TWI645358B - Risk identification insurance recommendation and policy valuation method - Google Patents

Abstract

A risk identification insurance recommendation and a policy evaluation method are implemented by a server connected to a user terminal via a communication network, the method comprising: the server receiving a target information related to a target object And obtaining a plurality of risk assessment levels respectively corresponding to the plurality of different disaster categories; the server determines whether there is at least one first risk assessment level in the risk assessment levels; and when the at least one first risk assessment level exists, the The server generates and transmits at least one first recommended insurance item corresponding to the disaster type corresponding to the at least one first risk assessment level to the use end; the server obtains the at least one first recommendation according to the input signal of the use end The premium rate corresponding to at least one of the insured items to be insured.

Description

Risk identification insurance recommendation and policy valuation method

The present invention relates to a method for obtaining a proposed policy and its premium, and more particularly to a risk identification insurance recommendation and a policy valuation method.

As Taiwan is in the earthquake zone and the discussion on soil liquefaction in recent years, consumers are paying more and more attention to the safety of buildings and the protection of "outside the building". Therefore, the insurers are also rushing to promote various types of insurance related to the subject matter, in an attempt to incorporate the important elements of human life into the category of insurance products.

However, at present, the insurance business service personnel must conduct a risk assessment on the surrounding environment of the subject matter of the evaluation (that is, the entire building to be purchased or insured) before recommending and quoting the consumer, and then based on the risk assessment result. The corresponding insured items and their insured amount are recommended. However, the existing risk assessment methods often require the surveying engineer to go to the target site to conduct the survey and produce the risk assessment report of the subject matter. The insurance business service personnel will insure the required risk according to the risk assessment report. The project is recommended to consumers. This kind of quotation method consumes a lot of time and human resources, which is inconvenient, so it is necessary to propose a solution.

Accordingly, it is an object of the present invention to provide an insurance claim and a policy valuation method by providing a plurality of insurance items and their premium rates that are automatically associated with a subject matter, thereby effectively saving time and manpower risks.

Therefore, the risk identification insurance recommendation and the policy evaluation method of the present invention are implemented by a server, and the server is connected to a user terminal via a communication network, and the server stores a disaster rate adjustment table, and the risk identification is insured. The proposal and policy valuation method includes a step (A), a step (B), a step (C), and a step (D).

The step (A) is that, after receiving the information of the target object from the use end and related to a target object, the server obtains a plurality of objects related to the target target and respectively corresponding to the plurality of different objects. The level of risk assessment for the type of disaster.

The step (B) is to determine, by the server, whether at least one first risk assessment level located in a first risk range exists in the risk assessment levels.

The step (C) is: when the server determines that the at least one first risk assessment level exists, the server generates and transmits at least one corresponding to the disaster type corresponding to the at least one first risk assessment level. The first recommended insurance item of the disaster category corresponding to the at least one first risk assessment level is to be used.

The step (D) is, by the server, after receiving a query request from the user terminal and related to at least one item to be insured in the at least one first recommended insurance item, for each item to be insured, The premium rate associated with the item to be insured is obtained based on at least the risk assessment level of the disaster type corresponding to the insured item and the disaster rate adjustment table.

The effect of the invention is that: the risk assessment of the target object is automatically performed, and according to the stored disaster rate adjustment table, the insurance item recommended by the server for the target object is automatically obtained, and finally, according to The user's choice obtains the premium rate corresponding to the item that the user wants to insure, thereby effectively saving time and manpower.

Referring to FIG. 1, an embodiment of a system 100 for implementing the risk identification insurance recommendation and the policy evaluation method of the present invention includes a server 1 and a user terminal connected to the server 1 via a communication network 101. 2.

The server 1 includes a server communication module 11 connected to the communication network 101, a server storage module 12, and a servo terminal for electrically connecting the server communication module 11 and the server storage module 12. Module 13.

The server storage module 12 of the server 1 stores a disaster rate adjustment table, a construction rate adjustment table, multiple risk assessment materials respectively corresponding to a plurality of objects, and multiple strokes corresponding to different types of Information on the disaster attribute of the disaster attribute.

Referring to Table 1 below, the disaster rate adjustment table includes a plurality of disaster weight coefficients respectively corresponding to multiple levels. It is worth noting that these levels and their disaster weighting factors can be freely modified by those with ordinary knowledge in the field to achieve the efficacy of the present invention, and therefore are not limited thereto. Table 1  <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td> level</td><td> 1 </td><td> 2 </td> <td> 3 </td><td> 4 </td><td> 5 </td></tr><tr><td> Disaster weight coefficient </td><td> 0.7 </td>< Td> 0.85 </td><td> 1 </td><td> 1.15 </td><td> 1.3 </td></tr></TBODY></TABLE>

Referring to Table 2 below, the construction rate adjustment table includes a plurality of building weight coefficients respectively corresponding to a plurality of building structures. In this embodiment, the structures include a reinforced concrete, a steel reinforced cement, a reinforced brick, a ferrule, and a wood, but are not limited thereto. It is worth noting that the construction structure and its construction weight coefficient can be freely modified by the general knowledge in the field to achieve the effect of the present invention, and therefore is not limited thereto. Table 2  <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td> building structure</td><td> reinforced concrete</td><td> steel cement </td><td> Strengthening brickwork</td><td> Iron sheet</td><td> Wood making</td></tr><tr><td> Building weight coefficient</td><td> 0.3 </td><td> 0.7 </td><td> 1 </td><td> 1.2 </td><td> 1.5 </td></tr></TBODY></TABLE>

Each risk assessment data includes a plurality of risk values for a plurality of risk factors corresponding to each of the consistent disaster attributes. Each risk factor can be classified into one of a likelihood factor and a scale factor. In this embodiment, the disaster-causing attributes include an active fault, an earthquake, a soil flow, a landslide, a flood, and a soil liquefaction, but not limited thereto.

Referring to Table 3 below, the risk assessment data respectively correspond to, for example, a latitude and longitude A, a latitude and longitude B, and a latitude and longitude latitude and longitude. For the disaster attribute belonging to the active fault, the risk assessment data includes a scale 6.5 earthquake. The probability, the distance from the fault line, and the risk factor of a fault upper and lower disk, wherein the probability of occurrence of the scale 6.5 earthquake is classified as the likelihood factor, and the distance from the fault line and the fault The magnification is classified into the scale factor. In addition, each risk factor corresponding to the latitude and longitude of each target (eg, latitude and longitude A, latitude and longitude B, and longitude and latitude C) (eg, the probability of occurrence of a scale 6.5 earthquake, the distance from the fault line, The risk values of the fault and the upper and lower disk magnifications are exemplified in Table 3 below, but are not limited thereto. It should be particularly noted that the present embodiment only exemplifies the risk assessment data corresponding to the latitude and longitude A, the latitude and longitude B, and the latitude and longitude C. However, the risk assessment data also includes more latitude and longitude of the target. The risk assessment data includes the latitude and longitude of the target, and in other embodiments, the risk assessment data may further include related to the latitude and longitude of the three objects as exemplified in the embodiment. The name or keyword of the object of the latitude and longitude of the object is such that the user operating the terminal 2 more intuitively searches for the desired object information, but not limited thereto. table 3  <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td> active fault</td></tr><tr><td> risk factor target latitude and longitude </td><td> probability factor</td><td> scale factor</td></tr><tr><td> probability of occurrence of scale 6.5 earthquake</td><td> and fault line Distance </td><td> Fault upper and lower disk magnification</td></tr><tr><td> Longitude and latitude A </td><td> 15% </td><td> 900m </td>< Td> upper plate</td></tr><tr><td> latitude and longitude B </td><td> 25% </td><td> 400m </td><td> upper plate</td> </tr><tr><td> Latitude and longitude C </td><td> 35% </td><td> 70m </td><td> Lower plate</td></tr></TBODY> </TABLE>

Refer to Table 4 below. For the disaster attribute belonging to the earthquake, the risk assessment data includes two peak risk factors: a peak surface acceleration and a shear wave velocity under the surface. The peak surface acceleration is classified as the probability. Factor, and the shear wave velocity under the surface is classified as the scale factor. In addition, each target latitude and longitude (eg, latitude and longitude A, latitude and longitude B, and latitude and longitude C) corresponds to each risk factor (eg, peak surface acceleration, and The risk values of the shear wave velocity under the surface are exemplified in Table 4 below, but are not limited thereto. Table 4  <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td> Earthquake</td></tr><tr><td> Risk factor latitude and longitude < /td><td> likelihood factor</td><td> scale factor</td></tr><tr><td> peak surface acceleration</td><td> shear wave velocity below the surface</ Td></tr><tr><td> Latitude and longitude A </td><td> 0.2g </td><td> 350m/s </td></tr><tr><td> Longitude and latitude B < /td><td> 0.32g </td><td> 450m/s </td></tr><tr><td> Latitude and longitude C </td><td> 0.22g </td><td> 550m/s </td></tr></TBODY></TABLE>

