Management support systems, methods, and programs

Abstract

The objective is to provide a management support system, method, and program that takes into account industry-specific circumstances to automatically suggest countermeasures in advance as a measure against customer harassment, thereby preventing customer complaints. [Solution] The management support system 100, which includes a storage means 120, a weighting means 121, and a suggestion means 122, automatically presents countermeasures against customer harassment in advance for similar cases, taking into account industry-specific circumstances, thereby efficiently preventing customer harassment.

Description

Technical Field

[0001] The present invention relates to a business support system, method, and program.

Background Art

[0002] In recent years, the problem of customer harassment, which refers to "significant nuisance behavior by customers, etc.", has been worsening, and companies are taking various measures to protect their employees.

[0003] For example, in Patent Document 1, a road and road facility management system is disclosed that can input the content of users' complaints regarding roads and road facilities and countermeasures, and automatically obtain countermeasures for similar complaints.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] However, in the case of dealing with customer harassment in financial institutions, there is a situation where the priority of response varies depending on the services subscribed to by the customer and the deposit balance. When considering such a situation, simply presenting countermeasures for complaints is not sufficient, and it is necessary to rely on the experience and intuition of employees to consider the priority of response.

[0006] In the invention of Patent Document 1, for example, for a complaint of "noise", road repair methods and materials used are displayed based on past information, but these are only presentations of countermeasures for complaints, and industry-specific circumstances are not considered. Also, in the invention of Patent Document 1, no means for preventing complaints is taken.

[0007] This invention was proposed in view of the above circumstances and aims to provide a management support system, method, and program that takes into account industry-specific circumstances as a measure against customer harassment, automatically suggests countermeasures in advance, and prevents customer complaints. [Means for solving the problem]

[0008] To achieve the above objective, the management support system according to the present invention comprises: a storage means for storing customer complaint information regarding banking operations, wherein the complaint information includes the content of the complaint and countermeasures corresponding to the customer's complaint; a weighting means for creating weighted information for complaint countermeasures, wherein the weighting is performed by ranking customer responses in order of priority using information including the complaint information, and the weighting is performed based on a comparison between the customer's account balance and a threshold; and a proposal means for receiving employee notification information, obtaining weighted information including keywords from the employee notification information, and displaying information including countermeasures and response ranks based on the ranking. [Effects of the Invention]

[0009] According to the present invention, customer harassment can be efficiently prevented because countermeasures against similar cases are automatically presented in advance, taking into account industry-specific circumstances. [Brief explanation of the drawing]

[0010] [Figure 1] This is a diagram showing the configuration of a management support system according to an embodiment of the present invention. [Figure 2] This figure shows an example configuration of a bank server according to an embodiment of the present invention. [Figure 3] This figure shows an example of a data structure for management support data according to an embodiment of the present invention. [Figure 4] This figure shows an example of a data structure for management support data according to an embodiment of the present invention. [Figure 5] This is a flowchart illustrating the storage means of a management support system according to an embodiment of the present invention. [Figure 6] This is a flowchart illustrating the weighting means of a management support system according to an embodiment of the present invention. [Figure 7] This is a flowchart illustrating the proposed means of a management support system according to an embodiment of the present invention. [Figure 8] This is a screen diagram illustrating the proposed means of a management support system according to an embodiment of the present invention. [Modes for carrying out the invention]

[0011] Embodiments of the present invention will be described below with reference to the drawings.

[0012] Referring to Figure 1, an example of the overall configuration of the management support system 100 in an embodiment of the present invention will be described. The management support system 100 includes a bank server 101 within the bank 104 and a plurality of terminals 103a, 103b, etc. (hereinafter referred to as "terminals 103").

[0013] Although only terminals 103a and 103b are shown in Figure 1 for convenience, the number of terminals 103 is not limited. The bank server 101 and terminals 103 are interconnected via network 102. Here, network 102 may be the Internet, a LAN (Local Area Network), or a WAN (Wide Area Network), and is not particularly limited.

