CN113344719A - Insurance user risk early warning monitoring system and monitoring method thereof - Google Patents
Insurance user risk early warning monitoring system and monitoring method thereof Download PDFInfo
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Abstract
An insurance user risk early warning monitoring method, the monitoring method comprises the following steps: randomly setting a plurality of time nodes in the valid period of the insurance product, and converting all the time nodes into binary character strings; 4 risk grade parameters are respectively arranged corresponding to each time node, wherein the risk grade parameters are sequentially arranged from small to large; multiplying the binary character string with the risk grade parameter in sequence to obtain a risk early warning monitoring image; establishing a coordinate system related to the time nodes and the risk level parameters, wherein the time nodes are used as horizontal coordinates, and the risk level parameters are used as vertical coordinates; setting a risk early warning monitoring image in a coordinate system; establishing an evaluation curve related to the time node and the risk level parameter in a coordinate system; the assessment curve divides the risk early warning monitoring image into a safe area and a dangerous area; detecting actual risk level parameters of the insurance product; and observing the position of the coordinate point to perform early warning monitoring evaluation on the risk of the insurance product.
Description
The technical field is as follows:
the invention relates to a risk early warning monitoring system for an insurance user and a monitoring method thereof.
Background art:
the insurance industry refers to the industry that collects the funds in the form of contracts to compensate the economic benefits business of the insured. The insurance market is a place where insurance is bought or sold, i.e., where both parties enter into an insurance contract. It may be a centralized tangible market or a decentralized intangible market.
The organization form of insurance industry can be divided into the following four types according to the different operation bodies: 1. the national operation insurance organization, also called as public insurance, refers to the insurance organization operated by the country, local government or other public groups; 2. the company operates insurance organization, belongs to one of the people's operation insurance organization. According to the form of responsibility, the companies include the forms of a company with limited responsibility, a company with limited shares, an unlimited company, and the like. The stockpile insurance company organization has the characteristics of flexible operation and high business efficiency, but because the control right of the company is controlled in stockholders, the rights and interests of an insured are easily limited and ignored, and thus the company operation insurance organization is supervised and managed by each country legislation; 3. an insurance cooperative organization belongs to a non-company type of people in the operation and insurance, and is an organization which is commonly organized by people or units needing insurance guarantee in the society and processes insurance business in a cooperative mode. There are forms of mutual insurance cooperative, mutual insurance company, insurance cooperative, etc.; 4. the individual operation insurance form, the individual underwriting insurance business is developed through the organization of the labour society; according to the rules of the original 'temporary regulations on the management of insurance enterprises' in China, the organization system of the insurance industry in China is composed of the national insurance administrative department, the Chinese people insurance company, other insurance enterprises and the rural cooperative insurance society of mutual assistance.
Under general conditions, after purchasing a corresponding insurance product, an insurance user needs to pay a premium according to a certain time period to ensure the effectiveness of the insurance product, any insurance product has certain loss risk within the validity period due to the variability of the market, and in order to ensure the rights and interests of the insurance user, the risk possibly occurring in the insurance product needs to be evaluated and early warned in advance; in the existing mode, an insurance manager carries out manual operation to avoid corresponding risks, the response speed is slow, and certain hysteresis is inevitable, so that potential user risks cannot be completely avoided, and the loss of benefits of insurance users is caused; meanwhile, as the types and the number of insurance products are more, the real-time monitoring and early warning of the insurance products one by one in a manual recording mode are unrealistic.
The invention content is as follows:
the embodiment of the invention provides a risk early warning monitoring system and a monitoring method thereof for insurance users, the structure and the method are reasonable in design, based on the mutual cooperation of a plurality of functional modules in the system, and by combining a plurality of mathematical models and operation methods, the risk early warning monitoring system can carry out early warning monitoring on the insurance products within the valid period of the insurance products, carry out early evaluation and early warning on the possible risks of the insurance products at the first time, improve the response speed, and avoid the generated hysteresis as far as possible, thereby eliminating the corresponding risks for the insurance users, effectively protecting the benefits of the insurance users, and solving the problems in the prior art.
