CN108596773A - A kind of control method for establishing subscriber household insurance cover combined system - Google Patents

A kind of control method for establishing subscriber household insurance cover combined system Download PDF

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Publication number
CN108596773A
CN108596773A CN201810393565.9A CN201810393565A CN108596773A CN 108596773 A CN108596773 A CN 108596773A CN 201810393565 A CN201810393565 A CN 201810393565A CN 108596773 A CN108596773 A CN 108596773A
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China
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user
information
priority
factor
value
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Inventor
张建辉
沙新
冯翔
王飞
许猛
王瑾
余文婧
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China Pacific Insurance Group Co Ltd CPIC
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China Pacific Insurance Group Co Ltd CPIC
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Priority to CN201810393565.9A priority Critical patent/CN108596773A/en
Publication of CN108596773A publication Critical patent/CN108596773A/en
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0635—Risk analysis of enterprise or organisation activities
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/08—Insurance

Abstract

The present invention provides a kind of control method for establishing subscriber household insurance cover combined system based on user basic information, determines the priority of the multiple risks of user and the desired value of the multiple risks of user successively according to the family structure information of user, includes the following steps：a：One or more essential informations based on user calculate one or more calculating factors of user；b：The priority of the multiple risks of user and the desired value of the multiple risks of user are determined based on the essential information of the user.Present invention combination artificial intelligence and big data are applied to insurance sciemtifec and technical sphere, and formulating family insurance from the angle of family for every kinsfolk based on the relevant information of user ensures combinatorial programming scheme.

Description

A kind of control method for establishing subscriber household insurance cover combined system
Technical field
The invention belongs to insure sciemtifec and technical sphere more particularly to a kind of combination big data algorithm and artificial intelligence based on user Essential information establishes the control method of subscriber household insurance cover combined system.
Background technology
With the raising of people's demand for insurance and the enhancing of Insurance consciousness, insurance has become risk guarantee and Asset Allocation In an important ring, the competition of insurance institution is also more and more fierce, and being analyzed by the demand for insurance to different user can To realize the consumption suggestion of specific aim insurance products to different target crowd.But demand for insurance at present on the market analyzes work More or less the having some limitations property of tool.It is mainly reflected in：1, the protection amount of inquiry's individual demand is only analyzed, not from family Angle provide the comprehensive family insurance of complete set and ensure combinatorial programming scheme；2, subscriber household risk point and wind are not informed Dangerous feature, from the perspective of family, it is not known that need which insurance cover, specific aim not strong；3, the insurance cover provided is built View is only based on age, gender and to take in three information and simple business rule, stereotyped, and it is fixed to be not carried out differentiation System, precision be not high；4, insurance cover suggestion is only substantially life insurance guarantee, and the guarantee planning for lacking weight disease, medical treatment etc. is built View, and without rejecting the secure of client；5, it is unable to support user's insurance cover assembled scheme whenever and wherever possible in 7*24 hours Demand for counseling；6, registration or real name under the guidance of salesman is needed to log in, self-help is very weak, and user's concern of data is revealed, Often being unwilling, fill message is calculated.
Therefore, it is necessary to provide a kind of combination policy guarantee rule extended to based on user information to kinsfolk's various risks It draws, " is for Whom bought with solutionWhat is boughtBuy how many" the problem of, final safety accurately provides customization insurance service.
Invention content
For technological deficiency of the existing technology, the object of the present invention is to provide one kind to be established based on user basic information The control method of subscriber household insurance cover combined system determines the multiple wind of user successively according to the family structure information of user The desired value of the multiple risks of priority and user of danger, which is characterized in that include the following steps：
a：One or more essential informations based on user calculate one or more calculating factors of user；
b：Based on the user essential information determine the multiple risks of user priority and the multiple risks of user it is pre- Time value.
Preferably, the step a includes the following steps：
a1：It obtains the gender of user, permanent place, and the gender based on user, permanent location calculations first and calculates factor A；
a2：Family structure information is obtained, based on the age of the family structure acquisition of information subscriber household member, and is based on The age of the subscriber household member obtains second and calculates factor B；
a3：The income information for obtaining user and subscriber household member, based on the income information calculate third calculating because Plain C；
a4：The expenditure information for obtaining user and subscriber household member, based on the expenditure information calculate the 4th calculating because Plain D；
a5：The assets information for obtaining user calculates the 5th based on the assets information and calculates factor E；
a6：The liability information for obtaining user calculates the 6th based on the liability information and calculates factor F；
a7：Obtain the social security information and endowment desired value of user, the social security information based on the user and endowment desired value Calculate the 7th calculating factor G；
a8：The behavioural habits for obtaining user, the behavioural habits based on the user calculate the 8th and calculate factor H.
Preferably, the family structure information includes following several situations：
It is unmarried；
It is married not educate；
It is married to have educated；
Divorce has been educated.
Preferably, in family's structural information, if unmarried, then it is B that the second of the unmarried age, which calculates factor,1； It is not educated if married, then it is B that second of the age in the family structure information, which calculates factor,21、B22；It has been educated if married, then The second calculating factor at the age in the family structure information is B31、B32、B33…B3x；It has been educated if divorce, then the family The second calculating factor at the age in structural information is B41、B42、B43…B4x。
Preferably, the second calculating factor is obtained according to the age of different members in the family structure information, It is obtained according to following formula：Wherein, the value of the x is 1~60.
Preferably, the step a1 includes the following steps：
a11：It is then A to obtain the gender value corresponding to the gender of user if male based on big data11, if female Property, then it is A12；
a12：It is multiple values according to the grade classification in city, obtains the value A in the permanent place of user2；
a13：Based on formula A=0.6A1m+0.4A2, obtain first and calculate factor A, wherein and if male, then A1mFor A11, If women, then A1mFor A12, the A2For the value in the permanent place of user.
Preferably, the step a3 includes the following steps：
a31：Obtain the income information C of user1；
a32：Obtain the miscellaneous receipt information C of family2；
a33：Based on formulaIt obtains the third and calculates factor C, wherein the A is the first calculating factor A, the S are that the user counted in big data takes in constant.
Preferably, the step a4 includes the following steps：
a41：Obtain the daily total expenses information D of user1；
a42：Obtain the information on spending D that supports one's parents of user2；
a43：Children's education information on spending D is judged whether based on the family structure information3, and if it exists, then execute Step a44 thens follow the steps a45 if being not present；
a44：Obtain the children's education information on spending D of user3, and according to formulaObtain the expenditure letter Breath calculates the 4th and calculates factor D；
a45：According to formulaIt obtains the described 4th and calculates factor D.
Preferably, the step a5 includes the following steps：
a51：Obtain the deposit of user, the property summation E of stock, fund information1；
a52：Judge user whether have house and or vehicle, if so, then obtain user's house and or vehicle property summation E2, And step a53 is executed, if not having, then follow the steps a54；
a53：According to formulaIt obtains the described 5th and calculates factor E；Wherein, the T is to be counted in big data User's assets constant.
a54：According to formulaIt obtains the described 5th and calculates factor E.
Preferably, the step a6 includes the following steps：
a61：Judge whether user has liability information, if so, thening follow the steps a62, if not having, it is 1 to define F；
a62：Obtain the moon refund information F of user1；
a63：Obtain the refund temporal information F of user2；
a64：Based on formulaObtain it is described 6th calculate factor F, wherein the A be first calculate because Element, the R are constant of being in debt in big data.
Preferably, the step a7 includes：
a71：Judge whether user has social security information, if so, thening follow the steps a72, if nothing, it is 0 to define G；
a72：Obtain the endowment desired value G of user1, and according to formulaObtain the 7th calculating factor G, wherein institute It is the first calculating factor to state A, and the V is the average value of the different social security standard in each city.
Preferably, in the step a8, the behavioural habits of the user include whether to have a meal on time, whether by When go to bed, whether drink, whether smoking, whether taking regular exercise, it is described 8th calculate factor H according to formulaWherein, when having a meal on time, H1It is 1, when being late for having a meal, H1It is 0；H.d. on time, H2It is 1, is late for h.d., H2It is 0；When drinking, H3It is 0, when no drinking, H3It is 1；When smoking, H4It is 0, when not smoking, H4For 1；When taking regular exercise, H5It is 1, when infrequently moving, H5It is 0.
