Personalized insurance product recommendation method and system

Abstract

The invention relates to the technical field of insurance services, and discloses a personalized insurance product recommendation method and system, and the method comprises the steps: obtaining the personal information and family member information of a target user, obtaining a first-level associated person, and recommending an insurance broker meeting a standard according to the family annual income of the user. And through the address book of the target user and the address book of the auxiliary user, further obtaining a second-level associated person. And obtaining insurance purchase records of the first associated person and the second associated person, and determining an insurance for shielding or recommending the target user according to the records. And finally, the insurance broker configures multiple types of personalized insurance products for the user according to the budget and the recommendation strategy of the user, and performs adjustment according to the feedback of the user until the user is satisfied.

Description

Technical Field

[0001] The present invention relates to the technical field of insurance services, and in particular to a personalized insurance product recommendation method and system. Background Art

[0002] With the continuous development of society and the enhancement of people's insurance awareness, insurance products have gradually become an important part of family financial planning. However, for ordinary consumers, it is not easy to choose the insurance products that suit them. The main reasons include: a wide variety of insurance products, complex terms, lack of professional knowledge, and unclear understanding of their own needs.

[0003] The traditional insurance sales model relies on the professional knowledge and one-to-one consulting services of insurance brokers, but this model has problems such as low efficiency, narrow coverage, and lack of personalization. Specifically, when recommending insurance brokers, the current insurance recommendation system usually selects them randomly or based on simple geographic location matching. This method ignores the professional ability and historical transaction records of insurance brokers, resulting in customers being unable to obtain the most suitable insurance broker services, thereby affecting the selection and purchase experience of insurance products; secondly, traditional insurance recommendations usually only focus on the individual situation of the customer, while ignoring the insurance purchase records of the customer's family members and associates; however, the customer's insurance needs are often affected by their family members and associates. For example, some insurance products may have been purchased by the customer's family members, or the customer's special needs may arise based on the situation of family members. The existing technology is obviously insufficient in considering this aspect, resulting in low effectiveness and accuracy of the recommendation results.

[0004] In summary, there is an urgent need for a personalized insurance product recommendation method and system to provide accurate and personalized insurance product recommendations, thereby significantly improving user satisfaction and insurance purchasing experience. Summary of the invention

[0005] The present invention provides a personalized insurance product recommendation method and system, which facilitates solving the problems mentioned in the above background technology.

[0006] The present invention provides the following technical solution: a personalized insurance product recommendation method and system, comprising:

[0007] Get users who need to purchase insurance products and record them as target users;

[0008] The target user enters personal information through the information input port;

[0009] The personal information includes the target user's name, contact information, the target user's family members, annual family income and family member contact information;

[0010] The target user's family members include the target user's spouse, parents, and children;

[0011] All family members of the target user are recorded as first-level associates;

[0012] Recommend qualified insurance brokers to target users based on their annual household income;

[0013] The recommended insurance broker is recorded as the target insurance broker;

[0014] Acquire the second-level associates of the target user according to the second-level associate acquisition strategy;

[0015] Obtain insurance purchase records of the target user's first-level associates and second-level associates;

[0016] The insurance purchase record includes all insurance purchased, the type of each insurance purchased, the validity period of each insurance purchased, and the insured of each insurance purchased;

[0017] Obtaining insurance that is blocked or recommended for the user based on the insurance purchase records of the first-level associates and second-level associates of the target user;

[0018] The target broker configures insurance for the target user according to the first strategy;

[0019] The insurance configuration refers to the insurance broker configuring various types of insurance for target users.

[0020] Optionally, the step of recommending an insurance broker who meets the criteria to the target user based on the target user's annual household income specifically includes:

[0021] Get the target user's annual household income;

[0022] Set the premium budget ratio threshold;

[0023] The premium budget ratio threshold is used to represent the maximum ratio of the premium budget to the target user's family annual income;

[0024] Calculate the maximum premium budget using the following formula:

[0025] Maximum premium budget = target user's annual household income × premium budget ratio threshold;

[0026] Set the premium budget range, specifically:

[0027] The first budget range is below 5,000 yuan;

[0028] 5,000 yuan to 6,000 yuan is the second budget range;

[0029] 6,000 yuan to 7,000 yuan is the third budget range;

[0030] 7,000 yuan to 8,000 yuan is the fourth budget range;

[0031] 8,000 yuan and above is the fifth budget range;

[0032] Get the maximum insurance budget;

[0033] Get the budget interval to which the maximum insurance budget belongs, and record it as the target interval.

[0034] Optionally, the step of recommending an insurance broker who meets the criteria to the target user according to the target user's annual household income also includes:

[0035] Get all insurance brokers;

[0036] For each insurance broker, the number of insurance combinations whose costs are within the target range among all insurance combinations concluded by the broker is obtained, and recorded as the first number;

[0037] Get the first quantity of all insurance brokers and sort them in descending order;

[0038] The insurance brokers corresponding to the first number ranked first are selected as insurance brokers that meet the standards and are recommended to the target users.