[0014] The bank server 101 is a computer device that performs the processing according to this embodiment. The bank server 101 is a server computer managed by the bank 104. Therefore, the bank server 101 may be implemented in a conventional administrator system such as a bank. The bank server 101 may be implemented by a single computer device or by multiple computer devices. The components and functions of the bank server 101 will be described later.

[0015] Terminal 103 represents the terminal used by the user who uses the business support system 100. Terminal 103 represents the terminal used by the employees of the bank 104, who are the users, in their work. The user can access the bank server 101 from terminal 103 and take measures against customer harassment based on the business support system 100. The components and functions of terminal 103 will be described later.

[0016] Terminal 103 has a human interface such as a keyboard or a touch panel. Specifically, examples include desktop personal computers, smartphones, tablet-type or notebook-type personal computers, and the like.

[0017] Next, referring to FIGS. 1 and 2, an example of the detailed components of the bank server 101 will be described.

[0018] The bank server 101 includes a control unit 110, an input unit 111, an output unit 112, a memory unit 113, a transmission / reception unit 114, and a storage unit 116, and each of these elements is coupled by a system bus 115. The components of the storage unit 116 will be described later.

[0019] The control unit 110 is also referred to as a processor and refers to, for example, a CPU or the like. The control unit 110 controls the above-described components and executes data calculations. The control unit 110 reads and executes a program in the memory unit 113 in order to execute each process according to the present embodiment. The program is a program for implementing a part of the functions executed by the business support system 100 and is stored in the storage unit 116.

[0020] The input unit 111 receives an operation instruction from the outside. Examples of the input unit 111 include a keyboard and a touch panel. The output unit 112 outputs the data stored in the storage unit 116 and the result of the arithmetic processing. Examples of the output unit 112 include a display and a printer.

[0021] The memory unit 113 is a volatile data storage device that stores data on the bank server 101, computer-executable instructions, and the like. The memory unit 113 is implemented using RAM such as DRAM (Dynamic Random Access Memory) or SRAM (Static Random Access Memory).

[0022] The transmitting / receiving unit 114 communicates with the bank server 101 and the terminal 103 via the network 102. For example, the transmitting / receiving unit 114 sends data such as customer harassment response measures to the terminal 103 via the bank server 101.

[0023] The storage unit 116 is implemented using any storage device such as a ROM, HDD, or SSD. The storage unit 116 includes storage means 120, weighting means 121, and suggestion means 122 related to processing performed by the management support system 100. Furthermore, the storage unit 116 includes a complaint information storage unit 130, a telephone complaint information storage unit 131, a customer information storage unit 132, an ATM information storage unit 133, an approval information storage unit 134, a weighting information storage unit 135, an employee notification information storage unit 136, a simulated experience information storage unit 137, an account information storage unit 138, and a deposit / withdrawal information storage unit 139 for storing data handled by the management support system 100. Details of each means 120 to 122 and each storage unit 130 to 139 will be described later.

[0024] The data stored in the complaint information storage unit 130, telephone complaint information storage unit 131, customer information storage unit 132, ATM information storage unit 133, approval information storage unit 134, weighted information storage unit 135, employee notification information storage unit 136, simulated experience information storage unit 137, account information storage unit 138, and deposit / withdrawal information storage unit 139 within the storage unit 116 of the bank server 101 will be explained below.

[0025] The complaint information storage unit 130 is a database in which the complaint data 300 shown in Figure 3, which is complaint information, is stored. The complaint data 300 consists of store complaint data 300a and telephone complaint data 300b (hereinafter referred to as "complaint data 300"), each using the same data format as the complaint data 300.

[0026] Refer to Figure 3 to explain the complaint data 300.

[0027] The complaint data 300 in Figure 3 consists of customer complaint content data 302 and complaint response data 303, which are associated with customer ID 301. The complaint data 300 is not limited to these data items and may include other data items as well.

[0028] The store complaint data 300a is created by the storage means 120 and is data about complaints received by employees of bank 104 from customers at the stores. Here, "store" refers to branches, the head office, etc., of bank 104. The storage means 120 will be described later.

