JP2003076838A - Name sorting method and name sorting processing program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a name sorting method and a name sorting processing program that can efficiently perform name sorting for more than one piece of customer data to grasp a correlation among them. SOLUTION: A management computer adds a common identifier A to a personal number associated with a client attribute common in part. Then, the computer adds, to the identifier A associated with common personal numbers, an identifier A of a small numeric value as an identifier B. Then, the computer substitute the identifier B of a small numeric value for the identifier B associated with a common identifier A. The computer iterates the above process until the combination of the same personal number and identifier B runs out, so that the name sorting can be performed efficiently.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a name identification processing method and a name identification processing program for managing a plurality of customer data in association with each other based on customer attribute information.

[0002]

2. Description of the Related Art A customer database that records customer attribute information (for example, address, telephone number, etc.) is important when conducting regular transactions with customers or sending guidance to customers. Is. For example, even in a financial institution, a database of customers having deposit accounts is essential for providing customer service and managing deposit accounts.

Such a customer database may be created by integrating a plurality of names. In this way, when integrating multiple rosters to construct one customer database, the same person may be listed in multiple rosters, in which case duplicate data will be created for the same person. .

The customer database in the financial institution is created based on the description of the deposit account application form that the customer submits to the financial institution when the customer opens the deposit account. It is also possible for one customer to open a plurality of deposit accounts, and in this case, customer data is generated corresponding to each deposit account. For this reason, it is difficult for the entire financial institution to grasp the customer's deposit account holding status, and there are cases in which duplicate processing (for example, guidance sending processing) is performed for the same customer.

Therefore, in managing such a customer database, name identification processing is important. Here, the name identification process refers to managing customer data in a specific unit. As a result, it is possible to promote customer management and rationalize marketing.

[0006]

However, even when the name identification process is performed, whether the description method of the address, telephone number, etc. is partially different depending on the name list or the deposit account application form submitted by the customer, and whether or not there is duplication. May be difficult to judge.
When the number of customer data is small, it is possible to grasp the mutual relation of the customer data by comparing the customer data with each other, but it is extremely difficult when the number of customer data is large.

Further, when judging whether or not the same person is used for a plurality of customer data, a plurality of comparison methods such as comparison by name and address or comparison by name and telephone number may be used together. As a result, for example, when it is determined that the customer A and the customer B are the same person because the names and addresses match, and when the customer B and the customer C are the same person because the names and the phone numbers match, the customer A and the customer C are the same person. C can be judged to be the same person. However, it is extremely difficult to actually grasp this mutual relationship when there is a large amount of customer data.

The present invention has been made to solve the above problems, and an object thereof is a name identification process capable of efficiently performing a name identification for a plurality of customer data and grasping a mutual relation of the customer data. It is to provide a method and a name identification processing program.

[0009]

In order to solve the above problems, the invention according to claim 1 performs data processing with a customer data storage means in which customer information associated with a first identifier is recorded. A name identification processing method performed by using a system having a management computer, wherein the management computer generates a first group configured by collecting first identifiers that at least part of the customer information match; And generating a second group by combining the first groups including at least one common first identifier among the first groups.

The invention according to claim 2 is a name identification processing method performed by using a system having a customer data storage means for recording customer information associated with the first identifier and a management computer for performing data processing. And the management computer associates the first identifier with which at least a part of the customer information matches with a common second identifier with the common first identifier. Assigning a common third identifier to the obtained second identifier based on a predetermined rule,
Assigning a common identifier to the third identifier associated with the common second identifier based on the predetermined rule, and duplicating the combination of the first identifier and the common identifier And a third step of repeating the second step by using the common identifier as the second identifier until the duplication of the first identifier is eliminated. That is the summary.

According to a third aspect of the present invention, in the name identification processing method according to the second aspect, the common identifier assigned based on the predetermined rule is associated with the common second identifier. The gist is that the identifier is selected from the three identifiers based on the predetermined rule.

The invention according to claim 4 is the invention according to claim 2 or 3.
In the name identification processing method described in (1), the second step is
The gist is that the method further comprises the step of deleting the second identifier after the common identifier is given.

According to a fifth aspect of the present invention, in the name identification processing method according to any one of the second to fourth aspects, a common identifier is added to an identifier associated with the common identifier. The predetermined rule is a rule for selecting an identifier having an earlier order among the associated identifiers.

According to a sixth aspect of the present invention, in the name identification processing method according to any one of the second to fourth aspects, a common identifier is added to the identifier associated with the common identifier. It is a gist that the predetermined rule is a rule for selecting a later-order identifier among the associated identifiers.

According to a seventh aspect of the present invention, in the name identification processing method according to any one of the second to sixth aspects, the first step is a duplication in the combination of the first and second identifiers. The gist is to further include the step of deleting the combination.

According to an eighth aspect of the present invention, in the name identification processing method according to any one of the second to seventh aspects, when the second identifier is assigned in the first step, the customer information is the same. Of the first identifiers to be performed, the first identifier having the earlier order is given as the second identifier.

According to a ninth aspect of the present invention, in the name identification processing method according to any one of the second to seventh aspects, the assignment of the second identifier in the first step is performed by matching the customer information. Of the first identifiers to be performed, the first identifier having the later order is given as the second identifier.

The invention according to claim 10 is a name identification processing program executed by using a system having a customer data storage means for recording customer information associated with the first identifier and a management computer for data processing. And a means for generating a first group configured by collecting the first identifiers that at least partially match the customer information, and at least one of the first group is common to the management computer. The gist is to cause a group including the first identifier to function as a unit for generating a second group.

The invention according to claim 11 is a name identification processing program executed by using a system having a customer data storage means for recording customer information associated with the first identifier and a management computer for data processing. And associating the management computer with a first means for assigning a common second identifier to the first identifier that at least partially matches the customer information, and the common first identifier. Means for assigning a common third identifier to the assigned second identifier based on a predetermined rule, and for the third identifier associated with the shared second identifier, the means Means for assigning a common identifier based on a predetermined rule, and means for deleting a duplicate combination in the combination of the first identifier and the common identifier Second means including said first
The gist is to cause the common identifier to function as the second identifier and to function as the third means for repeating the process of the second means until the duplicated identifiers are eliminated.

