the data with the probability of low risk occurrence, so as to facilitate the subsequent demand analysis.
In this embodiment, a core protection wind control monitoring instruction and a monitored insurance type input by a user are obtained, and a monitoring type represented by the core protection wind control monitoring instruction is judged, wherein the monitoring type comprises result monitoring and process monitoring; if the monitoring type is result monitoring, acquiring a policy corresponding to the insurance type and various policy information corresponding to the policy, and making a corresponding risk map according to the policy and the policy information, wherein the risk map comprises risk single amounts and risk scores of various insurance applying places divided in a preset geographic area; determining high-risk places in all the insuring places divided in the geographic area according to the risk single quantity and the risk score, and carrying out early warning on the high-risk places; if the monitoring type is process monitoring, analyzing the underwriting process of the policy according to the policy information to obtain process monitoring data; and sending the risk map or the process monitoring data to the user so as to enable the user to conduct nuclear security wind control analysis. According to the invention, different nuclear protection wind control monitoring methods are provided through different nuclear protection wind control monitoring instructions sent by a user, the nuclear protection wind control monitoring is carried out on the nuclear protection result and the nuclear protection process of the nuclear protection data, and a manager is helped to know information such as the nuclear protection rule, the risk type interception amount and the like through the result monitoring and the process monitoring, so that the follow-up data statistical analysis and the optimization of the risk prediction model are facilitated. In addition, the invention also relates to a blockchain technology, and the risk single quantity can be stored in the blockchain.
Referring to fig. 2, a second embodiment of a method for monitoring a nuclear protection wind control according to an embodiment of the present invention includes:
201. acquiring a nuclear protection wind control monitoring instruction and a monitored insurance type input by a user, and judging the monitoring type represented by the nuclear protection wind control monitoring instruction;
202. if the monitoring type is result monitoring, acquiring a policy corresponding to the insurance type, various policy information corresponding to the policy and geographic information of a geographic area;
in this embodiment, each item of policy information may be, but not limited to, one or more of offer data, application data, and lot data according to a underwriting process, and the geographic information is mainly used for drawing a map subsequently.
203. Carrying out geographic region classification on the policy according to the geographic information to obtain a geographic region classification result;
204. respectively inputting each item of policy information into a preset risk prediction model according to the geographical region classification result to obtain corresponding risk coefficients of each item of policy information;
in the present embodiment, the risk prediction model is a machine learning model previously established for predicting the risk of a policy. Specifically, the server may input each item of policy information into the risk prediction model to perform risk prediction, and output a single risk score of each item of policy information. I.e. outputting a single risk score corresponding to each item of policy information. For example, three items of policy information of A, B and C are input, then a single item risk score 1 corresponding to a, a single item risk score 2 corresponding to B, and a single item risk score 3 corresponding to C may be output.
205. Acquiring a single-item adjustment coefficient corresponding to each item of policy information;
in this embodiment, the server may directly acquire a single item adjustment coefficient preset in advance for each application item as a single item adjustment coefficient corresponding to each item of policy information. That is, the preset single item adjustment coefficient does not change with the change of the essential content of the policy information, but is preset according to the application item. For example, for the application item of the applicant information, a corresponding single item adjustment coefficient may be preset to be 0.7, and when the target policy 1 and the target policy 2 are respectively subjected to the verification processing, the single item adjustment coefficients corresponding to the applicant information of the target policy 1 and the applicant information of the target policy 2 are both 0.7. It is understood that the preset single adjustment coefficient is a preset stable experience value with universality.
206. The corresponding risk coefficients are adjusted through the single-item adjustment coefficients, so that single-item risk scoring values of all the policy information are obtained;
in this embodiment, the single item adjustment coefficient corresponding to each item of policy information is multiplied by the corresponding risk coefficient, and the obtained product is used as the single item risk score of each item of policy information.
