CN108961073B - Recommendation method of insurance products, storage medium and server - Google Patents
Recommendation method of insurance products, storage medium and server Download PDFInfo
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- CN108961073B CN108961073B CN201810613852.6A CN201810613852A CN108961073B CN 108961073 B CN108961073 B CN 108961073B CN 201810613852 A CN201810613852 A CN 201810613852A CN 108961073 B CN108961073 B CN 108961073B
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Abstract
The invention relates to the technical field of finance, and provides a recommendation method, a storage medium and a server for insurance products. The recommendation method of the insurance product comprises the following steps: acquiring characteristic information of a recommended object; calculating a target guarantee limit which the recommended object should have according to the characteristic information; product parameters of all insurance products are respectively obtained, wherein the product parameters comprise the guarantee limit which can be provided by the insurance products; determining an insurance product combination matched with the target guarantee limit according to the product parameters of each insurance product; recommending the insurance product combination to the recommended object. According to the method, the guarantee limit which the recommended object should have can be obtained through calculation according to the characteristic information of the recommended object, and then the insurance product combination matched with the guarantee limit is automatically generated by combining the product parameters of each existing insurance product, so that the appropriate insurance product can be recommended for the client in a targeted manner, and the service popularization effect is effectively improved.
Description
Technical Field
The present invention relates to the field of financial technologies, and in particular, to a recommendation method, a storage medium, and a server for insurance products.
Background
During the promotion of insurance services, a salesman can usually only recommend insurance products to customers according to experience values. However, since social personnel have different personal conditions and various insurance products, different product terms and application scenes are provided among the insurance products, and operators can hardly determine the insurance products suitable for clients through self-analysis, the service popularization effect is poor.
Disclosure of Invention
In view of the above, the embodiment of the invention provides a recommendation method, a storage medium and a server for insurance products, which aim to solve the problem that insurance products suitable for clients are difficult to determine in the insurance recommendation process and the service popularization effect is poor.
In a first aspect of an embodiment of the present invention, there is provided a recommendation method for an insurance product, including:
acquiring characteristic information of a recommended object;
calculating a target guarantee limit which the recommended object should have according to the characteristic information;
product parameters of all insurance products are respectively obtained, wherein the product parameters comprise the guarantee limit which can be provided by the insurance products;
determining an insurance product combination matched with the target guarantee limit according to the product parameters of each insurance product;
Recommending the insurance product combination to the recommended object.
In a second aspect of the embodiments of the present invention, there is provided a computer readable storage medium storing computer readable instructions which, when executed by a processor, implement the steps of the insurance product recommendation method as set forth in the first aspect of the embodiments of the present invention.
In a third aspect of the embodiments of the present invention, there is provided a server comprising a memory, a processor and computer readable instructions stored in the memory and executable on the processor, the processor executing the computer readable instructions to perform the steps of:
acquiring characteristic information of a recommended object;
calculating a target guarantee limit which the recommended object should have according to the characteristic information;
product parameters of all insurance products are respectively obtained, wherein the product parameters comprise the guarantee limit which can be provided by the insurance products;
determining an insurance product combination matched with the target guarantee limit according to the product parameters of each insurance product;
recommending the insurance product combination to the recommended object.
The recommendation method of the insurance product provided by the embodiment of the invention comprises the following steps: acquiring characteristic information of a recommended object; calculating a target guarantee limit which the recommended object should have according to the characteristic information; product parameters of all insurance products are respectively obtained, wherein the product parameters comprise the guarantee limit which can be provided by the insurance products; determining an insurance product combination matched with the target guarantee limit according to the product parameters of each insurance product; recommending the insurance product combination to the recommended object. According to the method, the guarantee limit which the recommended object should have can be obtained through calculation according to the characteristic information of the recommended object, and then the insurance product combination matched with the guarantee limit is automatically generated by combining the product parameters of each existing insurance product, so that the appropriate insurance product can be recommended for the client in a targeted manner, and the service popularization effect is effectively improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments or the description of the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a first embodiment of a method for recommending insurance products according to an embodiment of the present invention;
FIG. 2 is a flow chart of a second embodiment of a recommendation method for insurance products provided in accordance with an embodiment of the present invention;
FIG. 3 is a flow chart of a third embodiment of a recommendation method for insurance products provided in accordance with an embodiment of the present invention;
FIG. 4 is a block diagram of one embodiment of a recommendation device for insurance products provided in accordance with an embodiment of the present invention;
fig. 5 is a schematic diagram of a server according to an embodiment of the present invention.
Detailed Description
The embodiment of the invention provides a recommendation method, a storage medium and a server for insurance products, and aims to solve the problems that insurance products suitable for clients are difficult to determine in the insurance recommendation process and service popularization effects are poor.
In order to make the objects, features and advantages of the present invention more comprehensible, the technical solutions in the embodiments of the present invention are described in detail below with reference to the accompanying drawings, and it is apparent that the embodiments described below are only some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a first embodiment of a recommendation method for insurance products according to an embodiment of the present invention includes:
101. acquiring characteristic information of a recommended object;
first, feature information of a recommended object is acquired. The recommended object can be an applicable target of insurance products such as a person or a car, and if the recommended object is a person, the characteristic information can be information such as age, occupation, income, health record and the like; if the recommended object is a car, the feature information can be information such as a car type, a car age, a running mileage number and the like.