[0039] Optionally, acquiring the second-level associated persons of the target user according to the second-level associated persons acquisition strategy specifically includes:

[0040] Send a contact list query request to the target user;

[0041] If the target user does not agree to query the address book, the target insurance broker will configure insurance for the target user who does not agree to query the address book, specifically:

[0042] Get the target user's annual household income;

[0043] Calculate the premium budget cap using the following formula:

[0044] Premium budget cap = target user's annual household income × premium budget ratio;

[0045] The target broker configures insurance for the target user without exceeding the premium budget limit;

[0046] If the target user agrees to query the address book, obtain the target user's address book;

[0047] Get the name, age and mobile phone number of each contact in the user's address book and form a pairing relationship;

[0048] Get all users who have purchased insurance a non-zero number of times and record them as auxiliary users;

[0049] Sending a request for querying the address book to the auxiliary user;

[0050] Obtain the name, age and mobile phone number of each contact in the address book of the auxiliary user who agrees to query the address book, and form a pairing relationship;

[0051] Set the age range, specifically:

[0052] Those under 20 years old are recorded as the first age range;

[0053] 20-35 years old is recorded as the second age range;

[0054] 35-50 years old is recorded as the third age range;

[0055] Those aged 50 and above are recorded as the fourth age range;

[0056] Determine whether the target user and the auxiliary user have the same pairing relationship in each age range, specifically:

[0057] Acquire the pairing relationships of the target users whose ages are in the first age range to form a first pairing relationship group; acquire the pairing relationships of the target users whose ages are in the second age range to form a second pairing relationship group; acquire the pairing relationships of the target users whose ages are in the third age range to form a third pairing relationship group; acquire the pairing relationships of the target users whose ages are in the fourth age range to form a fourth pairing relationship group;

[0058] The pairing relationship in the auxiliary user pairing relationship that is the same as a pairing relationship in the first pairing relationship group constitutes a first judgment set, the pairing relationship in the auxiliary user pairing relationship that is the same as a pairing relationship in the second pairing relationship group constitutes a second judgment set, the pairing relationship in the auxiliary user pairing relationship that is the same as a pairing relationship in the third pairing relationship group constitutes a third judgment set, and the pairing relationship in the auxiliary user pairing relationship that is the same as a pairing relationship in the fourth pairing relationship group constitutes a fourth judgment set;

[0059] The auxiliary users corresponding to each pairing relationship in the first judgment set constitute a first auxiliary set, the auxiliary users corresponding to each pairing relationship in the second judgment set constitute a second auxiliary set, the auxiliary users corresponding to each pairing relationship in the third judgment set constitute a third auxiliary set, and the auxiliary users corresponding to each pairing relationship in the fourth judgment set constitute a fourth auxiliary set;

[0060] Take the intersection of the first auxiliary set, the second auxiliary set, the third auxiliary set and the fourth auxiliary set, and record it as the target set;

[0061] The auxiliary users in the target set are recorded as second-level associated persons.

[0062] Optionally, obtaining the insurance that is blocked or recommended to the user according to the insurance purchase records of the first-level associated persons and the second-level associated persons of the target user specifically includes:

[0063] Obtain the first-level associated persons and second-level associated persons of the target user to form the target population;

[0064] For each user in the target population, obtain the user's insurance purchase record;

[0065] Obtain the currently effective insurance among the insurance purchased by the user, which constitutes the first auxiliary insurance;

[0066] For each policy in the first supplementary policy;

[0067] the insured person who obtains insurance;

[0068] Determine whether the insured persons include the target users;

[0069] Record the insurance type corresponding to the insurance whose insured includes the target user as the first auxiliary type;

[0070] Perform insurance shielding on the first auxiliary type of insurance.

[0071] Optionally, the obtaining of insurances blocked or recommended to the user according to the insurance purchase records of the first-level associates and the second-level associates of the target user further includes:

[0072] Get the number of target populations, recorded as auxiliary number;

[0073] Set the recommended ratio threshold;

[0074] The recommendation ratio threshold is used to determine whether to recommend insurance to the user;

[0075] Obtain all insurance purchased by all users in the target population, and record them as the first insurance, the second insurance, and so on.

[0076] N refers to the number of all insurance policies purchased by all users in the target population;

[0077] Obtain the number of users in the target population who have purchased the first insurance, recorded as the first number; obtain the number of users in the target population who have purchased the second insurance, recorded as the second number... obtain the number of users in the target population who have purchased the Nth insurance, recorded as the Nth number;

[0078] Calculate the result of the first quantity ÷ the auxiliary quantity, the result of the second quantity ÷ the auxiliary quantity, and so on, the result of the Nth quantity ÷ the auxiliary quantity, and determine whether the result is greater than or equal to the recommended ratio threshold;

[0079] The insurance with the result greater than or equal to the recommended ratio threshold is recorded as the second auxiliary insurance;

[0080] The type of second auxiliary insurance is obtained, recorded as the second auxiliary type;

[0081] Make insurance recommendations for the second type of insurance.

