JP2009230689A - Reservation processing system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a reservation processing system for coping with a request from each customer. <P>SOLUTION: This reservation processing system 1 is configured to process reservation related with a face-to-face task from a customer, and provided with a customer information database 8 for storing history data related with the use result of a customer by customer ID; a reservation server 4 for predicting a delivery channel 2 matched with a request from the customer on the basis of the history data with respect to the reservation content of the customer, and for extracting the candidate of the delivery channel 2 can copy with the reservation content; and a presentation means for presenting the extracted candidate of the delivery channel 2 to the customer. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to a system for processing a reservation related to an interpersonal service applied by a customer through a delivery channel.

  When a customer makes a consultation reservation for a financial product (deposit, loan, investment trust, insurance, etc.) with a bank or other financial institution, he or she makes a call to a specific sales store and calls the product manager to speak verbally. The method of determining the consultation date is common.

  In recent years, some of the delivery channels that serve as contact points between customers and financial institutions have begun to be used, and there are reservation systems that use the Internet in the presence of various delivery channels such as sales outlets, ATMs, the Internet, and call centers. It is operated.

Although not related to a financial institution, in a management system that shares customer information among a plurality of tenants, an example relating to a processing technology for reservation input via a dedicated terminal installed in a tenant building or via the Internet is disclosed in Patent Literature 1.
JP 2001-256285 A (paragraphs 0029 to 0036)

  The customer's verbal reservation method with the person in charge of the product can determine the desired consultation date and time, but the place of consultation is limited to the business store where the person in charge of the product is present. As customer needs, for example, you may want to consult with a sales office near your workplace on weekdays, or with a family on a holiday, so you may want to consult with a sales office near your home or on a shopping path. It is very convenient for the customer to present a choice of a consultation place that suits his / her request as much as possible, but it is difficult to cope with the verbal reservation method at the store.

  The reservation method using the Internet is, for example, automatically extracting the nearest sales store from the place where the call is made based on the outgoing wave of the mobile phone connected to the Internet, and guiding the customer. As with the reservation method, it does not present options for consultation locations that meet customer needs.

  Note that the technology of Patent Document 1, which is a conventional example of a reservation system using a dedicated terminal or the Internet, relates to a reservation process after a customer makes a reservation to a tenant that he / she wants to use. There is no.

  The present invention was created to solve the above-described problems, and an object of the present invention is to provide a reservation processing system that can respond to each customer's request.

  The means of the present invention is a system for processing a reservation related to an interpersonal operation from a customer in order to solve the above-mentioned problem, and a storage means for storing history data related to a customer's usage record for each customer ID, and a reservation content of the customer In contrast, an extraction unit that predicts a delivery channel that meets a customer's request based on the history data, and extracts the delivery channel candidate that can correspond to the reservation content, and presents the delivery channel candidate to the customer A reservation processing system characterized by comprising:

  This reservation processing system predicts delivery channel candidates that are likely to meet the customer's needs based on the customer's usage record, and can respond to the customer's reservation contents, that is, reservation is possible Therefore, it is possible to provide a reservation service that meets the customer's request.

  The delivery channel may include a plurality of sales stores, and the extraction unit may extract a predetermined number of the plurality of sales stores as candidates.

  According to this reservation processing system, since a predetermined number of business store candidates are extracted, it is possible for a customer to reserve a business store most suitable for his / her request.

  Further, the reservation processing system is characterized in that the extraction means predicts a delivery channel that meets a customer's request based on at least reservation information in the history data.

  According to this reservation processing system, since the delivery channel is predicted based on at least the reservation information of the customer, it is possible to extract a delivery channel with a high probability that the customer desires, and to provide a reservation service with excellent prediction accuracy. Here, “reservation information” is information relating to a customer's reservation history, which includes a customer ID for identifying a customer, a reservation date indicating a reservation specified date, a reservation time indicating a reservation specified time, insurance, investment It consists of a transaction type indicating specific contents of consultation such as trust and loan, a reservation channel indicating the name of a store designated for reservation, a person-in-charge ID indicating the person in charge.