According to a twelfth aspect of the present invention, in the name identification processing program according to the eleventh aspect, the common identifier given based on the predetermined rule is associated with the common second identifier. The gist is that the identifier is selected from the three identifiers based on the predetermined rule.

The invention described in claim 13 is the name identification processing program according to claim 11 or 12, wherein the second means further has means for deleting the second identifier after the common identifier is given. That is the summary.

The invention described in claim 14 relates to claims 11 to 11.
13. In the name identification program according to any one of 13 above, the predetermined rule for assigning a common identifier to an identifier associated with a common identifier is the order of the associated identifiers. The gist is that it is a rule that selects an early identifier.

The invention described in claim 15 is based on claims 11 to 11.
13. In the name identification program according to any one of 13 above, the predetermined rule for assigning a common identifier to an identifier associated with a common identifier is the order of the associated identifiers. The gist is that it is a rule that selects a late identifier.

The invention according to claim 16 is the invention according to claims 11 to 11.
The name identification processing program according to any one of 15 is characterized in that the first means further includes means for deleting a duplicate combination in the combination of the first and second identifiers.

The invention as defined in claim 17 is defined in claims 11 to 11.
16. In the name identification process program according to any one of 16, the second identifier is assigned by the first means in the first identifier having the earliest order among the first identifiers with which the customer information matches. It is the gist to give as the second identifier.

The invention described in claim 18 relates to claims 11 to 11.
16. In the name identification processing program according to any one of 16, the second identifier is assigned by the first means in the first identifier having the latest order among the first identifiers with which the customer information matches. It is the gist to give as the second identifier.

(Operation) According to the invention described in claim 1 or 10, the management computer generates a first group composed of the first identifiers at least a part of which the customer information matches, and the first group, Among the one group, groups including at least one common first identifier are combined to generate a second group. Therefore, even the first identifiers that are not associated in the first group can be associated by grouping the first group (generation of the second group) using the first identifier. Therefore, the name identification process can be efficiently performed.

According to the invention described in claim 2 or 11,
The management computer assigns a common third identifier to the second identifier associated with the common first identifier based on a predetermined rule. Then, a common identifier is given to the third identifier associated with the common second identifier based on the predetermined rule. Next, in the combination of the first identifier and the common identifier, overlapping combinations are deleted, and the common identifier is used as the second identifier until the second identifier is eliminated, and the second step is performed. repeat.
As a result, the name identification process can be efficiently performed by a relatively simple mechanical process using a combination of a plurality of identifiers.

According to the invention of claim 3 or 12,
The common identifier given based on the predetermined rule is
It is an identifier selected based on the predetermined rule from among the third identifiers associated with the common second identifier. Therefore, the name identification process can be performed without increasing the types of identifiers.

According to the invention of claim 4 or 13,
The second step further comprises deleting the second identifier after the step of assigning the common identifier. For this reason,
The used identifier is deleted, and the processing can be performed efficiently without increasing the storage capacity.

According to the invention of claim 5 or 14,
The predetermined rule for assigning the common identifier to the identifiers associated with the common identifier is a rule for selecting an identifier having an earlier order among the associated identifiers. Therefore, the identifier to be selected can be determined by a simple judgment.

According to the invention of claim 6 or 15,
The predetermined rule for assigning a common identifier to an identifier associated with a common identifier is a rule for selecting an identifier having a later order among the associated identifiers. Therefore, the identifier to be selected can be determined by a simple judgment.

According to the invention of claim 7 or 16,
The management computer deletes an overlapping combination of the first and second identifier combinations. Therefore, the name identification process can be performed with a small amount of data.

According to the invention described in claim 8 or 17,
The management computer uses the first identifier having the earliest turn among the first identifiers with which the customer information matches as the second identifier to be given first. Therefore, there is a possibility that duplicated combinations of the first and second identifiers will be generated in the first stage, and the duplicated combinations can be deleted. Therefore, the name identification process can be performed with a small amount of data. Further, in the data for which the name identification process has been completed, since the common first identifier is associated with the first identifiers belonging to the same group, the mutual relationship can be easily grasped.

According to the invention of claim 9 or 18,
The management computer uses the first identifier having the latest order among the first identifiers with which the customer information matches as the second identifier to be given first. Therefore, there is a possibility that duplicated combinations of the first and second identifiers will be generated in the first stage, and the duplicated combinations can be deleted. Therefore, the name identification process can be performed with a small amount of data. Further, in the data for which the name identification process has been completed, the first identifiers belonging to the same group are associated with the common first identifier, so that the name identification mutual relationship can be easily grasped.

[0036]

BEST MODE FOR CARRYING OUT THE INVENTION (First Embodiment) A first embodiment of the present invention will be described below with reference to FIGS. In this embodiment, a name identification process method and a name identification process program used when performing a name identification process on customer data of a customer who has a deposit account in a financial institution will be described. The customer management system 20 is used for this name identification process. The customer management system 20 is a computer system that manages customer data.

As shown in FIG. 1, the customer management system 20 includes a management computer 21. The management computer 21 uses the customer data to perform a name identification process. The management computer 21 is a control unit (C
PU), storage means (RAM, ROM, hard disk, etc.), input means such as keyboard, mouse, etc., output means such as display, etc., and executes data processing described later by executing the name identification processing program. It functions as each means (first to third means, etc.).

A customer data storage unit 22 as customer data storage means is connected to the management computer 21. In the customer data storage unit 22, as shown in FIG. 1, customer attribute data 220 regarding each customer is recorded. The customer attribute data 220 is recorded when a customer submits a deposit account application form to a financial institution to open a deposit account. In the present embodiment, in the customer attribute data 220, data relating to the personal number as the first identifier, customer name as a customer information, kana name, address code, auxiliary address, telephone number, and date of birth are mutually exchanged. Is recorded in association with.

In this personal number data area, data relating to the identification number assigned by the financial institution to the customer who opened the deposit account is recorded. In the name data area, data about the name of the customer who opened the deposit account is recorded. In the kana name data area, data on the phonetic kana of the name of the customer who opened the deposit account is recorded.