[0082] Optionally, the target broker configures insurance for the target user according to the first strategy, specifically including:

[0083] Get the target user's annual household income;

[0084] Calculate the premium budget cap using the following formula:

[0085] Premium budget cap = target user's annual household income × premium budget ratio;

[0086] The target broker configures insurance for the target user without exceeding the premium budget cap, where:

[0087] Not purchasing the first auxiliary type of insurance when configuring insurance;

[0088] When configuring insurance, give priority to purchasing the second auxiliary type of insurance.

[0089] Optionally, also include:

[0090] The target user views the insurance configuration results of the target broker;

[0091] If the target user is satisfied with the result of insurance configuration;

[0092] Then, the target broker purchases insurance for the target user according to the result of insurance configuration;

[0093] If the target user is not satisfied with the result of the insurance configuration;

[0094] Then, the target broker reconfigures the insurance until the target user is satisfied with the result of the insurance configuration.

[0095] Optional, including:

[0096] Input port, used for users to enter personal information;

[0097] Information collection system, used to collect insurance purchase records of all users;

[0098] Information storage system, used to store insurance purchase records of all users;

[0099] The target broker recommendation system is used to recommend insurance brokers to target users.

[0100] The present invention has the following beneficial effects:

[0101] 1. A personalized insurance product recommendation method and system obtains the personal information of the target user through an information input port. The design of this port can also guide the user to gradually input necessary information to avoid omissions, thereby ensuring the integrity and accuracy of the data, which is particularly important for the recommendation of insurance products, because any missing or incorrect information may lead to inaccurate recommendations; these advantages make the input port an important link in system data collection and provide a solid foundation for subsequent personalized recommendations.

[0102] 2. A personalized insurance product recommendation method and system, by obtaining the target user's annual family income, calculating the target user's maximum premium budget according to the target user's annual family income, and then obtaining the number of insurance combinations whose fees are in this budget interval among all insurance combinations sold by all insurance brokers according to the budget interval to which the maximum premium budget belongs, and selecting the insurance broker with the largest number to recommend to the target user; this method ensures that the recommended insurance broker can provide insurance products that match the user's economic ability, avoids insurance plans that are not suitable for the user's economic situation, thereby improving the user's satisfaction and the success rate of insurance purchase. Specifically, the annual family income is an important indicator for measuring the user's ability to pay. Based on this, the recommended insurance broker can provide users with suitable insurance products in a more targeted manner, avoiding over-insurance or under-insurance. This recommendation method matching economic conditions can effectively reduce the user's economic pressure when purchasing insurance and enhance their willingness to purchase. At the same time, this method can also improve the professionalism and service accuracy of insurance brokers, because the recommended insurance brokers are more aware of the needs and preferences of users at this income level and can provide more personalized services. This not only enhances users' trust and loyalty to insurance brokers, but also improves the sales efficiency and customer retention rate of insurance companies.

[0103] 3. A personalized insurance product recommendation method and system, which forms a pairing relationship by combining the name, age and mobile phone number of each contact in the user's address book, combining the name, age and mobile phone number of each contact in the auxiliary user's address book, and then setting four age intervals, and obtaining the pairing relationship of the target user in the age interval for the first, second, third and fourth age intervals, forming the first, second, third and fourth pairing relationship groups; for each pairing relationship group, obtaining the pairing relationship with the same pairing relationship in the pairing relationship group in the auxiliary user pairing relationship, forming the first, second, third and fourth judgment sets; for each judgment set, obtaining the auxiliary user corresponding to each pairing relationship in the judgment set, forming the first, second, third and fourth auxiliary sets; finally, taking the intersection of the first, second, third and fourth auxiliary sets, and recording the auxiliary users in the intersection as second-level associated persons; in this way, auxiliary users with very close relationships with the target user can be screened out from all auxiliary users, and the insurance purchase records of the second-level associated persons have a significant reference role in configuring insurance for the target user, thereby improving the accuracy and effectiveness of configuring insurance for the target user.

[0104] 4. This personalized insurance product recommendation method and system obtains the insurance purchase records of the first-level associated persons and the second-level associated persons, and screens the insurances that are still in effect, to determine whether the insured persons of these insurances include the target user. If the target user is included, the insured person is blocked. In this way, it can be avoided that when the target user configures insurance, he purchases insurance whose coverage already includes the target user, resulting in unnecessary insurance and thus wasting the budget. This method improves user experience and satisfaction.