Refer to Table 5 below. For the disaster attribute belonging to the earth-rock flow, the risk assessment data also includes a risk potential level of the earth-rock flow potential stream, a baseline value of the earth-rock flow warning, a distance of the earth-rock flow potential stream, and the influence of a earth-rock flow potential stream. Four risk factors, such as the range distance, wherein the earth-rock flow potential risk potential level and the earth-rock flow warning reference value are classified as the possibility factor, and the distance between the earth-rock flow potential stream and the influence of the earth-rock flow potential stream is Classified as the scale factor. In addition, each target latitude and longitude (eg, latitude and longitude A, latitude and longitude B, and longitude and latitude C) corresponds to each risk factor (eg: earth-rock flow potential stream risk potential level, earth-rock flow warning reference value, earth-rock flow dive The risk values of the potential flow distance and the distance between the influence of the earth and rock flow potential are shown in Table 5 below, but not limited thereto. table 5  <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td> Earth and Stone Flow</td></tr><tr><td> Risk Factor latitude and longitude < /td><td> probability factor</td><td> scale factor</td></tr><tr><td> earth-rock flow potential stream potential level</td><td> earth-rock flow warning benchmark Value </td><td> Earth-rock flow potential stream </td><td> Earth-rock flow potential stream distance range </td></tr><tr><td> Longitude and latitude A </td><td> Medium </td><td> 480mm </td><td> 35m </td><td> 7% </td></tr><tr><td> latitude and longitude B </td><td> low </td><td> 900mm </td><td> 15m </td><td> 13% </td></tr><tr><td> Longitude and latitude C </td><td> Continuous observation </td><td> 350mm </td><td> 28m </td><td> 17% </td></tr></TBODY></TABLE>

Refer to Table 6 below. For the disaster attribute belonging to the landslide, the risk assessment data also includes a landslide potential, a maximum 24-hour cumulative rainfall during a return period, the peak surface acceleration, a landslide type, and a landslide area. And a risk factor such as a landslide distance, wherein the landslide potential, the maximum 24-hour accumulated rainfall during the return period, and the peak surface acceleration are classified as the likelihood factor, and the landslide type, the landslide The area, and the distance from the landslide are classified as the scale factor. In addition, each target latitude and longitude (eg, latitude and longitude A, latitude and longitude B, and longitude and latitude C) corresponds to each risk factor (eg, landslide potential, maximum return period) The risk values for twenty-four hours of accumulated rainfall, surface spike acceleration, landslide type, landslide area, and landslide distance are illustrated in Table 6 below, but are not limited thereto. Table 6  <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td> landslide</td></tr><tr><td> risk factor target latitude and longitude < /td><td> likelihood factor</td><td> scale factor</td></tr><tr><td> landslide potential</td><td> maximum twenty-four hour return period Cumulative rainfall</td><td> surface peak acceleration</td><td> landslide type</td><td> landslide area</td><td> and landslide distance</td></tr><tr ><td> latitude and longitude A </td><td> </td><td> 440 mm </td><td> 0.5g </td><td> lithic chipping slip</td><td > 0.7 hectares</td><td> 0.7H </td></tr><tr><td> latitude and longitude B </td><td> </td><td> 480 mm</td> <td> 0.32g </td><td> Rock chip collapse</td><td> 0.85 hectare</td><td> 0.45H </td></tr><tr><td> latitude and longitude C </td><td> low </td><td> 650 mm</td><td> 0.22g </td><td> lithic chipping slip</td><td> 1.2 hectares</td ><td> 0.75H </td></tr></TBODY></TABLE>

Refer to Table 7 below. For the disaster attribute belonging to the flooding, the risk assessment data also includes a warning rainfall value and a flooding depth. The warning rainfall value is classified as the likelihood factor. The flooding depth is classified as the scale factor. In addition, each target latitude and longitude (eg, latitude and longitude A, latitude and longitude B, and longitude and latitude C) corresponds to each risk factor (eg, warning rainfall value, and flooding depth). The risk values are exemplified in Table 7 below, but are not limited thereto. Table 7  <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td> Flooding</td></tr><tr><td> Risk factor target latitude and longitude </td><td> likelihood factor</td><td> scale factor</td></tr><tr><td> warning rainfall value</td><td> flooding depth</td> </tr><tr><td> latitude and longitude A </td><td> 550 </td><td> 0m </td></tr><tr><td> latitude and longitude B </td><td > 490 </td><td> 0.3m </td></tr><tr><td> Latitude and longitude C </td><td> 290 </td><td> 1.2m </td></ Tr></TBODY></TABLE>

Refer to Table 8 below. For the disaster attribute belonging to the soil liquefaction, the risk assessment data also includes four kinds of risk factors: the peak acceleration, a groundwater depth, an elevation, and a stratum. The surface peak acceleration and The groundwater level depth is classified into the probability factor, and the elevation is classified into the scale factor, and in addition, each target latitude and longitude (eg, latitude and longitude A, latitude and longitude B, and longitude and latitude C) corresponds to each risk factor. The risk values for (eg, surface peak acceleration, groundwater depth, elevation, and formation) are shown in Table 8 below, but are not limited thereto. Table 8  <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td> Soil liquefaction</td></tr><tr><td> Risk factor target latitude and longitude </td><td> likelihood factor</td><td> scale factor</td></tr><tr><td> surface peak acceleration</td><td> groundwater level depth</td> <td> elevation </td><td> stratum</td></tr><tr><td> latitude and longitude A </td><td> 0.5g </td><td> within 20m from the surface </ Td><td> 25m </td><td> terrace layer </td></tr><tr><td> latitude and longitude B </td><td> 0.32g </td><td> Within 20m of the surface </td><td> 55m </td><td> Other </td></tr><tr><td> Longitude and latitude C </td><td> 0.22g </td><td > More than 20m from the surface </td><td> 112m </td><td> Terrace layer </td></tr></TBODY></TABLE>

In this embodiment, the disaster-tolerant attribute information respectively corresponds to the disaster-causing attribute, and each of the consistent disaster attribute information includes a risk level score table and a risk degree classification conversion rule.

The disaster attribute information includes an activity fault information, an earthquake information, a soil flow information, a landslide information, a flooding information, and a soil liquefaction information, but not limited thereto.

The risk level score table corresponding to each consistent disaster attribute includes the risk factors corresponding to the corresponding disaster-causing attributes, the plurality of hierarchical steps corresponding to each risk factor, and the level corresponding to each hierarchical level Distance score.

The hazard grading conversion rule corresponding to each consistent disaster attribute includes a likelihood factor formula, a scale factor formula, and a conversion matrix having a plurality of likelihood factor intervals, a plurality of scale factor intervals, and each A likelihood factor step is a hazard level corresponding to each of the scale factor intervals.

Referring to Table 9 below, for the disaster attribute information corresponding to the disaster attribute belonging to the active fault, the risk level score table includes the probability F ₁ of the magnitude 6.5 earthquake, the distance M ₁ from the fault line, and the There are three risk factors such as the fault upper and lower disk magnification M ₂ , wherein the probability F _{1 of} the occurrence of the scale 6.5 earthquake is classified as the likelihood factor M ₁ , and the distance from the fault line and the upper and lower disk magnification M ₂ are classified as The scale factor, in addition, the rank ranks corresponding to each risk factor, and the rank scores corresponding to each graded pitch are exemplified in the following Table 9, but are not limited thereto. Table 9 <TABLE border="1"borderColor="#000000"width="85%"><TBODY><tr><td> active fault</td></tr><tr><td> factor category</td><td> Risk Factor</td><td>Number</td><td> Grading Spacing</td><td> Spacing Score</td></tr><tr><td> Possibility factor</td><td> probability of occurrence of scale 6.5 earthquake</td><td>F₁</td><td> 0%~10% </td><td > 20 </td></tr><tr><td> 10%~20% </td><td> 40 </td></tr><tr><td> 20%~30% </ Td><td> 60 </td></tr><tr><td>>30%</td><td> 100 </td></tr><tr><td> scale factor</td ><td> Distance from fault line</td><td>M₁</td><td><30m</td><td> 50 </td></tr><tr><td> 30~50m </td><td> 30 </td></tr><tr><td> 50~100m </td><td> 10 </td></tr><tr><td>>100m</td><td> 0 </td></tr><tr><td> Fault Upper and Lower Disk Magnification</td><td>M₂</td><td> Upper plate</td><td> 2 </td></tr><tr><td> Lower plate</td><td> 1 </td></tr></TBODY></TABLE>