102. Calculating a target guarantee limit which the recommended object should have according to the characteristic information;
after feature information of a recommended object is obtained, calculating a target guarantee limit which the recommended object should have according to the feature information. Specifically, a preset calculation model may be adopted, the feature information is used as an input parameter to perform calculation, and a calculation result is used as a target guarantee limit to be output.
103. Respectively acquiring product parameters of each insurance product;
and respectively acquiring product parameters of each insurance product, wherein the product parameters comprise the guarantee limit which can be provided by the insurance product. It should be noted that the target guarantee limit may be a guarantee limit of multiple aspects, and the guarantee limit that the insurance product can provide may also be a guarantee limit of multiple aspects. For example, the target guarantee limit is 150 ten thousand, including 100 ten thousand of the stature guarantee limit and 50 ten thousand of the serious disease guarantee limit; the insurance product A can provide 20 ten thousand of the fortification guarantee line and 40 ten thousand of the serious disease guarantee line in unit insurance fee (for example, 1 ten thousand).
104. Determining an insurance product combination matched with the target guarantee limit according to the product parameters of each insurance product;
after obtaining the product parameters of the existing individual insurance products, determining the insurance product combination matching the target guarantee amount according to the product parameters of the individual insurance products. Specifically, the sum of the guarantee limits that can be provided by the respective insurance products in the insurance product combination matching the target guarantee limit should be greater than or equal to the target guarantee limit. If the target guarantee line is a unilateral guarantee line, such as 100 ten thousand statue guarantee lines, and the insurance product a can provide 40 ten thousand statue guarantee lines and the insurance product B can provide 60 ten thousand statue guarantee lines, the insurance product combination formed by the insurance products a and B is a group of insurance product combinations matching the target guarantee line. If the target guarantee limit is a multi-aspect guarantee limit, the matched insurance product combination can provide the guarantee limit of each aspect, and the requirement of the target guarantee limit needs to be met. For example, if the target guarantee limit is 100 ten thousand of the statue guarantee limit and 50 ten thousand of the serious disease guarantee limit, and the insurance product a can provide 40 ten thousand of the statue guarantee limit and 20 ten thousand of the serious disease guarantee limit, the insurance product B can provide 60 ten thousand of the statue guarantee limit, and the insurance product C can provide 30 ten thousand of the serious disease guarantee limit, the insurance product combination formed by the insurance products A, B and C is a group of insurance product combinations matching the target guarantee limit.
Obviously, the number of combinations of insurance products obtained in the manner described above is high, due to the wide variety of insurance products. To more specifically recommend insurance products for customers, step 104 may specifically include one of 3 ways:
mode 1:
(1) Searching a first insurance product which can provide a guarantee limit closest to the target guarantee limit from the insurance products;
(2) If the guarantee limit which can be provided by the first insurance product is greater than or equal to the target guarantee limit, determining the first insurance product as an insurance product combination matched with the target guarantee limit;
(3) If the guarantee limit which can be provided by the first insurance product is smaller than the target guarantee limit, calculating the difference between the guarantee limit which can be provided by the first insurance product and the target guarantee limit, and searching a second insurance product which is closest to the difference and can be provided by the first insurance product from the insurance products;
(4) If the guarantee limit which can be provided by the second insurance product is greater than or equal to the difference value, determining the first insurance product and the second insurance product as an insurance product combination matched with the target guarantee limit;
(5) If the guarantee limit which can be provided by the second insurance product is smaller than the difference value, continuously calculating the difference value between the guarantee limit which can be provided by the second insurance product and the difference value until the insurance product combination with the sum of the guarantee limit which can be provided being greater than or equal to the target guarantee limit is obtained.
Assuming that the target guarantee amount is 100 ten thousand, the available guarantee amount and 100 ten thousand nearest first insurance products are searched from the existing insurance products. If the first insurance product can provide the guarantee amount which is more than or equal to 100 ten thousand, the first insurance product is directly used as an insurance product combination matched with the target guarantee amount, namely the insurance product combination only comprises one insurance product. If the first insurance product can provide less than 100 ten thousand of insurance lines, and supposing 80 ten thousand of insurance lines, calculating to obtain a 20 ten thousand difference between the two insurance lines, and searching the existing insurance products for the second insurance product which can provide the insurance line and is closest to the 20 ten thousand of insurance lines. If the guarantee limit which can be provided by the second insurance product is more than or equal to 20 ten thousand, the first insurance product and the second insurance product are used as the insurance product combination matched with the target guarantee amount; if the guarantee limit which can be provided by the second insurance product is less than 20 ten thousand, continuously calculating the difference between the guarantee limit which can be provided by the second insurance product and the difference value, and continuously processing by adopting the same method until the insurance product combination with the sum of the guarantee limit which can be provided being greater than or equal to the target guarantee limit is obtained.