[0105] 5. A personalized insurance product recommendation method and system first obtains the number of target populations, sets a recommendation ratio threshold, and then obtains all insurances purchased by all users in the target population; for each insurance, the number of users who purchase this insurance in the target population is compared with the number of the target population. If the result is greater than the recommendation ratio threshold, it means that there are many people who purchase this insurance in the target population. At this time, this insurance is recommended to target users who are closely connected with the target population; by analyzing the purchase ratio of each insurance product in the target population, the system can identify insurance products that are popular in the user's social circle; this recommendation method based on purchase data can increase the relevance of recommendations and the user's trust in the recommended products. Users are more likely to accept and choose insurance products that are widely recognized in their social circles because these products have been verified and recognized by their friends or family. Secondly, giving priority to recommending insurance products with a high purchase ratio can reduce users' uncertainty and resistance to new products and increase purchase conversion rates. This method can also improve the efficiency of the recommendation system, reduce unnecessary recommendation attempts, and save users' time and energy.

[0106] 6. A personalized insurance product recommendation method and system, which can significantly improve the accuracy of personalized recommendations and user satisfaction by adjusting insurance configuration according to user feedback. Specifically, allowing users to view and feedback the results of insurance configuration can improve user participation and trust in insurance recommendations. User feedback can help insurance brokers adjust insurance configuration in a timely manner to ensure that the final plan meets the user's real needs and preferences. This dynamic adjustment mechanism can enhance users' trust in the system and insurance brokers, and improve the personalization of services and user experience. For example, if users are not satisfied with the insurance configuration recommended for the first time, they can provide specific feedback, and insurance brokers can make adjustments based on these opinions until the user is satisfied. This method can not only improve user satisfaction and loyalty, but also help insurance companies accumulate more user preference data and optimize recommendation algorithms and strategies. In addition, adjusting insurance configuration according to user feedback can also reduce unnecessary insurance configuration attempts, save time and energy of users and insurance brokers, and improve overall service efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0107] Figure 1 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0108] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0109] Example, see Figure 1 , a personalized insurance product recommendation method and system, comprising:

[0110] Get users who need to purchase insurance products and record them as target users;

[0111] The target user enters personal information through the information input port;

[0112] The personalized insurance product recommendation method and system obtains the personal information of the target user through the information input port. The design of this port can also guide the user to gradually input the necessary information to avoid omissions, thereby ensuring the integrity and accuracy of the data, which is particularly important for the recommendation of insurance products, because any missing or wrong information may lead to inaccurate recommendations; these advantages make the input port an important link in the system data collection, and provide a solid foundation for subsequent personalized recommendations;

[0113] The personal information includes the target user's name, contact information, the target user's family members, annual family income and family member contact information;

[0114] The target user's family members include the target user's spouse, parents, and children;

[0115] All family members of the target user are recorded as first-level associates;

[0116] Recommend qualified insurance brokers to target users based on their annual household income;

[0117] The recommended insurance broker is recorded as the target insurance broker;

[0118] Acquire the second-level associates of the target user according to the second-level associate acquisition strategy;

[0119] Obtain insurance purchase records of the target user's first-level associates and second-level associates;

[0120] The insurance purchase record includes all insurance purchased, the type of each insurance purchased, the validity period of each insurance purchased, and the insured of each insurance purchased;

[0121] Obtaining insurance that is blocked or recommended for the user based on the insurance purchase records of the first-level associates and second-level associates of the target user;

[0122] The target broker configures insurance for the target user according to the first strategy;

[0123] The insurance configuration refers to the insurance broker configuring various types of insurance for target users.

[0124] The step of recommending a qualified insurance broker to a target user based on the target user's annual household income specifically includes:

[0125] Get the target user's annual household income;

[0126] Set the premium budget ratio threshold;

[0127] The premium budget ratio threshold is used to represent the maximum ratio of the premium budget to the target user's family annual income;

[0128] Calculate the maximum premium budget using the following formula:

[0129] Maximum premium budget = target user's annual household income × premium budget ratio threshold;

[0130] Set the premium budget range, specifically:

[0131] The first budget range is below 5,000 yuan;

[0132] 5,000 yuan to 6,000 yuan is the second budget range;

[0133] 6,000 yuan to 7,000 yuan is the third budget range;

[0134] 7,000 yuan to 8,000 yuan is the fourth budget range;

[0135] 8,000 yuan and above is the fifth budget range;

[0136] Get the maximum insurance budget;

[0137] Get the budget interval to which the maximum insurance budget belongs, and record it as the target interval.