Preferably, the step b includes the following steps：
b1：Based on user the first essential information determine the multiple risks of user priority and the multiple risks of user it is pre- Time value；
b2：Family structure information based on user judges whether with spouse, if having, thens follow the steps b3, if not having Have, thens follow the steps b4：
b3：Based on user the first essential information determine the multiple risks of spouse priority and the multiple risks of spouse it is pre- Time value；
b4：Family structure information based on user judges whether with children, if having, thens follow the steps b5, if not having Have, thens follow the steps b6；
b5：Based on user the first essential information determine the multiple risks of children priority and the multiple risks of children it is pre- Time value；
b6：Assets information based on user judges whether with property, if having, thens follow the steps b7；
b7：Based on user the first essential information determine the multiple risks of property priority and the multiple risks of property it is pre- Time value.
Preferably, the step b1 includes the following steps：
b11：User's weight disease, accident, life insurance and the preferential journey of medical treatment are determined successively based on the first essential information of user Angle value；
b12：To the heavy disease of the user, accident, life insurance and the degree of priority of medical treatment value according to sequence from big to small It is ranked up, determines the priority of the multiple risks of user；
b13：User's weight disease, accident, life insurance and the desired value of medical treatment are determined successively based on the first essential information of user.
Preferably, in the step b11, the user insure weight disease degree of priority value obtained by following formula：
The user unexpected degree of priority value of insuring is obtained by following formula：J=ACF；
The insure degree of priority value of life insurance of the user is obtained by following formula：K=ACE；
The user insure medical treatment degree of priority value obtained by following formula：
Preferably, in the step b13, the user insure weight disease desired value obtained by following formula：NI= (C1+C2+E1+E2)I；
The user unexpected desired value of insuring is obtained by following formula：NJ=(C1+C2+E1+E2)J；
The insure desired value of life insurance of the user is obtained by following formula：NK=(C1+C2+E1+E2)K；
The user insure medical treatment desired value obtained by following formula:NL=(C1+C2+E1+E2)L。
Preferably, the step b3 includes the following steps：
b31：Spouse's weight disease, accident, life insurance and the preferential journey of medical treatment are determined successively based on the first essential information of user Angle value；
b32：To the heavy disease of the spouse, accident, life insurance and the degree of priority of medical treatment value according to sequence from big to small It is ranked up, determines the priority of the multiple risks of spouse；
b33：Spouse's weight disease, accident, life insurance and the desired value of medical treatment are determined successively based on the first essential information of user.
Preferably, in the step b31, the spouse insure weight disease degree of priority value obtained by following formula：
The spouse unexpected degree of priority value of insuring is obtained by following formula：J=ACF；
The insure degree of priority value of life insurance of the spouse is obtained by following formula：K=ACE；
The spouse insure medical treatment degree of priority value obtained by following formula：
Preferably, in the step b33, the spouse insure weight disease desired value obtained by following formula：NI= (C1+C2+E1+E2)I；
The spouse unexpected desired value of insuring is obtained by following formula：NJ=(C1+C2+E1+E2)J；
The insure desired value of life insurance of the spouse is obtained by following formula：NK=(C1+C2+E1+E2)K；
The spouse insure medical treatment desired value obtained by following formula:NL=(C1+C2+E1+E2)L。
Preferably, the step b5 includes the following steps：
b51：Children's education, weight disease, unexpected and medical preferential journey are determined successively based on the first essential information of user Angle value；
b52：To the educating of the children, weight disease, unexpected and medical degree of priority value according to sequence from big to small It is ranked up, determines the priority of the multiple risks of children；
b53：Children's education, weight disease, unexpected and medical desired value are determined successively based on the first essential information of user.
Preferably, in the step b51, the insure degree of priority value of education of the children is obtained by following formula：
The children insure weight disease degree of priority value obtained by following formula：
The children unexpected degree of priority value of insuring is obtained by following formula：
The children insure medical treatment degree of priority value obtained by following formula：
Preferably, in the step b53, the insure desired value of education of the children is obtained by following formula：WO= (C1+C2+E1+E2)O；
The children insure weight disease desired value obtained by following formula：WP=(C1+C2+E1+E2)P；
The children unexpected desired value of insuring is obtained by following formula：WQ=(C1+C2+E1+E2)Q；
The children insure medical treatment desired value obtained by following formula：WU=(C1+C2+E1+E2)U。
Preferably, the step b7 includes the following steps：
b71：Three duty of property vehicle, the degree of priority value of family property are determined successively based on the first essential information of user；
b72：The property vehicle three duty, the degree of priority value of family property are ranked up according to sequence from big to small, really Determine the priority of the multiple risks of property；
b73：Three duty of property vehicle, the desired value of family property are determined successively based on the first essential information of user.
Preferably, in the step b71, if E1More than E2, then family property of preferentially insuring, if E1Less than E2, then vehicle of insuring Three duties.
Preferably, in the step b73, the desired value that vehicle three is blamed of the property insuring is obtained by following formula It takes：
The insure desired value of family property of the property is obtained by following formula：
The present invention utilizes big data and machine learning algorithm, and analysis calculating is carried out to user's difference information, is single with family Position provides insurance cover assembled scheme from ensure type, ensure priority, ensure amount etc. for every kinsfolk.From And realize differentiation, accurately insurance cover suggestion.
Description of the drawings
Upon reading the detailed description of non-limiting embodiments with reference to the following drawings, other feature of the invention, Objects and advantages will become more apparent upon：
Fig. 1 shows that the specific embodiment of the present invention, one kind establishing subscriber household based on user basic information The control method flow chart of insurance cover combined system；
Fig. 2 shows the specific embodiment of the present invention, one or more essential informations based on user, which calculate, to be used The flow chart of one or more calculating factors at family；
Fig. 3 shows the specific embodiment of the present invention, obtains and the gender based on user, permanent location calculations the One calculates the flow chart of factor A；
Fig. 4 shows the specific embodiment of the present invention, obtains and calculates factor C based on income information calculating third Flow chart；
Fig. 5 shows the specific embodiment of the present invention, acquisition and the branch based on user and subscriber household member Go out information and calculates the 4th flow chart for calculating factor D；
Fig. 6 shows the specific embodiment of the present invention, obtains and the assets information based on user calculates the 5th meter The flow chart of calculation factor E；
Fig. 7 shows the specific embodiment of the present invention, obtains and the liability information based on user calculates the 6th meter Calculate the flow chart of factor F；
Fig. 8 shows the specific embodiment of the present invention, obtains and the social security information based on user and endowment it is expected Value calculates the 7th flow chart for calculating factor G；
Fig. 9 shows the specific embodiment of the present invention, and the multiple risks of user are determined based on the essential information of user Priority and the multiple risks of user desired value flow chart；
Figure 10 shows the specific embodiment of the present invention, determines that user is multiple based on the first essential information of user The flow chart of the desired value of the priority of risk and the multiple risks of user；
Figure 11 shows the specific embodiment of the present invention, determines that spouse is multiple based on the first essential information of user The flow chart of the desired value of the priority of risk and the multiple risks of spouse；
Figure 12 shows the specific embodiment of the present invention, obtains and the assets information based on user calculates the 5th meter The flow chart of calculation factor E；And
Figure 13 shows the specific embodiment of the present invention, determines that property is multiple based on the first essential information of user The flow chart of the desired value of the multiple risks of priority and property of risk.
Specific implementation mode
In order to preferably technical scheme of the present invention be made clearly to show, the present invention is made into one below in conjunction with the accompanying drawings Walk explanation.
Fig. 1 shows the specific implementation mode of the present invention, a kind of to establish subscriber household insurance based on user basic information Ensure the control method flow chart of combined system.The present invention determines the multiple risks of user successively according to the family structure information of user Priority and desired value.It should be noted that the control that the acquisition of the essential information can both have been applied through the invention System processed is based on individual subscriber wish and is actively obtained to user, can also be obtained by the way that any third-party institution or approach are legal It takes.In the present invention, acquired data are more, are more conducive to obtain accurate statistical result.The user basic information include but It is not limited to the name of user, gender, the age, address, takes in expenditure, social security welfare, asset-liabilities, living habit, individual Credit and family structure, and the including but not limited to information such as the number of kinsfolk, age, income, health status.Tool Body, as shown in Figure 1, initially enter step S101, one or more essential informations based on user calculate one of user or Multiple calculating factors.Wherein, one or more essential informations are as previously mentioned, control method through the invention, by calculating Machine quantifies the essential information of aforementioned one or more based on big data and machine learning algorithm, comprehensive assessment.Calculating obtains The one or more of calculating factors taken and the data type of one or more of essential informations, to represent meaning corresponding, To carry out quantitative evaluation to the essential information from different considerations.Such as healthy custom, asset-liabilities, income branch Go out, insure preference etc., the present invention will subsequently do more detailed description.