Mode 2:
(1) Determining the quantity X of insurance products to be recommended according to service requirements;
(2) Dividing the target guarantee limit by X to obtain an average guarantee limit;
(3) Searching X insurance products which can be provided and are closest to the average insurance amount from the insurance products;
(4) If the sum of the guarantee limits which can be provided by the X insurance products is greater than or equal to the target guarantee limit, determining the X insurance products as insurance product combinations matched with the target guarantee limit;
(5) If the sum of the guarantee limits which can be provided by the X insurance products is smaller than the target guarantee limit, removing the insurance product with the smallest guarantee limit which can be provided by the X insurance products, and calculating the difference between the rest X-1 guarantee limits which can be provided by the insurance products and the target guarantee limit;
(6) Searching a third insurance product which can provide a guarantee amount greater than or equal to the difference value and is closest to the difference value from the insurance products;
(7) And determining the third insurance product and the X-1 insurance products as an insurance product combination matching the target guarantee amount.
Mode 2 is one way to fix the number of recommended insurance products, and first, the number of insurance products to be recommended is determined according to the service requirement. Assuming that the target guarantee amount is 100 ten thousand and the number of insurance products to be recommended is 4, the average guarantee amount is 100/4=25 ten thousand. The 4 insurance products which can provide the guarantee limit closest to 25 ten thousand are searched from the existing insurance products, and the 4 insurance products are assumed to be the insurance products A-25 ten thousand, the insurance products B-22 ten thousand, the insurance products C-26 ten thousand and the insurance products D-24 ten thousand respectively. If the sum of the guarantee limits which can be provided by the 4 insurance products is more than or equal to 100 ten thousand, the 4 insurance products are directly used as the insurance product combination matched with the target guarantee limit. In practice, the sum of the guaranteeing limits that can be provided by the 4 insurance products is 25+22+26+24=97ten thousand, that is, less than the target guaranteeing limit, and the insurance product with the smallest guaranteeing limit that can be provided by the 4 insurance products is removed, that is, the insurance product B is removed. Next, the remaining 3 insurance products were calculated as the difference between the amount of assurance that could be provided and 100 tens of thousands, i.e., 100- (25+26+24) =25 tens of thousands. Then, searching the third insurance product which can provide the guarantee amount greater than or equal to 25 ten thousand and is closest to the 25 ten thousand, namely E-29 ten thousand. Finally, insurance products A, C, D and E are combined as insurance products matching the target guarantee amount.
Mode 3:
(1) Determining all insurance product combinations that all of the insurance products can produce;
(2) Respectively calculating the sum of the guarantee amount which can be provided by each insurance product combination;
(3) Removing the insurance product combination with the sum of the available guarantee amount being smaller than the target guarantee amount in all the insurance product combinations;
(4) Calculating the premium of the rest insurance product combinations respectively, wherein the premium of each insurance product combination is equal to the sum of the premium of each insurance product contained in the insurance product combination;
(5) And determining the insurance product combination with the lowest premium from the rest insurance product combinations as the insurance product combination matching the target guarantee amount.
Mode 3 is one mode in which premium is considered. First, all insurance product combinations that can be generated for all insurance products are determined, i.e., all possible combinations are traversed. For example, if the existing insurance products are A-50 ten thousand (premium 1 ten thousand), B-30 ten thousand (premium 0.5 ten thousand) and C-80 ten thousand (premium 2 ten thousand), the possible insurance product combinations are: A. b, C, A + B, A + C, B +C and A+B+C. And then, respectively calculating the sum of the available guarantee amount of each insurance product combination, and removing the insurance product combination in which the sum of the available guarantee amount is smaller than the target guarantee amount. Assuming a target guarantee limit of 100 ten thousand, insurance product combinations A, B, C and a+b are removed, leaving combinations a+c, b+c, and a+b+c. And then, respectively calculating the premium of the rest insurance product combinations, wherein the premium of each insurance product combination is equal to the sum of the premium of each insurance product contained in the insurance product combinations, and determining the insurance product combination with the lowest premium in the rest insurance product combinations as the insurance product combination matched with the target guarantee amount. For the above example, the policy fee of the combination a+c is 3 ten thousand, the policy fee of the combination b+c is 2.5 ten thousand, and the policy fee of the combination a+b+c is 3.5 ten thousand, so the final insurance product combination matching the target policy credit is b+c.
105. Recommending the insurance product combination to the recommended object.
And recommending the insurance product combination to the recommended object after determining the insurance product combination matching the target guarantee amount.
The recommendation method of the insurance product provided by the embodiment of the invention comprises the following steps: acquiring characteristic information of a recommended object; calculating a target guarantee limit which the recommended object should have according to the characteristic information; product parameters of all insurance products are respectively obtained, wherein the product parameters comprise the guarantee limit which can be provided by the insurance products; determining an insurance product combination matched with the target guarantee limit according to the product parameters of each insurance product; recommending the insurance product combination to the recommended object. According to the method, the guarantee limit which the recommended object should have can be obtained through calculation according to the characteristic information of the recommended object, and then the insurance product combination matched with the guarantee limit is automatically generated by combining the product parameters of each existing insurance product, so that the appropriate insurance product can be recommended for the client in a targeted manner, and the service popularization effect is effectively improved.