[0138] The recommending of insurance brokers meeting the criteria to the target user based on the target user's annual household income also includes:

[0139] Get all insurance brokers;

[0140] For each insurance broker, the number of insurance combinations whose costs are within the target range among all insurance combinations concluded by the broker is obtained, and recorded as the first number;

[0141] Get the first quantity of all insurance brokers and sort them in descending order;

[0142] The insurance brokers with the first number of rankings are selected as insurance brokers meeting the criteria and recommended to the target users;

[0143] The personalized insurance product recommendation method and system obtains the target user's annual family income, calculates the target user's maximum premium budget according to the target user's annual family income, and then obtains the number of insurance combinations whose fees are in this budget interval among all insurance combinations sold by all insurance brokers according to the budget interval to which the maximum premium budget belongs, and selects the insurance broker with the largest number to recommend to the target user; this method ensures that the recommended insurance broker can provide insurance products that match the user's economic ability, avoids insurance plans that are not suitable for the user's economic situation, and thus improves the user's satisfaction and the success rate of insurance purchase. Specifically, the annual family income is an important indicator for measuring the user's ability to pay. Based on this, the recommended insurance broker can provide users with suitable insurance products in a more targeted manner, avoiding over-insurance or under-insurance. This economic status matching recommendation method can effectively reduce the user's economic pressure when purchasing insurance and enhance their willingness to purchase. At the same time, this method can also improve the professionalism and service accuracy of insurance brokers, because the recommended insurance brokers are more aware of the needs and preferences of users at this income level and can provide more personalized services. This not only enhances the user's trust and loyalty to insurance brokers, but also improves the sales efficiency and customer retention rate of insurance companies.

[0144] The step of acquiring the second-level associated persons of the target user according to the second-level associated persons acquisition strategy specifically includes:

[0145] Send a contact list query request to the target user;

[0146] If the target user does not agree to query the address book, the target insurance broker will configure insurance for the target user who does not agree to query the address book, specifically:

[0147] Get the target user's annual household income;

[0148] Calculate the premium budget cap using the following formula:

[0149] Premium budget cap = target user's annual household income × premium budget ratio;

[0150] The target broker configures insurance for the target user without exceeding the premium budget limit;

[0151] If the target user agrees to query the address book, obtain the target user's address book;

[0152] Get the name, age and mobile phone number of each contact in the user's address book and form a pairing relationship;

[0153] Get all users who have purchased insurance a non-zero number of times and record them as auxiliary users;

[0154] Sending a request for querying the address book to the auxiliary user;

[0155] Obtain the name, age and mobile phone number of each contact in the address book of the auxiliary user who agrees to query the address book, and form a pairing relationship;

[0156] Set the age range, specifically:

[0157] Those under 20 years old are recorded as the first age range;

[0158] 20-35 years old is recorded as the second age range;

[0159] 35-50 years old is recorded as the third age range;

[0160] Those aged 50 and above are recorded as the fourth age range;

[0161] Determine whether the target user and the auxiliary user have the same pairing relationship in each age range, specifically:

[0162] Acquire the pairing relationships of the target users whose ages are in the first age range to form a first pairing relationship group; acquire the pairing relationships of the target users whose ages are in the second age range to form a second pairing relationship group; acquire the pairing relationships of the target users whose ages are in the third age range to form a third pairing relationship group; acquire the pairing relationships of the target users whose ages are in the fourth age range to form a fourth pairing relationship group;

[0163] The pairing relationship in the auxiliary user pairing relationship that is the same as a pairing relationship in the first pairing relationship group constitutes a first judgment set, the pairing relationship in the auxiliary user pairing relationship that is the same as a pairing relationship in the second pairing relationship group constitutes a second judgment set, the pairing relationship in the auxiliary user pairing relationship that is the same as a pairing relationship in the third pairing relationship group constitutes a third judgment set, and the pairing relationship in the auxiliary user pairing relationship that is the same as a pairing relationship in the fourth pairing relationship group constitutes a fourth judgment set;

[0164] The auxiliary users corresponding to each pairing relationship in the first judgment set constitute a first auxiliary set, the auxiliary users corresponding to each pairing relationship in the second judgment set constitute a second auxiliary set, the auxiliary users corresponding to each pairing relationship in the third judgment set constitute a third auxiliary set, and the auxiliary users corresponding to each pairing relationship in the fourth judgment set constitute a fourth auxiliary set;

[0165] Take the intersection of the first auxiliary set, the second auxiliary set, the third auxiliary set and the fourth auxiliary set, and record it as the target set;

[0166] The auxiliary users in the target set are recorded as second-level associated persons;

[0167] The method and system for recommending personalized insurance products are as follows: the name, age and mobile phone number of each contact in the user's address book are combined to form a pairing relationship; the name, age and mobile phone number of each contact in the auxiliary user's address book are combined to form a pairing relationship; and then four age intervals are set. For the first, second, third and fourth age intervals, the pairing relationship of the target user in the age interval is obtained to form the first, second, third and fourth pairing relationship groups; for each pairing relationship group, the pairing relationship with the same pairing relationship in the pairing relationship group of the auxiliary user is obtained to form the first, second, third and fourth judgment sets; for each judgment set, the auxiliary user corresponding to each pairing relationship in the judgment set is obtained to form the first, second, third and fourth auxiliary sets; finally, the intersection of the first, second, third and fourth auxiliary sets is taken, and the auxiliary users in the intersection are recorded as second-level associated persons; in this way, auxiliary users with very close relationships with the target user can be screened out from all auxiliary users, and the insurance purchase records of the second-level associated persons have a significant reference role in configuring insurance for the target user, thereby improving the accuracy and effectiveness of configuring insurance for the target user.

