CN113128595A - Method, apparatus, device and computer readable medium for integrating customer information - Google Patents
Method, apparatus, device and computer readable medium for integrating customer information Download PDFInfo
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Abstract
The invention discloses a method, a device, equipment and a computer readable medium for integrating customer information, and relates to the technical field of computers. One embodiment of the method comprises: determining the basic similarity degree of the input customer information and the existing customer information if the input customer information is the same as the basic customer information of the existing customer information, wherein the basic customer information comprises name and gender; analyzing the degree of similarity of the relationship between the input customer information and the existing customer information based on the policyholder, the insured person and the beneficiary in the policy to which the customer information belongs; and integrating the input customer information and the existing customer information by combining the basic similarity degree and the relation similarity degree. The implementation mode can integrate the customer information of the same customer in different insurance systems, and guarantee the normal operation of the insurance systems.
Description
Technical Field
The present invention relates to the field of computer technologies, and in particular, to a method, an apparatus, a device, and a computer-readable medium for integrating customer information.
Background
Due to differences in insurance products, different sources of customer information, and different insurance systems, the customer information for the same customer may vary greatly. Even if it is the same customer of the fact, the customer information stored in different insurance systems may not be the same.
In the process of implementing the invention, the inventor finds that at least the following problems exist in the prior art: in different insurance systems, the client information of the same client exists in a large quantity under different conditions, so that the client information is disordered, and the normal operation of the insurance systems is seriously influenced.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method, an apparatus, a device, and a computer readable medium for integrating customer information, which can integrate customer information of a same customer in different insurance systems to ensure normal operation of the insurance systems.
To achieve the above object, according to an aspect of an embodiment of the present invention, there is provided a method of integrating customer information, including:
determining the basic similarity degree of the input customer information and the existing customer information if the input customer information is the same as the basic customer information of the existing customer information, wherein the basic customer information comprises name and gender;
analyzing the degree of similarity of the relationship between the input customer information and the existing customer information based on the policyholder, the insured person and the beneficiary in the policy to which the customer information belongs;
and integrating the input customer information and the existing customer information by combining the basic similarity degree and the relation similarity degree.
The input customer information is the same as basic customer information of the existing customer information, and comprises the following steps:
and determining that the names of the input customer information and the existing customer information are the same, and then judging that the sexes of the input customer information and the existing customer information are consistent.
Determining a degree of substantial similarity of the input customer information to the existing customer information if the input customer information is the same as basic customer information of the existing customer information, comprising:
the input customer information is the same as basic customer information of the existing customer information, and the basic similarity degree of the input customer information and the existing customer information is determined according to the birth date of the input customer information and/or the birth date of the existing customer information.
Analyzing the degree of similarity of the relationship between the client information and the existing client information based on the policyholder, the insured person and the beneficiary in the policy to which the client information belongs, and comprising the following steps:
establishing an input information set according to an applicant, an insured life and a beneficiary in the insurance policy to which the input client information belongs;
searching the same identification in the policyholder, the policyholder and the beneficiary in the policy to which the existing customer information belongs according to the identification in the input information set;
and determining the similarity degree of the relationship between the input customer information and the existing customer information based on the number of the same identifications.
The determining the degree of similarity of the relationship between the input customer information and the existing customer information based on the number of the same identifications comprises:
the number of the same marks is 1, and the similarity degree of the relationship between the input customer information and the existing customer information is determined to be similar;
and if the number of the same identifications is more than 1, determining that the similarity degree of the relationship between the input customer information and the existing customer information is the same.
The integrating the input customer information and the existing customer information by combining the basic similarity degree and the relationship similarity degree comprises:
acquiring the health similarity degree of the input customer information and the existing customer information based on the health information in the policy to which the customer information belongs;
integrating the input customer information and the existing customer information in combination with the basic similarity degree, the relationship similarity degree and the health similarity degree.
The integrating the input customer information and the existing customer information by combining the basic similarity degree and the relationship similarity degree comprises:
combining the basic similarity degree and the relation similarity degree to determine that the input customer information is partially overlapped with the existing customer information, and combining other information for integration again;
and combining the basic similarity degree and the relation similarity degree to determine that the input customer information is completely overlapped with the existing customer information, and combining the input customer information and the existing customer information.
According to a second aspect of the embodiments of the present invention, there is provided an apparatus for integrating customer information, including:
the basic module is used for determining the basic similarity degree of the input customer information and the existing customer information if the input customer information is the same as the basic customer information of the existing customer information, wherein the basic customer information comprises name and gender;
the analysis module is used for analyzing the similarity degree of the relationship between the input customer information and the existing customer information based on an applicant, an insured person and a beneficiary in the policy to which the customer information belongs;
and the integration module is used for integrating the input customer information and the existing customer information by combining the basic similarity degree and the relation similarity degree.
According to a third aspect of the embodiments of the present invention, there is provided an electronic device for integrating customer information, including:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method as described above.
According to a fourth aspect of embodiments of the present invention, there is provided a computer readable medium, on which a computer program is stored, which when executed by a processor, implements the method as described above.