207. Obtaining the scoring weights of all the policy information, and carrying out weighted summation on all the item scoring values according to the corresponding scoring weights to obtain risk scores;
208. Judging whether the risk score is larger than a preset risk score threshold value or not;
209. if yes, determining a policy corresponding to the risk score as a risk policy;
210. counting the number of the risk orders, and calculating regional risk scores of the geographic regions according to the risk scores corresponding to the risk orders;
211. displaying the number of risk orders and the regional risk scores on a map according to a preset display mode and geographic information to obtain a risk map;
in this embodiment, the application location, the corresponding risk score and the corresponding risk score may be displayed on the map in a predetermined display manner, and of course, the risk score and the corresponding risk score may also be displayed at a specified location outside the map.
In this embodiment, the level may also be set according to the regional risk score, for example, a predetermined range may include: greater than 0 and less than or equal to 0.1, greater than 0.1 and less than or equal to 0.4, greater than 0.4 and less than or equal to 0.6, and greater than 0.6, respectively correspond to risk levels of: when the regional risk score is 0.6, the corresponding score range can be determined to be more than 0.4 and less than or equal to 0.6, and the risk grade corresponding to the score range is the next highest grade, so that the next highest grade can be displayed at the corresponding insuring place position on the map.
212. Determining high-risk places in the classified insurance places in the geographic area according to the risk single quantity and the risk score, and early warning the high-risk places;
213. if the monitoring type is process monitoring, analyzing the underwriting process of the policy according to the policy information to obtain process monitoring data;
214. and sending the risk map or the process monitoring data to a user for the user to perform the verification and wind control analysis.
The embodiment describes in detail the process of acquiring the policy corresponding to the insurance type and each item of policy information corresponding to the policy based on the previous embodiment, and making a corresponding risk map according to the policy and the policy information, by acquiring the policy corresponding to the insurance type, each item of policy information corresponding to the policy, and geographic information of the geographic area; carrying out geographic region classification on the policy according to the geographic information to obtain a geographic region classification result; respectively inputting each item of policy information into a preset risk prediction model according to the geographical region classification result to obtain the risk score of the policy corresponding to the geographical region, and judging whether the policy corresponding to the risk score is the risk policy according to the risk score; counting the number of the risk orders, and calculating regional risk scores of the geographic regions according to the risk scores corresponding to the risk orders; according to a preset display mode and geographic information, displaying the number of risk orders and regional risk scores on a map to obtain a risk map, generating the risk map by the method, facilitating the supervision of a manager to check and control the air supply, and adjusting the operation strategy according to the supervision result.
Referring to fig. 3, a third embodiment of a method for monitoring a wind control of a nuclear protection device according to an embodiment of the present invention includes:
301. acquiring a nuclear protection wind control monitoring instruction and a monitored insurance type input by a user, and judging the monitoring type represented by the nuclear protection wind control monitoring instruction;
302. if the monitoring type is result monitoring, acquiring a policy corresponding to the insurance type and various policy information corresponding to the policy, and making a corresponding risk map according to the policy and the policy information, wherein the risk map comprises risk single amounts and risk scores of various insurance applying places divided in a preset geographic area;
303. determining high-risk places in the classified insurance places in the geographic area according to the risk single quantity and the risk score, and early warning the high-risk places;
304. acquiring an insuring place name input by a user, and inquiring corresponding historical scoring data according to the insuring place name;
305. drawing a risk score trend graph corresponding to the name of the insuring place according to the risk score and the historical score data;
in this embodiment, the policy data may be divided according to different time periods, risk scores may be performed, risk scores obtained by inputting policy data other than the current time period into the risk score model may be used as history score data, risk scores obtained by inputting policy data in the current time period into the risk score model may be used as risk scores, according to different time nodes corresponding to the risk scores and the historical score data, a risk score trend graph which is continuously changed along with time is generated, each risk trend is checked through the score trend, the risk control capability of each institution can be scored by the early-warning risk control force of each institution, the benign competition of wind control among the institutions is promoted, and the risk score trend graph can be used as a reference of performance judging indexes.