For the disaster attribute information corresponding to the disaster attribute belonging to the active fault, the probability factor corresponding to the active fault is S _{1 =} F ₁ , and the scale factor corresponding to the active fault is S _{2 =} M ₁ × M ₂ The conversion matrix corresponding to the active fault is as shown in Table 10 below. In addition, each hazard level corresponding to each scale factor step is corresponding to a hazard level corresponding to each scale factor in the following Table 10, but not limited thereto. . Table 10 <TABLE border="1"borderColor="#000000"width="85%"><TBODY><tr><td> active fault conversion matrix</td><td> probability factor score (S<sub >1</sub>) </td></tr><tr><td> 80~100 </td><td> 50~80 </td><td> 0~50 </td></ Tr><tr><td> scale factor score (S₂) </td><td> 80~100 </td><td> 5 </td><td> 4 </ Td><td> 3 </td></tr><tr><td> 50~80 </td><td> 4 </td><td> 3 </td><td> 2 </td ></tr><tr><td> 0~50 </td><td> 3 </td><td> 2 </td><td> 1 </td></tr></TBODY></TABLE>

Refer to Table 11 below. For the disaster attribute information corresponding to the disaster attribute of the earthquake, the risk level score table includes the peak surface acceleration F ₂ and the shear wave velocity M ₃ under the surface. Wherein the peak surface acceleration F ₂ is classified as the likelihood factor, and the shear wave velocity M ₃ under the surface is classified as the scale factor, and further, each of the risk factors corresponds to the hierarchical step, And the step scores corresponding to each hierarchical step are exemplified in the following Table 11, but are not limited thereto. Table 11 <TABLE border="1"borderColor="#000000"width="85%"><TBODY><tr><td>Earthquake</td></tr><tr><td> Factor category</ Td><td> risk factor</td><td>number</td><td> hierarchical distance</td><td> level score</td></tr><tr><td> possible Sex factor </td><td> peak surface acceleration</td><td>F₂</td><td> 0~0.23g </td><td> 30 </td ></tr><tr><td> 0.23~0.33g </td><td> 40 </td></tr><tr><td> 0.33~0.48g </td><td> 60 </td></tr><tr><td> 0.48~0.66g </td><td> 80 </td></tr><tr><td>>0.66g</td><td> 100 </td></tr><tr><td> scale factor</td><td> shear wave velocity under the surface</td><td>M₃</td><Td> 0~180m/s </td><td> 100 </td></tr><tr><td> 180~300 m/s </td><td> 70 </td></tr ><tr><td> 300~500 m/s </td><td> 40 </td></tr><tr><td>>500 m/s </td><td> 0 </ Td></tr></TBODY></TABLE>

For the disaster attribute information corresponding to the disaster attribute of the earthquake, the probability factor formula corresponding to the earthquake is S _{3 =} F ₂ , and the scale factor formula corresponding to the earthquake is S _{4 =} M ₃ , and the earthquake corresponds to The conversion matrix is as shown in Table 12 below. In addition, a hazard level corresponding to each scale factor step relative to each scale factor step is illustrated in Table 12 below, but is not limited thereto. Table 12 <TABLE border="1"borderColor="#000000"width="85%"><TBODY><tr><td> Earthquake Conversion Matrix</td><td> Possibility Factor Rating (S₃)</td></tr><tr><td> 70~100 </td><td> 50~70 </td><td> 30~50 </td><td> 0~30 </td></tr><tr><td> Scale factor score (S₄) </td><td> 70~100 </td><td> 5 </td><td> 5 </td><td> 4 </td><td> 3 </td></tr><tr><td> 50~70 </td><td> 5 </ Td><td> 4 </td><td> 3 </td><td> 2 </td></tr><tr><td> 30~50 </td><td> 4 </td ><td> 3 </td><td> 2 </td><td> 1 </td></tr><tr><td> 0~30 </td><td> 3 </td><td> 2 </td><td> 1 </td><td> 1 </td></tr></TBODY></TABLE>

Referring to Table 13 below, for the disaster attribute information corresponding to the disaster attribute of the earth-rock flow, the risk level score table includes the earth-rock flow potential flow potential level F ₃ , the earth-rock flow warning reference value F ₄ , the earth-rock flow The potential stream distance M ₄ and the influence range of the earth-rock flow potential stream distance M ₅ are four risk factors, wherein the earth-rock flow potential stream potential level F ₃ and the earth-rock flow warning reference value F ₄ are classified as the possibility a sex factor, and the earth-rock flow potential flow distance M ₄ and the earth-rock flow potential flow range distance M ₅ are classified as the scale factor, and, in addition, each of the risk factors corresponds to the hierarchical step size, and each grade The step scores corresponding to the step distance are exemplified in Table 13 below, but are not limited thereto. Table 13 <TABLE border="1"borderColor="#000000"width="85%"><TBODY><tr><td> Earth and Stone Flow</td></tr><tr><td> Factor Category</ Td><td> risk factor</td><td>number</td><td> hierarchical distance</td><td> level score</td></tr><tr><td> possible Sex factor </td><td> Earth and rock flow potential risk potential level</td><td>F₃</td><td>high</td><td> 40 </td></tr><tr><td>Medium</td><td> 30 </td></tr><tr><td>Low</td><td> 10 </td></tr><tr><td> Continuous observation</td><td> 5 </td></tr><tr><td> Earth and rock flow warning reference value</td><td>F₄</td><td> 200~300mm </td><td> 35 </td></tr><tr><td> 300~400mm </td><td> 20 </td></tr><tr><td> 400~500mm </td><td> 10 </td></tr><tr><td> 500~600mm </td><td> 0 </td></tr><tr><td> scale factor</td><td> earth-rock flow potential stream distance</td><td>M₄</td><td> below 10m</td><td> 100 </td></tr><tr><td> 10~20m </td><td> 60 </td></tr><tr><td> 20~30m </td><td> 30 </td></tr><tr><td> 30~40m </td><td> 5 </td></tr><tr><td> Earth and Rock Flow Potential Stream Influence range distance </td><td>M₅</td><td> Scope of influence </td><td> 100 </td></tr><tr><td> 0~10% area</td><td> 60 </td></tr><tr><td > 10~20% area</td><td> 30 </td></tr></TBODY></TABLE>

For the disaster attribute information corresponding to the disaster attribute of the earth-rock flow, the probability factor corresponding to the earth-rock flow is S ₅₌ F ₃ +F ₄ , and the scale factor corresponding to the earth-rock flow is S ₆₌ MAX{ M ₄ , M ₅ }, that is, the higher the intermediate level scores of both M ₄ and M ₅ , and the conversion matrix corresponding to the earth and stone flow is as shown in Table 14 in addition, and each likelihood factor step is relative to each scale factor level. A corresponding hazard level is exemplified in Table 14 below, but is not limited thereto. Table 14 <TABLE border="1"borderColor="#000000"width="85%"><TBODY><tr><td> Earth and Stone Flow Conversion Matrix</td><td> Probability Factor Score (S₅)</td></tr><tr><td> 70~100 </td><td> 40~70 </td><td> 0~40 </td></tr ><tr><td> Scale factor score (S₆) </td><td> 70~100 </td><td> 5 </td><td> 4 </td ><td> 3 </td></tr><tr><td> 40~70 </td><td> 4 </td><td> 3 </td><td> 2 </td></tr><tr><td> 0~40 </td><td> 3 </td><td> 2 </td><td> 1 </td></tr></TBODY></TABLE>