One embodiment of the above invention has the following advantages or benefits: determining the basic similarity degree of the input customer information and the existing customer information if the input customer information is the same as the basic customer information of the existing customer information, wherein the basic customer information comprises name and gender; analyzing the degree of similarity of the relationship between the client information and the existing client information based on the policyholder, the insured person and the beneficiary in the policy to which the client information belongs; and integrating the input customer information and the existing customer information by combining the basic similarity degree and the relation similarity degree. According to the basic similarity and the relation similarity, the client information of the same client in different insurance systems can be integrated, so that the normal operation of the insurance systems is guaranteed.
Further effects of the above-mentioned non-conventional alternatives will be described below in connection with the embodiments.
Drawings
The drawings are included to provide a better understanding of the invention and are not to be construed as unduly limiting the invention. Wherein:
FIG. 1 is a schematic diagram of a main flow of a method of integrating customer information according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart illustrating a process of analyzing similarity between customer information and existing customer information according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of determining a degree of similarity of a relationship of input customer information to existing customer information, according to an embodiment of the invention;
FIG. 4 is another schematic diagram for determining a degree of similarity of a relationship of input customer information to existing customer information, in accordance with an embodiment of the present invention;
FIG. 5 is a schematic diagram of yet another method for determining similarity of relationship between input customer information and existing customer information, in accordance with embodiments of the present invention;
fig. 6 is a schematic diagram of a main structure of an apparatus for integrating customer information according to an embodiment of the present invention;
FIG. 7 is an exemplary system architecture diagram in which embodiments of the present invention may be employed;
fig. 8 is a schematic structural diagram of a computer system suitable for implementing a terminal device or a server according to an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present invention are described below with reference to the accompanying drawings, in which various details of embodiments of the invention are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
In different insurance systems, the client information of the same client is different. As an example, a customer Zhang Sanqi purchases a life insurance with an identity card at the same insurance company. Then buy a health risk again with the passport. In this scenario, even if the life insurance and the health insurance belong to the same company, the five elements of the client are different, and the client can only be regarded as two different clients. Wherein, the five elements of the client comprise: name, gender, date of birth, credential type and credential number.
When the situations exist in large quantity, not only the customer experience is negatively influenced, but also the business development of the company is greatly negatively influenced. The company cannot accurately master the client information, cannot realize accurate panoramic images of the clients, cannot accurately serve businesses, and cannot even talk about service expansion.
The establishment of the panoramic image of the client is a target which is dedicated to the realization of the insurance industry and has important significance for the continuous development of the current business and the subsequent business expansion. A client has only one identity authentication at an enterprise. The primary task is to integrate those instances where one customer has multiple pieces of information in the existing customer information.
Specifically, the following methods are mainly adopted:
the method comprises the following steps: the customer asks for questions and then integrates the question data. This integration, starting from customer doubts, is clearly already not suitable for the current business development needs. The method has no business prospect and greatly harms the experience of customers.
The second method comprises the following steps: and screening data by service personnel at regular time to realize subsequent integration. When the data volume is small, the method is an effective scheme. However, when the method is used for dealing with massive client data and the client data come from various different sales ends, the screening of business personnel can not obviously adapt to the requirements.
Illustratively, a suspected integrable customer information list is manually screened out through a certain rule, then confirmed by a worker through a telephone, and then the same customer information is manually merged. Although the current scheme ensures the accuracy of integration, a large amount of manual operation necessarily influences the efficiency of integration. When the customer information sources are various, the data dimension is more complex, and the data volume of the customer information reaches a certain degree, most of the problems cannot be solved by the method of manual confirmation.
The third method comprises the following steps: and a simple rule is established for automatic screening, and due to the simplicity of the screening rule, the referential property of the screened data is low, and the integration rate is low.
Therefore, in different insurance systems, the condition that the client information of the same client is inconsistent exists in a large quantity, so that the client information is disordered, and the normal operation of the insurance systems is seriously influenced.
In order to solve the problem that the same client has different client information in different systems, the following technical scheme in the embodiment of the invention can be adopted.
Referring to fig. 1, fig. 1 is a schematic diagram of a main flow of a method for integrating customer information according to an embodiment of the present invention, and integrates customer information in combination with basic customer information and relationship similarity. As shown in fig. 1, the method specifically comprises the following steps:
s101, if the input customer information is the same as basic customer information of the existing customer information, determining the basic similarity degree of the input customer information and the existing customer information, wherein the basic customer information comprises name and gender.
In an embodiment of the invention, the customer information is information in the policy related to the customer. There is customer information for each policy. A plurality of customer information items are stored in a database. The customer information to be integrated is referred to as input customer information, and the customer information stored in the database is referred to as existing customer information. The input customer information and the existing customer information are integrated by comparing the input customer information and the existing customer information. As one example, the input customer information is integrated with a plurality of existing customer information, respectively.
The basic customer information is the information which characterizes the basic characteristics of the customer in the customer information. As one example, the base customer information includes name and gender.