306. If the monitoring type is process monitoring, analyzing the underwriting process of the policy according to the policy information to obtain process monitoring data;
307. and sending the risk map or the process monitoring data to a user for the user to perform the verification and wind control analysis.
The embodiment adds a process for generating a risk scoring trend graph on the basis of the previous embodiment, obtains the name of the insuring place input by the user, and queries corresponding historical scoring data according to the name of the insuring place; according to the risk score and the historical score data, a risk score trend chart corresponding to the name of the insuring place is drawn, the risk score trend chart is generated through the method, a manager can check each risk trend through the score trend, the risk control force of each institution is early-warned, the risk control capability of each institution can be scored, the benign competition of wind control among the institutions is promoted, and the risk score trend chart can be used as a reference of performance judging indexes.
Referring to fig. 4, a fourth embodiment of a method for monitoring a wind control of a nuclear protection device according to an embodiment of the present invention includes:
401. acquiring a nuclear protection wind control monitoring instruction and a monitored insurance type input by a user, and judging the monitoring type represented by the nuclear protection wind control monitoring instruction;
402. If the monitoring type is result monitoring, acquiring a policy corresponding to the insurance type and various policy information corresponding to the policy, and making a corresponding risk map according to the policy and the policy information, wherein the risk map comprises risk single amounts and risk scores of various insurance applying places divided in a preset geographic area;
403. determining high-risk places in the classified insurance places in the geographic area according to the risk single quantity and the risk score, and early warning the high-risk places;
404. if the monitoring type is process monitoring, inputting the quotation data into a risk prediction model to obtain a single risk scoring value of the quotation data;
405. if the single risk score value is larger than a preset single risk score threshold value, determining that the corresponding quotation data does not pass;
406. judging whether the quotation data which do not pass through the risk prediction model is in accordance with the fusion rule or not;
407. counting the quantity of quotation data which does not accord with the fusion rule;
408. the quotation data and the risk prediction model which accord with the fusing rules are determined to be the application data of the policy data corresponding to the passed quotation data and are input into the risk prediction model, whether the application data which do not pass through the risk prediction model is determined to accord with the fusing rules is judged, and the quantity of the application data which do not accord with the fusing rules is counted;
409. The method comprises the steps of inputting batch bill data of the insurance bill data corresponding to the insurance data which accords with the fusing rule and the risk prediction model into the risk prediction model, judging whether the batch bill data which does not accord with the fusing rule and is determined by the risk prediction model accords with the fusing rule, and counting the quantity of the batch bill data which does not accord with the fusing rule;
410. the quotation data, the application data and the wholesale data which do not accord with the fusion rule are output as process monitoring data;
411. and sending the risk map or the process monitoring data to a user for the user to perform the verification and wind control analysis.
The embodiment describes in detail the process of acquiring process monitoring data according to the warranty information by analyzing the warranty process according to the warranty information on the basis of the previous embodiment, and also describes in detail the process of inputting the quotation data in the warranty data into the risk prediction model, judging whether the quotation data which does not pass through the risk prediction model accords with the fusion rule, counting the quantity of quotation data which does not accord with the fusion rule, and checking the prior risk quantity, and the processes of quotation, application, correction, etc. by monitoring the warranty process, a manager can display and check the prior risk quantity through a billboard, find out the risk pain point, know which piece is likely to be a multiple region which cannot be applied by the applicant, and conveniently analyze the region and count the quality and the wind control condition of the applicant in each region.