Referring to Table 15 below, for the disaster attribute information corresponding to the disaster attribute of the landslide, the risk level score table includes the landslide potential F ₅ and the maximum 24-hour accumulated rainfall F _{6 of} the return period, The peak surface acceleration F ₂ , the landslide type M ₆ , the landslide area M ₇ , and the risk factor of the landslide distance M ₈ , wherein the landslide potential F ₅ , the maximum twenty-four hour accumulation of the return period The rainfall amount F ₆ and the peak surface acceleration F ₂ are classified as the likelihood factor, and the landslide type M ₆ , the landslide area M ₇ , and the landslide distance M ₈ are classified as the scale factor, and further, each The hierarchical ranks corresponding to the risk factors and the grade scores corresponding to each graded pitch are exemplified in Table 15 below, but are not limited thereto. Table 15 <TABLE border="1"borderColor="#000000"width="85%"><TBODY><tr><td>landslide</td></tr><tr><td> factor category</ Td><td> risk factor</td><td>number</td><td> hierarchical distance</td><td> level score</td></tr><tr><td> possible Sex factor </td><td> landslide potential </td><td>F₅</td><td> high </td><td> 50 </td></ Tr><tr><td></td><td> 35 </td></tr><tr><td>low</td><td> 10 </td></tr><tr ><td> Maximum 24-hour accumulated rainfall during the return period</td><td>F₆</td><td>>750mm</td><td> 50 </td></tr><tr><td> 600~750 mm</td><td> 40 </td></tr><tr><td> 450~600 mm</td><Td> 25 </td></tr><tr><td> 300~450 mm</td><td> 15 </td></tr><tr><td><300mm</Td><td> 5 </td></tr><tr><td> Surface peak acceleration</td><td>F₂</td><td> 0~0.23g </td><td> 30 </td></tr><tr><td> 0.23~0.33g </td><td> 40 </td></tr><tr><td> 0.33~ 0.48g </td><td> 60 </td></tr><tr><td> 0.48~0.66g </td><td> 80 </td></tr><tr><td>>0.66g</td><td> 100 </td></tr><tr><td> scale factor</td><td> landslide type</td><td>M₆</td><td>顺坡坡</td><td> 2 </td></tr><tr><td> rock mass sliding</td><td> 1.5 </td></tr><tr><td>Rockfall</td><td> 1.2 </td></tr><tr><td> Rock debris collapse</td><td> 1 </td></tr><tr><td> landslide area</td><td>M₇</td><td> 10 hectares or more</td><td> 25 </td></tr><tr><td> 5~10 hectares</td><td> 20 </td></tr><tr><td> 1~5 hectares</td><td> 15 </td></tr><tr><td> below 1 hectare</td><td> 10 </td></tr><tr><td> distance from landslide</td><td>M₈</td><td> below 0.5H</td><td> 25 </td></tr><tr><td> 0.5H~1H </td><Td> 15 </td></tr><tr><td> 1H~2H </td><td> 5 </td></tr></TBODY></TABLE>

For the disaster attribute information corresponding to the disaster attribute of the landslide, the likelihood factor corresponding to the landslide is S ₇₌ MAX{F ₅ +F ₆ , F ₅ +F ₂ }, that is, taking (F ₅ +F ₆ ) And (F ₅ +F ₂ ) both have higher rankings, and the scale factor corresponding to the landslide is S ₈₌ M ₆ ×(M ₇ +M ₈ ), and the conversion matrix corresponding to the landslide is as shown in Table 16 below. For each of the probability factor levels, a hazard level corresponding to each scale factor step is exemplified in the following Table 16, but is not limited thereto. Table 16 <TABLE border="1"borderColor="#000000"width="85%"><TBODY><tr><td> landslide conversion matrix</td><td> probability factor score (S₇)</td></tr><tr><td> 70~100 </td><td> 25~70 </td><td> 0~25 </td></tr ><tr><td> Scale factor score (S₈) </td><td> 70~100 </td><td> 5 </td><td> 4 </td ><td> 3 </td></tr><tr><td> 25~70 </td><td> 4 </td><td> 3 </td><td> 2 </td></tr><tr><td> 0~25 </td><td> 3 </td><td> 2 </td><td> 1 </td></tr></TBODY></TABLE>

Referring to Table 17 below, for the disaster attribute information corresponding to the flooding attribute of the flooding, the risk level score table includes the warning rainfall value F ₇ and the flooding depth M ₉ and the like, wherein The warning rainfall value F ₇ is classified as the likelihood factor, and the flooding depth M ₉ is classified into the scale factor, and further, each of the risk factors corresponds to the hierarchical step, and each hierarchical level Examples of the pitch scores corresponding to the distances are shown in Table 17, below, but are not limited thereto. Table 17 <TABLE border="1"borderColor="#000000"width="85%"><TBODY><tr><td>Flooding</td></tr><tr><td> Factor Category</td><td> Risk Factor</td><td>Number</td><td> Grading Spacing</td><td> Spacing Score</td></tr><tr><td> Possibility factor</td><td> warning rainfall value</td><td>F₇</td><td> 200~300 </td><td> 100 </td ></tr><tr><td> 300~400 </td><td> 80 </td></tr><tr><td> 400~500 </td><td> 60 </td ></tr><tr><td> 500~700 </td><td> 10 </td></tr><tr><td> scale factor</td><td> depth of flooding </ Td><td>M₉</td><td> 3m or more</td><td> 100 </td></tr><tr><td> 2~3m </ Td><td> 100 </td></tr><tr><td> 1~2m </td><td> 90 </td></tr><tr><td> 0~1m </ Td><td> 80 </td></tr><tr><td> 0m </td><td> 0 </td></tr></TBODY></TABLE>

For the disaster attribute information corresponding to the disaster attribute attributed to the flooding, the probability factor formula corresponding to the flooding is S ₉₌ F ₇ , and the scale factor formula corresponding to the flooding is S ₁₀₌ M ₉ , and the The conversion matrix corresponding to the flooding is as shown in Table 18 below. In addition, a hazard level corresponding to each factor factor step relative to each scale factor step is exemplified in the following Table 18, but is not limited thereto. Table 18 <TABLE border="1"borderColor="#000000"width="85%"><TBODY><tr><td> Flooding conversion matrix</td><td> likelihood factor score (S<sub >9</sub>) </td></tr><tr><td> 80~100 </td><td> 60~80 </td><td> 40~60 </td><td > 0~40 </td></tr><tr><td> Scale factor score (S₁₀) </td><td> 80~100 </td><td> 5 </td><td> 5 </td><td> 4 </td><td> 3 </td></tr><tr><td> 60~80 </td><td> 5 </td><td> 4 </td><td> 3 </td><td> 2 </td></tr><tr><td> 40~60 </td><td> 4 </ Td><td> 3 </td><td> 2 </td><td> 1 </td></tr><tr><td> 0~40 </td><td> 3 </td ><td> 2 </td><td> 1 </td><td> 1 </td></tr></TBODY></TABLE>

Referring to Table 19 below, for the disaster attribute information corresponding to the disaster attribute of the soil liquefaction, the risk level score table includes the surface peak acceleration F ₂ , the water table depth F ₈ , the elevation M ₁₀ , and the Four risk factors, such as formation M ₁₁ , wherein the surface peak acceleration F ₂ and the groundwater level depth F ₈ are classified as the likelihood factor, and the elevation M ₁₀ and the formation M ₁₁ are classified as the scale factor, The rankings corresponding to each of the risk factors, and the step scores corresponding to each of the hierarchical intervals are exemplified in the following Table 19, but are not limited thereto. Table 19 <TABLE border="1"borderColor="#000000"width="85%"><TBODY><tr><td> Soil liquefaction</td></tr><tr><td> Factor category</td><td> Risk Factor</td><td>Number</td><td> Grading Spacing</td><td> Spacing Score</td></tr><tr><td> Possibility factor</td><td> Surface peak acceleration</td><td>F₂</td><td> 0~0.23g </td><td> 30 </ Td></tr><tr><td> 0.23~0.33g </td><td> 40 </td></tr><tr><td> 0.33~0.48g </td><td> 60 </td></tr><tr><td> 0.48~0.66g </td><td> 80 </td></tr><tr><td>>0.66g</td><td> 100 </td></tr><tr><td> Groundwater depth</td><td>F₈</td><td> Within 20m from the surface </td><Td> 50 </td></tr><tr><td> more than 20m from the surface </td><td> 0 </td></tr><tr><td> scale factor</td><Td> elevation </td><td>M₁₀</td><td> 0~20m </td><td> 40 </td></tr><tr><td > 20~100m </td><td> 0 </td></tr><tr><td> 100m or more or slope 6% or more</td><td> given hazard level 1 </td></tr><tr><td>Strata</td><td>M₁₁</td><td> Alluvium </td><td> 50 </td></tr ><tr><td> Terrace Stacking Layer</td></tr><tr><td> Others </ Td><td> 0 </td></tr></TBODY></TABLE>

For the disaster attribute information corresponding to the disaster attribute of the soil liquefaction, the probability factor formula corresponding to the soil liquefaction is S ₁₁₌ F ₂ +F ₈ , and the scale factor formula corresponding to the soil liquefaction is S ₁₂₌ M ₁₀ +M ₁₁ , and the conversion matrix corresponding to the soil liquefaction is as shown in the following Table 20. In addition, a hazard level corresponding to each factor factor step relative to each scale factor step is exemplified in the following Table 20, but not limit. Table 20 <TABLE border="1"borderColor="#000000"width="85%"><TBODY><tr><td> Soil Liquefaction Conversion Matrix</td><td> Possibility Factor Score (S<sub >11</sub>) </td></tr><tr><td> 80~100 </td><td> 60~80 </td><td> 40~60 </td><td > 0~40 </td></tr><tr><td> Scale factor score (S₁₂) </td><td> 80~100 </td><td> 5 </td><td> 5 </td><td> 4 </td><td> 3 </td></tr><tr><td> 60~80 </td><td> 5 </td><td> 4 </td><td> 3 </td><td> 2 </td></tr><tr><td> 40~60 </td><td> 4 </ Td><td> 3 </td><td> 2 </td><td> 1 </td></tr><tr><td> 0~40 </td><td> 3 </td ><td> 2 </td><td> 1 </td><td> 1 </td></tr></TBODY></TABLE>

The user terminal 2 has a positioning function, and includes a user terminal communication module 21 connected to the communication network 101, a user terminal input module 22, and an electrical connection terminal device communication module 21 and the user terminal input module. The use end of the processing module 23 of 22.