The degree of substantial similarity of the input customer information to the existing customer information is determined by comparing the input customer information with the underlying customer information of the existing customer information. As an example, if the input customer information is the same as basic customer information of existing customer information, determining that the degree of substantial similarity between the input customer information and the existing customer information is equal to a preset basic value; the input customer information is different from the basic customer information of the existing customer information, and it is determined that the degree of substantial similarity of the input customer information and the existing customer information is equal to 0. The basic customer information of the input customer information and the existing customer information is the same, and the input customer information and the basic customer information of the existing customer information comprise the same name and the same gender. The difference between the input customer information and the base customer information of the existing customer information includes name difference and/or gender inconsistency.
It is understood that in the case of different names and/or different genders, the input customer information is different from the existing customer information, and thus the degree of similarity is substantially equal to 0.
In one embodiment of the present invention, in order to improve the efficiency of integrating the customer information, it may be determined whether the names of the input customer information and the existing customer information are the same, and then it may be determined whether the genders of the input customer information and the existing customer information are the same. In the case where it is determined that the name of the input customer information is the same as that of the existing customer information, it is necessary to determine whether or not the sex of the input customer information is consistent with that of the existing customer information. In the case where it is determined that the names of the input customer information and the existing customer information are different, it is not necessary to judge whether or not the genders of the input customer information and the existing customer information coincide with each other.
This is because the name is the most important information among the customer information. If the names are different, the input customer information can be directly confirmed to be different from the existing customer information, and the input customer information and the existing customer information do not belong to the same customer, so that integration is not needed. Similarly, in the case of the same name, it is determined whether or not the genders match to further determine the similarity between the input customer information and the existing customer information.
In one embodiment of the present invention, to improve the accuracy of the basic similarity degree, the birth date may also be determined based on the determination of the name and gender. It should be noted that the birth date is determined after confirming that the sex of the input client information is the same as that of the existing client information and the sex is the same.
That is, the input client information is the same as the basic client information of the existing client information, and the degree of substantial similarity between the input client information and the existing client information is determined according to the birth date of the input client information and/or the birth date of the existing client information.
As an example, the input client information is the same as basic client information of existing client information, the birth date of the input client information is consistent with the birth date of the existing client information, and it is determined that the degree of substantial similarity between the input client information and the existing client information is equal to the preset basic value + the birth date consistent increment value. Such as: the birth date was consistently increased by a value equal to 10.
As another example, the input customer information is the same as basic customer information of existing customer information, the input customer information does not include a date of birth or the existing customer information does not include a date of birth, and it is determined that the input customer information is substantially similar to the existing customer information to a degree equal to the preset basic value + 5.
As still another example, the input customer information is identical to basic customer information of existing customer information, a birth date of the input customer information is different from a birth date of the existing customer information, and it is determined that a degree of substantial similarity of the input customer information to the existing customer information is equal to a preset basic value.
S102, analyzing the similarity degree of the relationship between the customer information and the existing customer information based on the policyholder, the insured person and the beneficiary in the policy to which the customer information belongs.
In the embodiment of the invention, the technical scheme is mainly applied to the policy, namely, the customer information in the policy is integrated. Not only needs to be related to the basic customer information, but also related to interpersonal relationship similarity. That is, the degree of similarity of the relationship of the input customer information with the existing customer information is analyzed from the perspective of the interpersonal relationship.
Interpersonal relationships can be characterized in a variety of forms. In integrating the customer information in the policy, the policy necessarily includes the applicant, the insured life and the beneficiary. Relevant regulations stipulate that there is either a direct relationship or some interest between the applicant and the insured life. The interest relationship mainly refers to the laborers who have a labor relationship with the applicant. So for a particular customer, the customer may be present as an insured life, as an insurer, or as a beneficiary across multiple policy entities. But whatever role the client appears in, its interpersonal relationships are highly overlapping. It will be appreciated that the applicant, insured life and beneficiary within the same policy constitute the aforementioned interpersonal relationships.
Therefore, the degree of similarity of the relationship between the input customer information and the existing customer information is analyzed based on the applicant, the insured person and the beneficiary in the policy to which the customer information belongs.
Referring to fig. 2, fig. 2 is a schematic flowchart of analyzing a similarity degree between customer information and existing customer information according to an embodiment of the present invention, which specifically includes the following steps:
s201, establishing an input information set according to an applicant, an insured life and a beneficiary in the insurance policy to which the input client information belongs.
The policy to which the input client information belongs includes an applicant, an insured life and a beneficiary, and then an input information set can be established according to the applicant, the insured life and the beneficiary in the policy to which the input client information belongs.
As an example, an applicant in a policy to which customer information pertains is entered: zhang III; the insured life: plum four; the beneficiary: plum one, plum two and plum three. The input information set comprises: zhang three, Liqu, Liyi, Liqu two and Zhang three. It should be noted that the plurality of parameters in the input information set are not sequential.
S202, searching the same identification in the policyholder, the policyholder and the beneficiary in the policy to which the existing customer information belongs according to the identification in the input information set.
In the policy to which the existing customer information belongs, including the applicant, the insured life and the beneficiary as well, the number of the same identifiers in the policy to which the input information set and the existing customer information belong needs to be known. It will be appreciated that the applicant, the insured life and the beneficiary in the policy each have a corresponding identification, and as an example the applicant's identification is: and 4, plum four. Then, the same identification can be searched in the policy to which the existing customer information belongs, such as the policyholder, the policyholder and the beneficiary according to the identification in the input information set.