In the address code data area, data for identifying the customer's address area described in the deposit account application form is recorded. In this embodiment, a customer's address area converted into a predetermined address code is used. For example, "Otemachi 1-chome, Chiyoda-ku, Tokyo" has the address code "12345.
6 "is converted.

Data for identifying the customer's address in more detail is recorded in the auxiliary address data area. For example,
"1-5-5 Otemachi, Chiyoda-ku, Tokyo" is represented by the address code "123456" and the auxiliary address "5-5". Also, "5-5-A1 Otemachi 1-5-5, Chiyoda-ku, Tokyo
02 ”is represented by the address code“ 123456 ”and the auxiliary address“ 5-5-A102 ”. In particular, even if this auxiliary address is the same address (for example, "No. 5 No. 5"), the customer may write "No. 5 No. 5" or "5-5" on the deposit account application form. However, it will be recorded as described in the deposit account application form in the auxiliary address data area.

Data relating to the telephone number of the customer who opened the deposit account is recorded in the telephone number data area. The date of birth data area records the date of birth of the customer who opened the deposit account. If the deposit account application does not have a telephone number or date of birth, the telephone number data area and the date of birth data area will be blank.

Next, the procedure for performing the name identification process in the system configured as described above will be described with reference to FIG. Here, individual numbers "10001" to "1001"
A case will be described in which the name identification process is performed for a customer who is given "4".

First, the management computer 21 performs grouping based on each attribute recorded in the customer data storage unit 22, and assigns a common identifier A as a second identifier to individual numbers belonging to the same group ( S1-
1). In this case, regarding the names, if at least one of the name and the kana name match, it is determined that they match. For example, personal numbers "10003" and "1000"
The names of "4" and "Kana" are "A Yamaha Hajime" and "A Yamagen", respectively.
Since it is the same as “Original”, it is judged that the names match.

Further, regarding the auxiliary address, when the alphanumeric characters match, it is judged that they are in the same group. For example,
The auxiliary addresses of the individual numbers "10003" and "10008" are "5-5-A102" and "5-5 A102", respectively.
However, since the order of alphanumeric characters is the same, it is judged that the auxiliary addresses match.

Further, the telephone number is judged based on the numbers excluding the area code. Therefore, "03-11
It is determined that “11-1111” and “1111-1111” match with respect to the telephone. Furthermore, with regard to the date of birth, the era notation is converted to the year notation to determine the identity.
Therefore, it is determined that “February 12, 1968” and “February 12, 1968” are the same.

Therefore, first, the management computer 21
Grouping is performed using a combination of name (or kana name), address code and auxiliary address. In this case, the individual numbers "10001", "10003" and "1000"
8 ”belongs to the same group because it is determined that the name (or kana name), address code, and auxiliary address match.
Therefore, a common identifier A (here, “10”) is given to each individual number and recorded. Similarly, individual numbers “10006” and “1001” in which the combination of the name (or kana name), the address code, and the auxiliary address match.
4 ”, the identifier A is“ 11 ”, and the personal number is“ 10 ”.
"12" as the identifier A for "007" and "10013", and individual numbers "10011" and "10012"
“13” is added as an identifier A to the record.

Next, the management computer 21 performs grouping using a combination of name (or kana name), address code and telephone number. In this case, the individual number "1
Since "0003" and "10004" are determined to have the same name (or kana name), address code and telephone number, they belong to the same group. Therefore, a common identifier A (here, “20”) is added to each individual number and recorded. Similarly, the individual numbers “10007” and “100” in which the combination of the address code and the telephone number match
"21" as the identifier A for "13" and the personal number "1"
“22” is assigned as an identifier A to “0002” and “10010” and recorded.

Next, the management computer 21 performs grouping using the combination of name (or kana name), address code and date of birth. In this case, the individual number "1
Since "0004" and "10014" are determined to have the same name (or Kana name), address code and date of birth, they belong to the same group. Therefore, the same identifier A (here, “30”) is given to each individual number and recorded. Similarly, the personal number “100” that matches the combination of name (or kana name), address code and date of birth.
02 "and" 10013 "as the identifier A" 3
1 ”is added and recorded.

As a result, the data 300 shown in FIG. 3A is recorded in the management computer 21. In this data 300, the identifier A assigned to the identifier A data area is recorded in association with the personal number recorded in the personal number data area. In addition, personal number "10
“005” and “10009” are not included in the data 300 because there is no individual number having the same attribute and do not form a group.

Next, the management computer 21 groups the individual numbers and assigns an identifier A having a smaller numerical value, that is, an earlier order as an identifier B as a third identifier (S1-2). Here, as a predetermined rule,
The rule "select an identifier with a small numerical value" is used. In the case of the present embodiment, the data 300 includes personal numbers “10002”, “10003”, and “1000”.
4 "," 10007 "," 10013 "," 1001 "
4 ”are included in plurality to form each group. For example, as for the personal number “10002”, “22” and “31” are associated with each other as the identifier A. Therefore, “22” is assigned as the identifier B to the personal number “10002”. The identifier B is similarly given to the other groups.

For individual numbers that do not form a group (for example, individual numbers “10001” and “10006”), the identifier A is directly associated with the identifier B and recorded. As a result, the management computer 21 records the data 310 shown in FIG. In this data 310, the identifier B assigned in the identifier B data area is recorded in association with the personal number recorded in the personal number data area.

Next, the management computer 21 sends the data 3
Only the identifiers A and B associated with each other are extracted from 10, and sorting is performed by the identifier A (S1-3).
As a result, the management computer 21 generates the data 320 shown in FIG.

Next, the management computer 21 gives a common identifier B to the same identifier A (S1-
4). For example, in the data 320, the identifier A “2
Since "0" is associated with "10" and "20" as the identifier B, "10" is given as the common identifier B. In this case, as the identifier B, an identifier B having a small numerical value is given as a new identifier B. As a result,
The management computer 21 uses the data 33 shown in FIG.
Generates 0.