In this embodiment, the implementation of the server 1 is, for example, a personal computer, a server, or a cloud host, but is not limited thereto. The implementation of the terminal 2 is, for example, a tablet computer, a notebook computer, a smart phone or a personal computer, but is not limited thereto.

Referring to FIG. 1 and FIG. 2, the following is a description of the operation of the server 1 and the components of the terminal 2 by the embodiment of the risk identification insurance recommendation and the policy evaluation method of the present invention. The risk identification recommendation and the policy valuation are described. This embodiment of the method comprises the following steps: a step 61, a step 62, a step 63, a step 64, a step 65, a step 66, a step 67, and a step 68.

In step 61, the user terminal processing module 23 generates an object information related to a target object according to the input signal from the user input module 22, and communicates the target object information through the user terminal. The module 21 is transmitted to the servo terminal 1 through the communication network 101. The target object information includes an address of the target object, and a structure structure related to the structure of the target object, wherein the target object structure is one of the structure structures. It is particularly worth mentioning that, in this embodiment, the target object information is an address containing, for example, the target object. In other embodiments, the target object information may also include a name or keyword related to the target object, so that the user more intuitively searches for the target object. Alternatively, the target object information includes the latitude and longitude data of the target object obtained by using the positioning function of the user terminal 2 to achieve the same effect.

In step 62, after receiving the target object information through the server communication module 11, the server processing module 13 converts the target object information into a corresponding positioning information, and stores the information in the servo. The end storage module 12 obtains a plurality of risk assessment levels that are all related to the target object and respectively correspond to a plurality of different disaster categories. It should be noted that, in this embodiment, the positioning information corresponding to the target object information is latitude and longitude data.

Referring to FIG. 3, it is particularly noted that in this embodiment, step 62 further includes a sub-step 621, a sub-step 622, a sub-step 623, and a sub-step 624 detail flow.

In the sub-step 621, the server processing module 13 converts the target object information into the corresponding positioning information after receiving the target object information through the server communication module 11, and stores the information in the corresponding information. The risk assessment data in the server storage module 12 obtains a target risk assessment data corresponding to the target object information.

In the sub-step 622, the server processing module 13 selects the target risk assessment data according to the risk level score table corresponding to the disaster attribute stored in the server storage module 12 for each consistent disaster attribute. The risk value of each risk factor of the disaster-causing attribute is given a first-level distance score to obtain a score result of a step score of each risk factor including the disaster-causing attribute.

Referring to FIG. 4, it is particularly noted that in this embodiment, sub-step 622 further includes a sub-step 622A, and a sub-step 622B detail flow.

In the sub-step 622A, for each consistent disaster attribute, the server processing module 13 obtains the target risk assessment data according to the risk level score table corresponding to the disaster attribute stored in the server storage module 12. The rank of the risk value of each risk factor of the disaster-causing attribute belongs to.

In the sub-step 622B, the server processing module 13 obtains the target risk assessment data according to the risk level score table corresponding to the disaster attribute stored in the server storage module 12 for each consistent disaster attribute. The rank value corresponding to the risk level of each risk factor of the disaster attribute in the score is scored to obtain a score result of the rank score of each risk factor including the disaster attribute.

Continuing to refer to FIG. 3, in sub-step 623, for each consistent disaster attribute, the server processing module 13 imports the scoring result of the disaster attribute into the disaster attribute stored in the server storage module 12. The corresponding hazard grading conversion rules are respectively obtained to obtain a target hazard level.

Referring to FIG. 5, it is particularly noted that in this embodiment, the sub-step 623 further includes a sub-step 623A, a sub-step 623B, and a sub-step 623C.

In sub-step 623A, for each consistent disaster attribute, the server processing module 13 is based on the rank score of the likelihood factor and the disaster attribute according to the disaster attribute stored in the server storage module 12. a likelihood factor formula, calculating a likelihood factor score, and calculating a scale according to the scale score belonging to the scale factor and the scale factor formula of the disaster attribute in the disaster attribute stored in the server storage module 12 Factor score.

In the sub-step 623B, for each of the consistent disaster attributes, the server processing module 13 obtains the probability factor of the disaster attribute according to the conversion matrix corresponding to the disaster attribute stored in the server storage module 12. The probability factor level to which the score belongs, and the scale factor level to which the scale factor score of the disaster attribute belongs.

In the sub-step 623C, for each of the consistent disaster attributes, the server processing module 13 obtains the possibility that the disaster attribute belongs to according to the conversion matrix corresponding to the disaster attribute stored in the server storage module 12. The target level of hazard corresponding to the scale factor level to which the scale factor score belongs to the scale factor score of the disaster attribute.

Referring to FIG. 3, in sub-step 624, the server obtains a plurality of target hazard levels corresponding to each target of each of the consistent disaster attributes stored in the server storage module 12, and respectively obtains a plurality of objects related to the target object and respectively Corresponds to the risk assessment level for many different disaster categories. It is worth noting that the disasters corresponding to each type of disaster are related to at least the same disaster attributes. In this embodiment, the server processing module 13 obtains an earthquake of an earthquake type according to the target hazard level belonging to the disaster attribute of the active fault and the target hazard level belonging to the disaster attribute of the earthquake. Risk assessment level. The servo end processing module 13 obtains a rock and stone flow risk assessment level of the earth and rock flow according to the target hazard level belonging to the disaster attribute of the earth and rock flow. The server processing module 13 obtains a landslide risk assessment level of a landslide according to a target hazard level belonging to the disaster attribute of the landslide. The server processing module 13 obtains a flooding risk assessment level of a flood type according to a target hazard level belonging to the disaster attribute of the flooding. The servo end processing module 13 obtains a soil liquefaction risk assessment level of soil liquefaction according to a target hazard level belonging to the disaster attribute of the soil liquefaction. It is worth mentioning that the server processing module 13 is based on the target hazard level belonging to the disaster attribute of the active fault, and the higher of the target hazard level belonging to the disaster attribute of the earthquake as the earthquake. The risk assessment level, the target hazard level of the disaster attribute of the earth-rock flow, the target hazard level belonging to the disaster attribute of the landslide, the target hazard level belonging to the hazard attribute of the flooding, and the disaster attribute belonging to the soil liquefaction The target hazard level is taken as the land flow risk assessment level, the landslide risk assessment level, the flood risk assessment level, and the soil liquefaction risk assessment level.

Please continue to refer to FIG. 2. In step 63, the server processing module 13 determines whether there is at least one first in a first risk range among the risk assessment levels stored in the server storage module 12. A risk assessment level, and/or at least one second risk assessment level within a second risk range. When the server processing module 13 determines that there is at least one first risk assessment level in a first risk range, and/or at least one second risk assessment in a second risk range In the case of a level, the process proceeds to step 64; when the server processing module 13 determines that there is no at least one first risk assessment level within a first risk range, and at least one is located in a second When the second risk assessment level is within the risk range, the process proceeds to step 68. In this embodiment, the server processing module 13 determines whether there is at least one first risk assessment level located in a first risk range among the risk assessment levels stored in the server storage module 12. And determining whether the at least one second risk assessment level located in a second risk range exists in the risk assessment levels stored in the server storage module 12. However, in other embodiments of the present invention, the server processing module 13 may only determine whether the at least one first risk assessment level is within a first risk range, and is not limited to the risk assessment level. this.

In step 64, the server processing module 13 generates at least one corresponding to the disaster type corresponding to the at least one first risk assessment level and/or the disaster type corresponding to the at least one second risk assessment level. a first recommended insured item of the disaster category corresponding to the at least one first risk assessment level, and/or at least one second recommended insured item corresponding to the disaster category corresponding to the at least one second risk assessment level, and the at least A first recommended insurance item, and/or the at least one second recommended insurance item is transmitted to the user terminal 2 via the communication network 101 via the server communication module 11.