Further, in step s 102, the essential information based on the user determines the priority of the multiple risks of user And the desired value of the multiple risks of user.Specifically, the multiple risk is corresponding with the essential information, and the user is multiple The priority of risk refer to family structure based on the user and its kinsfolk, age composition, household income and expenditure situation, The user that the different dimensions index evaluations such as physical condition, living habit, social security welfare obtain to the abilities to take the burden of different risks and The significance level ordering scenario of insurance will is further embodied in the user and its kinsfolk for different home The importance of member and insurance kind demand.Such as it preferentially for Whom buysAny insurance boughtIn the concrete application of the present invention In, setting ensures that the recommendation rules of priority can be：Pillar is first protected, first protects after adult protects child, first guarantor's risk again and saves Property is protected after financing, first guarantor；Ensure that priority is followed successively by preferred, preferential, recommendation and does not recommend four classes from high to low.More into one Step ground, the desired value of the multiple risks of user refer to the guarantee amount of different insurance kinds corresponding to the user and its kinsfolk Desired value.More specifically, the present invention will be described below in specific embodiment and do more detailed description in conjunction with attached drawing.
To sum up, technical scheme of the present invention is based on big data analysis and machine learning algorithm, is user from the angle of family Customized family insurance ensures combinatorial programming, to be user's solution is which kind of some or multiple members in family buy Insurance kind, and the problem of guarantee amount, optimize allocation of resources.
Referring now to Figure 2, Fig. 2 shows the specific embodiment of the present invention, one or more bases based on user This information calculates the method flow diagram of one or more calculating factors of user.The calculating factor and the essential information pair Answer, and as it is of the invention final formulate family insurance ensure an assessment that can specifically quantify in combinatorial programming scheme because Son.As a sub- embodiment of step S101 in embodiment illustrated in fig. 1, specifically comprise the following steps：
Step S1011 obtains the gender of user, permanent place, and the gender based on user, permanent location calculations first are counted Calculation factor A.Specifically, obtain the gender of the user, permanent place can questionnaire by inquiry form, institute through the invention The application program of application or website are actively obtained from user, can also be based on the registration of other application in terminal used by a user Gender example and permanent the place such as Shanghai, Hunan for obtaining the user are accessed in information and positioning or public information library. Due to men and women, the personnel of different geographical have differences in various aspects such as insurance awareness, and therefore, the first calculating factor A is based on The gender of the user, permanent place judge such as family status of the user, location economy, society for assessment Situations such as guarantee environment, and as one of evaluation factors, the weights influence in all calculating factors is used The priority of the multiple risks in family and the desired value of the multiple risks of user.
Similarly, by step S1012, family structure information is obtained, is based on family structure acquisition of information user man The age of front yard member, and obtain second based on the age of the subscriber household member and calculate factor B.The family structure packet Include number and personal status relationship of the kinsfolk of the user, such as marriage, children's situation etc..Further, it is determined that each The age of the kinsfolk, and obtain described second based on the age of the subscriber household member and calculate factor B.It needs to illustrate , the age corresponding demand for insurance of different members and insurance awareness have differences in family, for example, child or green strong Year and old man are different to the necessity and guarantee amount of amount insured care and the required insurance kind insured.Therefore, described Two calculating factor B can be from another dimension for judging priority and desired value of the user to different risks.
Above-mentioned first, which calculates factor A and second, calculates factor B synthesis from dimensions such as gender, region, ages to user's Demand for insurance is evaluated, and backstage can obtain statistical sample through the invention, and in general, female user is with respect to male user More concern insurance, in age composition, concern insurance in more position after 70/80 calculates factor A and described second in conjunction with described first Calculating factor B, the big data statistics based on acquisition, the male for paying close attention to insurance at an early age will be more than women, and mature women is more Concern insurance.
Step S1013 obtains the income information of user and subscriber household member, and third is calculated based on the income information Calculating factor C.Similarly, in one family, the income information includes the revenue source such as work of each kinsfolk Natural endowments income, non-Income from wage and salary (including rent, interest etc.) and amount information such as annual pay 100000,200,000 etc..It is based on The third calculating factor C of the income acquisition of information is corresponding with the income information, can be used for assessing the family Risk-recovery ability, the indexs such as insurance will.
Step S1014 obtains the expenditure information of user and subscriber household member, and the 4th is calculated based on the expenditure information Calculating factor D.Similarly, the expenditure information of the user and kinsfolk include the various aspects such as clothing, food, lodging and transportion -- basic necessities of life amusement. More position specifically, can be daily expenditure, children's education pay, support one's parents, repaying, existing insurance expenditure etc..Described Four calculate that factor D are corresponding with the user and the expenditure information of kinsfolk, are used to assess the user and kinsfolk The condition of consumption can reflect the demand for insurance etc. of the user.
Above-mentioned third calculates factor C, the 4th calculating factor D and is directed to different risks from family income expenditure angle estimator user Priority and desired value.In a concrete application, based on the statistical data that backstage of the invention obtains, and in conjunction with described the One calculates factor A, the second calculating factor B, can obtain different level annual pay user population proportion, revenue and expenditure Regional Distribution situation (a line city be higher than three or four line cities), age distribution, non-Income from wage and salary accounting, different home member's income level difference, The statistical results such as family's surplus ratio, burden.
Step S1015 obtains the assets information of user, and calculating the 5th based on the assets information calculates factor E.The use The assets information at family include deposit, real estate, the stock of investment, fund of the user etc. can with valuation Assets, it is described 5th calculate factor it is corresponding with the assets information, can equally react the user and its kinsfolk Economic strength.
Step S1016 obtains the liability information of user, and calculating the 6th based on the liability information calculates factor F.It is described negative Debt information includes but not limited to the information such as the personal debt-credit, bank loan, estate mortagage of the user, and the described 6th calculates factor F is corresponding with the liability information, for assessing the economic strength of the user and kinsfolk.
Above-mentioned 5th calculates factor E, the 6th calculating factor F is directed to different risks from asset-liabilities angle to the user Priority and desired value are assessed.In a concrete application, based on the statistical data that backstage of the invention obtains, in conjunction with aforementioned Every calculating factor can obtain family's accounting, the Regional Distribution of room and/or vehicle, the statistical results such as consumption concept.
Step S1017 obtains the social security information and endowment desired value of user, based on the social security information of the user and endowment Desired value calculates the 7th and calculates factor G.The social security information include the existing social security range of the user, social security payment the time limit, The information such as social security radix and accumulating sum, the endowment desired value refer to being obtained from endowment investment after user it is expected retirement Income, for example, it is desirable to the income level after retirement maintain before retirement it is horizontal, taken in before retirement 70%, take in before retirement 50% or minimum social security level etc..To calculate the endowment insurance demand that factor G reflects user according to the described 7th.
Step S1018 obtains the behavioural habits of user, and the behavioural habits based on the user calculate the 8th and calculate factor H. The behavioural habits be primarily referred to as with the relevant behavioural habits of user health, such as, if having a meal on time, on time sleep, smoke, The behavioural habits such as excessive drinking, regular exercise.The 8th calculating factor H is corresponding with the behavioural habits of the user, can be anti- The user should be gone out and its kinsfolk needs the necessity insured.In conjunction with aforementioned every calculating factor, at one of the present invention In application scenarios, the statistical data based on acquisition can obtain the relationships such as living habit and region, age, further include for example, Wedding has the different homes structure daily life such as baby rule, tobacco and wine consumption etc..