[0168] The obtaining of insurance that is blocked or recommended to the user based on the insurance purchase records of the first-level associated persons and the second-level associated persons of the target user specifically includes:

[0169] Obtain the first-level associated persons and second-level associated persons of the target user to form the target population;

[0170] For each user in the target population, obtain the user's insurance purchase record;

[0171] Obtain the currently effective insurance among the insurance purchased by the user, which constitutes the first auxiliary insurance;

[0172] For each policy in the first supplementary policy;

[0173] the insured who obtains insurance;

[0174] Determine whether the insured persons include the target users;

[0175] Record the insurance type corresponding to the insurance whose insured includes the target user as the first auxiliary type;

[0176] Perform insurance shielding on the first auxiliary type of insurance;

[0177] The personalized insurance product recommendation method and system obtains the insurance purchase records of the first-level associated persons and the second-level associated persons, and screens the insurances that are still in effect, to determine whether the insured persons of these insurances include the target user. If the target user is included, the insured person is blocked. In this way, it can be avoided that when configuring insurance for the target user, the insurance whose coverage already includes the target user is purchased, resulting in unnecessary insurance and thus wasting the budget. This method improves the user experience and satisfaction.

[0178] The obtaining of insurance that is blocked or recommended to the user based on the insurance purchase records of the first-level associated persons and the second-level associated persons of the target user also includes:

[0179] Get the number of target populations, recorded as auxiliary number;

[0180] Set the recommended ratio threshold;

[0181] The recommendation ratio threshold is used to determine whether to recommend insurance to the user;

[0182] Obtain all insurance purchased by all users in the target population, and record them as the first insurance, the second insurance, and so on.

[0183] N refers to the number of all insurance policies purchased by all users in the target population;

[0184] Obtain the number of users in the target population who have purchased the first insurance, recorded as the first number; obtain the number of users in the target population who have purchased the second insurance, recorded as the second number... obtain the number of users in the target population who have purchased the Nth insurance, recorded as the Nth number;

[0185] Calculate the result of the first quantity ÷ the auxiliary quantity, the result of the second quantity ÷ the auxiliary quantity, and so on, the result of the Nth quantity ÷ the auxiliary quantity, and determine whether the result is greater than or equal to the recommended ratio threshold;

[0186] The insurance with the result greater than or equal to the recommended ratio threshold is recorded as the second auxiliary insurance;

[0187] The type of second auxiliary insurance is obtained, recorded as the second auxiliary type;

[0188] Make insurance recommendations for the second type of insurance;

[0189] A personalized insurance product recommendation method and system first obtains the number of target populations, sets a recommendation ratio threshold, and then obtains all insurances purchased by all users in the target population; for each insurance, the number of users who purchase this insurance in the target population is compared with the number of the target population. If the result is greater than the recommendation ratio threshold, it means that there are many people who purchase this insurance in the target population, and this insurance is recommended to target users who are closely connected with the target population; by analyzing the purchase ratio of each insurance product in the target population, the system can identify insurance products that are popular in the user's social circle; this recommendation method based on purchase data can increase the relevance of the recommendation and the user's trust in the recommended product. Users are more likely to accept and choose insurance products that are widely recognized in their social circles because these products have been verified and recognized by their friends or family. Secondly, giving priority to recommending insurance products with a high purchase ratio can reduce users' uncertainty and resistance to new products and increase purchase conversion rates. This method can also improve the efficiency of the recommendation system, reduce unnecessary recommendation attempts, and save users' time and energy.

[0190] The target broker configures insurance for the target user according to the first strategy, specifically including:

[0191] Get the target user's annual household income;

[0192] Calculate the premium budget cap using the following formula:

[0193] Premium budget cap = target user's annual household income × premium budget ratio;

[0194] The target broker configures insurance for the target user without exceeding the premium budget cap, where:

[0195] Not purchasing the first auxiliary type of insurance when configuring insurance;

[0196] When configuring insurance, give priority to purchasing the second auxiliary type of insurance.