Referring to fig. 2, a second embodiment of a recommendation method for insurance products according to an embodiment of the present invention includes:
201. Acquiring characteristic information of a recommended object;
in an embodiment of the present invention, the characteristic information includes an age, personal income, family expense, loan amount, and deposit amount of the recommended object. These information may be entered into the system in advance of recommending insurance products.
202. Obtaining the dependence of the family of the recommended object on the recommended object according to the age calculation;
and after the age of the recommended object is obtained, calculating the dependence of the family of the recommended object on the recommended object according to the age. The dependency degree is that the family of the recommended object depends on the age of the recommended object, for example, if the family of the recommended object a needs to depend on a for 30 years, the dependency degree of the family of a on a is 30 years.
Further, the feature information further includes a health record of the recommended object, and step 202 may include:
(1) Determining an upper age limit on which the recommended object may depend based on the health record and the personal income;
(2) And subtracting the age upper limit on which the recommended object can depend from the age to obtain the dependence of the family of the recommended object on the recommended object.
For example, if the upper age limit on which the recommended object can depend is 65 years, and the current age is 40 years, the family of the recommended object has a degree of dependence on the recommended object of 65-40=25 years. Generally, the better the health record of the recommended subject, the higher the personal income, the higher the age cap it can rely on.
203. Calculating and obtaining contribution degree of the recommended object to the household income according to the personal income and the household income;
and calculating the contribution degree of the recommended object to the household income according to the personal income and the household income when the sum of the personal income and the household income of the recommended object is obtained. The personal income can be personal month income or personal year income; the household income can be the household month income and the household year income.
Specifically, step 203 may include:
(1) Calculating a ratio of the personal revenue to the household revenue;
(2) And determining the duty ratio as the contribution degree of the recommended object to the household income.
For example, if the personal monthly income of the recommended object is 2 ten thousand and the family monthly income is 4 ten thousand, the contribution degree of the recommended object to the family income can be calculated to be 50%. In addition, average personal income and average household income in a longer period (such as 10-20 years) can be calculated according to the variation rule of personal income and household income, and the ratio of the average personal income to the average household income is used as the contribution degree so as to improve the accuracy of calculating the contribution degree.
204. Calculating to obtain a target guarantee limit which the recommended object should have according to the family expense, the loan amount, the deposit amount, the dependence and the contribution;
after obtaining the household expense, the loan amount, the deposit amount, the dependency degree and the contribution degree, a target guarantee limit which the recommended object should have can be calculated according to the parameters.
Specifically, step 204 may be:
calculating to obtain a target guarantee limit which the recommended object should have by adopting a formula g=max [ a, (p×12×y+l-D) ×c ];
wherein G represents the target guarantee amount, a is a preset constant (for example, 30 ten thousand, may be set), P represents the family expenses, Y represents the dependency degree, L represents the loan amount, D represents the deposit amount, and C represents the contribution degree.
205. Respectively acquiring product parameters of each insurance product;
206. determining an insurance product combination matched with the target guarantee limit according to the product parameters of each insurance product;
207. recommending the insurance product combination to the recommended object.
Steps 205-207 are identical to steps 103-105, and reference is made specifically to the relevant description of steps 103-105.
The recommendation method of the insurance product provided by the embodiment of the invention comprises the following steps: acquiring characteristic information of a recommended object; obtaining the dependence of the family of the recommended object on the recommended object according to the age calculation; calculating and obtaining contribution degree of the recommended object to the household income according to the personal income and the household income; calculating to obtain a target guarantee limit which the recommended object should have according to the family expense, the loan amount, the deposit amount, the dependence and the contribution; respectively acquiring product parameters of each insurance product; determining an insurance product combination matched with the target guarantee limit according to the product parameters of each insurance product; recommending the insurance product combination to the recommended object. Compared with the first embodiment of the invention, the embodiment enumerates a specific algorithm for calculating the target guarantee limit, and is mainly used for calculating the guarantee limit which the personal statutes should have.
Referring to fig. 3, a third embodiment of a recommendation method for insurance products according to an embodiment of the present invention includes:
301. acquiring characteristic information of a recommended object;
in the embodiment of the invention, the characteristic information comprises social security information and expected life years of the recommended objects. In actual operation, the target guarantee limit which the recommended object should have can be calculated according to the social security information, the expected life span and the preset inflation rate.
In addition, the social security information includes an age, a sex, a social security payment identification, personal income, an amount of pension, and a retirement age of the recommended object. These information may be entered into the system in advance of recommending insurance products.
302. Judging whether the recommended object has social security according to the social security payment identifier;
after the equipment payment identification of the recommended object is obtained, judging whether the recommended object has social security or not according to the social security payment identification. If the recommended object has social security, executing the steps 303-304; if the recommended object has no social security, step 305 is performed.
303. Determining social security payment years of the recommended objects according to the sexes;
and determining the social security payment age of the recommended object according to the gender at the moment. Due to the fact that retirement ages corresponding to different identities are different, corresponding social security payment ages are also different.
304. Calculating to obtain a target guarantee limit which the recommended object should have according to the age, the sex, the personal income, the pension number, the retirement age, the expected life age, the social security payment age and the preset currency expansion rate;
After the age, the gender, the personal income, the pension quantity, the retirement age, the expected life span, the social security payment span and the preset commodity expansion rate are obtained, the target security quota which the recommended object should have can be calculated according to the parameters.