It should be noted that the acquisition of above-mentioned calculating factor can synchronize progress, can also obtain successively, it is respective to hold Row does not influence each other independently of each other.And obtained in terms of different and insure relevant every important indicator with user, by counting greatly According to and machine learning algorithm, calculated based on its respective calculating factor and its weight comprehensive analysis, help the insurance for obtaining user Demand.In favor of achieving the object of the present invention.
Further, in the present invention, the family structure information includes mainly following several situations, such as unmarried, Wedding do not educate, it is married educated, divorce educated.Diversity of family structure information except can react kinsfolk number, composition in addition to, The economic structure of family and otherwise information can be embodied, it will not be described here.Further, in the family structure In information, if unmarried, indicate there was only one people of user in the family structure, then second calculating at the unmarried age because Element is B1；It is not educated if married, indicates that member is two people of user man and wife in the family structure, then in the family structure information It is B that the second of age, which calculates factor,21、B22；Wherein B21、B22The second calculating factor at respectively represent man and wife wherein age of a people； It has been educated if married, has indicated that there are several members, such as couple and its children in the family structure, according to kinsfolk people The second calculating factor at the age in the family structure information is that calculate separately value be B by several differences31、B32、B33… B3x.Wherein x is the married number for having educated kinsfolk in family structure, such as 3 people, 4 people or more；Further, if It has been educated for divorce, has indicated there is not certain number of kinsfolk in the family structure, including divorce user and its children, It is B that then second of the age in the family structure information, which calculates factor,41、B42、B43…B4x.Wherein x is described married to have educated house The number of kinsfolk in the structure of front yard.
Further, in the present invention, described second factor is calculated according to different members in the family structure information Age obtains, and is obtained according to following formula：Wherein, the value of the x is 1~60.The x value ranges Cover a case where people is from birth to retired each age level.Also, described second calculates factor BxIt is inversely proportional with the age, Age is bigger, then BxIt is smaller.
As a sub- embodiment of step S1011 in above-mentioned Fig. 2, Fig. 3 shows the embodiment of the present invention, obtains and uses The gender at family, permanent place, and the gender based on user, permanent location calculations first calculate the flow chart of factor A.
Step S10111 is first carried out, the gender value corresponding to the gender of user is obtained based on big data, if male, It is then A11, if women, then be A12.As is generally understood, men and women is in health degree, diet, living habit, insurance Idea etc. is all many-sided in the presence of the difference caused by gender itself, therefore, is chosen to men and women user based on gender differences different Gender value is as parameter.Wherein, the A11、A12Specific value can be set as needed, this have no effect on the present invention Essence.
Step S10112 is multiple values according to the grade classification in city, obtains the value A in the permanent place of user2.Tool Body is divided into a line city, such as Beijing, Shanghai according to the city level in China, tier 2 cities such as Hangzhou, Changsha, and three Line city such as Zhuzhou, Xiang Tan and four line cities.Based on big data analysis, one, tier 2 cities are in income, the level of consumption, family Front yard surplus ratio etc. is higher than three, four line cities.The A2According to the grade in the permanent place of the user and in National urban In specific location carry out corresponding value, it will not be described here.
Step S10113 is based on formula A=0.6A1m+0.4A2, obtain first and calculate factor A, wherein if male, then A1mFor A11, if women, then A1mFor A12, the A2For the value in the permanent place of user.This step is in conjunction with the step The gender value and place value obtained in the S10111 and step S10112, and its respectively weight, base are set Described first, which is obtained, in above-mentioned formula calculates factor A.
As a sub- embodiment of step S1013 in above-mentioned Fig. 2, Fig. 4 shows the embodiment of the present invention, obtains and uses The income information of family and subscriber household member calculate the flow chart that third calculates factor C based on the income information.It is specific Including：
Step S10131 obtains the income information C of user1.The income information includes the Income from wage and salary of the user And different the revenue source information and amount received information etc. such as non-Income from wage and salary.
Step S10132 obtains the miscellaneous receipt information C of family2.The miscellaneous receipt information includes other kinsfolks Income from wage and salary and different the revenue source information and amount received information etc. such as non-Income from wage and salary.The income information C1、C2It is preferred that directly being provided by user.
Further, in step S10133, it is based on formulaIt obtains the third and calculates factor C, In, the A is the first calculating factor, and the S is that the user counted in big data takes in constant, and it is one which, which takes in constant, Statistics, revocable numerical value is related to user site average income level, the user job content etc..Described Three calculating factor C and the income information of the user and subscriber household member are proportionate.
As a sub- embodiment of step S1014 in above-mentioned Fig. 2, Fig. 5 shows the embodiment of the present invention, obtains and uses The expenditure information of family and subscriber household member calculate the 4th flow chart for calculating factor D based on the expenditure information.
First in step S10141, the daily total expenses information D of user is obtained1.The daily total expenses information includes But it is not limited to the daily expenditure of the user, children's education expenditure, expenditure of supporting one's parents, repaying and insurance expenditure information.
Step S10142 obtains the information on spending D that supports one's parents of user2.It can react the use to a certain extent Family influences its planning to insurance expenditure to a certain extent in the support one's parents attitude and values of aspect.
Further, in step S10143, judge whether that children's education is paid wages based on the family structure information Information D3, specifically, it is primarily based on the family structure information and determines whether with children, if any children, then is based on the use The age of family children, presence information of receiving an education further confirm that with the presence or absence of children's education information on spending D3.If in the presence of executing Step S10144 thens follow the steps S10145 if being not present.Specifically, feelings are not educated to be unmarried, married such as the family structure Condition then shows that there is no the children's educations to pay wages；If conversely, the family structure has educated to be married, divorced and educated, show There may be children's education spendings.
Correspondingly, if there are the children's education information on spending D3, then in step S10144, children's religion of user is obtained Educate information on spending D3, and according to formulaIt obtains the expenditure information and calculates the 4th calculating factor D, refuse herein It repeats.The formula is based on information on spending and the children's education information on spending of supporting one's parents in the daily total of the user Information on spending D1Proportion, determine that the described 4th calculates factor D.It will be appreciated by those skilled in the art that children's education is paid wages and is supported Adoptive parent's spending proportion in total expenses is bigger, shows that the family more more payes attention to children's education and supports one's parents, in related field Insurance spending demand and wish priority higher.
If the children's education information on spending D is not present3, S10145 is thened follow the steps, according to formula：It obtains Described 4th calculates factor D, i.e., only need to consider to support one's parents proportion of the spending in middle spending, and it will not be described here.
As a sub- embodiment of step S1015 in above-mentioned Fig. 2, Fig. 6 shows the embodiment of the present invention, obtains and uses The assets information at family calculates the 5th flow chart for calculating factor E based on the assets information.In such embodiments：
Step S10151 is first carried out, obtains the deposit of user, the property summation E of stock, fund information1.According to usual Understand, deposit is to weigh each most important index of family's property, and secondly, the family of difference income level is likely present stock And the investings property such as fund.
Step S10152, judge user whether have house and or vehicle, provided according to the user or flat according to common data The room and/or vehicle register information for the user that platform obtains, it is preferable that in the case where improving data validity preferably by described User provides.Further, judge the user about room and/or information of vehicles in the assets information based on the user Whether house and/or vehicle are had.If so, then obtain user's house and or vehicle property summation E2, and step S10153 is executed, if No, S10154 is thened follow the steps.
Specifically, in step S10153, according to formulaIt obtains the described 5th and calculates factor E；Wherein, The T is the user's assets constant counted in big data.As a statistics constant, with region, industry, age residing for user Etc. information have relevance.When the user does not have room and/or vehicle, according to formula in step S10154It obtains Described 5th calculates factor E, i.e., only considers the basic assets information such as user's deposit.To sum up, it can be seen based on above description Go out, the 5th calculating factor and the assets value of the user are proportionate.
As a sub- embodiment of step S1016 in above-mentioned Fig. 2, Fig. 7 shows the embodiment of the present invention, obtains and uses The liability information at family calculates the 6th flow chart for calculating factor F based on the liability information.It specifically comprises the following steps：
Step S10161 is first carried out, judges whether user has liability information, the liability information includes but not limited to The associated bank credit information of the user, including housing loan, vehicle is borrowed and other debts, loan etc..
If the user has liability information, S10162 is thened follow the steps, the moon refund information F of the user is obtained1.Institute State moon refund information F1The information such as refund project, repayment amount and refund platform including at least the user.