[0197] Also includes:

[0198] The target user views the insurance configuration results of the target broker;

[0199] If the target user is satisfied with the result of insurance configuration;

[0200] Then, the target broker purchases insurance for the target user according to the result of insurance configuration;

[0201] If the target user is not satisfied with the result of the insurance configuration;

[0202] Then, the target broker reconfigures the insurance until the target user is satisfied with the result of the insurance configuration;

[0203] A personalized insurance product recommendation method and system, which can significantly improve the accuracy of personalized recommendations and user satisfaction by adjusting insurance configuration according to user feedback. Specifically, allowing users to view and feedback the results of insurance configuration can improve users' participation and trust in insurance recommendations. User feedback can help insurance brokers adjust insurance configuration in a timely manner to ensure that the final plan meets the user's real needs and preferences. This dynamic adjustment mechanism can enhance users' trust in the system and insurance brokers, and improve the personalization of services and user experience. For example, if users are not satisfied with the insurance configuration recommended for the first time, they can provide specific feedback, and insurance brokers can make adjustments based on these opinions until the user is satisfied. This method can not only improve user satisfaction and loyalty, but also help insurance companies accumulate more user preference data and optimize recommendation algorithms and strategies. In addition, adjusting insurance configuration according to user feedback can also reduce unnecessary insurance configuration attempts, save time and energy of users and insurance brokers, and improve overall service efficiency.

[0204] include:

[0205] Input port, used for users to enter personal information;

[0206] Information collection system, used to collect insurance purchase records of all users;

[0207] Information storage system, used to store insurance purchase records of all users;

[0208] The target broker recommendation system is used to recommend insurance brokers to target users.

[0209] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0210] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A personalized insurance product recommendation method, characterized in that: include: Get users who need to purchase insurance products and record them as target users; The target user enters personal information through the information input port; The personal information includes the target user's name, contact information, the target user's family members, annual family income and family member contact information; The target user's family members include the target user's spouse, parents, and children; All family members of the target user are recorded as first-level associates; Recommend qualified insurance brokers to target users based on their annual household income; The recommended insurance broker is recorded as the target insurance broker; Acquire the second-level associates of the target user according to the second-level associate acquisition strategy; Obtain insurance purchase records of the target user's first-level associates and second-level associates; The insurance purchase record includes all insurance purchased, the type of each insurance purchased, the validity period of each insurance purchased, and the insured of each insurance purchased; Obtaining insurance that is blocked or recommended for the user based on the insurance purchase records of the first-level associates and second-level associates of the target user; The target broker configures insurance for the target user according to the first strategy; The insurance configuration refers to the insurance broker configuring various types of insurance for target users.

2. A personalized insurance product recommendation method according to claim 1, characterized in that: The step of recommending a qualified insurance broker to a target user based on the target user's annual household income specifically includes: Get the target user's annual household income; Set the premium budget ratio threshold; The premium budget ratio threshold is used to represent the maximum ratio of the premium budget to the target user's family annual income; Calculate the maximum premium budget using the following formula: Maximum premium budget = target user's annual household income × premium budget ratio threshold; Set the premium budget range, specifically: The first budget range is below 5,000 yuan; 5,000 yuan to 6,000 yuan is the second budget range; 6,000 yuan to 7,000 yuan is the third budget range; 7,000 yuan to 8,000 yuan is the fourth budget range; 8,000 yuan and above is the fifth budget range; Get the maximum insurance budget; Get the budget interval to which the maximum insurance budget belongs, and record it as the target interval.

3. A personalized insurance product recommendation method according to claim 2, characterized in that: The recommending of insurance brokers meeting the criteria to the target user based on the target user's annual household income also includes: Get all insurance brokers; For each insurance broker, the number of insurance combinations whose costs are within the target range among all insurance combinations concluded by the broker is obtained, and recorded as the first number; Get the first quantity of all insurance brokers and sort them in descending order; The insurance brokers corresponding to the first number ranked first are selected as insurance brokers that meet the standards and are recommended to the target users.