Next, the management computer 21 deletes the combination of duplicated identifiers and creates a conversion table (S1).
-5). For example, in the data 330, the identifier A “1
0 "and identifier B" 10 ", identifier A" 1 "
Since the combination of “1” and the identifier B “11” and the like overlap, one combination is left and the other is deleted. As a result, a conversion table for converting the identifier A into the identifier B, that is, the data 340 shown in FIG. 4C is generated.

Next, the management computer 21 assigns the identifier B to the identifier A associated with the personal number by using the conversion table (S1-6). In this case, data 31
Data obtained by converting the identifier A into the identifier B using the conversion table is recorded in the identifier B data area of 0. As a result, the management computer 21 stores the data 350 shown in FIG.
Is recorded.

Next, the management computer 21 replaces the identifier A associated with the personal number with the generated identifier B (S1-7). As a result, the management computer 21
In this area, the data 360 shown in FIG. 5B is recorded.

Next, the management computer 21 groups the personal numbers to delete the duplicate combinations (S
1-8). For example, in the data 360, since the combination of the identifier A “10” is duplicated with the personal number “10003”, one is deleted. On the other hand, for the personal number “10002”, there is a combination in which “22” and “12” are assigned as the identifier A. In this case, since the identifier A is different, each combination is left as it is. As a result, the data 370 shown in FIG. 5C is recorded in the management computer 21.

Next, the management computer 21 confirms whether there is a duplicate personal number (S1-9). If duplicated personal numbers exist (“Yes” in step (S1-9)), the steps following step (S1-2) are repeated. In the present embodiment, since the data 370 has duplicate data regarding the personal numbers “10002” and “10004”, the steps following step (S1-2) are executed.

That is, the management computer 21 groups the individual numbers and assigns the identifier A having a small numerical value as the identifier B (S1-2). In this embodiment, the data 370 includes personal numbers “10002” and “1000”.
4 ”are included in plurality to form each group. For example, with respect to the personal number “10002”, “22” and “12” are associated as the identifier A. Therefore, “12” is assigned as the identifier B to the personal number “10002”. Similarly, the individual number "1000
The identifier B (here, "10") is also given to "4". It should be noted that for individual numbers that do not form a group, the identifier A is directly associated with the identifier B and recorded. As a result, the management computer 21 is displayed in FIG.
The data 380 shown in (a) is recorded.

Next, the management computer 21 sends the data 3
Only the mutually associated identifiers A and B are extracted from 80 and sorted by the identifier A (S1-3). As a result, the management computer 21 generates the data 390 shown in FIG.

Next, the management computer 21 gives a common identifier B to the grouped identifier A (S1-4). Here, in the data 390, the identifier A “11” is replaced with the identifier B “10” and “11”.
And 10 are associated with each other, "10" is given as the common identifier B. In this case, as the identifier B, the one with the smaller numerical value is given. As a result, the management computer 21 generates the data 400 shown in FIG.

Next, the management computer 21 deletes the combination of duplicated identifiers and creates a conversion table (S1).
-5). As a result, a conversion table for converting the identifier A into the identifier B, that is, the data 410 shown in FIG. 7A is generated.

Next, the management computer 21 uses the conversion table to assign the identifier B as a common identifier to the identifier A associated with the personal number (S1-6). In this case, the data obtained by converting the identifier A into the identifier B using the conversion table is recorded in the identifier B data area of the data 380. As a result, the data 420 shown in FIG. 7B is generated. Next, the management computer 21 replaces the identifier A associated with the personal number with the identifier B (S1-
7). As a result, the management computer 21 is displayed in FIG.
The data 430 shown in (c) is recorded.

Next, the management computer 21 groups the personal numbers to delete the duplicate combinations (S
1-8). In the data 430, the personal number “100
Since the combination of the identifier A “12” for “02” and the combination of the identifier A “10” for the personal number “10004” are duplicated, one is deleted for each. As a result, the data 440 shown in FIG. 8A is recorded in the management computer 21.

Next, the management computer 21 confirms whether or not there is a duplicate personal number (S1-9). If duplicated personal numbers are present (“Yes” in step (S1-9)), step (S1-2) and subsequent steps are repeated. When there is no duplicate personal number (in the case of "none"), the personal numbers are sorted by the identifier A (S1-1).
0). Here, since there is no duplicate personal number in the data 440, step (S1-10) is executed. As a result, the data 450 shown in FIG. 8B is recorded in the management computer 21. With the above, the name identification process ends.

That is, individual numbers "10001", "1"
"0003", "10004", "10006", "10"
The same identifier A for “008” and “10014”
Since (10 in this case) is added, it can be seen that these belong to the same group. Further, since the same identifier A is given to the individual numbers “10002”, “10007”, “10010” and “10013”, it can be seen that they belong to the same group. Further, since the same identifier A is given to the individual numbers “10011” and “10012”, it can be seen that they belong to the same group. Thus, the generated identifier A
Is recorded in association with the personal number, it is possible to determine whether or not different personal numbers belong to the same group.

As described above, according to this embodiment, the following effects can be obtained. In the above embodiment, individual numbers are grouped based on a plurality of attributes (here, auxiliary address, telephone number, or date of birth), and a common identifier A is given to individual numbers belonging to the same group. To be done. Therefore, based on the identifier A, individual numbers belonging to the same group can be grasped. Therefore, for example, when providing guidance or the like to an individual, it is sufficient to send it to one address or the like belonging to the same group, and there is no need to perform duplicate processing.

In the above embodiment, the name identification is performed using the personal number and the identifier A generated based on the attribute, so that the name identification process can be efficiently performed without making a complicated determination. Therefore, there are cases where tens of millions of individual numbers are given, such as when performing the name identification process using the individual numbers corresponding to the deposit accounts of large financial institutions. It is effective when processing.

In the embodiment described above, the name identification process is performed using the personal number and the identifier A generated based on a plurality of attributes (here, auxiliary address, telephone number, or date of birth). In this case, by repeating the grouping process using the personal number and the grouping process using the identifier A,
Initially, personal numbers that were not directly associated can be identified. For example, in this embodiment, data 3
In 00, personal numbers “10001” and “1001”
4 ”did not belong to the same group, but as a result of the name identification process, it can be determined in the data 450 that they belong to the same group. That is, the personal number "1000
1 ”and“ 10003 ”belong to the same group (first group), and personal numbers“ 10003 ”and“ 10004 ”
Belong to the same group, and individual numbers “10004” and “10014” belong to the same group (first group). As a result, by performing the name identification process of the present invention, the same identifier A can be assigned to the personal numbers “10001” and “10014” via “10003” and “10004”. That is, it is possible to generate a second group by grouping groups including at least one common personal number (first identifier) in the first group.