Specifically, step 304 may be:
using the formula
Calculating to obtain a target guarantee limit which the recommended object should have;
wherein G represents the target guarantee amount, R represents the pension number, I represents the inflation rate, ar represents the retired age, an represents the age, D represents the personal income, ai represents the expected life span, S represents the social security payment span, and B is a preset constant determined according to gender (e.g., b=139 if gender is male, b=170 if gender is female).
After step 304 is performed, step 306 is performed.
305. Calculating to obtain a target guarantee limit which the recommended object should have according to the age, the pension number, the retirement age, the expected life span and the preset currency expansion rate;
and the recommended object has no social security, and the target guarantee limit which the recommended object should have is calculated according to the age, the pension quantity, the retirement age, the expected life span and the preset currency expansion rate.
Specifically, step 305 may be:
using the formula
Calculating to obtain a target guarantee limit which the recommended object should have;
wherein G represents the target guarantee amount, R represents the pension number, I represents the inflation rate, ar represents the retirement age, an represents the age, ai represents the expected life span.
306. Respectively acquiring product parameters of each insurance product;
307. determining an insurance product combination matched with the target guarantee limit according to the product parameters of each insurance product;
308. recommending the insurance product combination to the recommended object.
Steps 306-308 are identical to steps 103-105, and reference is specifically made to the relevant descriptions of steps 103-105.
The recommendation method of the insurance product provided by the embodiment of the invention comprises the following steps: acquiring characteristic information of a recommended object; judging whether the recommended object has social security according to the social security payment identifier; if the social security exists, determining the social security payment age of the recommended object according to the gender; then calculating to obtain the target guarantee limit which the recommended object should have according to the age, sex, personal income, pension quantity, retirement age, expected life age, social security payment age and preset commodity expansion rate; if the social security is not available, calculating to obtain a target security limit which the recommended object should have according to the age, the pension number, the retirement age, the expected life span and the preset currency expansion rate; respectively acquiring product parameters of each insurance product; determining an insurance product combination matched with the target guarantee limit according to the product parameters of each insurance product; recommending the insurance product combination to the recommended object. Compared with the first embodiment of the invention, the embodiment enumerates a specific algorithm for calculating the target guarantee limit, and is mainly used for calculating the guarantee limit which the person should have in the aspect of pension.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic, and should not limit the implementation process of the embodiment of the present invention.
The above mainly describes a recommendation method of an insurance product, and a recommendation device of an insurance product will be described in detail.
Referring to fig. 4, an embodiment of a recommendation device for insurance products according to an embodiment of the present invention includes:
a feature information obtaining module 401, configured to obtain feature information of a recommendation object;
a target guarantee amount calculation module 402, configured to calculate a target guarantee amount that the recommended object should have according to the feature information;
a product parameter obtaining module 403, configured to obtain product parameters of each insurance product, where the product parameters include a guarantee limit that the insurance product can provide;
an insurance product combination determining module 404, configured to determine an insurance product combination matching the target guarantee amount according to the product parameters of each insurance product;
and the insurance product combination recommending module 405 is configured to recommend the insurance product combination to the recommended object.
Further, the feature information includes an age, personal income, family expense, loan amount, and deposit amount of the recommended object, and the target guarantee amount calculation module may include:
a dependency calculation unit, configured to calculate, according to the age, a dependency of the family of the recommendation object on the recommendation object, where the dependency is a year in which the family of the recommendation object depends on the recommendation object;
a contribution degree calculation unit, configured to calculate, according to the personal income and the household income, a contribution degree of the recommendation object to the household income;
and the first guarantee limit calculation unit is used for calculating and obtaining the target guarantee limit which the recommended object should have according to the household expense, the loan quantity, the deposit quantity, the dependence and the contribution.
Still further, the feature information further includes a health record of the recommended object, and the dependency calculation unit may include:
an upper limit determination subunit configured to determine an age upper limit on which the recommended object may depend according to the health record and the personal income;
the dependence calculation subunit is used for subtracting the age upper limit on which the recommended object can depend from the age to obtain the dependence of the family of the recommended object on the recommended object;
The contribution calculating unit may include:
a revenue duty cycle calculation subunit for calculating a duty cycle of the personal revenue in the household revenue;
a contribution determining subunit configured to determine the duty ratio as a contribution of the recommendation object to the household income;
the first protection credit calculation unit may specifically be configured to: calculating to obtain a target guarantee limit which the recommended object should have by adopting a formula g=max [ a, (p×12×y+l-D) ×c ];
wherein G represents the target guarantee amount, a is a preset constant, P represents the household expense, Y represents the dependency, L represents the loan amount, D represents the deposit amount, and C represents the contribution.
Further, the feature information includes social security information and expected life span of the recommended object, and the target guarantee quota calculation module may be specifically configured to:
and calculating the target guarantee limit which the recommended object should have according to the social security information, the expected life years and the preset inflation rate.
