JP6908229B2 - Matching program and data matching method - Google Patents

Description

The present invention relates to a collation program that causes a computer to perform collation processing between a plurality of billing data and a plurality of deposit data, and a data collation method that performs collation processing between a plurality of billing data and a plurality of deposit data.

Generally, payment by wire transfer is widely used as a payment method for commercial transactions. In the settlement by transfer, when the seller sells the product or the like to the buyer, the seller issues an invoice to the buyer based on the information of the product or the like. The buyer requests the amount of the invoice to be transferred to the seller's bank account using EB (Electronic Banking), a window of a financial institution such as a bank, an ATM (automated teller machine), or the like. A bank requested to transfer money by a buyer transfers funds from the buyer's bank account to the seller's bank account through a payment network such as Zengin. As a result, payment is made by wire transfer.

By the way, the same seller may issue a plurality of invoices to the same buyer. In such a case, it is very complicated for the buyer to perform the transfer process for each invoice. In addition, a transfer fee will be charged for each transfer process. Therefore, it is common practice for a buyer to add up the total amount of a plurality of invoices and transfer them to the seller's bank account.

However, when the buyer adds up the total amount of a plurality of invoices and makes a transfer, it may be difficult for the seller to identify which invoice the amount deposited is based on. Here, for example, if a total transfer is made for all unpaid invoices issued by the seller, and the total amount of the invoices and the total amount of the invoices are in agreement with each other, the seller determines the buyer. All unpaid invoices can be cleared at once. However, the total amount billed by the seller and the total amount transferred by the buyer may not match each other. Therefore, it is desired to improve efficiency and accuracy in collation processing of a plurality of billing data and a plurality of deposit data.

By the way, in recent years, not only in online shops mainly for BtoC, but also in business-to-business transactions, third-party collection by a storage agent such as credit card settlement and cash on delivery settlement is becoming mainstream, and the company's orders (shipments) are surely received. In order to confirm that the payment has been made quickly and accurately, it is complicated to check the payment information for omissions by individually comparing the payment details information that can be obtained from the storage agent with the order (shipment) details information of the company. Administrative work should be done.

In addition, there are cases where a plurality of storage agents are employed, which makes the management of payment status complicated.
In addition, there is a request to automatically collate payment details information with company's order / sales and shipping information to manage miscalculations.
In addition, there are both BtoB / BtoC transactions, and credit management has become complicated.
Furthermore, it is necessary to manage the status of the company's order information such as before settlement / settlement / payment collection for auditing before listing.
Furthermore, there is a demand to streamline the man-hours for creating accounting journals by automatically journalizing settlement results.

The present invention has been made to solve the above problems, and in order to quickly and accurately confirm that the order (shipment) of the company has been settled reliably and accurately, the payment details information that can be obtained from the storage agent and the company It is an object of the present invention to provide a collation program and a data collation method that can easily confirm whether or not there is any omission in the settlement information by individually comparing the order (shipment) detailed information of the above.

The collation program of the present invention identifies unmatched transaction data indicating the unmatched transaction data by the transaction settlement collation step of performing the first collation of the transaction data and the settlement data and the first collation. Not based on the transaction identification step, the unmatched settlement specifying step that identifies the unmatched settlement data indicating the unmatched settlement data by the first matching, and the settlement data that succeeded in the first matching. A billing / payment collation that performs a second collation between a plurality of billing data including the receivable billing data generated in the receivable billing generation step and the receivable billing data generated in the receivable billing generation process Let the computer perform the process.

Preferably, for the unmatched transaction data specified in the unmatched transaction specifying process, unmatched transaction status data indicating that the unmatched transaction data is deleted or new billing data corresponding to the data is issued is generated. The computer is made to perform the transaction status generation process further.

Preferably, a new billing issuance step of issuing new billing data based on the unmatched transaction data in which the unmatched transaction status data generated in the unmatched transaction status generation step indicates the issuance of the new billing data. Is further executed by the computer.

Preferably, the for the unreconciled payment data specified in uncollated settlement identifying step, non of generating unreconciled settlement status data indicating whether the manual association with the transaction data to the MiTeru if settlement data The computer is made to further execute the matching settlement status generation process.

Preferably, the unmatched settlement status data generated in the unmatched settlement status generation step is manually associated with the unmatched settlement data indicating that the unmatched settlement status data is associated with the transaction data. The computer is made to perform the unmatched settlement manual processing step further.

Preferably, the receivable claim generation step generates the receivable bill data including the receivable bill corresponding to the unmatched settlement data manually associated in the unmatched settlement manual processing step.

Preferably, the computer is further executed with the transaction data input step of inputting the transaction data from the ordering system, and at the time of inputting the transaction data, the sales related to the transaction data are the accounts receivable to the orderer related to the transaction. Manage as.

Preferably, the receivables related to the receivable bill data generated in the receivable bill generation step are managed as receivables for the settlement institution that issued the settlement data.