In the above embodiment, the personal number, the identifier A, and the identifier B are used as parameters for performing the name identification process. Then, the identifier A grouped by the identifier B is replaced with the identifier B as in step (S1-7). Therefore, the name identification can be performed without increasing the number of identifiers. In this way, since the data relating to the original identifier A can be deleted, it is possible to efficiently perform the name identification without unnecessarily increasing the storage capacity.

In the above embodiment, if at least one of the name and the kana name match, it is determined that both match. Regarding the auxiliary address, if the alphanumeric characters match, it is determined that the two match. Furthermore, the telephone number is judged based on the numbers excluding the area code. In addition, regarding the date of birth, the era notation is converted into the year notation to determine the identity. Therefore, it is possible to perform appropriate grouping even when the notation of the deposit account application form from the customer is different.

(Second Embodiment) A second embodiment of the present invention will be described below with reference to FIGS. 9 to 17. This embodiment will also be described as a name identification process method and a name identification process program used when performing a name identification process on customer data of a customer who has a deposit account in a financial institution. The second embodiment is different from the first embodiment in the way of assigning the identifier A.

The procedure for performing the name identification process in the second embodiment will be described below with reference to FIG. Also in the present embodiment, a case will be described in which the name identification process is performed for the customers with the individual numbers “10001” to “10014” recorded in the customer data storage unit 22.

Also in the second embodiment, first, the management computer 21 performs grouping based on each attribute recorded in the customer data storage unit 22, and gives an identifier A common to individual numbers belonging to the same group. (S2
-1). Also in the second embodiment, as in the first embodiment, grouping is performed using a combination of a name (or kana name), an address code, and an auxiliary address (or telephone number, date of birth). However, in the present embodiment, the identifier A
As, the smallest (earliest) personal number in the group is used. For example, the same identifier A (here, “10001”) is assigned to individual numbers “10001”, “10003”, and “10008” that form the same group. Similarly, individual numbers "10006" and "100"
“10006” is given as an identifier A to “14”. Similarly, a minimum personal number is given to the other groups and recorded as the identifier A.

As a result, the data 500 shown in FIG. 10A is recorded in the management computer 21. The individual numbers “10005” and “10009” do not form a group and are therefore not included in the data 500.

Next, the management computer 21 deletes the duplicate combination of the personal number and the identifier A (S2-
2). The data 500 includes a combination of the individual number “10007” and the identifier A “10007”, and the individual number “10”.
The combination of “013” and the identifier A “10007” and the combination of the personal number “10002” and the identifier A “10002” are included in duplicate. Therefore, one combination is left and the duplicate combination is deleted. As a result, the management computer 21 is displayed in FIG.
Data 510 shown in (b) is recorded.

Next, the management computer 21 groups the individual numbers into the identifier A having a smaller numerical value and the identifier B.
(S2-3). In the case of the present embodiment, the data 510 includes personal numbers “10003” and “1000”.
4 ”,“ 10013 ”, and“ 10014 ”are included.
Belong to each group. For example, the personal number "10
Regarding “003”, since “10001” and “10003” are associated as the identifier A, the identifier B
"10001" is given to both. The identifier B is similarly given to the other groups. An individual number that does not form a group (for example, an individual number "10
For example, “001” and “10006”), the identifier A is directly associated with the identifier B and recorded. As a result, the data 520 shown in FIG. 10C is recorded in the management computer 21.

Next, the management computer 21 sends the data 5
Only the identifiers A and B associated with each other are extracted from 20, and sorting is performed by the identifier A (S2-4).
As a result, the management computer 21 generates the data 530 shown in FIG.

Next, the management computer 21 gives a common identifier B to the same identifier A (S2-
5). For example, in the data 530, the identifier A “10
003 ”includes“ 10001 ”and“ 10 ”as identifiers B.
003 ”is associated with the common identifier B.
“10001” is given as In this case, the identifier B
As a result, an identifier B having a small numerical value is given as a new identifier B. In addition, the identifier A "10004", "1"
"0006" and the like are processed in the same manner. As a result, the management computer 21 generates the data 540 shown in FIG.

Next, the management computer 21 deletes the combination of duplicated identifiers and creates a conversion table (S2).
-6). For example, in the data 540, the identifier A “1
Since three combinations of “0001” and the identifier B “10001” are included, two duplicates are deleted. As a result, a conversion table for converting the identifier A into the identifier B, that is, the data 550 shown in FIG. 11C is generated.

Next, the management computer 21 uses the conversion table for the identifier A associated with the personal number,
An identifier B as a common identifier is given (S2-7).
In this case, the data obtained by converting the identifier A into the identifier B using the conversion table is recorded in the identifier B data area of the data 520. As a result, the management computer 21 is displayed in FIG.
The data 560 shown in (a) is recorded. Next, the management computer 21 determines the identifier A associated with the personal number.
Is replaced with the generated identifier B (S2-8). As a result, the data 570 shown in FIG. 12B is recorded in the management computer 21.

Next, the management computer 21 groups the personal numbers to delete the duplicate combinations (S
2-9). For example, in the data 570, since the combination of the identifier A “10001” overlaps with the personal number “10003”, one is deleted. On the other hand, for the personal number “10004”, the identifier A is “1”.
There is a combination of "0001" and "10003". In this case, since the identifier A is different, each combination is left as it is. As a result, the management computer 2
The data 580 shown in FIG.

Next, the management computer 21 confirms whether or not there is a duplicate personal number (S2-10). If duplicated personal numbers exist (“YES” in step (S2-10)), the steps following step (S2-3) are repeated. In this embodiment, the personal number “1000
Since "4" and "10014" are duplicated, steps (S2-3) and the following steps are repeated.