  In addition, the extraction means is a reservation processing system characterized in that the delivery channel is extracted from the number of times that the customer has previously specified reservation.

  According to this reservation processing system, since the delivery channel is extracted from the number of times that the customer has previously specified the reservation, it is possible to extract the delivery channel having a higher probability that the customer desires and to provide a reservation service with excellent prediction accuracy. .

  The reservation content of the customer includes a transaction type, and the extraction unit extracts a delivery channel from a number of times that the customer has previously specified a reservation with the same transaction type.

  According to this reservation processing system, since the delivery channel is extracted based on the customer's reservation tendency with respect to the transaction type, it is possible to extract a delivery channel having a higher probability that the customer desires and to provide a reservation service with excellent prediction accuracy.

  Further, the reservation contents of the customer include date and time information, and the extracting means extracts the delivery channel from the number of times that the customer previously specified a reservation at substantially the same reservation time zone and the condition whether the customer is a weekday or a holiday is the same. The reservation processing system is characterized by this.

  According to this reservation processing system, since the delivery channel is predicted based on the customer's reservation tendency with respect to the transaction date and time, a delivery channel with a higher probability that the customer desires can be extracted, and a reservation service with excellent prediction accuracy can be provided.

  The reservation processing system further includes a person-in-charge tentative determination unit that temporarily determines a person in charge for each delivery channel candidate extracted by the extraction unit.

  According to this reservation processing system, the setup when the person in charge is decided later becomes smooth, and it becomes easy for the person in charge to grasp the situation where the person in charge is appointed. The name of the person who has been tentatively decided can be presented to the customer together with the delivery channel candidate. Furthermore, if there are multiple qualified personnel, the candidate can be presented to the customer by consulting with the customer. Choose the right person for your environment.

  According to the present invention, since a delivery channel is predicted based on a customer's behavior history, a reservation service that meets each customer's request can be provided.

  An embodiment in which the present invention is applied to a reservation processing system of a financial institution will be described. FIG. 1 shows a configuration example of a reservation processing system according to the present invention, and FIG. 2 schematically shows a flow of reservation processing in the present invention.

  In FIG. 2, when a customer makes a reservation for a consultation application through a delivery channel where a reservation operation is performed (step S1), the reservation processing system is called (step S2), and the reservation processing system can handle the consultation through each process. And predicting delivery channels (stores) that meet customer needs. The predicted delivery channel is set as a consultation reservation as a delivery channel reservation candidate desired by the customer (step S3), and the reservation candidate is presented to the customer (step S4). When one of the customers presented is selected and a reservation is made, reservation information such as the location (delivery channel) and date desired by the customer is recorded in the customer information database (step S5). The reservation candidate is presented by an output means such as a delivery channel display device or an audio output device for performing a reservation operation.

  Hereinafter, a specific configuration of the reservation processing system will be described with reference to FIG. The basic configuration of the reservation processing system 1 is a delivery channel 2 that is a route for providing financial services to customers, and is connected to the delivery channel 2 via a network 3 such as a WAN (Wide Area Network) or a LAN (Local Area Network). The reservation server 4 includes a CRM (Customer Relationship Management) server 5 and a customer information database 8 having reservation information 6 respectively connected to the reservation server 4.

  The delivery channel 2 when performing a reservation operation includes a customer terminal 9 such as a personal computer or a mobile phone owned by the customer, a terminal system 10A installed at the window of the sales store 10, an ATM 11 which is an automatic transaction apparatus for various financial institutions, a telephone The call center 12 is a guidance service by The reservation contents that the customer applies for in the delivery channel 2 are the reservation date / time to be consulted, the transaction type (consultation contents of specific financial products such as insurance, investment trust, loan) and the like.

  If insurance consultation is reserved, the operation mode in each delivery channel 2 is generally as follows.