Further, the refund temporal information F that step S10163 obtains user is executed2.The refund temporal information is available Judge whether in time, in full amount the user refunds in assessment, if there are the situations such as promise breaking.Subsequently, based on above-mentioned steps S10162 And the user's refund information F obtained in step S101631And refund temporal information F2, according to formulaIt obtains Described 6th calculates factor F, wherein the A is the first calculating factor, and the R is constant of being in debt in big data.In this way Embodiment in, coefficient 12 is the moon number of a year and a day, and the described 6th calculates factor F and user's refund information F1And also Money temporal information F2Product it is directly proportional.
In the present embodiment, if the user described in the step S10161 does not have liability information, the described 6th is set It is 1 to calculate factor F, and it will not be described here.
Further, a sub- embodiment as step S1017 in above-mentioned Fig. 2, Fig. 8 show the embodiment of the present invention , the social security information and endowment desired value of user are obtained, social security information and endowment desired value based on the user calculate the 7th The flow chart of calculating factor G.Statistics indicate that comparing general population, the ratio higher for having basic social security in the crowd of insurance is paid close attention to. In such embodiments, step S10171 is initially entered, judges whether user has social security information, the social security information includes The existing social security type of user, pays the information such as the social security time limit, social security standard.If the user without the social security information, It is 0 then to define the described 7th and calculate factor G.If conversely, the user has social security information, in step S10172, obtain The endowment desired value G of user1, and according to formulaObtain the 7th calculating factor G, wherein the A be first calculate because Element, the V are the average value of the different social security standard in each city.Based on above description as can be seen that the social security in each city Standard means are higher, then user more pays close attention to insurance；The endowment desired value of user is higher, then volume of insuring increases, to a certain extent Reduce the described 7th and calculates factor G.
Further, next the sub- embodiment as step S1018 in embodiment illustrated in fig. 2 is accustomed to the user Acquisition and the calculating of the 8th factor carried out relatively sharp description.Specifically, in the present embodiment, the user Whether whether whether behavioural habits include whether to have a meal on time, go to bed, drink on time, smoking, taking regular exercise.Specifically Ground, the described 8th calculates factor H according to formulaWherein, when having a meal on time, H1It is 1, no When having a meal on time, H1It is 0；H.d. on time, H2It is 1, is late for h.d., H2It is 0；When drinking, H3It is 0, when no drinking, H3For 1；When smoking, H4It is 0, when not smoking, H4It is 1；When taking regular exercise, H5It is 1, when infrequently moving, H5It is 0.Based on above description As can be seen that living habit is more healthy, the described 8th to calculate factor H bigger, it is no it, the described 8th to calculate factor H smaller.
Further, Fig. 9 shows another embodiment of the present invention, and user is determined based on the essential information of the user The flow chart of the desired value of the priority of multiple risks and the multiple risks of user.A son as step S102 in Fig. 1 is real Example is applied, is specifically comprised the following steps：
Step S1021 determines that the priority of the multiple risks of user and user are multiple based on the first essential information of user The desired value of risk.Wherein, first essential information includes but not limited to the age of the user, gender, income, is good for The information such as health situation.Further, based on the data analysis to first essential information, present in user described in comprehensive descision Multiple risks, the plurality of risk has corresponding type of insurance, such as life insurance, serious illness insurance, medical insurance etc..According to The significance level and urgency level of different risks are ranked up confirmation to its priority, such as health status is poorer, serious illness insurance, The priority of medical insurance is higher；Meanwhile also to being matched with the guarantee amount of adaptation desired by the user.
Step S1022, the family structure information based on user judge whether that with spouse, the family structure information is as before Described includes the situations such as unmarried, married, divorce.Further, if there is spouse, S1023 is thened follow the steps, first based on user Essential information determines the expection of the priority and the multiple risks of spouse of the multiple risks of spouse, specifically, above-mentioned step can be referred to Rapid S1021, it should be noted that described due to the difference that spouse and user pay etc. in gender, age, income Type, priority and the desired value of the multiple risks of spouse and the type, priority and expection of multiple risks of the user are deposited In difference.After executing step S1023, then execute step S1024.If conversely, not having spouse, it can save and obtain spouse The expection of multiple risk priorities and the multiple risks of spouse, and it is directly entered step S1024.
In step S1024, the family structure information based on user judges whether with children.Specifically, in conjunction with above-mentioned Step S1022, the user have children situation include, it is married educated and divorced do not educate；And without children Situation, then include married not educating situation.If the user has children, in step S1025, the first base based on user This information determines the priority of the multiple risks of children and the desired value of the multiple risks of children, specifically, can refer to above-mentioned step Rapid S1021, it should be noted that the children due to the age, gender, take in, situation of receiving an education etc. it is many-sided exist it is different, Therefore the type of the multiple risks of children, priority and expection have differences with the user and its spouse.It is executing After step S1025, then execute step S1026.If conversely, the user does not have children, it is directly entered step S1026.
Further, step S1026, the assets information based on user judge whether with property, the assets of the user Information includes the assets such as deposit, house property, the vehicle of user.If the user has property, in step S1027, it is based on user The first essential information determine the expection of the multiple risk priorities of property and the multiple risks of property.Multiple risks of the property Correspond to vehicle insurance, family property insurance and property trust etc..In a concrete application, the expection of the multiple risks of property can be Vehicle insurance three blames the dangerous local third party people of guarantee amount covering and hinders the residue after accident highest compensation standard deduction compulsory insurance for traffic accident of motor-drivenvehicle protection amount Part.It is possible that the guarantee amount of family property insurance can compensate for house, decoration, indoor property etc. caused by the generation of disaster or accident Loss.The family assets selection that the guarantee amount of property trust passes on as needed, generally the 50% of family assets accumulation are left It is right.
Further, a sub- embodiment as step S1021 in above-mentioned Fig. 9, Figure 10 show the implementation of the present invention Example, the priority of the multiple risks of user and the desired value of the multiple risks of user are determined based on the first essential information of user Flow chart.It in turn includes the following steps：
Step S10211 determines user's weight disease, accident, life insurance and medical treatment successively based on the first essential information of user Degree of priority value.Specifically, according to physical condition, job category, the age etc. in the first essential information of the user Information can go out the requirements of support of the user for above-mentioned four classes risk in conjunction with big data analysis with comprehensive descision.
Then, by step S10212, the heavy disease of the user, accident, life insurance and the degree of priority of medical treatment value are pressed Quantization sequence is carried out according to sequence from big to small, determines the priority of the multiple risks of user.Such as preferred medical insurance is insured, is excellent Disease insurance is first weighed, recommends accident/injury insurance, recommend life insurance.
Further, in step S10213, based on user the first essential information successively determine user weight disease, accident, Life insurance and the desired value of medical treatment.The amount insured of the insurance kinds such as the desired value and above-mentioned user weight disease, accident, life insurance and medical treatment The expection of degree.Such as the user it is expected the guarantees amount of life insurance and accident/injury insurance cover family loan balance, The expenses such as bring up one's children, support one's parents, and once the family income loss brought of dieing.The guarantee amount of major disease insurance The diagnoses and treatment expense of 25 kinds of major diseases and rehabilitative sanatorium care as defined in covering Insurance Regulatory Commission take.The guarantee amount of medical insurance covers The medical expense that the social securities such as the Emergency call expense, Operation Fee, the hospitalization benefit that occur during institute can not be submitted an expense account.
Further, user insure weight disease degree of priority value obtained by following formula：Wherein, A first Calculating factor, C are that third calculates factor, and H is the 8th calculating factor.Its influence factor includes age of user, permanent place, receipts Enter and the behavioural habits of the user.
Correspondingly, the user unexpected degree of priority value of insuring is obtained by following formula：J=ACF；Wherein A is the One calculates factor, and C is that third calculates factor, and F is the 6th calculating factor.Its influence factor includes age, permanent of the user Place, income and liability information.
Correspondingly, the insure degree of priority value of life insurance of the user is obtained by following formula：K=ACE；Wherein, A One calculates factor, and C is that third calculates factor, and E is the 5th calculating factor.Its influence factor include age of user, permanent place, Take in information and assets information.