In step 65, the user terminal processing module 23 selects at least one of the at least one first recommended insurance item and/or the at least one second recommended insurance item according to the input signal from the user input module 22 In order to insure an item, and generate a query request related to the at least one item to be insured, and transmit the inquiry request related to the at least one item to be insured via the communication terminal 101 to the communication network 101 Servo terminal 1.

In step 66, after receiving the query request related to the at least one insured item via the server communication module 11, the server processing module 13 processes the server processing module for each item to be insured. According to the risk assessment level of the disaster type corresponding to the insured item and the disaster rate adjustment table stored in the server storage module 12, the risk assessment level of the disaster type corresponding to the item to be insured is obtained. a disaster weight coefficient corresponding to the level, and at the same time, according to the structure data of the building, and the construction rate adjustment table stored in the server storage module 12, obtaining a building weight of the building structure to which the target object belongs Coefficient, finally, calculating and obtaining the premium rate corresponding to the item to be insured according to the obtained disaster weight coefficient and the building weight coefficient. It should be particularly noted that, in this embodiment, the premium rate corresponding to the item to be insured is obtained by multiplying a predetermined basic rate by the obtained disaster weight coefficient and multiplying the obtained building. Obtained by the weight coefficient. In addition, in this embodiment, the server processing module 13 is based on the risk assessment level of the disaster type corresponding to the item to be insured and the structure structure data, and the disaster rate in the server storage module 12. The adjustment table and the construction rate adjustment table calculate and obtain the premium rate corresponding to the item to be insured, and in other embodiments, the server processing module 13 may only be based on the type of disaster corresponding to the item to be insured. The risk assessment level, and the disaster rate adjustment table stored in the server storage module 12, obtain the premium rate corresponding to the item to be insured. In other embodiments, the server processing module 13 is based on the risk assessment level of the disaster type corresponding to the item to be insured, and the disaster rate adjustment table stored in the server storage module 12. Obtaining the disaster weight coefficient corresponding to the level to which the risk assessment level of the disaster type corresponding to the insured item belongs, and calculating and obtaining the premium rate corresponding to the insured item according to the disaster weight coefficient.

In step 67, for each item to be insured, the server processing module 13 calculates the premium corresponding to the item to be insured according to the premium rate corresponding to the item to be insured, and corresponds to the item to be insured. The premium is transmitted to the user terminal 2 via the communication network 101 via the server communication module 11. It should be particularly noted that in this embodiment, the premium corresponding to the item to be insured is calculated by multiplying the corresponding premium rate by an insurance amount.

In step 68, the server processing module 13 transmits a basic insured item to the user terminal 2 via the server communication module 11. It is worth noting that the basic insurance items can be fire insurance, but not limited to this.

The embodiment of the risk identification insurance recommendation and the policy evaluation method of the present invention will be described below in conjunction with an application example. In this application example, the above Tables 3 to 8 are used as the risk assessment data, and the latitude and longitude A is used as the latitude and longitude of the target object.

As shown in step 61, the user-side processing module 23 generates an object information related to a target object according to an input signal from the user input module 22, where the target object information includes the target. The address of the subject matter (eg, 91 Xueshi Road, North District, Taichung City), and the structure of the target object (eg, reinforced concrete), and the target object information is transmitted through the communication network via the communication terminal 21 101 is transmitted to the servo terminal 1. It should be particularly noted that, in this application example, the target object information is an address including, for example, the target object, however, in other embodiments, the name of the object related to the target object may also be used (eg, China) Medical University) or keywords (eg, hospitals, universities) to help users more intuitively search for the desired target, or use the positioning device 2 to directly obtain the latitude and longitude data of China Medical University .

As shown in sub-step 621, after receiving the target object information through the server communication module 11, the server processing module 13 converts the target object information into corresponding positioning information, and stores the information in the corresponding information. A target risk assessment data is obtained in the risk assessment data in the server storage module 12 (that is, all risk factors related to latitude and longitude A in Tables 3 to 8 and risk values corresponding to all risk factors), The latitude and longitude A corresponding to the target risk assessment data is consistent with the latitude and longitude indicated by the target object information.

As shown in sub-step 622A, for each consistent disaster attribute, the server processing module 13 obtains the target risk assessment according to the risk level score table corresponding to the disaster attribute stored in the server storage module 12. The hierarchical value of the risk value of each risk factor of the disaster-causing attribute in the data (the hierarchical level in Table 21 to Table 24 below).

As shown in sub-step 622B, for each consistent disaster attribute, the server processing module 13 obtains the target risk assessment according to the risk level score table corresponding to the disaster attribute stored in the server storage module 12. The graded distance corresponding to the risk value of each risk factor of the disaster attribute in the data (the graded distance in the following Table 21 to Table 24) corresponds to the grade score (as shown in Table 21 to Table 24 below). Rank score) to obtain a score result of the rank score of each risk factor including the disaster attribute.  <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td> Latitude and longitude A </td></tr><tr><td> Risk factor</td ><td> F₁</td><td> M₁</td><td> M₂</td>< Td> F₂</td><td> M₃</td></tr><tr><td> probability of magnitude 6.5 earthquake</td ><td> Distance from fault line</td><td> Fault upper and lower disk magnification</td><td> Peak surface acceleration</td><td> Shear force velocity under surface</td></tr ><tr><td> Risk value</td><td> 15% </td><td> 900m </td><td> Upper plate</td><td> 0.2g </td><td > 350m/s </td></tr><tr><td> Grading level </td><td> 10%~20% </td><td> 100m or more</td><td> Disk</td><td> 0~0.23g </td><td> 300~500 m/s </td></tr><tr><td> Grade score</td><td> 40 </td><td> 0 </td><td> 2 </td><td> 30 </td><td> 40 </td></tr></TBODY></TABLE>Table 22  <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td> Latitude and longitude A </td></tr><tr><td> Risk factor</td ><td> F₃</td><td> F₄</td><td> M₄</td>< Td> M₅</td><td> F₅</td></tr><tr><td> Earth-rock flow potential stream potential level < /td><td> Earth and Rock Flow Warning Base Value</td><td> Earth and Rock Flow Potential Stream Distance</td><td> Earth and Rock Flow Potential Stream Distance </td><td> Landslide Potential</td> </tr><tr><td> risk value</td><td> </td><td> 480mm </td><td> 35m </td><td> 7% </td>< Td> 中</td></tr><tr><td> hierarchical distance </td><td> </td><td> 400~500mm </td><td> 30~40m </ Td><td> 0~10% area</td><td> medium</td></tr><tr><td> level score</td><td> 30 </td><td> 10 </td><td> 5 </td><td> 60 </td><td> 35 </td></tr></TBODY></TABLE> Table 23  <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td> Latitude and longitude A </td></tr><tr><td> Risk factor</td ><td> F₆</td><td> M₆</td><td> M₇</td>< Td> M₈</td><td> F₇</td></tr><tr><td> Maximum twenty-four hour accumulation in the return period Rainfall</td><td> Landslide Type</td><td> Landslide Area</td><td> and Landslide Distance</td><td> Warning Rainfall Value</td></tr><tr> <td> Risk value</td><td> 440 mm</td><td> Rock chip collapse</td><td> 0.7 hectare</td><td> 0.7H </td><td > 550 </td></tr><tr><td> Grading step size</td><td> 300~450 mm</td><td> Debris slumping</td><td> 1 Below hectare</td><td> 0.5H~1H </td><td> 500~700 </td></tr><tr><td> Grade score</td><td> 15 </ Td><td> 1 </td><td> 10 </td><td> 15 </td><td> 10 </td></tr></TBODY></TABLE>Table 24  <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td> Latitude and longitude A </td></tr><tr><td> Risk factor</td ><td> M₉</td><td> F₈</td><td> M₁₀</td>< Td> M₁₁</td></tr><tr><td> Flooding depth</td><td> Groundwater depth</td><td> elevation</td> <td> stratum</td></tr><tr><td> risk value</td><td> 0m </td><td> within 20m from the surface </td><td> 25m </td ><td> Terrace stacking layer</td></tr><tr><td> Grading step size</td><td> 0m </td><td> Within 20m from the surface </td><td > 20~100m </td><td> Terrace layer</td></tr><tr><td> Grade score</td><td> 0 </td><td> 50 </ Td><td> 0 </td><td> 50 </td></tr></TBODY></TABLE>