  (1) When making a reservation via the Internet using the customer terminal 9, after entering his / her customer ID and password, click “insurance” from each transaction type on the reservation guide screen displayed on the monitor. If the reservation date is specified, the desired date is input.

  (2) When making a reservation using the terminal system 10A of the sales store 10, after telling the person in charge the customer's own customer ID and password, tell them that they want to make a reservation for consultation about insurance and the desired date and time. .

  (3) When making a reservation using the ATM 11, after entering the customer's customer ID and password, the user presses the "insurance" field from the respective transaction types on the reservation guide screen displayed on the operation display. If the reservation date is specified, the desired date is input.

  (4) When making a reservation using the call center 12, after telling the telephone person in charge his / her customer ID and password, tell the customer that he / she wants to make a reservation for consultation about insurance and the desired date and time, and use a dedicated terminal installed in the call center 12. Ask for input.

  The CRM server 5 is a server that processes a CRM service, that is, a service that predicts and provides a financial service suitable for each customer based on the behavior and preference of each customer, and is connected to the customer information database 8.

  The customer information database 8 is configured as a storage unit that stores history data relating to customer usage results for each customer ID, and includes customer information 7 and reservation information 6 described in detail later. The customer information 7 includes, for example, basic customer information (name, address, age, occupation, family structure, etc.), account information (held account information, deposit amount, loan amount, etc.), transaction history information (payment, withdrawal, etc.) Stores transaction information (such as time series information), work information (introduction / recommended product information, etc.), work history information (sales history, results, etc.), and other information (for example, customer hobbies, lifestyle, products of interest, etc.) Has been. The CRM server 5 performs analysis according to each purpose based on such information, and performs processing such as picking up a promising customer for a new campaign product.

  The reservation server 4 predicts the delivery channel 2 that meets the customer's request based on the customer's usage history based on the customer's reservation content applied via the delivery channel 2, On the other hand, an extraction means for extracting a candidate for the delivery channel 2 that can be dealt with, that is, still has a vacant space for accepting a reservation is configured. The candidate to be extracted is, of course, the delivery channel 2 capable of interpersonal operations such as consultation of financial products, and the most preferable is the sales store 10 capable of direct customer service. Can be an extraction target.

  As a configuration example of the reservation server 4, it is assumed that a reservation reception processing unit 41, a customer reservation prediction processing unit 42, and a recommended channel extraction unit 43 are provided. The reservation reception processing unit 41 performs a reception process for reservation contents of a customer who is applied through the delivery channel 2.

  The customer reservation prediction processing unit 42 searches at least the reservation information 6 with respect to the reservation content received by the reservation reception processing unit 41, searches the customer information 7 as appropriate, and predicts the delivery channel 2 that meets the customer's request. .

  A configuration example of the reservation information 6 is shown in FIG. The reservation information 6 is information relating to a customer's reservation history, and includes a customer ID that identifies the customer, a reservation date that indicates a reservation specified date, a reservation time that indicates a reservation specified time, insurance, an investment trust, a loan, etc. The transaction type indicates the contents of consultation of a typical financial product, the reservation channel indicates the name of the store designated for reservation, the person in charge ID that indicates the person in charge, and the like. The reservation information 6 is basically stored as a result of a reservation being made and an actual consultation. In some cases, it is possible to store, for example, a customer whose reservation has been made but the customer canceled halfway and was not consulted. In this case, it is sufficient to make only the person in charge column blank. become.

  In the example shown in FIG. 3, the customer identified by the customer ID of the number “0001” makes a reservation to make a consultation about insurance at the store A at 10:00 am on September 1, 2007, and the person in charge at that time The person in charge of ID “A001” consults and makes a reservation for consultation on investment trusts at store C at 2 pm on November 25 of the same year, and the person in charge of person ID “C003” consults at that time. It is shown that the person in charge with the person in charge ID “A002” consulted at 10:00 am on March 7, 2008 for a loan consultation at the store A. Data is stored and managed in time series.