[0029] The telephone complaint information storage unit 131 is a database in which the complaint data 300 shown in Figure 3, which is complaint information, is stored. The telephone complaint data 300b is created by the storage means 120 and is data about complaints received by operators from customers at the call center of the bank 104.

[0030] The customer information storage unit 132 is a database in which customer information data of the bank 104 is stored. The customer information data includes data such as name data, account identification information data, place of residence / workplace data, and date of birth data, all associated with a customer ID that identifies the customer. The customer information data is an example and is not limited to these data items.

[0031] The ATM information storage unit 133 is a database that stores ATM data, which is information about the ATMs of the bank 104. The ATM data is data that associates the branch number that identifies the branch that manages the ATM, the ATM's installation location data, and update information data indicating the decommissioning or setting up of the ATM with the ATM number that identifies the ATM. The ATM data is an example and is not limited to these data items.

[0032] The approval information storage unit 134 is a database that stores approval data, which is approval information for obtaining approval for matters at Bank 104. The approval data is data that associates the department name of the department submitting the approval request, the content of the approval request, etc., with a department code that identifies the department. The approval data is an example and is not limited to these data items.

[0033] The weighted information storage unit 135 is a database in which the weighted information data 400 shown in Figure 4 is stored.

[0034] The weighted information data 400 is created by the weighting means 121 and is data that ranks customer service priorities based on account balances, including the complaint data 300. The weighting means 121 will be described later.

[0035] Refer to Figure 4 to explain the weighted information data 400.

[0036] The weighted information data 400 in Figure 4 includes data associated with customer ID 401, such as customer account branch number 402, branch name data 403, account type data 404, account number 405, name data 406, age data 407, address data 408, account balance data 409, bank 104 service usage data 410, customer complaint details data 411, complaint response data 412, remarks data 413 containing information that increases the priority of customer service, and response rank data 414 describing the ranking results. The weighted information data 400 is not limited to these data items and can include other data items as well.

[0037] The employee notification information storage unit 136 is a database that stores employee notification data, which is internal employee notification information such as "Notices." Employee notification data is data where the department name of the department issuing the notification, the content of the notification, etc., are associated with a department code that identifies the department. The employee notification data is an example and is not limited to these data items.

[0038] The simulated experience information storage unit 137 contains training videos, audio, and other materials used when displaying countermeasures in the proposed means 122. The proposed means 122 will be described later.

[0039] The account information storage unit 138 is a database that stores account data, which is information about accounts held by customers of bank 104. The account data includes branch name data, account type data, account holder number, name data, address data, account balance data, and service usage data, all of which are associated with branch numbers that identify branches and accounts, and account numbers. The account data is an example and is not limited to these data items.

[0040] The deposit and withdrawal information storage unit 139 is a database that stores deposit and withdrawal data for customer accounts, such as the amount of deposits and withdrawals received from the ATM. The deposit and withdrawal data includes account identification information data, transaction date and time data, deposit and withdrawal location data, deposit and withdrawal category data, amount data, and account balance data, all of which are associated with the branch number and account number included in the account identification information data. The deposit and withdrawal data is an example and is not limited to these data items.

[0041] In addition to the databases mentioned above, any database where customer complaints may be recorded, such as corporate databases, MCIF databases, and information systems databases, can be used.

[0042] Next, referring to Figures 1 to 8, we will explain the processes of the storage means 120, weighting means 121, and proposal means 122 within the memory unit 116 of the bank server 101.

[0043] The processing of the storage means 120 will be explained with reference to Figures 3 and 5.

[0044] When an employee at a bank branch 104 receives and responds to a customer complaint at the counter or elsewhere, the employee inputs the customer ID 301 of the complaining customer, the customer complaint details 302, and the response measures 303 as branch complaint data 300a using a terminal 103 within the branch. At this time, the employee may also input the department handling the complaint.