That is, the management computer 21 groups the personal numbers and assigns the identifier A having a small numerical value as the identifier B (S2-3). Where the data 58
0 includes a plurality of individual numbers “10004” and “10014”, and forms each group. For the personal number “10004”, the identifier A is “1000”.
Since “1” and “10003” are associated with each other, “10001” is assigned to both as the identifier B. Similarly, the identifier B (here, “10003”) is also given to the personal number “10014”. It should be noted that for individual numbers that do not form a group, the identifier A is directly associated with the identifier B and recorded. As a result, the data 590 shown in FIG. 13A is recorded in the management computer 21.

Next, the management computer 21 extracts only the identifiers A and B associated with each other and sorts by the identifier A (S2-4). As a result, the management computer 21 generates the data 600 shown in FIG.

Next, the management computer 21 gives a common identifier B to the grouped identifier A (S2-5). Here, in the data 600, the identifier A “10003” has the identifier B “1000”.
Since “1” and “10003” are associated with each other, “10001” is given as the common identifier B. In this case, as the identifier B, the one with the smaller numerical value is given. The other identifiers are similarly processed. As a result, the management computer 21 generates the data 610 shown in FIG.

Next, the management computer 21 deletes the combination of duplicated identifiers and creates a conversion table (S2).
-6). As a result, a conversion table for converting the identifier A into the identifier B, that is, the data 620 shown in FIG. 14A is generated.

Next, the management computer 21 assigns the identifier B to the identifier A associated with the personal number using the conversion table (S2-7). In this case, data 59
Data obtained by converting the identifier A into the identifier B using the conversion table is recorded in the identifier B data area of 0. As a result,
Data 630 shown in 4 (b) is generated. Next, the management computer 21 replaces the identifier A associated with the personal number with the identifier B (S2-8). As a result,
Data 640 shown in FIG. 14C is recorded in the management computer 21.

Next, the management computer 21 groups the personal numbers to delete the duplicate combinations (S
2-9). In the data 640, the personal number “100
Since the combination of the identifier A “10001” with respect to “04” is duplicated, one is deleted. As a result, the management computer 21 stores data 650 shown in FIG.
Is recorded.

Next, the management computer 21 confirms whether or not there is a duplicate personal number (S2-10). If duplicated personal numbers exist (“YES” in step (S2-10)), the steps following step (S2-3) are repeated. In this embodiment, the personal number “1001
4 ”is duplicated, the steps following step (S2-3) are executed again.

Therefore, the management computer 21 groups the individual numbers and assigns the identifier A having a small numerical value as the identifier B (S2-3). In the present embodiment, the data 650 includes a plurality of individual numbers “10014”,
As the identifier A, “10001” and “10003” are associated with each other. Therefore, "10001" is given to the individual number "10014" as a common identifier B. It should be noted that for individual numbers that do not form a group, the identifier A is directly associated with the identifier B and recorded. As a result, the management computer 21 is displayed in FIG.
Data 660 shown in (b) is recorded.

Next, the management computer 21 extracts only the identifiers A and B associated with each other, and sorts by the identifier A (S2-4). As a result, the management computer 21 generates the data 670 shown in FIG.

Next, the management computer 21 gives a common identifier B to the grouped identifier A (S2-5). Here, in the data 670, the identifier A “10003” has the identifier B “1000”.
Since “1” and “10003” are associated with each other, “10001” is given as the common identifier B. In this case, as the identifier B, the one with the smaller numerical value is given. As a result, the management computer 21 generates the data 680 shown in FIG.

Next, the management computer 21 deletes the combination of duplicated identifiers and creates a conversion table (S2).
-6). As a result, a conversion table for converting the identifier A into the identifier B, that is, the data 690 shown in FIG. 16B is generated.

Next, the management computer 21 gives the identifier B to the identifier A associated with the personal number by using the conversion table (S2-7). In this case, the data 66
Data obtained by converting the identifier A into the identifier B using the conversion table is recorded in the identifier B data area of 0. As a result,
Data 700 shown in 6 (c) is generated. Next, the management computer 21 replaces the identifier A associated with the personal number with the identifier B (S2-8). As a result,
Data 710 shown in FIG. 17A is recorded in the management computer 21.

Next, the management computer 21 groups the personal numbers to delete the duplicate combinations (S
2-9). In the data 710, the personal number “100
Since the combination of the identifier A “10001” with respect to “14” is duplicated, one is deleted. As a result, the management computer 21 stores the data 720 shown in FIG.
Is recorded.

Next, the management computer 21 confirms the presence or absence of duplicate personal numbers (S2-10). If duplicated personal numbers are present (“Yes” in step (S2-10)), step (S2-3) and subsequent steps are repeated. If there is no duplicate personal number ("No")
Case), the personal numbers are sorted by the identifier A (S2-1).
1). Here, since there is no duplicate personal number in the data 720, step (S2-11) is executed. As a result, the data 730 shown in FIG. 17C is recorded in the management computer 21. With the above, the name identification process ends.

That is, individual numbers "10001" and "1"
"0003", "10004", "10006", "10"
Since the same identifier A (here, “10001”) is given to “008” and “10014”, it can be seen that these belong to the same group. In addition, individual numbers “10002”, “10007”, “10010”,
“10013” also has the same identifier A (here, “1000
2 ”) is added, it can be seen that they belong to the same group. Furthermore, individual numbers “10011” and “1”
0012 ”also has the same identifier A (here,“ 10011 ”)
Is added, it can be seen that they belong to the same group. In this way, by recording the generated identifier A in association with the personal number,
It can be determined whether they belong to the same group.

As described above, according to this embodiment, the following effects can be obtained in addition to the effects obtained in the first embodiment. In the above embodiment, in step (S2-1), the management computer 21 performs grouping based on each attribute recorded in the customer data storage unit 22 and assigns the identifier A to the individual numbers belonging to the same group. Here, the smallest personal number in the same group is used as the identifier A. Therefore, step (S2-2)
In, duplicate combinations can be deleted. Therefore, it is possible to reduce the number of data required for processing such as grouping, and it is possible to efficiently perform the name identification processing while reducing the storage capacity. In particular, when there are few variations in the attributes of each individual recorded in the customer data storage unit 22, there are many overlapping combinations, so the effect of deleting is great.