Still further, the social security information may include an age, a gender, a social security payment identifier, a personal income, a pension number, and a retirement age of the recommended object, and the target guarantee credit calculation module may include:
The social security judging unit is used for judging whether the recommended object has social security according to the social security payment identifier;
the second guarantee limit calculation unit is used for determining the social security payment limit of the recommended object according to the gender if the recommended object has social security, and calculating the target guarantee limit which the recommended object should have according to the age, the gender, the personal income, the pension number, the retirement age, the expected life limit, the social security payment limit and the preset currency expansion rate;
and the third guarantee limit calculation unit is used for calculating the target guarantee limit which the recommended object should have according to the age, the pension number, the retirement age, the expected life period and the preset currency expansion rate if the recommended object has no social security.
Further, the second guarantee amount calculating unit may specifically be configured to: using the formula
Calculating to obtain a target guarantee limit which the recommended object should have;
wherein G represents the target guarantee amount, R represents the pension quantity, I represents the inflation rate, ar represents the retired age, an represents the age, D represents the personal income, ai represents the expected life span, S represents the social security payment span, and B is a preset constant determined according to gender;
The third guarantee amount calculating unit may specifically be configured to: calculating to obtain a target guarantee limit which the recommended object should possess by adopting a formula g=r (1+iar-An 12 (1+i) (Ai-Ar) -1I);
wherein G represents the target guarantee amount, R represents the pension number, I represents the inflation rate, ar represents the retirement age, an represents the age, ai represents the expected life span.
Further, the insurance product combination determination module may include:
the first searching unit is used for searching the first insurance products which can be provided and are closest to the target insurance amount from the insurance products;
the first product combination determining unit is used for determining the first insurance product as an insurance product combination matched with the target guarantee limit if the guarantee limit which can be provided by the first insurance product is greater than or equal to the target guarantee limit;
the second searching unit is used for calculating the difference between the guarantee limit which can be provided by the first insurance product and the target guarantee limit if the guarantee limit which can be provided by the first insurance product is smaller than the target guarantee limit, and searching the second insurance product which is closest to the difference in the available guarantee limit from the insurance products;
A second product combination determining unit, configured to determine the first insurance product and the second insurance product as an insurance product combination matching the target guarantee amount if the guarantee amount that the second insurance product can provide is greater than or equal to the difference value;
and the third product combination determining unit is used for continuously calculating the difference between the guarantee limit which can be provided by the second insurance product and the difference if the guarantee limit which can be provided by the second insurance product is smaller than the difference until the sum of the obtained guarantee limits which can be provided is larger than or equal to the target guarantee limit.
Further, the insurance product combination determination module may include:
the insurance product quantity determining unit is used for determining the quantity X of insurance products to be recommended according to business requirements;
the average guarantee limit calculation unit is used for dividing the target guarantee limit by X to obtain an average guarantee limit;
a third searching unit, configured to search, from the respective insurance products, for X insurance products that can be provided with a guarantee amount closest to the average guarantee amount;
a fourth product combination determining unit, configured to determine the X insurance products as an insurance product combination matching the target guarantee amount if the sum of the guarantee amounts that the X insurance products can provide is greater than or equal to the target guarantee amount;
The first insurance product removing unit is used for removing the insurance product with the smallest insurance limit which can be provided in the X insurance products if the sum of the insurance limits which can be provided by the X insurance products is smaller than the target insurance limit, and calculating the difference between the remaining X-1 insurance products and the target insurance limit;
a fourth searching unit, configured to search for a third insurance product that can provide a guarantee amount greater than or equal to the difference and closest to the difference from the respective insurance products;
and a fifth product combination determining unit, configured to determine the third insurance product and the X-1 insurance products as an insurance product combination matching the target guarantee amount.
Further, the product parameters may further include premium of the insurance product, and the insurance product combination determining module may include:
an insurance product combination traversing unit for determining all insurance product combinations that all of the insurance products can produce;
the sum of the guarantee amount calculation unit is used for calculating the sum of the guarantee amounts which can be provided by each insurance product combination respectively;
the second insurance product removing unit is used for removing the insurance product combination with the sum of the available guarantee amount smaller than the target guarantee amount in all the insurance product combinations;
A premium calculation unit for calculating premium of the remaining insurance product combinations, respectively, the premium of each insurance product combination being equal to sum of premium of the respective insurance products contained therein;
and a sixth product combination determining unit, configured to determine an insurance product combination with the lowest premium of the remaining insurance product combinations as an insurance product combination matching the target guarantee amount.
Embodiments of the present invention also provide a computer readable storage medium storing computer readable instructions that, when executed by a processor, implement the steps of a recommendation method for an insurance product as any of the insurance products shown in fig. 1 to 3.
The embodiment of the invention also provides a server, which comprises a memory, a processor and computer readable instructions stored in the memory and capable of running on the processor, wherein the steps of the recommendation method of any insurance product as shown in fig. 1 to 3 are realized when the processor executes the computer readable instructions.
Fig. 5 is a schematic diagram of a server according to an embodiment of the present invention. As shown in fig. 5, the server 5 of this embodiment includes: a processor 50, a memory 51, and computer readable instructions 52 stored in the memory 51 and executable on the processor 50. The processor 50, when executing the computer readable instructions 52, implements the steps of the preferred method embodiments of the respective insurance products described above, such as steps 101 through 105 shown in fig. 1. Alternatively, the processor 50, when executing the computer readable instructions 52, performs the functions of the modules/units of the apparatus embodiments described above, such as the functions of modules 401 through 405 shown in fig. 4.