[0045] For example, in Figure 3, customer ID 301 "2345678901" makes a complaint with complaint data 302 stating, "On [Date], some ATMs were discontinued, and now only one is available. It's inconvenient because I have to queue again when it's crowded." The bank 104 then inputs the response data 303, stating that in the future, when ATMs are discontinued, they will provide advance notice with posters and send direct mail to customers.

[0046] Furthermore, the countermeasure data 303 may include not only future countermeasures, but also actual countermeasures taken in response to the complaint data 302, such as "explaining that subscribers to services for affluent customers can be served without waiting in line if they request it at the store," as in the case of customer ID 301 "1234567890" in Figure 3.

[0047] When an operator at the Bank 104 call center receives and handles a customer complaint over the phone, the operator inputs the customer ID 301 of the complaining customer, the customer's complaint details 302, and the Bank 104's response data 303 into the telephone complaint data 300b from terminal 103, similar to the branch complaint data 300a. Note that the complaint details 302 in the telephone complaint data 300b may be automatically entered using an existing voice-to-text conversion tool or similar.

[0048] When the storage means 120 receives store complaint data 300a from terminal 103, it stores it as complaint data 300 in the complaint information storage unit 130. When the storage means 120 receives telephone complaint data 300b from terminal 103, it stores it as complaint data 300 in the telephone complaint information storage unit 131 (step S501).

[0049] The processing of the weighting means 121 will be explained with reference to Figures 4 and 6.

[0050] The weighting means 121 reads and obtains complaint data 300 from the complaint information storage unit 130 or the telephone complaint information storage unit 131 (step S601).

[0051] The weighting means 121 obtains information from the database necessary to create weighted information data 400 based on the acquired complaint data 300 (step S602).

[0052] For example, the weighting means 121 uses the customer ID 301 of the complaint data 300 as a search key to search for the customer ID in the customer information storage unit 132, and obtains account identification information data from the matching customer information data. The weighting means 121 further obtains the branch number 402, account data 404, and account number 405 from the account identification information data.

[0053] The weighting means 121 retrieves name data 406 from customer information data where the customer ID matches in the customer information storage unit 132, age data 407 from date of birth data, and customer address data 408 from place of residence / place of work data.

[0054] The weighting means 121 retrieves any information that influences ranking, such as "former employee," within the matching customer information data as remarks data 413. Here, customer information data is just an example; the weighting means 121 can retrieve information that influences ranking from any information, such as databases or audio data. "Information that influences ranking" will be described later.

[0055] The weighting means 121 uses the acquired branch number 402 and account number 405 as search keys to search the branch number and account number in the account information storage unit 138, and obtains branch name data 403, customer account balance data 409, and service usage data 410 from the matching account data. Service usage data 410 refers to financial services that the bank 104 provides to its customers, such as services for wealthy individuals or biometric authentication.

[0056] The weighting means 121 compares the acquired customer account balance data 409 with the average account balance of customers subscribed to a specific service of the bank 104, using this as a threshold (step S603). For example, in the case of customers subscribed to the bank's services for wealthy individuals, the weighting means 121 selects the account balance data of customers whose service usage data in the account information storage unit 138 is for services for wealthy individuals, calculates the average value, and obtains the acquired value. Note that the threshold setting is not limited to this and can be applied to any service of the bank.

[0057] Generally, the account balances of customers subscribed to services for the wealthy are very high, often in the hundreds of millions of yen. When a complaint is received from a customer whose account balance exceeds the average for customers subscribed to such services, it is necessary to prioritize customer service for industry-specific reasons, such as preventing account closure and thus preventing losses to the bank.

[0058] If the weighting means 121 determines in step S603 that the customer's account balance data 409 is equal to or greater than the average account balance of customers who are subscribed to a specific service of the bank, the process proceeds to step S604. On the other hand, if the weighting means 121 determines that the customer's account balance data 409 is less than the average account balance of customers who are subscribed to a specific service of the bank, the process proceeds to step S605.

[0059] If the process proceeds to step S604, the weighting means 121 determines that customer ID 401 is a customer that requires a higher priority in customer service for complaints and adds points for ranking (step S604). For example, points may be added based on the customer's account balance data 409, but this is not limited to this. In this case, if the customer's account balance data 409 in Figure 4 is 100 million yen, then 100 million points will be awarded.