S203, determining the similarity degree of the relationship between the input customer information and the existing customer information based on the number of the same identifications.
According to the number of the marks in the input set information, the similarity degree of the relationship between the input client information and the existing client information can be determined according to the number of the marks which are the same as those in the policyholder, the policyholder and the beneficiary in the policy to which the existing client information belongs. As an example, the similarity degree of the relationship between the input customer information and the existing customer information is similar, and is obtained as 15 points; the degree of similarity of the relationship between the input customer information and the existing customer information is the same, and is given as 30 points.
Multiple times of practice shows that the same customer information can not be effectively integrated if the quantity of the same identification is set to be larger; the relationship between the applicant, the insured life and the beneficiary in the policy cannot be reflected if the number of the same identification is set to be small.
As an example, consider that the same customer may be an applicant in one policy and an applicant, insured person or beneficiary in another policy. Wherein the number of policemen, the number of insureds and the number of beneficiaries are all at least 1. That is, if the number of the same identifier in the two policy is 0, it indicates that the two policies are irrelevant; the presence of the same identifier in both policies, i.e., the number of identical identifiers in both policies is not 0, indicates that both policies have a relationship. Considering that in the scheme of integrating customer information, in addition to analyzing the degree of similarity of the relationship, basic customer information needs to be combined, a threshold value of 1 is set to determine similarity or identity through multiple practices. If other numbers greater than 1 are set to determine similar or identical thresholds, similar or identical conditions are more strict, and practically identical customer information is difficult to integrate.
Setting 1 to determine similar or identical thresholds can be understood as: the number of identical labels in both policies is 1. Specifically, the number of the same identifiers is 1, and the similarity degree of the relationship between the input customer information and the existing customer information is determined to be similar; the number of the same marks is larger than 1, and the similarity degree of the relationship between the input customer information and the existing customer information is determined to be the same.
The degree of similarity is illustratively described below in connection with the figures.
Referring to fig. 3, fig. 3 is a schematic diagram for determining a degree of similarity between the relationship of the input customer information and the existing customer information according to an embodiment of the present invention.
In fig. 3, two policies are included, policy 1 being the policy to which the input customer information belongs, and policy 2 being the policy to which the existing customer information belongs.
The policyholder, insured person and beneficiary involved in policy 1 are: zhang three, Liyi and Zhang three.
The policyholder, insured person and beneficiary involved in policy 2 are: leersia 1, leersia, Zhang III, leersia and leersia 1.
Since the number 2 of identical identifiers in the policy 1 and the policy 2 is greater than 1, it is determined that the degree of similarity of the relationship between the input customer information and the existing customer information is the same.
Referring to fig. 4, fig. 4 is another schematic diagram for determining similarity of relationship between input customer information and existing customer information according to an embodiment of the present invention.
In fig. 4, two policies are included, policy 1 being the policy to which the input customer information belongs, and policy 4 being the policy to which the existing customer information belongs.
The policyholder, insured person and beneficiary involved in policy 1 are: zhang three, Liyi and Zhang three.
The policyholder, insured person and beneficiary involved in policy 4 are: three of Zhang, one of Zhang, four of plum 2 and five of urheen.
Because of the number of identical identifiers 1 in policy 1 and policy 4, it is determined that the degree of similarity of the relationship of the input customer information to the existing customer information is similar.
Referring to fig. 5, fig. 5 is a schematic diagram of determining a similarity degree of a relationship between input customer information and existing customer information according to another embodiment of the present invention.
In fig. 5, two policies are included, policy 3 being the policy to which the input customer information belongs, and policy 5 being the policy to which the existing customer information belongs.
The policyholder, insured person and beneficiary involved in policy 3 are: plum four 1, plum one, plum three and plum two.
The applicant, insured person and beneficiary persons involved in policy 5: zhang three 2, Wang five and Han seven.
Since the number 0 of identical identifiers in the policy 3 and the policy 5 is less than 1, it is determined that the degree of similarity of the relationship between the input customer information and the existing customer information is different.
And S103, integrating the input customer information and the existing customer information by combining the basic similarity degree and the relation similarity degree.
And comparing the basic customer information to obtain basic similarity, analyzing interpersonal relationship to obtain relationship similarity, and integrating the input customer information and the existing customer information by combining the basic similarity and the relationship similarity.
In one embodiment of the invention, the basic similarity degree and the relation similarity degree are combined, the input customer information is determined to be partially overlapped with the existing customer information, and then the integration is carried out again by combining other information.
And combining the basic similarity degree and the relation similarity degree to determine that the input client information is completely overlapped with the existing client information, and combining the input client information and the existing client information.
In specific implementation, whether the input customer information and the existing customer information are combined or not is determined according to the relation between the sum of the scores of the basic similarity degree and the scores of the relation similarity degree and the complete coincidence threshold value and the partial coincidence threshold value.
As one example, the score of the substantial degree of similarity is known based on the substantial degree of similarity according to a preset rule. Such as: the input customer information is the same as the basic customer information of the existing customer information, and the score of the degree of similarity of the levels is 50.