The technical scheme adopted by the invention for solving the technical problems is as follows:
an insurance user risk early warning monitoring method, the monitoring method comprises the following steps:
s1, randomly setting a plurality of time nodes in the validity period of the insurance product, namely a time node A, a time node B, a time node C and a time node D, converting all the time nodes into binary character strings and recording the binary character strings as a, B, C and D respectively;
s2, 4 risk level parameters R (e, f, g, h) are respectively arranged corresponding to each time node, wherein the risk level parameters are sequentially arranged from small to large;
s3, multiplying the binary character strings a, b, c and d with the risk grade parameters R (e, f, g and h) in sequence to obtain a 4 x 4 risk early warning monitoring image;
s4, establishing a coordinate system related to the time nodes and the risk level parameters, wherein the time nodes are used as horizontal coordinates, and the risk level parameters are used as vertical coordinates;
s5, setting the risk early warning monitoring image in a coordinate system;
s6, establishing a node with respect to time in a coordinate systemAnd the evaluation curve R-Qe of the risk level parametert+St2Q is a first proportionality coefficient, S is a second proportionality coefficient, the magnitude order of S is larger than that of Q, and t is the remaining effective time of the insurance product;
s7, dividing the risk early warning monitoring image into a safety area and a dangerous area by the evaluation curve;
s8, detecting the actual risk grade parameters of the insurance products in a time node A, a time node B, a time node C and a time node D respectively, and converting the actual risk parameters into coordinate points to be recorded in a coordinate system;
and S9, observing the position of the coordinate point to perform early warning monitoring evaluation on the risk of the insurance product.
The binary string is 8 bits.
The risk rating parameter R (e, f, g, h) Klnt2+ θ, where K is the risk ratio, t is the remaining effective time of the insurance product, and θ is the correction.
The correction quantity theta being Euler constant Sn
Wherein n is the specific number of risk level parameters.
The position of the coordinate point is observed to carry out early warning monitoring evaluation on the risk of the insurance product, and the method comprises the following steps:
s9.1, when the coordinate point corresponding to the actual risk level parameter is in the safe area, the insurance product is in a forward development stage;
s9.2, when the coordinate point corresponding to the actual risk level parameter is in a dangerous area, indicating that the insurance product is in a negative development stage;
and S9.3, when the coordinate point corresponding to the actual risk level parameter is not in the risk early warning monitoring image, indicating that the acquired data has a large error, and repeating the step S8 to acquire the coordinate point.
The area of the safe area is larger than the area of the dangerous area.
Insurance user risk early warning monitored control system, monitored control system includes:
the time node setting module is used for randomly setting a plurality of time nodes, namely a time node A, a time node B, a time node C and a time node D, within the validity period of the insurance product, converting all the time nodes into binary character strings and recording the binary character strings as a, B, C and D respectively;
a risk level setting module, which is used for setting 4 risk level parameters R (e, f, g, h) corresponding to each time node;
the operation module is used for sequentially multiplying the binary character strings a, b, c and d with the risk grade parameters R (e, f, g and h) to obtain a 4 x 4 risk early warning monitoring image;
a modeling module for establishing a coordinate system and an evaluation curve with respect to time nodes and risk level parameters;
and the evaluation detection module is used for respectively detecting the actual risk grade parameters of the insurance products in the time node A, the time node B, the time node C and the time node D, converting the actual risk parameters into coordinate points, recording the coordinate points in a coordinate system, and observing the positions of the coordinate points so as to perform early warning monitoring evaluation on the risks of the insurance products.
The modeling module comprises a coordinate system modeling module and an evaluation curve modeling module.
By adopting the structure, a plurality of time nodes are set at will within the validity period of the insurance product through the time node setting module, and all the time nodes are converted into binary character strings; 4 risk grade parameters are respectively set corresponding to each time node through a risk grade setting module; the binary character string and the risk grade parameter are multiplied in sequence through the operation module to obtain an integral risk early warning monitoring image, so that later-stage detection and evaluation are more intuitively facilitated; establishing a coordinate system and an evaluation curve about the time node and the risk level parameter through a modeling module; the actual risk grade parameters of the insurance products are detected in the time node A, the time node B, the time node C and the time node D through the evaluation detection module respectively, the actual risk parameters are converted into coordinate points to be recorded in a coordinate system, the positions of the coordinate points are observed, the risks of the insurance products are subjected to early warning monitoring evaluation, and the safety insurance product early warning system has the advantages of high efficiency, practicability and sensitive response.
Description of the drawings:
FIG. 1 is a schematic structural diagram of the present invention.
FIG. 2 is a schematic diagram of the structure of the modeling module of the present invention.
FIG. 3 is a schematic flow chart of the present invention.