The method for monitoring the air control of the core protection in the embodiment of the present invention is described above, and the following describes the device for monitoring the air control of the core protection in the embodiment of the present invention, referring to fig. 5, one embodiment of the device for monitoring the air control of the core protection in the embodiment of the present invention includes:
the acquiring module 501 is configured to acquire a core protection wind control monitoring instruction and a monitored insurance type input by a user, and determine a monitoring type represented by the core protection wind control monitoring instruction, where the monitoring type includes result monitoring and process monitoring;
the map generation module 502 is configured to obtain a policy corresponding to the insurance type and various policy information corresponding to the policy when the monitoring type is result monitoring, and make a corresponding risk map according to the policy and the policy information, where the risk map includes a risk amount and a risk score of each insurance application place divided in a preset geographic area;
an early warning module 503, configured to determine a high risk location in each of the insurance application locations divided in the geographic area according to the risk single quantity and the risk score, and perform early warning on the high risk location;
the analysis module 504 is configured to analyze the warranty verification process according to the warranty information to obtain process monitoring data when the monitoring type is process monitoring;
And the sending module 505 is configured to send the risk map or the process monitoring data to the user, so that the user performs a verification and wind control analysis.
It is emphasized that to ensure privacy and security of data, existing risk singles may be stored in a blockchain node.
In the embodiment of the invention, the nuclear protection wind control monitoring device runs the nuclear protection wind control monitoring method, and the nuclear protection wind control monitoring method comprises the following steps: acquiring a nuclear protection wind control monitoring instruction and a monitored insurance type input by a user, and judging the monitoring type represented by the nuclear protection wind control monitoring instruction, wherein the monitoring type comprises result monitoring and process monitoring; if the monitoring type is result monitoring, acquiring a policy corresponding to the insurance type and various policy information corresponding to the policy, and making a corresponding risk map according to the policy and the policy information, wherein the risk map comprises risk single amounts and risk scores of various insurance applying places divided in a preset geographic area; determining high-risk places in all the insuring places divided in the geographic area according to the risk single quantity and the risk score, and carrying out early warning on the high-risk places; if the monitoring type is process monitoring, analyzing the underwriting process of the policy according to the policy information to obtain process monitoring data; and sending the risk map or the process monitoring data to the user so as to enable the user to conduct nuclear security wind control analysis. According to the invention, different nuclear protection wind control monitoring methods are provided through different nuclear protection wind control monitoring instructions sent by a user, the nuclear protection wind control monitoring is carried out on the nuclear protection result and the nuclear protection process of the nuclear protection data, and a manager is helped to know information such as the nuclear protection rule, the risk type interception amount and the like through the result monitoring and the process monitoring, so that the follow-up data statistical analysis and the optimization of the risk prediction model are facilitated. In addition, the invention also relates to a blockchain technology, and the risk single quantity can be stored in the blockchain.
Referring to fig. 6, a second embodiment of a nuclear protection wind control monitoring device according to an embodiment of the present invention includes:
the acquiring module 501 is configured to acquire a core protection wind control monitoring instruction and a monitored insurance type input by a user, and determine a monitoring type represented by the core protection wind control monitoring instruction, where the monitoring type includes result monitoring and process monitoring;
the map generation module 502 is configured to obtain a policy corresponding to the insurance type and various policy information corresponding to the policy when the monitoring type is result monitoring, and make a corresponding risk map according to the policy and the policy information, where the risk map includes a risk amount and a risk score of each insurance application place divided in a preset geographic area;
an early warning module 503, configured to determine a high risk location in each of the insurance application locations divided in the geographic area according to the risk single quantity and the risk score, and perform early warning on the high risk location;
the analysis module 504 is configured to analyze the warranty verification process according to the warranty information to obtain process monitoring data when the monitoring type is process monitoring;
and the sending module 505 is configured to send the risk map or the process monitoring data to the user, so that the user performs a verification and wind control analysis.
Wherein, the map generation module 502 includes:
a data obtaining unit 5021, configured to obtain a policy corresponding to the insurance type, each item of application data corresponding to the policy, and geographic information of the geographic area;
the classification unit 5022 is configured to classify the geographic area of the policy according to the geographic information, so as to obtain a classification result of the geographic area;
the model input unit 5023 is configured to input the various application data into a preset risk prediction model according to the geographical region classification result, obtain a risk score of a policy corresponding to the geographical region, and determine whether the policy corresponding to the risk score is a risk policy according to whether the policy corresponding to the risk score is a risk policy;
the statistics unit 5024 is configured to count the number of risk orders, and calculate an area risk score of the geographic area according to the risk score corresponding to the risk order;
the map display unit 5025 is configured to display the number of risk orders and the regional risk score on a map according to a preset display mode and the geographic information, so as to obtain a risk map.