[0060] After completing step S604, proceed to step S605. The ranking system will be explained later.

[0061] The weighting means 121 compares the acquired customer account balance data 409 with the average account balance of customers whose deposit and withdrawal amounts for a specific period are above a certain amount, using this as a threshold (step S605). The weighting means 121 calculates the average account balance of customers whose deposit and withdrawal amounts for a specific period are above a certain amount based on the account balance data of customers whose deposit and withdrawal information storage unit 139 amounts above a certain amount for the relevant period. However, the setting of the threshold is not limited to this.

[0062] For example, customers whose monthly deposits and withdrawals exceed a certain amount are likely to be valuable customers of Bank 104, such as those who receive their monthly salary deposits through Bank 104 or who regularly use ATMs. If a complaint is received from a customer whose monthly deposits and withdrawals exceed a certain amount and whose account balance is above the average of such customers, it is necessary to prioritize addressing the issue for industry-specific reasons, such as ensuring continued use of the service.

[0063] If the weighting means 121 determines in step S605 that the customer's account balance data 409 is equal to or greater than the average account balance of customers whose deposits and withdrawals for a specific period are above a certain amount, the process proceeds to step S606. On the other hand, if the weighting means 121 determines that the customer's account balance data 409 is below the average account balance of customers whose deposits and withdrawals for a specific period are above a certain amount, the process proceeds to step S607.

[0064] If the process proceeds to step S606, the weighting means 121 determines that customer ID 401 is a customer that requires a higher priority for complaint handling, and adds points for ranking, similar to step S604. After step S606 is completed, the process proceeds to step S607.

[0065] The weighting means 121 determines whether the remarks data 413 obtained in step S602 contains information that affects the ranking (step S607).

[0066] Information that influences ranking refers to information that, due to industry-specific reasons, is more likely to result in complaints than usual, and therefore should be given higher priority in customer service. For example, a "former bank employee" who previously worked at bank 104 is more likely to complain because they are familiar with the inner workings of the bank. Alternatively, in the case of customers who use biometric authentication at ATMs, discontinuing ATMs that support biometric authentication may increase the likelihood of complaints. Furthermore, the weighting means 121 may use existing AI technology to determine that complaints containing a high frequency of specific phrases in the complaint content data 411 should be given higher priority in customer service. In the case of complaints at a call center, the weighting means 121 can also analyze emotions from the voice data and acquire customers who are deemed to have a strong emotional response, such as those with large differences in pitch in their voice, as remarks data 413, and determine that this should be given higher priority in customer service.

[0067] If the weighting means 121 determines in step S607 that the remarks data 413 contains information that would affect the ranking, the process proceeds to step S608. On the other hand, if the weighting means 121 determines that the remarks data 413 does not contain information that would affect the ranking, the process proceeds to step S609.

[0068] For example, in Figure 4, the customer with customer ID "2345678901" has the remarks data 413 "former employee," so the weighting means 121 determines that it contains information that will affect the ranking, and proceeds to step S608.

[0069] If the system proceeds to step S608, the weighting means 121 determines that customer ID 401 is a customer that requires a higher priority for complaint handling and adds points for ranking, similar to step S604. After step S608 is completed, the system proceeds to step S609.

[0070] The weighting means 121 ranks the customer complaints according to the accumulated points to determine the priority order of customer service, and determines the corresponding rank data 414 (step S609).

[0071] For example, if the threshold for step S603 is 100 million yen, the threshold for step S605 is 6 million yen, and account balance data 409 is used as added points, then the total points for customer ID "1234567890" in Figure 4 will be 200 million points. On the other hand, the total points for customer ID "2345678901" will be 14 million points.

[0072] For example, customers with over 100 million points could be ranked as "5" in the customer service ranking data 414, as they have the highest priority for handling customer complaints. Customers with over 50 million points could be ranked as "4," those with over 10 million points as "3," those with over 5 million points as "2," and those with less than 5 million points as "1," but this is not limited to this. Furthermore, the ranking system is not limited to five levels and can be set arbitrarily.