Fig. 4 is a schematic structural diagram of a coordinate system according to the present invention.
The specific implementation mode is as follows:
in order to clearly explain the technical features of the present invention, the following detailed description of the present invention is provided with reference to the accompanying drawings.
As shown in fig. 1-4, an insurance user risk early warning monitoring method, the monitoring method comprising the steps of:
s1, randomly setting a plurality of time nodes in the validity period of the insurance product, namely a time node A, a time node B, a time node C and a time node D, converting all the time nodes into binary character strings and recording the binary character strings as a, B, C and D respectively;
s2, 4 risk level parameters R (e, f, g, h) are respectively arranged corresponding to each time node, wherein the risk level parameters are sequentially arranged from small to large;
s3, multiplying the binary character strings a, b, c and d with the risk grade parameters R (e, f, g and h) in sequence to obtain a 4 x 4 risk early warning monitoring image;
s4, establishing a coordinate system related to the time nodes and the risk level parameters, wherein the time nodes are used as horizontal coordinates, and the risk level parameters are used as vertical coordinates;
s5, setting the risk early warning monitoring image in a coordinate system;
s6, establishing an evaluation curve R-Qe with respect to the time node and the risk level parameter in the coordinate systemt+St2Q is a first proportionality coefficient, S is a second proportionality coefficient, the magnitude order of S is larger than that of Q, and t is the remaining effective time of the insurance product;
s7, dividing the risk early warning monitoring image into a safety area and a dangerous area by the evaluation curve;
s8, detecting the actual risk grade parameters of the insurance products in a time node A, a time node B, a time node C and a time node D respectively, and converting the actual risk parameters into coordinate points to be recorded in a coordinate system;
and S9, observing the position of the coordinate point to perform early warning monitoring evaluation on the risk of the insurance product.
The binary string is 8 bits.
The risk rating parameter R (e, f, g, h) Klnt2+ θ, where K is the risk ratio, t is the remaining effective time of the insurance product, and θ is the correction.
The correction quantity theta being Euler constant Sn
Wherein n is the specific number of risk level parameters.
The position of the coordinate point is observed to carry out early warning monitoring evaluation on the risk of the insurance product, and the method comprises the following steps:
s9.1, when the coordinate point corresponding to the actual risk level parameter is in the safe area, the insurance product is in a forward development stage;
s9.2, when the coordinate point corresponding to the actual risk level parameter is in a dangerous area, indicating that the insurance product is in a negative development stage;
and S9.3, when the coordinate point corresponding to the actual risk level parameter is not in the risk early warning monitoring image, indicating that the acquired data has a large error, and repeating the step S8 to acquire the coordinate point.
The area of the safe area is larger than the area of the dangerous area.
Insurance user risk early warning monitored control system, monitored control system includes:
the time node setting module is used for randomly setting a plurality of time nodes, namely a time node A, a time node B, a time node C and a time node D, within the validity period of the insurance product, converting all the time nodes into binary character strings and recording the binary character strings as a, B, C and D respectively;
a risk level setting module, which is used for setting 4 risk level parameters R (e, f, g, h) corresponding to each time node;
the operation module is used for sequentially multiplying the binary character strings a, b, c and d with the risk grade parameters R (e, f, g and h) to obtain a 4 x 4 risk early warning monitoring image;
a modeling module for establishing a coordinate system and an evaluation curve with respect to time nodes and risk level parameters;
and the evaluation detection module is used for respectively detecting the actual risk grade parameters of the insurance products in the time node A, the time node B, the time node C and the time node D, converting the actual risk parameters into coordinate points, recording the coordinate points in a coordinate system, and observing the positions of the coordinate points so as to perform early warning monitoring evaluation on the risks of the insurance products.
The modeling module comprises a coordinate system modeling module and an evaluation curve modeling module.
The working principle of the insurance user risk early warning monitoring system and the monitoring method thereof in the embodiment of the invention is as follows: based on the mutual cooperation of a plurality of functional modules in the system, the system combines a plurality of mathematical models and operation methods, can carry out early warning monitoring to insurance products in the life of insurance products, and the risk that probably appears to insurance products is assessed and early warned in advance the very first time, promotes response speed, avoids the hysteresis quality of production as far as possible to eliminate corresponding risk for insurance users, effectively protect insurance users' interests, can be applicable to multiple different insurance products.