Correspondingly, the user insure medical treatment degree of priority value obtained by following formula：Wherein G is the Seven calculate factor, and H is the 8th calculating factor.Its influence factor includes the social security information, endowment desired value and row of the user For custom.
Further, in the step S10213, the user insure weight disease desired value obtained by following formula：
NI=(C1+C2+E1+E2)I；
Wherein, C1、C2The respectively miscellaneous receipt information of the income information of user and family；E1、E2Respectively user deposits Money, stock, the property summation of fund information and user's house and or vehicle property summation；I insures for the user and weighs disease Degree of priority value.
Correspondingly, the user unexpected desired value of insuring is obtained by following formula：
NJ=(C1+C2+E1+E2)J；
Wherein, C1、C2The respectively miscellaneous receipt information of the income information of user and family；E1、E2Respectively user deposits Money, stock, the property summation of fund information and user's house and or vehicle property summation；J is that the user insures accident Degree of priority value.
The insure desired value of life insurance of the user is obtained by following formula：
NK=(C1+C2+E1+E2)K；
Wherein, C1、C2The respectively miscellaneous receipt information of the income information of user and family；E1、E2Respectively user deposits Money, stock, the property summation of fund information and user's house and or vehicle property summation；K is that the user insures life insurance Degree of priority value.
The user insure medical treatment desired value obtained by following formula:
NL=(C1+C2+E1+E2)L。
Wherein, C1、C2The respectively miscellaneous receipt information of the income information of user and family；E1、E2Respectively user deposits Money, stock, the property summation of fund information and user's house and or vehicle property summation；L is that the user insures medical treatment Degree of priority value.
Further, a sub- embodiment as step S1023 in above-mentioned Fig. 9, Figure 11 show the implementation of the present invention Example, the priority of the multiple risks of spouse and the desired value of the multiple risks of spouse are determined based on the first essential information of user Flow chart.Specifically comprising following steps：
Step S10231 determines spouse's weight disease, accident, life insurance and medical treatment successively based on the first essential information of user Degree of priority, those skilled in the art can refer to step S10211 and its specific implementation mode in above-mentioned Figure 10, refuse herein It repeats.
Step S10232, to the heavy disease of the spouse, accident, life insurance and the degree of priority of medical treatment value according to from big to small Sequence be ranked up, determine the priority of the multiple risks of spouse, specifically, those skilled in the art can refer to above-mentioned Figure 10 Middle step S10212 and its specific implementation mode, it will not be described here.
Step S10233 determines spouse's weight disease, accident, life insurance and medical treatment successively based on the first essential information of user Desired value, specifically, those skilled in the art can refer to step S10213 and embodiments thereof in above-mentioned Figure 10, refuse herein It repeats.
Further, in the step S10231, the spouse insure weight disease degree of priority value pass through following formula It obtains：The spouse unexpected degree of priority value of insuring is obtained by following formula：J=ACF；The spouse insures The degree of priority value of life insurance is obtained by following formula：K=ACE；The spouse insure medical treatment degree of priority value pass through it is as follows Formula obtains：More specifically, those skilled in the art can refer to step S10211 and in fact in above-mentioned Figure 10 It applies mode to insure weight disease, accident, description as described in life insurance and medical treatment such as the user, it will not be described here.
Further, in the step S10233, the spouse insure weight disease desired value obtained by following formula：
NI=(C1+C2+E1+E2)I；
The spouse unexpected desired value of insuring is obtained by following formula：
NJ=(C1+C2+E1+E2)J；
The insure desired value of life insurance of the spouse is obtained by following formula：
NK=(C1+C2+E1+E2)K；
The spouse insure medical treatment desired value obtained by following formula:
NL=(C1+C2+E1+E2)L。
Specifically, those skilled in the art can refer to insure weights of the step S10213 about the user in above-mentioned Figure 10 The description of disease, accident, life insurance and the desired value of medical treatment, it will not be described here.
As a sub- embodiment of step S1025 in above-mentioned Fig. 9, Figure 12 shows the embodiment of the present invention, obtains The assets information of user calculates the 5th flow chart for calculating factor E based on the assets information.In such embodiments, have Body includes the following steps：
Step S10251 determines children's education, weight disease, unexpected and medical successively based on the first essential information of user Degree of priority value.In this step, the risk of children and user and its spouse have weight disease, accident and medical treatment Three, include education difference lies in children, without including life insurance in Inner.Its respective degree of priority value is by the described first basic letter The influence of neutron woman's health degree, situation of receiving an education is ceased, it will not be described here.
Step S10252, to the educating of the children, weight disease, unexpected and medical degree of priority value according to from big to small Sequence be ranked up, determine the priority of the multiple risks of children.The present invention is based on big data analysis to above-mentioned different risk Classification carries out quantitative analysis, and to its degree of priority value according to being ranked sequentially from big to small.
Step S10253 determines children's education, weight disease, unexpected and medical successively based on the first essential information of user Desired value.Specifically, comprehensive analysis is carried out to the relevant information for including in first essential information using big data, to right Children's education, weight disease, unexpected and medical desired value are determined.
Specifically, those skilled in the art can refer to above-mentioned Figure 10, Figure 11 and its specific embodiment, not superfluous herein It states.
Further, in a preferred variant of the step S10251, the present invention also insures religion to the children The degree of priority value educated is obtained by following formula：
Wherein, C, D, E, F be respectively third calculate factor, the 4th calculating factor, the 5th calculating factor, the 6th calculate because Element.Its influence factor is respectively income, expenditure, assets and the liability information of the family of the children, the BxFor the son The second of woman's age calculates factor.
Further, the children insure weight disease degree of priority value obtained by following formula：
Wherein, A, C, H are respectively the first calculating factor, third calculating factor and the 8th calculating factor.Its influence factor Age, permanent place and the behavioural habits of the respectively described children, the BxFor the children age second calculate because Element.
The children unexpected degree of priority value of insuring is obtained by following formula：
Wherein, described A, C, F are respectively the first calculating factor, third calculating factor and the 6th calculating factor.It is influenced Factor is the age of the children, permanent place, family income, family's liability information, the BxFor the age of the children Second calculates factor.
The children insure medical treatment degree of priority value obtained by following formula：
Wherein, described A, C, E are respectively the first calculating factor, third calculating factor and the 5th calculating factor.It is influenced Factor is respectively age of the children, permanent place, family income, family assets information, the BxFor the year of the children The second of age calculates factor.
Further, in the step S10253, the insure desired value of education of the children is obtained by following formula：
WO=(C1+C2+E1+E2)O；
The children insure weight disease desired value obtained by following formula：
WP=(C1+C2+E1+E2)P；
The children unexpected desired value of insuring is obtained by following formula：
WQ=(C1+C2+E1+E2)Q；
The children insure medical treatment desired value obtained by following formula：
WU=(C1+C2+E1+E2)U。
Specifically, those skilled in the art can refer to insure weights of the step S10213 about the user in above-mentioned Figure 10 The description of disease, accident, life insurance and the desired value of medical treatment, it will not be described here.
Further, a sub- embodiment as step S1027 in above-mentioned Fig. 9, Figure 13 show the implementation of the present invention Example, the priority of the multiple risks of property and the desired value of the multiple risks of property are determined based on the first essential information of user Flow chart.Specifically, the present embodiment includes the following steps：
Step S10271, based on user the first essential information determine successively property vehicle three blame, the degree of priority of family property Value.Specifically, those skilled in the art can refer to step S10211 and embodiment in above-mentioned Figure 10.
Step S10272 carries out the property vehicle three duty, the degree of priority value of family property according to sequence from big to small Sequence, determines the priority of the multiple risks of property.Specifically, those skilled in the art can refer to step in above-mentioned Figure 10 S10212 and embodiment.
Step S10273 determines three duty of property vehicle, the desired value of family property successively based on the first essential information of user.Tool Body, those skilled in the art can refer to step S10213 and embodiment in above-mentioned Figure 10.It should be noted that above-mentioned step Rapid S10271, step S10272 and step S10273 are different from step S10211 in Figure 10, step S10212, step S10213 Difference lies in the corresponding risk classifications of different home member have differences and specific control method by big data analysis and machine Device learning algorithm obtains.