As another example, the relationship similarity degrees are similar, and the score of the relationship similarity degrees is 25 scores; the degree of relationship similarity is the same, and the score of the degree of relationship similarity is 40.
The complete overlap threshold is 89 minutes, and the partial overlap threshold is 69 minutes. And the sum of the scores of the basic similarity degrees and the scores of the relationship similarity degrees is between a complete coincidence threshold value and a partial coincidence threshold value, and if the input customer information and the existing customer information are determined not to be merged, other information needs to be merged again. As one example, the other information may be information obtained from a system.
And determining that the sum of the scores of the basic similarity degree and the scores of the relationship similarity degree is greater than a complete coincidence threshold value, and combining the input customer information and the existing customer information.
And determining that the input customer information and the existing customer information do not belong to the same customer without combining the input customer information and the existing customer information when the sum of the scores of the basic similarity degree and the scores of the relationship similarity degree is smaller than a partial coincidence threshold.
In one embodiment of the invention, in order to improve the accuracy of integrating the customer information, the health information in the policy to which the customer information belongs can be considered in the process of integrating the input customer information and the existing customer information.
In the big data era, more and more dimensions of the client health information can be mastered. Generally, some unique health information can be even used as direct identification of the client, such as DNA data, iris data and the like. However, because the health information in the policy is not as accurate as the applicant, the data of the insured person and the beneficiary are highly accurate and are not verified with accuracy. Thus, the health information in the policy serves as one factor, but not the only factor, in integrating the customer information. As one example, the health information includes one or more of DNA, blood type, face recognition, iris recognition, fingerprint recognition, and critical illness features.
Firstly, based on the health information in the policy to which the client information belongs, the health similarity degree between the input client information and the existing client information is obtained. And secondly, integrating the input customer information and the existing customer information by combining the basic similarity degree, the relationship similarity degree and the health similarity degree. The input customer information and the existing customer information are integrated similarly to the combination of the score for the degree of substantial similarity and the score for the degree of relational similarity. The input customer information and the existing customer information may be integrated in combination with the score for the degree of substantial similarity, the score for the degree of relationship similarity, and the score for the degree of health similarity.
The health similarity level is briefly described below.
If the health information of the input client information is 2 items or more than 2 items of health information of the existing client information, the similarity degree of the health of the input client information and the health of the existing client information is the same. As one example, the health information entered into the customer information includes blood type a and thrombocytopenia with platelets less than 80. The health information of the existing client information includes DNA information, blood type A and thrombocytopenia and platelets are less than 80.
If the health information of the input client information is 1 item the same as the health information of the existing client information, the similarity degree of the health of the input client information and the health of the existing client information is similar. As one example, the health information entered into the customer information includes blood type a and thrombocytopenia with platelets less than 80. The health information of the existing client information includes DNA information, blood type B and thrombocytopenia with platelets less than 80.
If the health information of the input client information does not have the same item as the health information of the existing client information, the similarity degree of the health of the input client information and the health of the existing client information is different. As one example, the health information entered into the customer information includes blood type a and thrombocytopenia with platelets less than 80. The health information of the existing client information comprises DNA information and blood type B.
In the above embodiment, if the input customer information is the same as the basic customer information of the existing customer information, determining the basic similarity degree between the input customer information and the existing customer information, where the basic customer information includes name and gender; analyzing the degree of similarity of the relationship between the client information and the existing client information based on the policyholder, the insured person and the beneficiary in the policy to which the client information belongs; and integrating the input customer information and the existing customer information by combining the basic similarity degree and the relation similarity degree. According to the basic similarity and the relation similarity, the client information of the same client in different insurance systems can be integrated, so that the normal operation of the insurance systems is guaranteed.
In the embodiment of the invention, a set of intelligent customer information integration method is provided aiming at some characteristics of insurance data. The degree of similarity of customer information can be integrated. Such as: if the customer information is the same above a preset threshold, the customer information is directly merged. Between the two preset thresholds, integration after completion of more information is required. If the value is lower than another preset threshold value, the customer information is considered to be completely different, and integration is not needed. The method and the system can not only realize automatic integration of customer information, but also know the difference of the customer information which is not integrated completely, thereby providing suggestions and basis for subsequent operations.
The existing insurance big data is used for automatically judging whether the two customer information are the same or not and whether the two customer information can be integrated or not. Completely breaks through the mode that business personnel need to actively contact the client to confirm data in the past. The automatic integration is realized by analyzing the characteristics of the existing insurance data and comparing the existing insurance data. Not only ensures the accuracy of combination, but also greatly improves the efficiency.
The technical solution in the embodiment of the present invention is exemplarily described below by a specific example.
The client shoplifter 2000 purchases a life insurance for the spouse Yang, and the beneficiary is Yang, Xiao and Xiao. The five elements of the customer left behind by the portrait at that time were:
name: a kind of portrait
Sex: for male
Year, month and day of birth: 1968, 12 months and 8 days
The certificate types are as follows: taiwan syndrome/pattern
Certificate number: 12345678910
In 2010, the customer purchases a car insurance with an identity card in the same insurance company, and the beneficiaries are shoal and shoal. The five elements of the customer left behind by the portrait at that time were:
name: a kind of portrait
Sex: for male
Year, month and day of birth: 1968, 12 months and 8 days
The certificate types are as follows: passport
Certificate number: 10987654321
In the health advice, the customer would like the advice blood type to be type a.