Illustratively, the computer readable instructions 52 may be partitioned into one or more modules/units that are stored in the memory 51 and executed by the processor 50 to accomplish the present invention. The one or more modules/units may be a series of computer readable instruction segments capable of performing a specific function describing the execution of the computer readable instructions 52 in the server 5.
The server 5 may be a computing device such as a desktop computer, a notebook computer, a palm computer, a cloud server, etc. The server 5 may include, but is not limited to, a processor 50, a memory 51. It will be appreciated by those skilled in the art that fig. 5 is merely an example of the server 5 and is not meant to be limiting of the server 5, and may include more or fewer components than shown, or may combine certain components, or different components, e.g., the server 5 may also include input and output devices, network access devices, buses, etc.
The processor 50 may be a central processing unit (CentraL Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (DigitaL SignaL Processor, DSP), application specific integrated circuits (AppLication Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (fierld-ProgrammabLe Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 51 may be an internal storage unit of the server 5, for example, a hard disk or a memory of the server 5. The memory 51 may be an external storage device of the server 5, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure DigitaL (SD) Card, a FLash Card (FLash Card) or the like, which are provided on the server 5. Further, the memory 51 may also include both an internal storage unit and an external storage device of the server 5. The memory 51 is used to store the computer readable instructions and other programs and data required by the server. The memory 51 may also be used to temporarily store data that has been output or is to be output.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a Read-OnLy Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (9)
1. A method of recommending insurance products, comprising:
acquiring characteristic information of a recommended object;
calculating a target guarantee limit which the recommended object should have according to the characteristic information;
product parameters of all insurance products are respectively obtained, wherein the product parameters comprise the guarantee limit which can be provided by the insurance products;
determining an insurance product combination matched with the target guarantee limit according to the product parameters of each insurance product;
recommending the insurance product combination to the recommended object;
wherein the feature information includes age, personal income, family expense, loan amount and deposit amount of the recommended object, and the calculating the target guarantee limit which the recommended object should have according to the feature information includes:
obtaining the dependence of the family of the recommended object on the recommended object according to the age calculation, wherein the dependence is the age of the family of the recommended object depending on the recommended object;
calculating and obtaining contribution degree of the recommended object to the household income according to the personal income and the household income;
calculating to obtain a target guarantee limit which the recommended object should have by adopting a formula g=max [ a, (p×12×y+l-D) ×c ];
Wherein G represents the target guarantee amount, a is a preset constant, P represents the household expense, Y represents the dependency, L represents the loan amount, D represents the deposit amount, and C represents the contribution.
2. The recommendation method according to claim 1, wherein the feature information further includes a health record of the recommended object, and the calculating the dependency of the family of the recommended object on the recommended object according to the age includes:
determining an upper age limit on which the recommended object may depend based on the health record and the personal income;
subtracting the age upper limit on which the recommended object can depend from the age to obtain the dependence of the family of the recommended object on the recommended object;
the calculating the contribution degree of the recommended object to the household income according to the personal income and the household income comprises the following steps:
calculating a ratio of the personal revenue to the household revenue;
and determining the duty ratio as the contribution degree of the recommended object to the household income.
3. The recommendation method according to claim 1, wherein the feature information includes social security information and expected life span of the recommended object, and the calculating a target guarantee amount that the recommended object should have based on the feature information includes:
And calculating the target guarantee limit which the recommended object should have according to the social security information, the expected life years and the preset inflation rate.
4. The recommendation method according to claim 3, wherein the social security information includes an age, a sex, a social security payment identifier, a personal income, a pension number, and a retirement age of the recommended object, and the calculating the target security credit that the recommended object should have according to the social security information, the expected life span, and a preset expansion rate includes:
judging whether the recommended object has social security according to the social security payment identifier;
if the recommended object has social security, determining the social security payment age of the recommended object according to the gender, and adopting a formula
Calculating to obtain a target guarantee limit which the recommended object should have;
wherein G represents the target guarantee amount, R represents the pension quantity, I represents the inflation rate, ar represents the retired age, an represents the age, D represents the personal income, ai represents the expected life span, S represents the social security payment span, and B is a preset constant determined according to gender;
If the recommended object has no social security, adopting a formula
Calculating to obtain a target guarantee limit which the recommended object should have;
wherein G represents the target guarantee amount, R represents the pension number, I represents the inflation rate, ar represents the retirement age, an represents the age, ai represents the expected life span.