In the whole scheme, the early warning monitoring system comprises a time node setting module, a risk level setting module, an operation module, a modeling module and an evaluation detection module; specifically, the time node setting module is used for arbitrarily setting a plurality of time nodes within the validity period of the insurance product, and converting all the time nodes into binary character strings, wherein generally, the number of the time nodes is 4, and the number of bits of the binary character strings is 8, so that the operation is convenient; the risk level setting module is used for respectively setting 4 risk level parameters R (e, f, g, h) corresponding to each time node; the operation module is used for multiplying the binary character strings a, b, c and d with the risk grade parameters R (e, f, g and h) in sequence to obtain a 4 x 4 risk early warning monitoring image; the modeling module is used for establishing a coordinate system and an evaluation curve of the time node and the risk level parameters; the evaluation detection module is used for respectively detecting the actual risk grade parameters of the insurance products in the time node A, the time node B, the time node C and the time node D, converting the actual risk parameters into coordinate points and recording the coordinate points in a coordinate system, and performing early warning monitoring on the insurance products in the valid period of the insurance products through the mutual cooperation of the functional modules, and performing early warning on the risks possibly appearing in the insurance products at the first time to protect the rights and interests of insurance users.
Preferably, the modeling module comprises a coordinate system modeling module and an evaluation curve modeling module, corresponding mathematical models are respectively established, interference cannot occur between the mathematical models, and modeling accuracy is guaranteed.
The early warning monitoring method mainly comprises the following steps: randomly setting a plurality of time nodes in the validity period of an insurance product, namely a time node A, a time node B, a time node C and a time node D, converting all the time nodes into binary character strings, and recording the binary character strings as a, B, C and D; 4 risk grade parameters R (e, f, g, h) are respectively arranged corresponding to each time node, wherein the risk grade parameters are sequentially arranged from small to large; multiplying the binary character strings a, b, c and d with risk grade parameters R (e, f, g and h) in sequence to obtain a 4 x 4 risk early warning monitoring image; establishing a coordinate system related to the time nodes and the risk level parameters, wherein the time nodes are used as horizontal coordinates, and the risk level parameters are used as vertical coordinates; setting a risk early warning monitoring image in a coordinate system; setting a risk early warning monitoring image in a coordinate system; the assessment curve divides the risk early warning monitoring image into a safe area and a dangerous area; respectively detecting actual risk grade parameters of insurance products in a time node A, a time node B, a time node C and a time node D, and converting the actual risk parameters into coordinate points to be recorded in a coordinate system; and observing the position of the coordinate point to perform early warning monitoring evaluation on the risk of the insurance product.
Preferably, the specific early warning monitoring evaluation process comprises the following steps: when the coordinate point corresponding to the actual risk level parameter is in the safe area, the insurance product is in the forward development stage; when the coordinate point corresponding to the actual risk grade parameter is in a dangerous area, the insurance product is in a negative development stage; when the coordinate point corresponding to the actual risk level parameter is not in the risk early warning monitoring image, it indicates that a large error exists in the acquired data, and the steps need to be repeated to acquire the coordinate point again.
Specifically, in the risk early warning monitoring image, the area of the safe area is larger than that of the dangerous area.
Preferably, the risk ranking parameter R (e, f, g, h) Klnt2+ theta, where K is the risk ratio, t is the remaining effective time of the insurance product, theta is the correction amount, and is the euler constant, set according to the specific number of risk level parameters.
Preferably, the evaluation curve R ═ Qe for the time nodes and the risk level parameterst+St2Q is a first proportionality coefficient, S is a second proportionality coefficient, the magnitude order of S is larger than that of Q, and t is the remaining effective time of the insurance product; the whole risk early warning monitoring image is divided into two parts, so that the risk early warning condition of the insurance product can be read more vividly and visually.
Generally, all detected coordinate points fall into the risk early warning monitoring image, when some points appear outside, errors generated in the acquisition process can be basically determined, corresponding discussion and operation are not needed, and meanwhile, new coordinate points are determined again and calculated again.
The number of the time nodes, the number of the risk level parameters and the number of bits of the binary character string can be modified and called through a background database.
In summary, the insurance user risk early warning monitoring system and the monitoring method thereof in the embodiment of the invention can perform early warning monitoring on the insurance product within the valid period of the insurance product based on the mutual cooperation of a plurality of functional modules in the system and by combining a plurality of mathematical models and operation methods, perform early evaluation and early warning on the possible risks of the insurance product at the first time, improve the response speed, and avoid the generated hysteresis as much as possible, thereby eliminating the corresponding risks for the insurance user, effectively protecting the benefits of the insurance user, and being applicable to a plurality of different insurance products and application scenes.