As shown in sub-step 623A, for each consistent disaster attribute, the server processing module 13 ranks the probability score belonging to the likelihood factor and the disaster attribute according to the disaster attribute stored in the server storage module 12. a likelihood factor formula for calculating a likelihood factor score (S ₁ , S ₃ , S ₅ , S ₇ , S ₉ , and S _{11 in} Table 23 below), and according to the storage in the server storage module 12 The scale attribute of the disaster attribute belonging to the scale factor and the scale factor formula of the disaster attribute, and calculating a scale factor score (S ₂ , S ₄ , S ₆ , S ₈ , S ₁₀ , and S _{12 in} Table 23 below) ). Here, the disaster attribute is used to illustrate the earth-rock flow (see Table 20). The probability factor corresponding to the earth-rock flow is S ₅₌ F ₃ +F ₄ , where F ₃ is the risk potential level of the earth-rock flow potential stream. For 30, F ₄ is the baseline value of the earth-rock flow warning, and its step score is 10, so the probability factor corresponding to the earth-rock flow is S ₅₌ 40, and the scale factor corresponding to the earth-rock flow is S ₆₌ MAX{ M ₄ , M ₅ }, where M ₄ is the earth-rock flow potential stream with a distance of 5, and M ₅ is the influence range of the earth-rock flow potential stream. The scale score is 60, so the scale factor score corresponding to the earth-rock flow is S ₆₌ 60 as shown in Table 25 below. .

As shown in sub-step 623B, for each consistent disaster attribute, the server processing module 13 obtains the possibility of the disaster attribute according to the conversion matrix corresponding to the disaster attribute stored in the server storage module 12. A probability factor level to which the factor score belongs, and a scale factor level to which the scale factor score of the disaster attribute belongs. Here, the disaster attribute is used to describe the earth-rock flow (see Table 14), and the probability factor corresponding to the earth-rock flow is S ₅₌ 40, so the corresponding probability factor level is 40-70, and the scale corresponding to the earth-rock flow The factor score S _{6 =} 60, so the corresponding scale factor scale is 40~70.

As shown in sub-step 623C, for each consistent disaster attribute, the server processing module 13 obtains the possibility that the disaster attribute belongs to the conversion matrix corresponding to the disaster attribute stored in the server storage module 12. The target factor level is the target hazard level corresponding to the scale factor level to which the scale factor score of the disaster attribute belongs. Here, the disaster attribute is used to illustrate the earth-rock flow (see Table 14). The probability factor step is 40-70, and the scale factor corresponding to the earth-rock flow is 40-70, so the corresponding target hazard level is 3. See Table 25 below. Table 25  <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td> latitude and longitude of the target </td><td> latitude and longitude A </td></tr> <tr><td> Disaster-causing attributes</td><td> Active faults</td><td> Earthquakes</td><td> Earth-rock flows</td><td> Landslides</td><td> Flooding </ s><td> ₂</td><td> S₃</td><td> S₄</td><td> S<sub >5</sub></td><td> S₆</td><td> S₇</td><td> S₈</td><td> S₉</td><td> S₁₀</td><td> S<sub>11</ Sub></td><td> S₁₂</td></tr><tr><td> Grade score</td><td> 40 </td><td> 0 </td><td> 30 </td><td> 40 </td><td> 40 </td><td> 60 </td><td> 65 </td><td> 25 < /td><td> 10 </td><td> 0 </td><td> 80 </td><td> 50 </td></tr><tr><td> Target Hazard Level </ Td><td> 1 </td><td> 1 </td><td> 3 </td><td> 2 </td><td> 1 </td><td> 3 </td> </tr><tr><td> Disaster Types</td><td> Earthquake</td><td> Earth and Rock Flow</td><td> Landslide</td><td> Flooding</td>< Td> soil liquefaction < /td></tr><tr><td> Risk Assessment Level</td><td> 1 </td><td> 3 </td><td> 2 </td><td> 1 </ Td><td> 3 </td></tr></TBODY></TABLE>

As shown in sub-step 624, the server-side processing module 13 has a target hazard level of 1 according to the disaster attribute attributed to the active fault (see Table 25), and the target hazard level belonging to the disaster attribute of the earthquake is 1 (see Table 25), the seismic risk assessment level obtained is 1. The servo end processing module 13 obtains a risk assessment level of 3 for the earth-rock flow according to a target hazard level of 3 (see Table 25) belonging to the disaster attribute of the earth-rock flow. The servo end processing module 13 obtains the landslide risk assessment level of 2 according to the target hazard level of the disaster attribute belonging to the landslide of 2 (see Table 25). The server processing module 13 obtains the flood risk assessment level of 1 according to the target hazard level of the flooding attribute belonging to the flooding level of 1 (see Table 25). The servo end processing module 13 obtains a soil liquefaction risk assessment level of 3 based on a target hazard level of 3 (see Table 25) belonging to the disaster mitigation attribute of the soil liquefaction.

As shown in step 63, the server processing module 13 determines whether there is at least one first risk assessment level in a first risk range among the risk assessment levels stored in the server storage module 12, and / or at least one second risk assessment level within a second risk range. Here, the risk assessment is set to 4 or 5 as the first risk assessment level within a first risk range, and the risk assessment is 2 or 3 is a second risk assessment level within a second risk range, and according to Table 25 Content, there is no first risk assessment level with a risk assessment rating of 4 or 5, but the earth-rock flow risk assessment rating is 3, the landslide risk assessment rating is 2, and the soil liquefaction risk assessment rating is 3, representing a risk assessment The level is a second risk assessment level of 2 or 3, so the process proceeds to step 64.

As shown in step 64, the server processing module 13 generates at least one second recommendation corresponding to the disaster category corresponding to the at least one second risk assessment level according to the disaster type corresponding to the at least one second risk assessment level. The insured item (eg, the earth-rock flow, the landslide, and the soil liquefaction), and the at least one second recommended insured item is transmitted to the use end 2 via the communication network 101 via the server communication module 11.

As shown in step 65, the user-side processing module 23 is based on the input signal from the user input module 22 from the at least one second recommended insurance item (eg, the earth-rock flow, the landslide, and the soil liquefaction). Selecting at least one item to be insured (assuming that the user only selects the earth and stone stream, and the soil liquefaction as an item to be insured), and generates a query request related to the at least one item to be insured, and correlates the at least one desire The inquiry request of the insurance item is transmitted to the server 1 via the communication network 101 via the communication terminal module 21.

As shown in step 66, after receiving the query request related to the at least one insured item via the server communication module 11, the server processing module 13 processes the server for each item to be insured. The group 13 is based on the risk assessment level of the disaster type corresponding to the insured item (eg, the risk assessment level of the earth and rock flow is 3, and the risk assessment level of the soil liquefaction is 3), and is stored in the server storage module 12 The disaster rate adjustment table (see Table 1) obtains a disaster weight coefficient corresponding to the level to which the risk assessment level of the disaster type corresponding to the item to be insured belongs (for example, the disaster weight coefficient of the earth-rock flow is 0.85, And the disaster weight coefficient of the soil liquefaction is 1), and according to the structural structure data (for example, reinforced concrete), and the construction rate adjustment table stored in the servo storage module 12 (see Table 2), Obtaining a building weight coefficient of the building structure to which the target object belongs (the building weight coefficient of the reinforced concrete is 0.3), and finally, according to the obtained damping weight coefficient, and the building And a weight coefficient calculating premium rates to obtain the corresponding item to be insured. Here, assuming that the basic rate of one of the earth-rock flows is 0.007, the calculation of the premium rate corresponding to the earth-rock flow is 0.007×0.85×0.3=0.001758.

As shown in step 67, for each item to be insured, the server processing module 13 calculates the premium corresponding to the item to be insured according to the premium rate corresponding to the item to be insured, in the example of step 66. If the insurance amount is 30,000 yuan, the premium of the earth-rock flow is (30000×0.007×0.85×0.3)÷0.555 ₌ 96, and the calculated premium (the premium of the earth-rock flow is 96) is passed through the servo communication mode. The group 11 is transmitted to the user terminal 2 via the communication network 101.

In summary, the risk identification insurance recommendation and the policy evaluation method of the present invention are performed by the server processing module 13 according to the risk assessment data stored by the server storage module 12, and the risk level distance score table. And the damage degree grading conversion rules automatically obtain the target hazard level corresponding to each consistent disaster attribute, and then automatically obtain the risk assessment level corresponding to each disaster type by the target hazard level corresponding to each consistent disaster attribute. And automatically recommend the corresponding insurance project to the user according to the risk assessment level corresponding to each disaster type, and obtain the premium rate corresponding to the project to be insured after the user selects the desired insurance project by himself, such as In one step, the user can provide a fast and professional customized insurance project, thereby reducing the labor and time cost required. Therefore, the object of the present invention can be achieved.