  The prediction calculation program in the customer reservation prediction processing unit 42 is appropriately set. First, when the customer designates only the transaction type as the reservation content, a first setting example includes a setting for preferentially selecting a delivery channel that the customer has previously designated for reservation. In other words, the delivery channel is selected from the ones that the customer has previously specified for reservation. In the example shown in FIG. 3, the sales store A store has a record of receiving the most twice reservations. Therefore, it is predicted that the sales store requested by the customer this time is likely to be the A store. The store A is selected with the highest priority, and then the store C that has received one reservation designation is selected.

  As a second setting example, there is a setting for preferentially selecting a delivery channel that the customer has previously reserved for the same transaction type. In other words, the delivery channel is selected from the ones that the customer has previously made a reservation designation with the same transaction type. For example, if the type of transaction that the customer wants to make a reservation for this time is an investment trust, in the example shown in FIG. 3, the sales store C store has a track record of consulting with an investment trust. Predicting that the store is likely to be a store, the store C is preferentially selected.

  In addition, when a customer designates a reservation date and time as a reservation content, a third setting example is a delivery in which a customer has made a reservation specification in the same reservation time zone when the conditions of a weekday or a holiday coincide with each other. A setting that preferentially selects channels is given. In other words, the delivery channel is selected from the ones in which the customer has previously met the conditions of weekdays or holidays and has a large number of reservations specified in substantially the same reservation time zone. For example, if the reservation date and time that the customer wants to make a reservation at this time is 10:00 am on a weekday, in the example shown in FIG. 3, assuming that September 1, 2007 and March 7, 2008 are weekdays, sales office A The store has a track record of receiving consultations twice a weekday at 10:00 am, so it is predicted that the store that the customer requests this time is likely to be the store A, and the store A is given priority. Pick out. The reservation time zone should have a certain tolerance. For example, if there is a track record of consulting at a time within 1 hour before and after the reservation specified time, it can be regarded as substantially the same reservation time zone and processed. Good.

  The reason for distinguishing between weekdays and holidays is that most sales stores can handle consultation work only on weekdays, and delivery channels that can handle holidays are often limited to special sales stores and call centers. This is to improve the prediction accuracy for the customer's request.

  Naturally, it is possible to make a prediction calculation program combining a plurality of setting examples as described above. However, in this case, the number of delivery channels to be predicted increases, and a situation where the candidates cannot be narrowed down as candidates may occur. For example, if it is desired to predict one delivery channel, but the three setting examples are set equally, both the store A and the store C satisfy the condition in the example of FIG. In this case, the number of delivery channels to be predicted can be reduced by performing different weighting processes on the delivery channels selected in each setting example. For example, if the largest weighting coefficient is applied to the delivery channel selected in the first setting example, the predicted number of the A store increases accordingly, so that the A store is selected and the delivery channel selected in the second setting example. C is selected if the largest weighting factor is applied. The weighting coefficient of each setting example is set appropriately.

  Further, in FIG. 1, in addition to the reservation information 6, customer information 7 can also be used as a prediction factor. For example, since the transaction history information of the customer information 7 indicates that the customer frequently makes transactions such as deposits / withdraws, transfers, and transfers at a sales office 10 or ATM 11, consulting reservations for financial products However, it is assumed that there is a high possibility of requesting this business store, and the business store 10 can be put into a prediction target by performing an appropriate weighting process. In another example, since the work history information of the customer information 7 shows the history of financial consultations applied directly at the counter instead of making a reservation, it is highly likely that the business store 10 will be requested even for a reservation. It is possible to enter a prediction target by performing an appropriate weighting process.

  Further, based on the customer's home address and work address, the business store 10 closest to the address may be appropriately weighted to be included in the prediction target. Information related to lifestyle can also be taken into account. For example, if there is information such as a customer living in a villa during the summer vacation period, the destination information such as the address of the destination during that period is stored as customer information in advance. When the reservation for the period is specified, the business store 10 close to the villa can be included in the prediction target.