The above-described embodiments should not be construed as limiting the scope of the invention, and any alternative modifications or alterations to the embodiments of the present invention will be apparent to those skilled in the art.
The present invention is not described in detail, but is known to those skilled in the art.
Claims (8)
1. An insurance user risk early warning monitoring method is characterized by comprising the following steps:
s1, randomly setting a plurality of time nodes in the validity period of the insurance product, namely a time node A, a time node B, a time node C and a time node D, converting all the time nodes into binary character strings and recording the binary character strings as a, B, C and D respectively;
s2, 4 risk level parameters R (e, f, g, h) are respectively arranged corresponding to each time node, wherein the risk level parameters are sequentially arranged from small to large;
s3, multiplying the binary character strings a, b, c and d with the risk grade parameters R (e, f, g and h) in sequence to obtain a 4 x 4 risk early warning monitoring image;
s4, establishing a coordinate system related to the time nodes and the risk level parameters, wherein the time nodes are used as horizontal coordinates, and the risk level parameters are used as vertical coordinates;
s5, setting the risk early warning monitoring image in a coordinate system;
s6, establishing an evaluation curve R-Qe with respect to the time node and the risk level parameter in the coordinate systemt+St2Q is a first proportionality coefficient, S is a second proportionality coefficient, the magnitude order of S is larger than that of Q, and t is the remaining effective time of the insurance product;
s7, dividing the risk early warning monitoring image into a safety area and a dangerous area by the evaluation curve;
s8, detecting the actual risk grade parameters of the insurance products in a time node A, a time node B, a time node C and a time node D respectively, and converting the actual risk parameters into coordinate points to be recorded in a coordinate system;
and S9, observing the position of the coordinate point to perform early warning monitoring evaluation on the risk of the insurance product.
2. The insurance user risk early warning monitoring method according to claim 1, characterized in that: the binary string is 8 bits.
3. The insurance user risk early warning monitoring method according to claim 1, characterized in that: the risk rating parameter R (e, f, g, h) Klnt2+ θ, where K is the risk ratio, t is the remaining effective time of the insurance product, and θ is the correction.
4. The insurance user risk early warning monitoring method according to claim 3, characterized in that: the correction quantity theta being Euler constant Sn
Wherein n is the specific number of risk level parameters.
5. The insurance user risk early warning monitoring method according to claim 1, wherein observing the position of the coordinate point to perform early warning monitoring evaluation on the risk of the insurance product comprises the following steps:
s9.1, when the coordinate point corresponding to the actual risk level parameter is in the safe area, the insurance product is in a forward development stage;
s9.2, when the coordinate point corresponding to the actual risk level parameter is in a dangerous area, indicating that the insurance product is in a negative development stage;
and S9.3, when the coordinate point corresponding to the actual risk level parameter is not in the risk early warning monitoring image, indicating that the acquired data has a large error, and repeating the step S8 to acquire the coordinate point.
6. The insurance user risk early warning monitoring method according to claim 1, characterized in that: the area of the safe area is larger than the area of the dangerous area.
7. Insurance user risk early warning monitored control system, its characterized in that, monitored control system includes:
the time node setting module is used for randomly setting a plurality of time nodes, namely a time node A, a time node B, a time node C and a time node D, within the validity period of the insurance product, converting all the time nodes into binary character strings and recording the binary character strings as a, B, C and D respectively;
a risk level setting module, which is used for setting 4 risk level parameters R (e, f, g, h) corresponding to each time node;
the operation module is used for sequentially multiplying the binary character strings a, b, c and d with the risk grade parameters R (e, f, g and h) to obtain a 4 x 4 risk early warning monitoring image;
a modeling module for establishing a coordinate system and an evaluation curve with respect to time nodes and risk level parameters;
and the evaluation detection module is used for respectively detecting the actual risk grade parameters of the insurance products in the time node A, the time node B, the time node C and the time node D, converting the actual risk parameters into coordinate points, recording the coordinate points in a coordinate system, and observing the positions of the coordinate points so as to perform early warning monitoring evaluation on the risks of the insurance products.
8. The insurance user risk early warning monitoring system of claim 7, wherein: the modeling module comprises a coordinate system modeling module and an evaluation curve modeling module.
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