Wherein the model input unit 5023 comprises:
the risk coefficient subunit 50231 is configured to input each item of insurance data into a preset risk prediction model according to the geographic region classification result, so as to obtain a corresponding coefficient of each item of policy information;
An adjustment coefficient subunit 50232, configured to obtain a single adjustment coefficient corresponding to each item of policy information;
the adjusting subunit 50233 is configured to adjust the corresponding risk coefficient by using the single-item adjusting coefficient to obtain a single-item risk score value of each item of the application data;
the risk judging subunit 50234 is configured to determine whether the policy corresponding to the single scoring value of each item of the application data is a risk policy.
Optionally, the risk determination subunit 50234 is specifically configured to:
obtaining scoring weights of the various item of application data;
weighting and summing all the single scoring values according to the corresponding scoring weights to obtain risk scores;
judging whether the risk score is larger than a preset risk score threshold value or not;
if yes, determining the policy corresponding to the risk score as a risk policy.
The core protection wind control monitoring device further includes a trend graph module 506, where the trend graph module 506 is specifically configured to:
acquiring an insuring place name input by a user, and inquiring corresponding historical scoring data according to the insuring place name;
and drawing a risk score trend graph corresponding to the insuring place name according to the risk score and the historical score data.
Optionally, the analysis module 505 is specifically configured to:
inputting the quotation data in the policy data into the risk prediction model, judging whether the quotation data which does not pass through the risk prediction model is determined to be in accordance with the fusion rule, and counting the quantity of the quotation data which does not meet the fusion rule;
the quotation data conforming to the fusion rule and the insurance data of the insurance policy data corresponding to the quotation data determined to pass through by the risk prediction model are input into the risk prediction model, whether the insurance data determined to not pass through by the risk prediction model conforms to the fusion rule or not is judged, and the quantity of the insurance data not conforming to the fusion rule is counted;
inputting the insurance data conforming to the fusing rules and the batch bill data of the insurance policy data corresponding to the insurance data determined by the risk prediction model as passing insurance data into the risk prediction model, judging whether the batch bill data determined by the risk prediction model as not passing batch bill data conforms to the fusing rules, and counting the quantity of batch bill data not conforming to the fusing rules;
and outputting the quotation data, the application data and the wholesale data which do not accord with the fusion rule as process monitoring data.
Optionally, the analysis module 505 is specifically further configured to:
Inputting the quotation data into the risk prediction model to obtain a single risk scoring value of the quotation data;
if the single risk score value is larger than a preset single risk score threshold value, determining that the corresponding quotation data does not pass;
judging whether the quotation data which do not pass through the risk prediction model is in accordance with a fusion rule or not;
the number of quotation data in which the convergence rule is not met is counted.
The embodiment describes the specific functions of each module and the unit constitution of part of the modules in detail on the basis of the previous embodiment, through the device, the manager can adjust the experience strategy according to the monitored data to reduce the risk policy of the insurance company, stop the cheating protection of part of the applicant, maintain the benefit of the company, and continuously optimize the existing risk prediction model according to the demonstration of the risk type of the insurance result and the insurance result.
The central-core security wind control monitoring device in the embodiment of the present invention is described in detail from the point of view of the modularized functional entity in fig. 5 and fig. 6, and the central-core security wind control monitoring device in the embodiment of the present invention is described in detail from the point of view of hardware processing.