4. A personalized insurance product recommendation method according to claim 1, characterized in that: The step of acquiring the second-level associated persons of the target user according to the second-level associated persons acquisition strategy specifically includes: Send a contact list query request to the target user; If the target user does not agree to query the address book, the target insurance broker will configure insurance for the target user who does not agree to query the address book, specifically: Get the target user's annual household income; Calculate the premium budget cap using the following formula: Premium budget cap = target user's annual household income × premium budget ratio; The target broker configures insurance for the target user without exceeding the premium budget limit; If the target user agrees to query the address book, obtain the target user's address book; Get the name, age and mobile phone number of each contact in the user's address book and form a pairing relationship; Get all users who have purchased insurance a non-zero number of times and record them as auxiliary users; Sending a request for querying the address book to the auxiliary user; Obtain the name, age and mobile phone number of each contact in the address book of the auxiliary user who agrees to query the address book, and form a pairing relationship; Set the age range, specifically: Those under 20 years old are recorded as the first age range; 20-35 years old is recorded as the second age range; 35-50 years old is recorded as the third age range; Those aged 50 and above are recorded as the fourth age range; Determine whether the target user and the auxiliary user have the same pairing relationship in each age range, specifically: Acquire the pairing relationships of the target users whose ages are in the first age range to form a first pairing relationship group; acquire the pairing relationships of the target users whose ages are in the second age range to form a second pairing relationship group; acquire the pairing relationships of the target users whose ages are in the third age range to form a third pairing relationship group; acquire the pairing relationships of the target users whose ages are in the fourth age range to form a fourth pairing relationship group; The pairing relationship in the auxiliary user pairing relationship that is the same as a pairing relationship in the first pairing relationship group constitutes a first judgment set, the pairing relationship in the auxiliary user pairing relationship that is the same as a pairing relationship in the second pairing relationship group constitutes a second judgment set, the pairing relationship in the auxiliary user pairing relationship that is the same as a pairing relationship in the third pairing relationship group constitutes a third judgment set, and the pairing relationship in the auxiliary user pairing relationship that is the same as a pairing relationship in the fourth pairing relationship group constitutes a fourth judgment set; The auxiliary users corresponding to each pairing relationship in the first judgment set constitute a first auxiliary set, the auxiliary users corresponding to each pairing relationship in the second judgment set constitute a second auxiliary set, the auxiliary users corresponding to each pairing relationship in the third judgment set constitute a third auxiliary set, and the auxiliary users corresponding to each pairing relationship in the fourth judgment set constitute a fourth auxiliary set; Take the intersection of the first auxiliary set, the second auxiliary set, the third auxiliary set and the fourth auxiliary set, and record it as the target set; The auxiliary users in the target set are recorded as second-level associated persons.

5. A personalized insurance product recommendation method according to claim 1, characterized in that: The obtaining of insurance that is blocked or recommended to the user based on the insurance purchase records of the first-level associated persons and the second-level associated persons of the target user specifically includes: Obtain the first-level associated persons and second-level associated persons of the target user to form the target population; For each user in the target population, obtain the user's insurance purchase record; Obtain the currently effective insurance among the insurance purchased by the user, which constitutes the first auxiliary insurance; For each policy in the first supplementary policy; the insured person who obtains insurance; Determine whether the insured persons include the target users; Record the insurance type corresponding to the insurance whose insured includes the target user as the first auxiliary type; Perform insurance shielding on the first auxiliary type of insurance.

6. A personalized insurance product recommendation method according to claim 5, characterized in that: The step of obtaining the insurance that is blocked or recommended to the user based on the insurance purchase records of the first-level associated persons and the second-level associated persons of the target user further includes: Get the number of target populations, recorded as auxiliary number; Set the recommended ratio threshold; The recommendation ratio threshold is used to determine whether to recommend insurance to the user; Obtain all insurance purchased by all users in the target population, and record them as the first insurance, the second insurance, and so on. N refers to the number of all insurance policies purchased by all users in the target population; Obtain the number of users in the target population who have purchased the first insurance, recorded as the first number; obtain the number of users in the target population who have purchased the second insurance, recorded as the second number... obtain the number of users in the target population who have purchased the Nth insurance, recorded as the Nth number; Calculate the result of the first quantity ÷ the auxiliary quantity, the result of the second quantity ÷ the auxiliary quantity, and so on, the result of the Nth quantity ÷ the auxiliary quantity, and determine whether the result is greater than or equal to the recommended ratio threshold; The insurance with the result greater than or equal to the recommended ratio threshold is recorded as the second auxiliary insurance; The type of second auxiliary insurance is obtained, recorded as the second auxiliary type; Make insurance recommendations for the second type of insurance.

7. A personalized insurance product recommendation method according to claim 1, characterized in that: The target broker configures insurance for the target user according to the first strategy, specifically including: Get the target user's annual household income; Calculate the premium budget cap using the following formula: Premium budget cap = target user's annual household income × premium budget ratio; The target broker configures insurance for the target user without exceeding the premium budget cap, where: Not purchasing the first auxiliary type of insurance when configuring insurance; When configuring insurance, give priority to purchasing the second auxiliary type of insurance.

8. A personalized insurance product recommendation method according to claim 1, characterized in that: Also includes: The target user views the insurance configuration results of the target broker; If the target user is satisfied with the result of insurance configuration; Then, the target broker purchases insurance for the target user according to the result of insurance configuration; If the target user is not satisfied with the result of the insurance configuration; Then, the target broker reconfigures the insurance until the target user is satisfied with the result of the insurance configuration.

9. A system for implementing the personalized insurance product recommendation method of claim 1, characterized in that: include: Input port, used for users to enter personal information; Information collection system, used to collect insurance purchase records of all users; Information storage system, used to store insurance purchase records of all users; The target broker recommendation system is used to recommend insurance brokers to target users.

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