  The delivery channel 2 predicted by the customer reservation prediction processing unit 42 described above is extracted by the recommended channel extraction unit 43 in a predetermined number from the one having a large prediction score.

  It should be noted that, even if there is an item for specifying the sales store 10, that is, an item for specifying a specific delivery channel 2 as an item of reservation contents of the customer, a means for extracting a plurality of delivery channel 2 candidates is effective. As an example, if the business store 10 is already filled with other reservations on the date on which it is desired to make a reservation, by extracting candidates for another business store 10 and presenting them to the customer, the customer has a predetermined date. The effect is that you can consult without changing.

  Next, the reservation server 4 can be provided with a person-in-charge tentative decision processing unit 44 that tentatively decides a person in charge for each delivery channel 2 candidate extracted by the recommended channel extraction unit 43. As a person in charge to make a provisional decision, a person who has previously responded to the customer is preferable, and a person who has responded under the same conditions as the transaction type, reservation time, etc. designated for reservation this time is more preferable.

In the example of FIG. 3, for example, if sales store A is listed as a candidate, if the transaction type of the current reservation is insurance, a person in charge with the person in charge ID “A001” is provisionally determined, and in the case of a loan, the person in charge is in charge. ID
A person in charge of “A002” is provisionally determined. Although not shown in the figure, if this reservation is designated at 2:00 pm for insurance and there is a history that another person in charge at the store A has consulted about insurance at 2:00 pm, the person in charge ID A person in charge other than the person in charge of “A001” is provisionally determined.

  If the person in charge is tentatively decided in this way, the final decision in the store can be made smoothly in the store, and the person in charge can easily grasp the situation in which the person is appointed. The name of the tentative person in charge can be presented to the customer together with the delivery channel 2 candidate. In addition, when there are a plurality of appropriate persons in charge, candidates for the persons in charge may be presented to the customer, and the customer may be tentatively determined by selecting the person to be selected.

  In FIG. 1, the delivery channel 2 candidates extracted by the recommended channel extraction unit 43 are presented to the customer through the delivery channel 2 that has performed the reservation operation. The number of candidates to be presented is set as appropriate. The presentation mode in each delivery channel 2 is as follows.

  (1) When a reservation operation is performed using the customer terminal 9 via the Internet, delivery channel 2 candidates that can be reserved are displayed on the monitor. If only the transaction type is input at the time of the first reservation operation, the date and time that can be reserved for each delivery channel 2 candidate is also displayed. The customer selects and clicks the desired delivery channel 2 from the candidates, specifies the date and time if necessary, and completes the reservation.

  (2) When a reservation is made using the terminal system 10A of the business store 10, candidates for the delivery channel 2 that can be reserved are displayed on the monitor of the terminal system 10A. If only the transaction type is input at the time of the first reservation operation, the date and time that can be reserved for each delivery channel 2 candidate is also displayed. The person in charge of the window prints the contents and presents it to the customer. The customer selects the desired delivery channel 2 from the candidates, and if it is necessary to specify the date and time, specifies it and informs the person in charge of the window. The person in charge of the window inputs the designated delivery channel 2 and date / time on the terminal system 10A, and completes the reservation.

  (3) When a reservation is made using the ATM 11, a candidate for a delivery channel 2 that can be reserved is displayed on the operation display. If only the transaction type is input at the time of the first reservation operation, the date and time that can be reserved for each delivery channel 2 candidate is also displayed. The customer selects and clicks the desired delivery channel 2 from the candidates, specifies the date and time if necessary, and completes the reservation.

  A presentation example on the operation display of the ATM 11 is shown in FIG. The presentation expression does not impose a place or date / time from the financial institution, but an expression in the form of a proposal is preferable, such as “We are ready for the customer's transaction contents at the following stores”. The example of presentation is not limited to Fig. 5, but various layouts are possible, such as displaying the name of the tentative person in charge as described above, or "If you are in a hurry or outside business hours, please use the call center" By displaying, better service can be provided.