[0073] In this case, the corresponding rank data 414 for customer ID "1234567890" will be "5", and the corresponding rank data 414 for customer ID "2345678901" will be "3".

[0074] The weighting means 121 creates weighted information data 400 using the corresponding rank data 414 determined in step S609 based on the data acquired in step S602, and stores it in the weighted information storage unit 135 (step S610).

[0075] The process of the proposed means 122 will be explained with reference to Figures 7 and 8.

[0076] The suggestion means 122 receives employee notification data entered by the employee from the terminal 103 and stores it in the employee notification information storage unit 136 (step S701). The employee notification data is data that employees within the bank should share in advance, such as planned equipment replacements for ATMs, and an example of such data is "We will partially discontinue the ATMs at Branch C on [Date] [Month] [Day], 202X." In addition, based on the employee notification data entered by the employee, the suggestion means 122 may display the contents of the employee notification data as a pop-up on the terminal 103. In this case, if the employee selects to display the pop-up, a screen for approval data for the entered employee notification data will be displayed, and if the employee approves the approval, the contents will be registered in the approval information storage unit 134 by pressing the registration button on the screen.

[0077] The proposed means 122 reads and acquires weighted information data 400 from the weighted information storage unit 135 (step S702).

[0078] The proposed means 122 searches the acquired weighted information data 400 for claim content data 411 using the keywords of the input bank employee notification data, and extracts the weighted information data for which the keywords match (step S703).

[0079] For example, in the proposal display screen 800 in Figure 8, the internal notification display screen 801 displays the internal notification data "On [Date], some ATMs at Branch C will be discontinued." The proposal means 122 extracts the keywords "ATM" and "discontinued" from this internal notification data.

[0080] Keyword extraction can be performed using dictionary databases (not shown), but is not limited to this method; any other means can be used.

[0081] The proposed means 122 searches the weighted information data 400 for complaint content data 411 based on the extracted keywords "ATM" and "abolished," and retrieves and displays the weighted information data 400 that includes the complaint content data 411 for customer ID "23456788901" in Figure 4, which reads, "Some ATMs were abolished on △ / × / 202X, and now only one is available. It's a hassle because you have to queue again when it's crowded." (Step S704).

[0082] The proposed means 122 displays the branch name data 403, name data 406, age data 407, remarks data 413, complaint content data 411, countermeasure data 412, and countermeasure rank data 414 from the acquired weighted information data 400 as shown in the countermeasure display screen 802 of Figure 8.

[0083] For example, by viewing the suggestion display screen 800, employees at Branch C can proactively implement measures to prevent complaints, such as "disclosing the ATMs in advance by posting posters and sending direct mail to customers." Furthermore, if former employees use Branch C, they can take precautions in advance to prevent complaints.

[0084] The proposed means 122 may use the simulated experience information storage unit 137 to display training videos explaining countermeasures for complaints, customer warning images, etc., to the terminal 103.

[0085] Furthermore, as an example, in the case of Figure 8, the suggestion means 122 may transmit an image indicating that some ATMs at Branch C will be discontinued in the future onto the screen of the ATM at Branch C, based on the ATM number, jurisdiction branch number, etc., of the ATM data.

[0086] On the countermeasure display screen 802, if there are multiple weighted information data 400 obtained in step S703, multiple entries of the claim content data 411 and countermeasure data 412 can be displayed, and employees can select the display content they deem most appropriate from among them. Furthermore, when displaying multiple entries, the weighted information data 400 may be displayed in descending or ascending order of the corresponding rank in the corresponding rank data 414, or only the claim content data 411 and countermeasure data 412 for a specific rank, or only within a specific range of ranks, may be displayed.

[0087] The order of processing described in the above embodiments does not necessarily have to be performed in the order described, and may be performed in any order. Furthermore, additional processing may be added without departing from the basic concept of the present invention.