Fig. 7 is a schematic structural diagram of a core protection wind control monitoring device according to an embodiment of the present application, where the core protection wind control monitoring device 700 may have a relatively large difference due to different configurations or performances, and may include one or more processors (central processing units, CPU) 710 (e.g., one or more processors) and a memory 720, and one or more storage mediums 730 (e.g., one or more mass storage devices) storing application programs 733 or data 732. Wherein memory 720 and storage medium 730 may be transitory or persistent. The program stored on the storage medium 730 may include one or more modules (not shown), each of which may include a series of instruction operations for the core protection wind control monitoring device 700. Still further, the processor 710 may be configured to communicate with the storage medium 730 and execute a series of instruction operations in the storage medium 730 on the nuclear care wind-controlled monitoring device 700 to implement the steps of the nuclear care wind-controlled monitoring method described above.
The core security wind control monitoring device 700 may also include one or more power supplies 740, one or more wired or wireless network interfaces 750, one or more input/output interfaces 760, and/or one or more operating systems 731, such as Windows Serve, mac OS X, unix, linux, freeBSD, and the like. It will be appreciated by those skilled in the art that the configuration of the disclosed nuclear protection pneumatic control monitoring device shown in fig. 7 is not limiting of the disclosed nuclear protection pneumatic control monitoring device and may include more or less components than those illustrated, or may be combined with certain components, or may be arranged with different components.
The blockchain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, consensus mechanism, encryption algorithm and the like. The Blockchain (Blockchain), which is essentially a decentralised database, is a string of data blocks that are generated by cryptographic means in association, each data block containing a batch of information of network transactions for verifying the validity of the information (anti-counterfeiting) and generating the next block. The blockchain may include a blockchain underlying platform, a platform product services layer, an application services layer, and the like.
The present invention also provides a computer readable storage medium, which may be a non-volatile computer readable storage medium, and may also be a volatile computer readable storage medium, where instructions are stored in the computer readable storage medium, where the instructions, when executed on a computer, cause the computer to perform the steps of the method for monitoring and controlling a nuclear protection wind.
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process of the system or apparatus and unit described above may refer to the corresponding process in the foregoing method embodiment, which is not repeated herein.
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 invention may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. 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.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims (6)

1. The nuclear protection wind control monitoring method is characterized by comprising the following steps of:
acquiring a nuclear protection wind control monitoring instruction and a monitored insurance type input by a user, and judging the monitoring type represented by the nuclear protection wind control monitoring instruction, wherein the monitoring type comprises result monitoring and process monitoring;
if the monitoring type is result monitoring, acquiring a policy corresponding to the insurance type and various policy information corresponding to the policy, and making a corresponding risk map according to the policy and the policy information, wherein the risk map comprises risk single amounts and risk scores of various insurance applying places divided in a preset geographic area;
determining high-risk places in all the insuring places divided in the geographic area according to the risk single quantity and the risk score, and carrying out early warning on the high-risk places;
if the monitoring type is process monitoring, analyzing the underwriting process of the policy according to the policy information to obtain process monitoring data;
the risk map or the process monitoring data are sent to the user so that the user can carry out the verification and wind control analysis;
the obtaining the policy corresponding to the insurance type and each item of policy information corresponding to the policy, and making a corresponding risk map according to the policy and the policy information includes:
Acquiring a policy corresponding to the insurance type, various policy information corresponding to the policy and geographic information of the geographic area;
carrying out geographical region classification on the policy according to the geographical information to obtain a geographical region classification result;