  (4) When making a reservation using the call center 12, candidates for the delivery channel 2 that can be reserved are displayed on the monitor of the dedicated terminal installed in the call center 12. If only the transaction type is input at the time of the first reservation operation, the date and time that can be reserved for each delivery channel 2 candidate is also displayed. The telephone staff informs the customer of the contents, and the customer selects the desired delivery channel 2 from the candidates, and if it is necessary to designate the date and time, designates it to the telephone staff. The telephone person in charge inputs the designated delivery channel 2 and date / time on the dedicated terminal and completes the reservation.

  When the reservation is completed as described above, the current reservation information is stored in the reservation information 6 of the customer information database 8 by the reservation server 4.

  A series of processing operations of the reservation processing system 1 will be described with reference to FIG. 4 and specific components will be described with reference to FIG. 1 as appropriate. FIG. 4 is a flowchart showing a processing flow of the reservation processing system 1. When a customer makes a reservation application with the input of a customer ID or password through a delivery channel 2 such as ATM 11 (YES in step S101), the reservation server 4 identifies the customer from the customer ID (step S102) and The customer information database 8 (reservation information 6, customer information 7) is searched (step S103). If NO in step S101, the process returns to step S101.

  The reservation server 4 compares the reservation contents with the retrieved data to predict and extract a delivery channel 2 that meets the customer's request (step S104). When the predetermined number is extracted (YES in step S105), the extracted predetermined number of delivery channel 2 candidates are presented via the delivery channel 2 used by the customer for application (step S106). The number of candidates for presentation is set as appropriate, may be the same for all customers, or may have different specifications for each customer. If NO in step S105, the process returns to step S104.

  Next, when a candidate is selected by the customer (YES in step S107), the reservation information of this time is stored (stored) in the reservation information 6 of the customer information database 8 by the reservation server 4 (step S108), and the reservation process is terminated. If NO in step S107, the process returns to step S107.

  As described above, in FIG. 1, the storage means (customer information database 8) for storing the history data relating to the customer usage record for each customer ID, and the customer's reservation content according to the customer's request based on the history data. Extraction means (customer reservation prediction processing unit 42, recommended channel extraction unit 43) for predicting a suitable delivery channel 2 and extracting candidates of the delivery channel 2 that can cope with the reservation content; If the reservation processing system 1 is provided with presentation means for presenting candidates (presentation screen of the delivery channel 2 used by the customer for application), the reservation is possible and the customer's request is likely to be met Multiple delivery channels 2 can be presented, and a reservation service can be provided that meets the needs of each customer.

  Further, if the extraction means (customer reservation prediction processing unit 42, recommended channel extraction unit 43) is configured to predict and extract a delivery channel that meets the customer's request based on at least the reservation information 6 in the history data, the customer Because a delivery channel that reflects the reservation tendency can be extracted, a reservation service with excellent prediction accuracy can be provided.

  Further, if the extraction means (customer reservation prediction processing unit 42, recommended channel extraction unit 43) extracts the delivery channel 2 from the number of times that the customer has previously specified the reservation, the same delivery channel 2 will be used this time. Assuming that the probability of selection is high, it is possible to extract a delivery channel 2 having a higher probability that the customer desires, and to provide a reservation service with excellent prediction accuracy.

  In addition, when the customer reservation content includes a transaction type, the extraction means (customer reservation prediction processing unit 42, recommended channel extraction unit 43) starts the delivery channel from the number of times that the customer has made a reservation with the same transaction type before. 2 is extracted, the delivery channel 2 is predicted based on the customer's reservation tendency regarding the transaction type. Therefore, the delivery channel 2 with a higher probability of the customer's desire can be extracted, and a reservation service with excellent prediction accuracy is provided. it can.

  In addition, when the reservation contents of the customer include date and time information, the extraction means (customer reservation prediction processing unit 42 and recommended channel extraction unit 43) uses the same reservation time when the condition whether the customer is a weekday or a holiday has previously been matched. If the delivery channel 2 is extracted from the number of times the reservation is specified in the band, the delivery channel 2 is predicted based on the customer's reservation tendency with respect to the transaction date and time. A reservation service that can be extracted and has excellent prediction accuracy can be provided.