A customer Yang in 2018 bought one million medical health risks to the same insurance company to the shoker, and the income people are Yang, Xiao and Da. The five elements of the customer left behind by the portrait at that time were:
name: a kind of portrait
Sex: for male
Year, month and day of birth: 1968, 12 months and 8 days
The certificate types are as follows: identity card
Certificate number: 1245678X
In the health advice, the customer has a type a of blood.
Since five elements of the above three policies are different from each other, the client information is stored as three different clients.
The scheme in the embodiment of the invention is adopted to realize customer integration. And taking the life insurance policy purchased in 2000 as the policy corresponding to the input customer information. The insurance policy of the vehicle purchased in 2010 is taken as the existing customer information. The health insurance policy purchased in 2018 is taken as the existing customer information.
First, a degree of substantial similarity of the input customer information to the existing customer information is determined. And respectively determining the scores of the basic similarity of the life insurance policy and the vehicle insurance policy as a preset basic value, wherein the preset basic value is 20 points. Secondly, if the input customer information is the same as the existing customer information in birth date, the increment value of the birth date consistency is 40 points, the basic similarity score of the input customer information and the existing customer information is the sum of the preset basic value and the increment value of the birth date consistency, and the basic similarity score is 60 points specifically.
Then, the number of the same marks in the input customer information and the existing customer information is 3, the degree of similarity of the relationship between the input customer information and the existing customer information is the same, and the score is 30.
Finally, the incoming customer information does not include health information, the existing customer information includes blood type a, and the score is 5.
And combining the scores of the basic similarity degree, the relationship similarity degree and the health similarity degree, wherein the total score is 95 scores and is greater than the same complete coincidence threshold value 89 scores, and determining to combine the input customer information with the existing customer information.
Similarly, the life insurance policy purchased in 2000 is taken as the policy corresponding to the input customer information. The health insurance policy purchased in 2018 is taken as the existing customer information. And combining the scores of the basic similarity degree, the relationship similarity degree and the health similarity degree, wherein the total score is 95 scores and is greater than the same complete coincidence threshold value 89 scores, and determining to combine the input customer information with the existing customer information.
Referring to fig. 6, fig. 6 is a schematic diagram of a main structure of an apparatus for integrating customer information according to an embodiment of the present invention, where the apparatus for integrating customer information can implement a method for integrating customer information, and as shown in fig. 6, the apparatus for integrating customer information specifically includes:
a basic module 601, configured to determine a basic similarity degree between the input customer information and existing customer information if the input customer information is the same as basic customer information of the existing customer information, where the basic customer information includes a name and a gender;
an analysis module 602, configured to analyze a degree of similarity between the input customer information and the existing customer information based on an applicant, an insured person and a beneficiary in a policy to which the customer information belongs;
an integrating module 603, configured to integrate the input customer information and the existing customer information according to the basic similarity degree and the relationship similarity degree.
In an embodiment of the present invention, the basic module 601 is specifically configured to determine that the names of the input customer information and the existing customer information are the same, and then determine that the gender of the input customer information is consistent with that of the existing customer information.
In an embodiment of the present invention, the basic module 601 is specifically configured to determine how similar the input customer information is to the existing customer information according to the birth date of the input customer information and/or the birth date of the existing customer information.
In an embodiment of the present invention, the analysis module 602 is specifically configured to establish an input information set according to an applicant, an insured life and a beneficiary in the policy to which the input customer information belongs;
searching the same identification in the policyholder, the policyholder and the beneficiary in the policy to which the existing customer information belongs according to the identification in the input information set;
and determining the similarity degree of the relationship between the input customer information and the existing customer information based on the number of the same identifications.
In an embodiment of the present invention, the analyzing module 602, specifically configured to determine that the number of the same identifiers is 1, determines that the similarity degrees of the relationships between the input customer information and the existing customer information are similar;
and if the number of the same identifications is more than 1, determining that the similarity degree of the relationship between the input customer information and the existing customer information is the same.
In an embodiment of the present invention, the integrating module 603 is specifically configured to obtain a health similarity between the input customer information and the existing customer information based on health information in a policy to which the customer information belongs;
integrating the input customer information and the existing customer information in combination with the basic similarity degree, the relationship similarity degree and the health similarity degree.
In an embodiment of the present invention, the integrating module 603 is specifically configured to combine the basic similarity degree and the relationship similarity degree, determine that the input customer information partially coincides with the existing customer information, and then integrate again by combining other information;
and combining the basic similarity degree and the relation similarity degree to determine that the input customer information is completely overlapped with the existing customer information, and combining the input customer information and the existing customer information.
Fig. 7 illustrates an exemplary system architecture 700 of a method of consolidating customer information or an apparatus for consolidating customer information to which embodiments of the present invention may be applied.