respectively inputting the various item of policy information into a preset risk prediction model according to the geographical region classification result to obtain a risk score of a policy corresponding to the geographical region, and judging whether the policy corresponding to the risk score is a risk policy according to whether the policy corresponding to the risk score is a risk policy or not;
counting the number of the risk orders, and calculating regional risk scores of the geographic regions according to the risk scores corresponding to the risk orders;
displaying the risk list quantity and the regional risk score on a map according to a preset display mode and the geographic information to obtain a risk map;
the step of respectively inputting the various item of policy information into a preset risk prediction model according to the geographical region classification result to obtain a risk score of a policy corresponding to the geographical region, and the step of judging whether the policy corresponding to the risk score is a risk policy according to whether the policy corresponding to the risk score is a risk policy or not comprises the following steps:
respectively inputting the various item of policy information into a preset risk prediction model according to the geographical region classification result to obtain corresponding risk coefficients of the various item of policy information;
Acquiring a single-item adjustment coefficient corresponding to each item of policy information;
the corresponding risk coefficients are adjusted through the single item adjustment coefficients, and single item risk scoring values of various item of policy information are obtained;
whether the policy corresponding to the single risk score value of each item of policy information is a risk policy or not is determined;
the step of determining whether the policy corresponding to the single grading value of each item of policy information is a risk policy includes:
obtaining the scoring weight of each item of policy information;
weighting and summing all the single scoring values according to the corresponding scoring weights to obtain risk scores;
judging whether the risk score is larger than a preset risk score threshold value or not;
if yes, determining the policy corresponding to the risk score as a risk policy;
the policy information includes quotation data, application data and wholesale data according to the underwriting process, the underwriting process of the policy is analyzed according to the policy information, and the process monitoring data are obtained by:
inputting the quotation data in the policy data into the risk prediction model, judging whether the quotation data which does not pass through the risk prediction model is determined to be in accordance with the fusion rule, and counting the quantity of the quotation data which does not meet the fusion rule;
The quotation data conforming to the fusion rule and the insurance data of the insurance policy data corresponding to the quotation data determined to pass through by the risk prediction model are input into the risk prediction model, whether the insurance data determined to not pass through by the risk prediction model conforms to the fusion rule or not is judged, and the quantity of the insurance data not conforming to the fusion rule is counted;
inputting the insurance data conforming to the fusing rules and the batch bill data of the insurance policy data corresponding to the insurance data determined by the risk prediction model as passing insurance data into the risk prediction model, judging whether the batch bill data determined by the risk prediction model as not passing batch bill data conforms to the fusing rules, and counting the quantity of batch bill data not conforming to the fusing rules;
the quotation data, the application data and the wholesale data which do not accord with the fusion rule are output as process monitoring data;
inputting the quotation data in the policy data into the risk prediction model, judging whether the quotation data which is determined to not pass by the risk prediction model accords with a fusion rule, and counting the quantity of the quotation data which does not accord with the fusion rule comprises the following steps:
inputting the quotation data into the risk prediction model to obtain a single risk scoring value of the quotation data;
If the single risk score value is larger than a preset single risk score threshold value, determining that the corresponding quotation data does not pass;
judging whether the quotation data which do not pass through the risk prediction model is in accordance with a fusion rule or not;
the number of quotation data in which the convergence rule is not met is counted.
2. The method for monitoring and controlling the security wind according to claim 1, further comprising, after determining a high-risk location among the security applications divided in the geographic area according to the risk score and the risk score, and pre-warning the high-risk location:
acquiring an insuring place name input by a user, and inquiring corresponding historical scoring data according to the insuring place name;
and drawing a risk score trend graph corresponding to the insuring place name according to the risk score and the historical score data.