In the above embodiment, in the finally generated data 730, the smallest personal number belonging to the same group is associated as the identifier A with the same group. Therefore, the smallest individual number of the group can be easily grasped.

The above embodiment may be modified into the following modes. In the first and second embodiments, the name identification process is performed on the customer data of the customer who has the deposit account. The present invention is not limited to this, and may be used for a name identification process in an individual name list configured by collecting a plurality of name lists. For example, it may be used when financial institutions are integrated to unify customer data or when creating a direct mail list from a plurality of names. Further, when the customer data is unified, the storage capacity can be reduced by deleting the duplicate customer data.

In the first and second embodiments, grouping is performed using a combination of name or kana name, auxiliary address, telephone number, and date of birth. In addition to this, other combinations and other items may be used. For example, a zip code may be used instead of the address code or the like.

In the first and second embodiments, the identifier A associated with the personal number is generated in step (S1-7) or step (S2-8), and the generated identifier B is generated.
Replace with. Alternatively, the identifier A may be left as it is. In this case, the generated identifier B is used as the identifier A, and the step (S1-8) or step (S2-) is performed.
9) Perform the following processing. In this way, the name identification process can be performed even when the replacement process is not performed.

In the first and second embodiments, the name identification process is performed for each customer who has a deposit account at a financial institution. Alternatively, it can be used in the case of household gathering. Here, household gathering is to group customers in the same household. In this case, in the grouping of steps (S1-1) and (S2-1), a combination of family name, address code and auxiliary address, family name,
Grouping is performed using a combination of an address code and a telephone number, and an identifier A is given. As a result, it is possible to grasp the customer situation that belongs to the same household.

In the first and second embodiments, when the common identifier B is given to the individual numbers belonging to the same group, the identifier A having a small numerical value is adopted. Here, as a predetermined rule, “adopt identifier A with a small numerical value”
However, if an identifier is selected based on a predetermined rule, for example, an identifier A having a larger numerical value (an identifier having a later order) may be given.

In the second embodiment, the identifier A
As, the smallest (earliest) personal number in the group is used. Instead of this, an identifier A having a larger numerical value (an identifier having a later order) may be given.

In the first and second embodiments, when the common identifier B is given to the individual numbers belonging to the same group, the identifier A having a small numerical value is adopted. Alternatively, a common new identifier may be given to the grouped personal numbers. For example, in the step (S1-4) of the first embodiment, the management computer 21
Replaces the same identifier A with a common identifier B. Instead of this, a new identifier C is used as the common identifier.
May be given. In this case, by deleting the data related to the second to third identifiers, it is possible to prevent unnecessary increase of data.

In the first and second embodiments, the name identification process is performed at once for the individual numbers “10001” to “10014”. Instead of this, first, the whole may be divided into a plurality of groups, and then the name identification process may be performed. In the case of the present embodiment, the identifier A in step (S2-1)
Since the address code is included when adding, the name identification process may be performed after first forming a plurality of groups using the address code. In this case, the name identification process shown in FIGS. 2 and 9 needs to be repeated for each set, but the amount of data handled in one process can be reduced.

In the first and second embodiments, only the identifier A and the identifier B are extracted and the identifier conversion table is created. For example, in the first embodiment, the data 340 as the conversion table is generated based on the data 320. Then, in step (S1-6), the identifier B is assigned using the conversion table. Alternatively, the data 350 may be generated without using the conversion table. In this case, sorting is performed using the identifier A while being associated with the personal number.
Then, the identifier B associated with the same identifier A is converted into the common identifier B based on a predetermined rule. For example, of the identifiers B associated with the identifier A, the smallest identifier B is replaced. Thereby, the data 350 can be generated without creating a conversion table.

In the first and second embodiments, the identifier B is further added to the personal number to which the identifier A is added. Instead of this, when the identifier A is assigned, the personal number may be divided into two groups and processed. For example, the first
In the embodiment, after the identifier A is added and the data 300 shown in FIG. 3A is generated, the data is divided into two groups and the processing from step (S1-2) is executed only on one group.

Here, first, sorting is performed by using individual numbers to extract duplicate individual numbers. In the first embodiment, “10002”, “10003”, “1000”.
4 "," 10007 "," 10013 "," 1001 "
4 ”is extracted.

Next, an individual number associated with the same identifier as the identifier A associated with the extracted individual number is extracted. In the first embodiment, an identifier other than "13" is extracted as the same identifier as the identifier A associated with the extracted personal number. Individual numbers associated with the identifier A other than "13" (here, "10001" to "1").
0010 ”,“ 10013 ”, and“ 10014 ”) as one set, and the processes after step (S1-2) are executed.

On the other hand, the personal numbers (here, "10011" and "1001") associated with the identifier A ("13").
2)), the processes after step (S1-2) are not executed, and the individual numbers “10011”, “10012” and their identifier A are added to the data after the process of step (S1-10). As a result, the data 450 shown in FIG. 8B can be generated. Identifier A ("1
3 ”), personal numbers“ 10011 ”and“ 1 ”associated with
"0012" is not grouped any more, so that the processes of steps (S1-2) to (S1-10) can be executed with a small amount of data.

The process of extracting the identifier A associated with the overlapping personal number and extracting only the personal number associated with this identifier A is performed from step (S1-2).
It may be performed every time (S1-10) is repeated. That is, the step (S1-
By performing steps 2) to (S1-10) and adding the remaining personal number to the end, the name identification process can be performed. As a result, the name identification process can be performed more efficiently.

In the first and second embodiments, the procedure up to the completion of the name identification process has been described.
0 and the data 730 include personal numbers that did not initially form a group (here, personal numbers “10005” and “10”).
009 "), the customer data can be created without omission.

[0117]

As described in detail above, according to the present invention,
By grouping the first identifiers with which at least a part of the customer information associated with the first identifiers is matched, and further grouping is performed based on the grouped first identifiers, the first identifiers are not associated with each other. Grouping of the first identifier can be performed. Therefore, efficient name identification processing can be performed.