As shown in fig. 7, the system architecture 700 may include terminal devices 701, 702, 703, a network 704, and a server 705. The network 704 serves to provide a medium for communication links between the terminal devices 701, 702, 703 and the server 705. Network 704 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
A user may use the terminal devices 701, 702, 703 to interact with a server 705 over a network 704, to receive or send messages or the like. The terminal devices 701, 702, 703 may have installed thereon various communication client applications, such as a shopping-like application, a web browser application, a search-like application, an instant messaging tool, a mailbox client, social platform software, etc. (by way of example only).
The terminal devices 701, 702, 703 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
The server 705 may be a server providing various services, such as a background management server (for example only) providing support for shopping websites browsed by users using the terminal devices 701, 702, 703. The backend management server may analyze and perform other processing on the received data such as the product information query request, and feed back a processing result (for example, target push information, product information — just an example) to the terminal device.
It should be noted that the method for integrating customer information provided by the embodiment of the present invention is generally executed by the server 705, and accordingly, the apparatus for integrating customer information is generally disposed in the server 705.
It should be understood that the number of terminal devices, networks, and servers in fig. 7 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Referring now to FIG. 8, shown is a block diagram of a computer system 800 suitable for use with a terminal device implementing an embodiment of the present invention. The terminal device shown in fig. 8 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 8, the computer system 800 includes a Central Processing Unit (CPU)801 that can perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)802 or a program loaded from a storage section 808 into a Random Access Memory (RAM) 803. In the RAM 803, various programs and data necessary for the operation of the system 800 are also stored. The CPU 801, ROM 802, and RAM 803 are connected to each other via a bus 804. An input/output (I/O) interface 805 is also connected to bus 804.
The following components are connected to the I/O interface 805: an input portion 806 including a keyboard, a mouse, and the like; an output section 807 including a signal such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 808 including a hard disk and the like; and a communication section 809 including a network interface card such as a LAN card, a modem, or the like. The communication section 809 performs communication processing via a network such as the internet. A drive 810 is also connected to the I/O interface 805 as necessary. A removable medium 811 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 810 as necessary, so that a computer program read out therefrom is mounted on the storage section 808 as necessary.
In particular, according to the embodiments of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication section 809 and/or installed from the removable medium 811. The computer program executes the above-described functions defined in the system of the present invention when executed by the Central Processing Unit (CPU) 801.
It should be noted that the computer readable medium shown in the present invention can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present invention, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules described in the embodiments of the present invention may be implemented by software or hardware. The described modules may also be provided in a processor, which may be described as: a processor includes a base module, an analysis module, and an integration module. The names of these modules do not constitute a limitation on the modules themselves in some cases, for example, the basic module may be further described as "basic customer information for the input customer information is the same as existing customer information, and the basic customer information includes name and gender", and then the degree of substantial similarity between the input customer information and the existing customer information is determined.
As another aspect, the present invention also provides a computer-readable medium that may be contained in the apparatus described in the above embodiments; or may be separate and not incorporated into the device. The computer readable medium carries one or more programs which, when executed by a device, cause the device to comprise:
determining the basic similarity degree of the input customer information and the existing customer information if the input customer information is the same as the basic customer information of the existing customer information, wherein the basic customer information comprises name and gender;
analyzing the degree of similarity of the relationship between the input customer information and the existing customer information based on the policyholder, the insured person and the beneficiary in the policy to which the customer information belongs;
and integrating the input customer information and the existing customer information by combining the basic similarity degree and the relation similarity degree.
According to the technical scheme of the embodiment of the invention, the basic similarity degree of the input customer information and the existing customer information is determined if the input customer information is the same as the basic customer information of the existing customer information, wherein the basic customer information comprises name and gender; analyzing the degree of similarity of the relationship between the client information and the existing client information based on the policyholder, the insured person and the beneficiary in the policy to which the client information belongs; and integrating the input customer information and the existing customer information by combining the basic similarity degree and the relation similarity degree. According to the basic similarity and the relation similarity, the client information of the same client in different insurance systems can be integrated, so that the normal operation of the insurance systems is guaranteed.
The above-described embodiments should not be construed as limiting the scope of the invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions can occur, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method of integrating customer information, comprising:
determining the basic similarity degree of the input customer information and the existing customer information if the input customer information is the same as the basic customer information of the existing customer information, wherein the basic customer information comprises name and gender;
analyzing the degree of similarity of the relationship between the input customer information and the existing customer information based on the policyholder, the insured person and the beneficiary in the policy to which the customer information belongs;
and integrating the input customer information and the existing customer information by combining the basic similarity degree and the relation similarity degree.
2. The method of integrating customer information as recited in claim 1, wherein the step of inputting customer information identical to the basic customer information of the existing customer information comprises:
and determining that the names of the input customer information and the existing customer information are the same, and then judging that the sexes of the input customer information and the existing customer information are consistent.
3. The method of integrating customer information as recited in claim 1, wherein determining a degree of substantial similarity of the incoming customer information to the existing customer information if the incoming customer information is the same as the underlying customer information of the existing customer information comprises:
the input customer information is the same as basic customer information of the existing customer information, and the basic similarity degree of the input customer information and the existing customer information is determined according to the birth date of the input customer information and/or the birth date of the existing customer information.