3. The utility model provides a nuclear insurance wind accuse monitoring device which characterized in that, nuclear insurance wind accuse monitoring device includes:
the system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring a nuclear protection wind control monitoring instruction and a monitored insurance type input by a user and judging the monitoring type represented by the nuclear protection wind control monitoring instruction, wherein the monitoring type comprises result monitoring and process monitoring;
The map generation module is used for acquiring a policy corresponding to the insurance type and various policy information corresponding to the policy when the monitoring type is result monitoring, and making a corresponding risk map according to the policy and the policy information, wherein the risk map comprises risk single amounts and risk scores of various insurance applying places divided in a preset geographic area;
the early warning module is used for determining high-risk places in all the insurance applying places divided in the geographic area according to the risk single quantity and the risk score and carrying out early warning on the high-risk places;
the analysis module is used for analyzing the underwriting process of the policy according to the policy information to obtain process monitoring data when the monitoring type is process monitoring;
the sending module is used for sending the risk map or the process monitoring data to the user so as to enable the user to conduct nuclear security wind control analysis;
the map generation module comprises:
the data acquisition unit is used for acquiring the insurance policy corresponding to the insurance type, various insurance policy information corresponding to the insurance policy and geographic information of the geographic area;
the classification unit is used for classifying the geographic areas of the policy according to the geographic information to obtain a geographic area classification result;
The model input unit is used for respectively inputting the various item of policy information into a preset risk prediction model according to the geographical region classification result to obtain the risk score of the policy corresponding to the geographical region, and judging whether the policy corresponding to the risk score is a risk policy according to whether the policy corresponding to the risk score is a risk policy or not;
the statistics unit is used for counting the number of the risk orders and calculating regional risk scores of the geographic regions according to the risk scores corresponding to the risk orders;
the map display unit is used for displaying the number of the risk orders and the regional risk scores on a map according to a preset display mode and the geographic information to obtain a risk map;
the model input unit includes:
the risk coefficient subunit is used for respectively inputting the various item of policy information into a preset risk prediction model according to the geographical region classification result to obtain the corresponding coefficient of the various item of policy information;
the adjustment coefficient subunit is used for acquiring a single adjustment coefficient corresponding to each item of policy information;
the adjustment subunit is used for adjusting the corresponding risk coefficient through the single item adjustment coefficient to obtain a single item risk scoring value of each item of policy information;
The risk judging subunit is used for judging whether the policy corresponding to the single grading value of each item of policy information is a risk policy or not according to the fact;
the risk judging subunit is specifically configured to:
obtaining the scoring weight of each item of policy information;
weighting and summing all the single scoring values according to the corresponding scoring weights to obtain risk scores;
judging whether the risk score is larger than a preset risk score threshold value or not;
if yes, determining the policy corresponding to the risk score as a risk policy;
the analysis module is specifically used for:
inputting the quotation data in the policy data into the risk prediction model, judging whether the quotation data which does not pass through the risk prediction model is determined to be in accordance with the fusion rule, and counting the quantity of the quotation data which does not meet the fusion rule;
the quotation data conforming to the fusion rule and the insurance data of the insurance policy data corresponding to the quotation data determined to pass through by the risk prediction model are input into the risk prediction model, whether the insurance data determined to not pass through by the risk prediction model conforms to the fusion rule or not is judged, and the quantity of the insurance data not conforming to the fusion rule is counted;
Inputting the insurance data conforming to the fusing rules and the batch bill data of the insurance policy data corresponding to the insurance data determined by the risk prediction model as passing insurance data into the risk prediction model, judging whether the batch bill data determined by the risk prediction model as not passing batch bill data conforms to the fusing rules, and counting the quantity of batch bill data not conforming to the fusing rules;
the quotation data, the application data and the wholesale data which do not accord with the fusion rule are output as process monitoring data;
the analysis module is specifically further configured to:
inputting the quotation data into the risk prediction model to obtain a single risk scoring value of the quotation data;
if the single risk score value is larger than a preset single risk score threshold value, determining that the corresponding quotation data does not pass;
judging whether the quotation data which do not pass through the risk prediction model is in accordance with a fusion rule or not;
the number of quotation data in which the convergence rule is not met is counted.
4. The nuclear protection wind control monitoring device according to claim 3, further comprising a trend graph module, wherein the trend graph module is specifically configured to:
acquiring an insuring place name input by a user, and inquiring corresponding historical scoring data according to the insuring place name;
And drawing a risk score trend graph corresponding to the insuring place name according to the risk score and the historical score data.
5. A nuclear security wind control monitoring device, characterized in that the nuclear security wind control monitoring device comprises: a memory and at least one processor, the memory having instructions stored therein, the memory and the at least one processor being interconnected by a line;
the at least one processor invokes the instructions in the memory to cause the nuclear care wind control monitoring device to perform the nuclear care wind control monitoring method of claim 1 or claim 2.
6. A computer readable storage medium having a computer program stored thereon, wherein the computer program when executed by a processor implements the method of the core protection wind control monitoring of claim 1 or claim 2.
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