5. The recommendation method according to any one of claims 1 to 4, wherein said determining an insurance product combination matching said target amount of insurance based on product parameters of said respective insurance products comprises:
searching a first insurance product which can provide a guarantee limit closest to the target guarantee limit from the insurance products;
if the guarantee limit which can be provided by the first insurance product is greater than or equal to the target guarantee limit, determining the first insurance product as an insurance product combination matched with the target guarantee limit;
if the guarantee limit which can be provided by the first insurance product is smaller than the target guarantee limit, calculating the difference between the guarantee limit which can be provided by the first insurance product and the target guarantee limit, and searching a second insurance product which is closest to the difference and can be provided by the first insurance product from the insurance products;
If the guarantee limit which can be provided by the second insurance product is greater than or equal to the difference value, determining the first insurance product and the second insurance product as an insurance product combination matched with the target guarantee limit;
if the guarantee limit which can be provided by the second insurance product is smaller than the difference value, continuously calculating the difference value between the guarantee limit which can be provided by the second insurance product and the difference value until the insurance product combination with the sum of the guarantee limit which can be provided being greater than or equal to the target guarantee limit is obtained.
6. The recommendation method according to any one of claims 1 to 4, wherein said determining an insurance product combination matching said target amount of insurance based on product parameters of said respective insurance products comprises:
determining the quantity X of insurance products to be recommended according to service requirements;
dividing the target guarantee limit by X to obtain an average guarantee limit;
searching X insurance products which can be provided and are closest to the average insurance amount from the insurance products;
if the sum of the guarantee limits which can be provided by the X insurance products is greater than or equal to the target guarantee limit, determining the X insurance products as insurance product combinations matched with the target guarantee limit;
If the sum of the guarantee limits which can be provided by the X insurance products is smaller than the target guarantee limit, removing the insurance product with the smallest guarantee limit which can be provided by the X insurance products, and calculating the difference between the rest X-1 guarantee limits which can be provided by the insurance products and the target guarantee limit;
searching a third insurance product which can provide a guarantee amount greater than or equal to the difference value and is closest to the difference value from the insurance products;
and determining the third insurance product and the X-1 insurance products as an insurance product combination matching the target guarantee amount.
7. The recommendation method according to any one of claims 1 to 4, wherein said product parameters further comprise premium of insurance products, said determining an insurance product combination matching said target guarantee credit based on product parameters of said respective insurance products comprising:
determining all insurance product combinations that all of the insurance products can produce;
respectively calculating the sum of the guarantee amount which can be provided by each insurance product combination;
removing the insurance product combination with the sum of the available guarantee amount being smaller than the target guarantee amount in all the insurance product combinations;
Calculating the premium of the rest insurance product combinations respectively, wherein the premium of each insurance product combination is equal to the sum of the premium of each insurance product contained in the insurance product combination;
and determining the insurance product combination with the lowest premium from the rest insurance product combinations as the insurance product combination matching the target guarantee amount.
8. A computer readable storage medium storing computer readable instructions which, when executed by a processor, implement the steps of the method of recommending an insurance product according to any of claims 1 to 7.
9. A server comprising a memory, a processor, and computer readable instructions stored in the memory and executable on the processor, wherein the processor, when executing the computer readable instructions, performs the steps of:
acquiring characteristic information of a recommended object;
calculating a target guarantee limit which the recommended object should have according to the characteristic information;
product parameters of all insurance products are respectively obtained, wherein the product parameters comprise the guarantee limit which can be provided by the insurance products;
determining an insurance product combination matched with the target guarantee limit according to the product parameters of each insurance product;
Recommending the insurance product combination to the recommended object;
wherein the feature information includes age, personal income, family expense, loan amount and deposit amount of the recommended object, and the calculating the target guarantee limit which the recommended object should have according to the feature information includes:
obtaining the dependence of the family of the recommended object on the recommended object according to the age calculation, wherein the dependence is the age of the family of the recommended object depending on the recommended object;
calculating and obtaining contribution degree of the recommended object to the household income according to the personal income and the household income;
calculating to obtain a target guarantee limit which the recommended object should have by adopting a formula g=max [ a, (p×12×y+l-D) ×c ];
wherein G represents the target guarantee amount, a is a preset constant, P represents the household expense, Y represents the dependency, L represents the loan amount, D represents the deposit amount, and C represents the contribution.
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| CN109785039A (en) * | 2018-12-13 | 2019-05-21 | 中国平安人寿保险股份有限公司 | Device, method and the storage medium of information recommendation |
| 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 |
| CN111178769A (en) * | 2019-12-31 | 2020-05-19 | 北京健康之家科技有限公司 | Evaluation method and device for virtual insurance product |
| CN113256437B (en) * | 2021-07-15 | 2021-11-02 | 大童保险销售服务有限公司 | Method, system and storage medium for configuring disease insurance product scheme |
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| CN107730386A (en) * | 2017-07-28 | 2018-02-23 | 上海壹账通金融科技有限公司 | Generation method, device, storage medium and the computer equipment of investment combination product |
| CN107767275A (en) * | 2016-08-22 | 2018-03-06 | 平安科技（深圳）有限公司 | Insure resource requirement analysis method and device |
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| CN108596773A (en) * | 2018-04-27 | 2018-09-28 | 中国太平洋保险（集团）股份有限公司 | A kind of control method for establishing subscriber household insurance cover combined system |
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| JP2005018812A (en) * | 2004-10-15 | 2005-01-20 | Kiyapitaru Asetsuto Planning:Kk | Automatic design device of optimum insurance based on individual life plan |
| CN107767275A (en) * | 2016-08-22 | 2018-03-06 | 平安科技（深圳）有限公司 | Insure resource requirement analysis method and device |
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