Further, for each candidate of the delivery channel 2 extracted by the extraction means (customer reservation prediction processing unit 42, recommended channel extraction unit 43), a person in charge tentative determination means (person in charge tentative determination processing unit) for tentatively determining the person in charge of the reception 44), the setup when the person in charge is decided later becomes smooth, and the person in charge can easily grasp the situation in which the person in charge is appointed.
The name of the person who has been tentatively decided may be presented to the customer together with the candidates for the delivery channel 2, and if there are multiple qualified persons in charge, if the candidate for the person in charge is presented to the customer, the customer You can choose the person who suits your consultation environment.

  The best embodiment of the present invention has been described above. The reservation processing system of the present invention can be applied to other than financial institutions, and can be applied to, for example, consultation reservation related to a mobile phone contract in a service network of a mobile phone company. In the embodiment described above, the reservation server 4 and the CRM server 5 are separated. However, the reservation server 4 includes a reservation reception processing unit 41, a customer reservation prediction processing unit 42, a recommended channel extraction unit 43, and a person in charge temporary determination processing unit 44. If so, both servers may be configured as a single unit. Further, in the embodiment described above, the customer information database 8 including the reservation information 6 and the customer information 7 is used. However, the database may be divided into a database dedicated to the reservation information 6 and a database dedicated to the customer information 7.

  In addition, as long as the predicted delivery channel 2 candidates can be presented to the customer, the presentation mode is not limited to that described, and various layouts of the presentation screens on the monitor and the operation display are conceivable.

  Using the feature of the present invention to search for customer usage results, forecasting and extracting financial products (such as new campaign products) that may be of interest to the customer along with the reservation process, and candidates for delivery channel 2 It is also possible to advertise the financial product in addition to the presentation.

It is a figure which shows the structural example of the reservation processing system which concerns on this invention. It is an image figure which shows the flow of the rough reservation process in this invention. It is a figure which shows the structural example of reservation information. It is a flowchart which shows the flow of a process of the reservation processing system which concerns on this invention. It is a figure which shows the example of presentation in the operation display of ATM.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Reservation processing system 2 Delivery channel 4 Reservation server 6 Reservation information 7 Customer information 8 Customer information database 41 Reservation reception process part 42 Customer reservation prediction process part 43 Recommended channel extraction part 44 Person in charge provisional decision process part

Claims (7)

A system for processing reservations related to interpersonal operations from customers,
Storage means for storing historical data relating to customer usage results for each customer ID;
Extraction means for predicting a delivery channel that meets a customer's request based on the history data for the reservation content of the customer, and extracting a candidate for the delivery channel that can correspond to the reservation content;
Presenting means for presenting the delivery channel candidates to the customer;
A reservation processing system comprising: The delivery channel includes a plurality of sales outlets,
The reservation processing system according to claim 1, wherein the extracting unit extracts a predetermined number of the plurality of business stores as candidates.   The reservation processing system according to claim 1, wherein the extraction unit predicts a delivery channel that meets a customer's request based on at least reservation information in the history data.   The reservation processing system according to claim 3, wherein the extraction unit extracts a delivery channel from a number of times that a customer has specified a reservation before. Customer reservation details include transaction type,
The reservation processing system according to claim 3, wherein the extraction unit extracts a delivery channel from a number of times that a customer has previously specified a reservation with the same transaction type. Customer reservations include date and time information,
The reservation unit according to claim 3, wherein the extraction unit extracts a delivery channel from a number of times that a customer has previously met a condition whether it is a weekday or a holiday and has made a reservation designation in substantially the same reservation time zone. Processing system.   7. The reservation processing according to claim 1, further comprising a person-in-charge tentative deciding means for tentatively deciding a person in charge for each delivery channel candidate extracted by the extracting means. system.

Images