[0088] As described above, the management support system 100 according to this embodiment is configured as described. Next, the effects of the management support system 100 will be explained.

[0089] According to this embodiment, since the threshold is the average account balance of customers subscribed to a specific service of bank 104, high-value depositors can be automatically identified by comparing the account balance of a customer who has made a complaint with the average account balance of customers with high deposit amounts, such as customers subscribed to the bank's services for wealthy individuals, and the priority of customer service can be efficiently determined. Furthermore, industry-specific circumstances can be efficiently taken into account in measures against customer harassment.

[0090] According to this embodiment, since the threshold is the average account balance of customers whose monthly deposits and withdrawals exceed a certain amount, by comparing the account balance of a customer who has made a complaint with the average account balance of customers whose monthly deposits and withdrawals exceed a certain amount, it is possible to automatically identify good customers who continuously use Bank 104, and to efficiently determine the priority of customer service. Furthermore, it is possible to efficiently consider industry-specific circumstances in customer harassment countermeasures.

[0091] According to this embodiment, since weighting is performed based on the presence or absence of information that increases the priority of customer service, it is efficient because industry-specific circumstances that make it relatively easier to generate complaints can be automatically taken into account when determining the priority of customer service.

[0092] Although embodiments of the present invention have been described above, it goes without saying that the present invention is not limited to these embodiments and can be implemented in various ways without departing from its spirit. For example, the roles of the means 120 to 124 of the management support system 100 and the storage unit 116 of the bank server 101 are not limited to the examples described above. [Explanation of Symbols]

[0093] 100 Business Support Systems 101 Bank Server 102 Network 103a, 103b terminals 104 Bank 110 Control Unit 111 Input Section 112 Output section 113 Memory section 114 Transmitter / Receiver 115 System Bus 116 Memory section 120 Storage means 121 Weighting method 122 Proposal means 130 Complaint Information Storage Unit 131 Telephone Complaint Information Storage Unit 132 Customer information storage unit 133 ATM information storage section 134 Approval Information Storage Unit 135 Weighted Information Storage Unit 136 Employee notification information storage unit 137 Simulated Experience Information Storage Unit 138 Account Information Storage Unit 139 Deposit and withdrawal information storage unit 800 Proposal display screen

Claims

1. A storage means for storing customer complaint information regarding banking services, wherein the complaint information includes the content of the complaint and the countermeasures taken in response to the customer's complaint. A weighting means for creating weighted information for complaint handling, wherein the weighted information is information that ranks the priority order of customer service based on information including the customer's account balance information, and the ranking is performed based on a comparison between the customer's account balance and a threshold for the complaint information, and the weighting means includes A proposal means that, in response to received employee notification information, obtains weighted information including keywords extracted from the employee notification information, and displays information including the countermeasures and the response rank based on the ranking, wherein the employee notification information indicates information that should be shared among employees within the bank. A management support system equipped with these features.

2. The management support system according to claim 1, wherein the threshold is the average value of the account balances of customers who are subscribed to a specific service of the bank.

3. The management support system according to claim 1, wherein the threshold is the average value of the account balances of the customer whose deposit and withdrawal amounts over a specific period are above a certain amount.

4. The management support system according to claim 1, further comprising performing the ranking based on the presence or absence of information that increases the priority of customer service included in the weighting information, wherein the information that increases the priority of customer service indicates information that the weighting means has determined to be highly likely to cause the customer's complaint.

5. A method performed by a computer, A step of storing customer complaint information regarding banking services, wherein the complaint information includes the content of the complaint and the countermeasures taken in response to the customer's complaint. A step of creating weighted information for complaint handling, wherein the weighted information is information that ranks the priority of customer service based on information including the customer's account balance information, and the ranking is performed based on a comparison between the customer's account balance and a threshold for the complaint information. A step of obtaining weighted information including keywords extracted from the received employee notification information, and displaying information including the countermeasures and the response rank based on the ranking, wherein the employee notification information indicates information that should be shared among employees within the bank. A method for providing this.

6. A program for causing a computer to perform the method described in claim 5.

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