Further, in another preferred change case of the step S10271 of the present invention, if E1More than E2, then preferential to throw Family property is protected, if E1Less than E2, then vehicle three of insuring duty.In such embodiments, if E1More than E2, indicate the preferential journey of family property Angle value is more than the degree of priority value that vehicle three is blamed, then family property of preferentially insuring；If conversely, E1Less than E2, indicate that vehicle three is blamed preferential Degree value is more than family property, then vehicle three of preferentially insuring duty.
Correspondingly, in a preferred change case of the step S10273 of the present invention,
The property insure vehicle three duty desired value obtained by following formula：
Wherein, wherein C1、C2The respectively miscellaneous receipt information of the income information of user and family；E1、E2Respectively use Deposit, stock, the property summation of fund information and user's house at family and or vehicle property summation；A be first calculate because Element, T are the user's assets constant counted in big data.
Further, the insure desired value of family property of the property is obtained by following formula：
Wherein, wherein C1、C2The respectively miscellaneous receipt information of the income information of user and family；E1、E2Respectively use Deposit, stock, the property summation of fund information and user's house at family and or vehicle property summation；A be first calculate because Element, T are the user's assets constant counted in big data.
To sum up, the present invention ensures that amount is calculated confirmation according to its priority to the desired value of different risk classifications, In the concrete application scene of the present invention, the guarantee amount of life insurance and accident/injury insurance can cover family Loan balance, the expenses such as bring up one's children, support one's parents, and once the family income loss brought of dieing.Major disease is insured Guarantee amount covering Insurance Regulatory Commission as defined in 25 kinds of major diseases diagnoses and treatment expense and rehabilitative sanatorium care take.The guarantee of medical insurance The medical expense that the social securities such as Emergency call expense, Operation Fee, the hospitalization benefit that amount covering occurs during being hospitalized can not be submitted an expense account.Endowment Wish the endowment insurance money notch total value got in the several years after guarantee amount covering insurant's retirement of annuity.Education The expense expenditure in guarantee amount covering children's non-compulsory education stage of gold insurance.It is local that vehicle insurance three blames dangerous guarantee amount covering Third party people hinders accident highest and compensates the remainder after standard deduction compulsory insurance for traffic accident of motor-drivenvehicle protection amount.The guarantee amount of family property insurance can compensate for House, decoration, indoor property etc. can the loss of energys caused by the generation of disaster or accident.The guarantee amount of property trust is according to need The family assets to be passed on selection, generally 50% or so of family assets accumulation.
Specific embodiments of the present invention are described above.It is to be appreciated that the invention is not limited in above-mentioned Particular implementation, those skilled in the art can make various deformations or amendments within the scope of the claims, this not shadow Ring the substantive content of the present invention.

Claims (25)

1. a kind of control method for establishing subscriber household insurance cover combined system, successively according to the family structure information of user Determine the priority of the multiple risks of user and the desired value of the multiple risks of user, which is characterized in that include the following steps：
a：One or more essential informations based on user calculate one or more calculating factors of user；
b：The priority of the multiple risks of user and the desired value of the multiple risks of user are determined based on the essential information of the user.
2. control method according to claim 1, which is characterized in that the step a includes the following steps：
a1：It obtains the gender of user, permanent place, and the gender based on user, permanent location calculations first and calculates factor A；
a2：Family structure information is obtained, based on the age of the family structure acquisition of information subscriber household member, and based on described The age of subscriber household member obtains second and calculates factor B；
a3：The income information for obtaining user and subscriber household member calculates third based on the income information and calculates factor C；
a4：The expenditure information for obtaining user and subscriber household member calculates the 4th based on the expenditure information and calculates factor D；
a5：The assets information for obtaining user calculates the 5th based on the assets information and calculates factor E；
a6：The liability information for obtaining user calculates the 6th based on the liability information and calculates factor F；
a7：The social security information and endowment desired value for obtaining user, social security information and endowment desired value based on the user calculate 7th calculates factor G；
a8：The behavioural habits for obtaining user, the behavioural habits based on the user calculate the 8th and calculate factor H.
3. computational methods according to claim 2, which is characterized in that the family structure information includes following several feelings Condition：
It is unmarried；
It is married not educate；
It is married to have educated；
Divorce has been educated.
4. computational methods according to claim 3, which is characterized in that if unmarried, then described in family's structural information It is B that the second of unmarried age, which calculates factor,1；It is not educated if married, then second meter at the age in the family structure information Calculation factor is B21、B22；It has been educated if married, then it is B that second of the age in the family structure information, which calculates factor,31、B32、 B33…B3x；It has been educated if divorce, then it is B that second of the age in the family structure information, which calculates factor,41、B42、B43…B4x。
5. computational methods according to claim 4, which is characterized in that described second calculates factor according to the family structure The age of different members obtains in information, is obtained according to following formula：Wherein, the value of the x be 1~ 60。
6. computational methods according to claim 2, which is characterized in that the step a1 includes the following steps：
a11：It is then A to obtain the gender value corresponding to the gender of user if male based on big data11, if women, then For A12；
a12：It is multiple values according to the grade classification in city, obtains the value A in the permanent place of user2；
a13：Based on formula A=0.6A1m+0.4A2, obtain first and calculate factor A, wherein and if male, then A1mFor A11, if Women, then A1mFor A12, the A2For the value in the permanent place of user.
7. computational methods according to claim 2, which is characterized in that the step a3 includes the following steps：
a31：Obtain the income information C of user1；
a32：Obtain the miscellaneous receipt information C of family2；
a33：Based on formulaIt obtains the third and calculates factor C, wherein the A is the first calculating factor A, institute It is that the user counted in big data takes in constant to state S.
8. computational methods according to claim 2, which is characterized in that the step a4 includes the following steps：
a41：Obtain the daily total expenses information D of user1；
a42：Obtain the information on spending D that supports one's parents of user2；
a43：Children's education information on spending D is judged whether based on the family structure information3, and if it exists, it thens follow the steps A44 thens follow the steps a45 if being not present；
a44：Obtain the children's education information on spending D of user3, and according to formulaObtain the expenditure information meter Calculate the 4th calculating factor D；
a45：According to formulaIt obtains the described 4th and calculates factor D.
9. computational methods according to claim 2, which is characterized in that the step a5 includes the following steps：
a51：Obtain the deposit of user, the property summation E of stock, fund information1；
a52：Judge user whether have house and or vehicle, if so, then obtain user's house and or vehicle property summation E2, and hold Row step a53 thens follow the steps a54 if not having；
a53：According to formulaIt obtains the described 5th and calculates factor E；Wherein, the T is the use counted in big data Family assets constant.
a54：According to formulaIt obtains the described 5th and calculates factor E.
10. computational methods according to claim 2, which is characterized in that the step a6 includes the following steps：
a61：Judge whether user has liability information, if so, thening follow the steps a62, if not having, it is 1 to define F；
a62：Obtain the moon refund information F of user1；
a63：Obtain the refund temporal information F of user2；
a64：Based on formulaIt obtains the described 6th and calculates factor F, wherein the A is the first calculating factor, described R is constant of being in debt in big data.
11. computational methods according to claim 2, which is characterized in that the step a7 includes：
a71：Judge whether user has social security information, if so, thening follow the steps a72, if nothing, it is 0 to define G；
a72：Obtain the endowment desired value G of user1, and according to formulaObtain the 7th calculating factor G, wherein the A Factor is calculated for first, the V is the average value of the different social security standard in each city.
12. computational methods according to claim 2, which is characterized in that in the step a8, the behavior of the user is practised It is used to include whether to have a meal on time, whether go to bed, whether drink on time, whether smoking, whether taking regular exercise, the described 8th calculate because Plain H is according to formulaIt obtains, wherein when having a meal on time, H1It is 1, when being late for having a meal, H1 It is 0；H.d. on time, H2It is 1, is late for h.d., H2It is 0；When drinking, H3It is 0, when no drinking, H3It is 1；When smoking, H4For 0, when not smoking, H4It is 1；When taking regular exercise, H5It is 1, when infrequently moving, H5It is 0.