However, the above is only the embodiment of the present invention, and the scope of the invention is not limited thereto, and all the simple equivalent changes and modifications according to the scope of the patent application and the patent specification of the present invention are still Within the scope of the invention patent.

100‧‧‧ system

101‧‧‧Communication network

1‧‧‧Server

11‧‧‧Server communication module

12‧‧‧Server storage module

13‧‧‧Server processing module

2‧‧‧Use side

21‧‧‧Using the end communication module

22‧‧‧Using the input module

23‧‧‧Using the end processing module

61~68‧‧‧Steps

621~624‧‧‧ substeps

622A, 622B‧‧‧ substeps

623A~623C‧‧‧ substeps

Other features and advantages of the present invention will be apparent from the embodiments of the present invention, wherein: Figure 1 is a block diagram illustrating a system for implementing one embodiment of the risk identification insurance recommendation and policy valuation method of the present invention. 2 is a flow chart illustrating the flow steps of the embodiment of the risk identification insurance recommendation and the policy evaluation method of the present invention; FIG. 3 is a flow chart illustrating how the embodiment of the risk identification insurance recommendation and the policy evaluation method of the present invention is Obtaining a risk assessment level; FIG. 4 is a flow chart illustrating how the embodiment of the wind list evaluation method of the present invention obtains a score result; and FIG. 5 is a flow chart illustrating how the embodiment of the wind list evaluation method of the present invention is Obtain a target hazard level.

Claims (9)

A risk identification insurance recommendation and a policy evaluation method are implemented by a server, and the server is connected to a user terminal via a communication network, and the server stores a disaster rate adjustment table, and the plurality of pens respectively correspond to the plurality of targets. The risk assessment data of the object and the plurality of disaster attribute information corresponding to a plurality of different disaster-producing attributes, each risk assessment data includes multiple risk values of each risk factor corresponding to each of the consistent disaster attributes, and each of the consistent disaster attributes The information includes a risk level score table and a hazard grading conversion rule, and the disaster corresponding to each disaster type is related to at least the consistent disaster attribute, and the risk identification insurance recommendation and the policy evaluation method include the following steps: (A-1) Receiving, by the server, the target risk assessment data corresponding to the target object information from the risk assessment data after receiving the information of the target object from the use end and related to the target object; (A-2) For each consistent disaster attribute, the target risk is determined by the server according to the risk level score table corresponding to the disaster attribute The risk value of each risk factor of the disaster attribute in the assessment data is given a first-level distance score to obtain a score result of a grade distance score of each risk factor including the disaster attribute; (A-3) for each consistency The disaster attribute is obtained by the server, and the score result of the disaster attribute is imported into the hazard level conversion rule corresponding to each disaster attribute to obtain a target hazard level; (A-4) for each disaster type And obtaining, by the server, a corresponding risk assessment level according to the disaster attribute corresponding to the disaster type; (B) determining, by the server, whether there is at least one first risk assessment level within a first risk range among the risk assessment levels; (C) when the server determines that the at least one first risk exists When the level is evaluated, the server generates and transmits at least one first recommended insurance item corresponding to the disaster type corresponding to the at least one first risk assessment level according to the disaster type corresponding to the at least one first risk assessment level. And the (D) by the server, after receiving a query request from the user terminal and related to at least one of the at least one first recommended insurance items, for each desire Insured items, at least according to the risk assessment level of the disaster type corresponding to the insured item and the disaster rate adjustment table, obtain the premium rate corresponding to the item to be insured. The risk identification insurance recommendation and the policy evaluation method according to claim 1, the disaster rate adjustment table includes a plurality of disaster weight coefficients respectively corresponding to the plurality of levels, wherein in the step (D), the server is first According to the disaster rate adjustment table, a disaster weight coefficient corresponding to the level to which the risk assessment level of the disaster type corresponding to the item to be insured belongs is obtained, and the premium rate corresponding to the item to be insured is calculated according to the disaster weight coefficient. . The risk identification insurance recommendation and the policy evaluation method according to claim 1, wherein in the step (A-4), the disaster types include an earthquake, a soil flow, a landslide, a flooding, and a soil liquefaction. According to the risk identification insurance recommendation and the policy evaluation method described in claim 1, the server further maintains a construction rate adjustment table, where the construction rate adjustment table includes a plurality of construction weight coefficients respectively corresponding to the plurality of building structures, wherein: In the step (A-1), the target object information includes a structure structure related to the structure of the target object, wherein the target object structure is one of the structure structures; and in the step ( In the D), the server obtains the desire based on the risk assessment level of the disaster type corresponding to the insured item and the disaster rate adjustment table, and the construction structure data and the construction rate adjustment table. The premium rate corresponding to the insured item. The risk identification insurance recommendation and the policy evaluation method according to claim 4, wherein the disaster rate adjustment table includes a plurality of disaster weight coefficients respectively corresponding to the plurality of levels, wherein in step (D), the server is first According to the disaster rate adjustment table, a disaster weight coefficient corresponding to the level of the risk assessment level of the disaster type corresponding to the item to be insured is obtained, and the construction item of the target object is obtained according to the construction rate adjustment table. The weight coefficient of a building structure is calculated, and the premium rate corresponding to the item to be insured is calculated according to the weight coefficient of the building and the weight coefficient of the disaster. The risk identification insurance recommendation and the policy evaluation method according to claim 4, wherein, in the step (A-1), the construction structures comprise a reinforced concrete, a steel reinforced cement, a reinforced brick, and a ferrous metal. And a wooden one. The risk identification insurance recommendation and the policy evaluation method according to claim 1, wherein: in the step (B), the server determines not only whether the at least one of the risk assessment levels exists in the first risk range a first risk assessment level within the first risk assessment level, and determining whether there is at least one second risk assessment level within a second risk range; In step (C), when the server determines that the at least one first risk assessment level, and/or the at least one second risk assessment level, the server is based on the at least one first risk assessment level Generating and transmitting at least one first recommended insurance item corresponding to the disaster type corresponding to the at least one first risk assessment level, corresponding to the type of disaster, and/or the type of disaster corresponding to the at least one second risk assessment level, And/or at least one second recommended insurance item corresponding to the disaster category corresponding to the at least one second risk assessment level to the use end; and in step (D), by the server, receiving a After the use end is related to the at least one first recommended insurance item, and/or related to the at least one request for the insured item in the at least one second recommended insurance item, for each item to be insured, at least according to The risk assessment level of the disaster type corresponding to the item to be insured and the disaster rate adjustment table obtain the premium rate corresponding to the item to be insured. The risk identification insurance recommendation and the policy evaluation method according to claim 1, wherein the risk level score table includes the risk factors corresponding to the corresponding disaster types, and the plurality of hierarchical intervals corresponding to each risk factor, and The step (A-2) includes the following steps: (A-2-1) for each consistent disaster attribute, by the server, according to the disaster attribute a risk level distance score table, which obtains a hierarchical level of the risk value of each risk factor of the disaster attribute in the target risk assessment data; and (A-2-2) for each consistent disaster attribute, by the Servo end, according to the a risk level distance score table corresponding to the disaster attribute, obtaining the level score corresponding to the level of the risk value of each risk factor of the disaster attribute in the target risk assessment data, to obtain an inclusion The score of the score of each risk factor of the disaster attribute. According to the risk identification insurance recommendation and the policy evaluation method described in claim 6, each risk factor corresponding to each disaster type may be classified into one of a likelihood factor and a scale factor, and each disaster type corresponds to The hazard grading conversion rule includes a likelihood factor formula, a scale factor formula, and a conversion matrix having a plurality of likelihood factor intervals, a plurality of scale factor intervals, and each likelihood factor interval The step (A-3) includes the following steps with respect to a respective hazard level corresponding to each scale factor level: (A-3-1) for each consistent disaster attribute, by the server, according to the disaster a rank probability score belonging to the likelihood factor and a likelihood factor formula of the disaster attribute, calculating a likelihood factor score, and according to the scale score belonging to the scale factor and the scale factor of the disaster attribute Formula, calculating a scale factor score; (A-3-2) for each consistent disaster attribute, by the server, according to the conversion matrix corresponding to the disaster attribute, the possibility of obtaining the disaster attribute a probability factor level to which the factor score belongs, a scale factor level to which the scale factor score of the disaster attribute belongs; and (A-3-3) for each consistent disaster attribute, by the server, according to the The conversion matrix corresponding to the disaster attribute obtains the rule of the probability factor level to which the disaster attribute belongs and the scale factor score of the disaster attribute The target hazard level corresponding to the mode factor step.