4. The method of integrating customer information according to claim 1, wherein analyzing the similarity of the relationship between the customer information and the existing customer information based on the applicant, the insured life and the beneficiary in the policy to which the customer information belongs comprises:
establishing an input information set according to an applicant, an insured life and a beneficiary in the insurance policy to which the input client information belongs;
searching the same identification in the policyholder, the policyholder and the beneficiary in the policy to which the existing customer information belongs according to the identification in the input information set;
and determining the similarity degree of the relationship between the input customer information and the existing customer information based on the number of the same identifications.
5. The method of integrating customer information according to claim 4, wherein said determining a degree of similarity of relationship between said incoming customer information and said existing customer information based on a number of identical identifiers comprises:
the number of the same marks is 1, and the similarity degree of the relationship between the input customer information and the existing customer information is determined to be similar;
and if the number of the same identifications is more than 1, determining that the similarity degree of the relationship between the input customer information and the existing customer information is the same.
6. The method of integrating customer information according to claim 1, wherein said integrating said input customer information with said existing customer information in combination with said degree of substantial similarity and said degree of relational similarity comprises:
acquiring the health similarity degree of the input customer information and the existing customer information based on the health information in the policy to which the customer information belongs;
integrating the input customer information and the existing customer information in combination with the basic similarity degree, the relationship similarity degree and the health similarity degree.
7. The method of integrating customer information according to claim 1, wherein said integrating said input customer information with said existing customer information in combination with said degree of substantial similarity and said degree of relational similarity comprises:
combining the basic similarity degree and the relation similarity degree to determine that the input customer information is partially overlapped with the existing customer information, and combining other information for integration again;
and combining the basic similarity degree and the relation similarity degree to determine that the input customer information is completely overlapped with the existing customer information, and combining the input customer information and the existing customer information.
8. An apparatus for integrating customer information, comprising:
the basic module is used for determining the basic similarity degree of the input customer information and the existing customer information if the input customer information is the same as the basic customer information of the existing customer information, wherein the basic customer information comprises name and gender;
the analysis module is used for analyzing the similarity degree of the relationship between the input customer information and the existing customer information based on an applicant, an insured person and a beneficiary in the policy to which the customer information belongs;
and the integration module is used for integrating the input customer information and the existing customer information by combining the basic similarity degree and the relation similarity degree.
9. An electronic device for integrating customer information, comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-7.
10. A computer-readable medium, on which a computer program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1-7.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117172792A (en) * | 2023-11-02 | 2023-12-05 | 赞塔(杭州)科技有限公司 | Customer information management method and device |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101452556A (en) * | 2008-12-31 | 2009-06-10 | 中国建设银行股份有限公司 | Customer information processing system and method |
| CN102930038A (en) * | 2012-11-12 | 2013-02-13 | 江苏外博资讯有限公司 | Combined method of search result similar items and system of the same |
| US20150199645A1 (en) * | 2014-01-15 | 2015-07-16 | Bank Of America Corporation | Customer Profile View of Consolidated Customer Attributes |
| CN106408316A (en) * | 2016-11-23 | 2017-02-15 | 泰康保险集团股份有限公司 | Method and device used for identifying clients |
| CN106777946A (en) * | 2016-12-07 | 2017-05-31 | 西安电子科技大学 | Personalized health service recommendation method based on hierarchal model |
| TWM583984U (en) * | 2019-03-12 | 2019-09-21 | 臺灣銀行股份有限公司 | Customer data automatic integration system |
| CN111785341A (en) * | 2020-06-30 | 2020-10-16 | 平安国际智慧城市科技股份有限公司 | Patient main index data merging method and device based on similarity |
| CN111882445A (en) * | 2020-07-24 | 2020-11-03 | 前海人寿保险股份有限公司 | Cross-system insurance user information management method, device, equipment and readable medium |
-
2021
- 2021-04-21 CN CN202110428369.2A patent/CN113128595A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101452556A (en) * | 2008-12-31 | 2009-06-10 | 中国建设银行股份有限公司 | Customer information processing system and method |
| CN102930038A (en) * | 2012-11-12 | 2013-02-13 | 江苏外博资讯有限公司 | Combined method of search result similar items and system of the same |
| US20150199645A1 (en) * | 2014-01-15 | 2015-07-16 | Bank Of America Corporation | Customer Profile View of Consolidated Customer Attributes |
| CN106408316A (en) * | 2016-11-23 | 2017-02-15 | 泰康保险集团股份有限公司 | Method and device used for identifying clients |
| CN106777946A (en) * | 2016-12-07 | 2017-05-31 | 西安电子科技大学 | Personalized health service recommendation method based on hierarchal model |
| TWM583984U (en) * | 2019-03-12 | 2019-09-21 | 臺灣銀行股份有限公司 | Customer data automatic integration system |
| CN111785341A (en) * | 2020-06-30 | 2020-10-16 | 平安国际智慧城市科技股份有限公司 | Patient main index data merging method and device based on similarity |
| CN111882445A (en) * | 2020-07-24 | 2020-11-03 | 前海人寿保险股份有限公司 | Cross-system insurance user information management method, device, equipment and readable medium |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117172792A (en) * | 2023-11-02 | 2023-12-05 | 赞塔(杭州)科技有限公司 | Customer information management method and device |
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