[Brief description of drawings]

FIG. 1 is a system schematic diagram of an embodiment of the present invention.

FIG. 2 is an explanatory diagram of a processing procedure according to the first embodiment of this invention.

FIG. 3 is an explanatory diagram of a data structure according to the first embodiment of this invention.

FIG. 4 is an explanatory diagram of a data structure according to the first embodiment of this invention.

FIG. 5 is an explanatory diagram of a data structure according to the first embodiment of this invention.

FIG. 6 is an explanatory diagram of a data structure according to the first embodiment of this invention.

FIG. 7 is an explanatory diagram of a data structure according to the first embodiment of this invention.

FIG. 8 is an explanatory diagram of a data structure according to the first embodiment of this invention.

FIG. 9 is an explanatory diagram of a processing procedure according to the second embodiment of this invention.

FIG. 10 is an explanatory diagram of a data structure according to the second embodiment of this invention.

FIG. 11 is an explanatory diagram of a data structure according to the second embodiment of this invention.

FIG. 12 is an explanatory diagram of a data structure according to the second embodiment of this invention.

FIG. 13 is an explanatory diagram of a data structure according to the second embodiment of this invention.

FIG. 14 is an explanatory diagram of a data structure according to the second embodiment of this invention.

FIG. 15 is an explanatory diagram of a data structure according to the second embodiment of this invention.

FIG. 16 is an explanatory diagram of a data structure according to the second embodiment of this invention.

FIG. 17 is an explanatory diagram of a data structure according to the second embodiment of this invention.

[Explanation of symbols]

21 ... Management computer, 22 ... Customer data storage unit as customer data storage means.

Claims (18)

[Claims] 1. A name identification processing method performed by using a system having a customer data storage unit that records customer information associated with a first identifier and a management computer that performs data processing, wherein the management computer comprises: Generating a first group configured by collecting first identifiers having at least a part of the customer information, and including at least one common first identifier in the first group, Second group together in the first group
And a step of generating a group of the name identification processing method. 2. A name identification processing method performed by using a system having a customer data storage unit recording customer information associated with a first identifier and a management computer for performing data processing, wherein the management computer comprises: A first step of assigning a common second identifier to the first identifier that at least part of the customer information matches; and the second identifier associated with the common first identifier. , Based on a predetermined rule, common third
Assigning a common identifier to the third identifier associated with the common second identifier based on the predetermined rule; and the first identifier, A second step of deleting a duplicate combination in the combination of common identifiers;
And a third step of repeating the second step by using the common identifier as the second identifier until the duplication of the first identifier is eliminated. 3. The common identifier assigned based on the predetermined rule is an identifier selected based on the predetermined rule from the third identifiers associated with the common second identifier. 3. The method according to claim 2, wherein
Name identification processing method described in. 4. The name identification processing method according to claim 2, wherein the second step further comprises the step of deleting the second identifier after the common identifier is given. 5. The predetermined rule for assigning a common identifier to an identifier associated with a common identifier is a rule for selecting an identifier having an earlier order among the associated identifiers. Claim 2 characterized by the above-mentioned.
4. The name identification processing method according to any one of 4 above. 6. The predetermined rule for assigning a common identifier to an identifier associated with a common identifier is a rule for selecting a later-order identifier among the associated identifiers. Claim 2 characterized by the above-mentioned.
4. The name identification processing method according to any one of 4 above. 7. The method according to claim 2, wherein the first step further includes a step of deleting a duplicate combination in the combination of the first and second identifiers.
6. The name identification processing method according to any one of 6 above. 8. The assignment of the second identifier in the first step is to assign, as the second identifier, the first identifier having the earlier order among the first identifiers having the same customer information. The name identification processing method according to claim 2, further comprising: 9. The assigning of the second identifier in the first step is performed by assigning the first identifier having a later order among the first identifiers having the same customer information as the second identifier. The name identification processing method according to claim 2, further comprising: 10. A name identification processing program executed by using a system having a customer data storage unit that records customer information associated with a first identifier, and a management computer that performs data processing, the management computer comprising: Means for generating a first group configured by collecting first identifiers that at least part of the customer information match, and a group including at least one common first identifier in the first group A name identification processing program for functioning as a means for collectively generating the second group. 11. A name identification processing program executed by using a system having a customer data storage unit, which records customer information associated with a first identifier, and a management computer for performing data processing, the management computer comprising: First means for giving a common second identifier to the first identifier that at least part of the customer information matches; and the second identifier associated with the common first identifier. , Based on a predetermined rule, common third
Means for assigning a common identifier to the third identifier associated with the common second identifier, based on the predetermined rule, means for assigning a common identifier, and the first identifier, A second means including means for deleting a duplicate combination in the combination of common identifiers;
And a name identification processing program for causing the common identifier as the second identifier to repeat the processing of the second means until the duplicate of the first identifier is eliminated. 12. The common identifier assigned based on the predetermined rule is an identifier selected based on the predetermined rule from among the third identifiers associated with the common second identifier. The name identification processing program according to claim 11, characterized in that 13. The name identification processing program according to claim 11, wherein the second means further includes means for deleting the second identifier after the common identifier is given. 14. The predetermined rule for assigning a common identifier to an identifier associated with a common identifier is a rule for selecting an identifier having an earlier order among the associated identifiers. Claim 1 characterized by the above-mentioned.
The name identification processing program according to any one of 1 to 13. 15. The predetermined rule for assigning a common identifier to an identifier associated with a common identifier is a rule for selecting a later-order identifier among the associated identifiers. Claim 1 characterized by the above-mentioned.
The name identification processing program according to any one of 1 to 13. 16. The first means further comprises means for deleting an overlapping combination in the combination of the first and second identifiers.
The name identification processing program according to any one of 1 to 15. 17. The second identifier is assigned by the first means, among the first identifiers with which the customer information matches.
The name identification processing program according to any one of claims 11 to 16, wherein the first identifier having the earliest turn is given as the second identifier. 18. The second identifier is assigned by the first means, among the first identifiers with which the customer information matches.
The name identification processing program according to any one of claims 11 to 16, wherein the first identifier having the latest order is given as the second identifier.