13. computational methods according to any one of claim 1 to 11, which is characterized in that the step b includes following step Suddenly：
b1：Based on user the first essential information determine the multiple risks of user priority and the multiple risks of user expection Value；
b2：Family structure information based on user judges whether with spouse, if having, thens follow the steps b3, if not having, Execute step b4：
b3：Based on user the first essential information determine the multiple risks of spouse priority and the multiple risks of spouse expection Value；
b4：Family structure information based on user judges whether with children, if having, thens follow the steps b5, if not having, Execute step b6；
b5：Based on user the first essential information determine the multiple risks of children priority and the multiple risks of children expection Value；
b6：Assets information based on user judges whether with property, if having, thens follow the steps b7；
b7：Based on user the first essential information determine the multiple risks of property priority and the multiple risks of property expection Value.
14. computational methods according to claim 13, which is characterized in that the step b1 includes the following steps：
b11：User's weight disease, accident, life insurance and the degree of priority value of medical treatment are determined successively based on the first essential information of user；
b12：The heavy disease of the user, accident, life insurance and the degree of priority of medical treatment value are carried out according to sequence from big to small Sequence, determines the priority of the multiple risks of user；
b13：User's weight disease, accident, life insurance and the desired value of medical treatment are determined successively based on the first essential information of user.
15. computational methods according to claim 14, which is characterized in that in the step b11, the user insures again The degree of priority value of disease is obtained by following formula：
The user unexpected degree of priority value of insuring is obtained by following formula：J=ACF；
The insure degree of priority value of life insurance of the user is obtained by following formula：K=ACE；
The user insure medical treatment degree of priority value obtained by following formula：
16. computational methods according to claim 14, which is characterized in that in the step b13, the user insures again The desired value of disease is obtained by following formula：NI=(C1+C2+E1+E2)I；
The user unexpected desired value of insuring is obtained by following formula：NJ=(C1+C2+E1+E2)J；
The insure desired value of life insurance of the user is obtained by following formula：NK=(C1+C2+E1+E2)K；
The user insure medical treatment desired value obtained by following formula:NL=(C1+C2+E1+E2)L。
17. computational methods according to claim 13, which is characterized in that the step b3 includes the following steps：
b31：Spouse's weight disease, accident, life insurance and the degree of priority value of medical treatment are determined successively based on the first essential information of user；
b32：The heavy disease of the spouse, accident, life insurance and the degree of priority of medical treatment value are carried out according to sequence from big to small Sequence, determines the priority of the multiple risks of spouse；
b33：Spouse's weight disease, accident, life insurance and the desired value of medical treatment are determined successively based on the first essential information of user.
18. computational methods according to claim 17, which is characterized in that in the step b31, the spouse insures again The degree of priority value of disease is obtained by following formula：
The spouse unexpected degree of priority value of insuring is obtained by following formula：J=ACF；
The insure degree of priority value of life insurance of the spouse is obtained by following formula：K=ACE；
The spouse insure medical treatment degree of priority value obtained by following formula：
19. computational methods according to claim 17, which is characterized in that in the step b33, the spouse insures again The desired value of disease is obtained by following formula：NI=(C1+C2+E1+E2)I；
The spouse unexpected desired value of insuring is obtained by following formula：NJ=(C1+C2+E1+E2)J；
The insure desired value of life insurance of the spouse is obtained by following formula：NK=(C1+C2+E1+E2)K；
The spouse insure medical treatment desired value obtained by following formula:NL=(C1+C2+E1+E2)L。
20. computational methods according to claim 13, which is characterized in that the step b5 includes the following steps：
b51：Children's education, weight disease, unexpected and medical degree of priority value are determined successively based on the first essential information of user；
b52：The educating of the children, weight disease, unexpected and medical degree of priority value are carried out according to sequence from big to small Sequence, determines the priority of the multiple risks of children；
b53：Children's education, weight disease, unexpected and medical desired value are determined successively based on the first essential information of user.
21. computational methods according to claim 20, which is characterized in that in the step b51, the children insure religion The degree of priority value educated is obtained by following formula：
The children insure weight disease degree of priority value obtained by following formula：
The children unexpected degree of priority value of insuring is obtained by following formula：
The children insure medical treatment degree of priority value obtained by following formula：
22. computational methods according to claim 20, which is characterized in that in the step b53, the children insure religion The desired value educated is obtained by following formula：WO=(C1+C2+E1+E2)O；
The children insure weight disease desired value obtained by following formula：WP=(C1+C2+E1+E2)P；
The children unexpected desired value of insuring is obtained by following formula：WQ=(C1+C2+E1+E2)Q；
The children insure medical treatment desired value obtained by following formula：WU=(C1+C2+E1+E2)U。
23. computational methods according to claim 13, which is characterized in that the step b7 includes the following steps：
b71：Three duty of property vehicle, the degree of priority value of family property are determined successively based on the first essential information of user；
b72：The property vehicle three duty, the degree of priority value of family property are ranked up according to sequence from big to small, determine wealth Produce the priority of multiple risks；
b73：Three duty of property vehicle, the desired value of family property are determined successively based on the first essential information of user.
24. computational methods according to claim 23, which is characterized in that in the step b71, if E1More than E2, then excellent It first insures family property, if E1Less than E2, then vehicle three of insuring duty.
25. computational methods according to claim 23, which is characterized in that in the step b73, the property is insured vehicle The desired values of three duties are obtained by following formula：
The insure desired value of family property of the property is obtained by following formula：
CN201810393565.9A 2018-04-27 2018-04-27 A kind of control method for establishing subscriber household insurance cover combined system Pending CN108596773A (en)

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Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108961073A (en) * 2018-06-14 2018-12-07 中国平安人寿保险股份有限公司 A kind of recommended method of insurance products, storage medium and server
CN109272362A (en) * 2018-09-29 2019-01-25 阿里巴巴集团控股有限公司 A kind of method for pushing, device and the electronic equipment of risk guarantee product
CN109300017A (en) * 2018-10-27 2019-02-01 平安科技（深圳）有限公司 Declaration form recommended method, device, server and storage medium based on data analysis
CN109492885A (en) * 2018-10-25 2019-03-19 平安医疗健康管理股份有限公司 Medical insurance risk project analysis method device, terminal and readable medium
CN110399559A (en) * 2019-07-26 2019-11-01 阳光保险集团股份有限公司 Intelligence insurance recommender system and computer storage medium
CN110674465A (en) * 2019-09-03 2020-01-10 北京量子保科技有限公司 Risk evaluation method, device, medium and electronic equipment
CN110910256A (en) * 2019-10-28 2020-03-24 世纪保众(北京)网络科技有限公司 Family risk evaluation method and device based on family member attributes
CN113724038A (en) * 2021-08-02 2021-11-30 泰康保险集团股份有限公司 Method, device, equipment and medium for personalized recommendation of insurance products
CN117670510A (en) * 2023-11-30 2024-03-08 广东省中保小额贷款股份有限公司 Small loan management system

Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108961073A (en) * 2018-06-14 2018-12-07 中国平安人寿保险股份有限公司 A kind of recommended method of insurance products, storage medium and server
CN109272362A (en) * 2018-09-29 2019-01-25 阿里巴巴集团控股有限公司 A kind of method for pushing, device and the electronic equipment of risk guarantee product
CN109492885A (en) * 2018-10-25 2019-03-19 平安医疗健康管理股份有限公司 Medical insurance risk project analysis method device, terminal and readable medium
CN109492885B (en) * 2018-10-25 2024-02-09 平安医疗健康管理股份有限公司 Medical insurance risk project analysis method and device, terminal and readable medium
CN109300017A (en) * 2018-10-27 2019-02-01 平安科技（深圳）有限公司 Declaration form recommended method, device, server and storage medium based on data analysis
CN110399559A (en) * 2019-07-26 2019-11-01 阳光保险集团股份有限公司 Intelligence insurance recommender system and computer storage medium
CN110674465A (en) * 2019-09-03 2020-01-10 北京量子保科技有限公司 Risk evaluation method, device, medium and electronic equipment
CN110910256A (en) * 2019-10-28 2020-03-24 世纪保众(北京)网络科技有限公司 Family risk evaluation method and device based on family member attributes
CN113724038A (en) * 2021-08-02 2021-11-30 泰康保险集团股份有限公司 Method, device, equipment and medium for personalized recommendation of insurance products
CN117670510A (en) * 2023-11-30 2024-03-08 广东省中保小额贷款股份有限公司 Small loan management system

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Application publication date: 20180928