Preferably, the billing / payment collation step collates the billing data with the deposit data based on a preset collation order, and among the plurality of billing data, the unpaid billing data and the paid payment have been made. The batch application process for automatically specifying the billing data, and the unpaid billing data and the paid payment among the plurality of billing data remaining without being cleared in the batch application process. The individual clearing process for manually specifying the data and the pattern that was cleared in the individual clearing process are learned and saved as a learning history, and the saved learning history is reflected in the batch clearing process. Let the computer execute the learning history processing.

Preferably, when the information regarding the due date cash payment notification is input, the billing data and the payment data are collated and the application processing is performed, and a new billing date notified by the payment notification is set as the due date. Further causes the computer to perform due date cash processing for automatically generating data.

In the data collation method of the present invention, the transaction settlement collation step of performing the first collation of the transaction data and the settlement data and the unmatched transaction data indicating the unmatched transaction data are not specified by the first collation. Based on the matching transaction specifying step, the unmatched settlement specifying step that specifies the unmatched settlement data indicating the unmatched settlement data by the first matching, and the settlement data that succeeded in the first matching. A billing deposit that secondly collates a plurality of billing data including the receivable billing data generated in the receivable billing generation step and the receivable billing data generated in the receivable billing data, and the plurality of deposit data. The collation process is performed by a computer based on a program .

According to the present invention, in order to quickly and accurately confirm that the company's order (shipment) has been settled reliably, the payment detail information that can be obtained from the storage agent and the company's order (shipment) detail information are individually compared. In addition, it is possible to provide a collation program and a data collation method that can easily confirm whether or not there is any omission in the payment information.

It is an overall block diagram of the system which concerns on this embodiment. It is a functional block diagram of the collation system shown in FIG. It is a hardware configuration diagram for realizing the function of a collation system. It is a flowchart for demonstrating the flow of the collation processing by the collation system 13 shown in FIGS. 1 to 3. It is a functional block diagram which concerns on the batch application processing of the billing payment verification part shown in FIG. It is a table explaining the batch application processing of this embodiment. It is a table explaining the setting of the collation order of this embodiment. It is a table explaining the individual clearing process of this embodiment. It is a table explaining the setting of billing data in the individual clearing process of this embodiment. It is a table explaining the setting of the deposit data in the individual application processing of this embodiment. It is a table explaining the application simulation processing of this embodiment. It is a table explaining the due date cash processing of this embodiment.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the drawings.
Since the embodiments described below are suitable specific examples of the present invention, various technically preferable limitations are added, but the scope of the present invention particularly limits the present invention in the following description. Unless otherwise stated, the present invention is not limited to these aspects. Further, in each drawing, the same components are designated by the same reference numerals, and detailed description thereof will be omitted as appropriate.

FIG. 1 is an overall configuration diagram of the system 1 according to the present embodiment. FIG. 2 is a functional block diagram of the collation system 13 shown in FIG.
The block diagram shown in FIG. 1 is an example of the main configuration of the application processing system in which the collation program PRG is stored, and may not necessarily match the configuration of the actual program module. The hardware configuration shown in FIG. 1 is an example. An integrated circuit such as an LSI (Large Scale Integration) or an IC (Integrated Circuit) chipset may be used as a part or all of the application processing system in which the collation program PRG according to the present embodiment is stored. .. Each functional block may be individually processorized. A part or all of each functional block may be integrated and made into a processor. The method of making an integrated circuit is not limited to LSI, and may be a method of making an integrated circuit with a dedicated circuit or a general-purpose processor.

The collation program PRG according to the present embodiment may be recorded on a computer-readable recording medium. The recording medium may be a storage device such as a server connected to the network. Further, the collation program PRG according to the present embodiment may be distributed via a network.

As shown in FIG. 1, the transaction system 1 of the present embodiment has an ordering system 11 and a collation system 13, and performs processing while communicating with a customer terminal 21, a storage agency system 23, and a bank system 25.

The ordering system 11 performs ordering and settlement processing of goods and services with the customer terminal 21, and outputs the transaction data to the collation system 13. The transaction data has the settlement agency code, customer code, transaction ID, order ID, sales date, scheduled settlement date, transaction amount, etc. as items. The ordering system 11 makes a transaction collection request to the storage agency system 23.

The storage agency system 23 performs a storage agency process or the like on the customer terminal 21 in response to a collection request from the ordering system 11, and outputs payment data to the collation system 13. The settlement data has a plurality of freely created items that can be used as items such as a settlement agency code, a settlement date, a settlement amount, and an order ID.

As shown in FIG. 2, the collation system 13 includes, for example, a transaction settlement collation unit 39, an unverified transaction identification unit 41, an unverified settlement identification unit 43, an unearned bill generation unit 45, a billing payment verification unit 47, and an unmatched transaction. It has a status generation unit 49 and a new billing unit 51.

The transaction settlement collation unit 39 first collates the transaction data 141 input from the ordering system 11 with the settlement data 143 input from the storage agency system 23.
The first collation is between transaction data and settlement data using a collation key that is freely patterned for each settlement agency, in which multiple items with transaction data and items with settlement data are selected and set. Match match / mismatch.

The unmatched transaction identification unit 41 identifies unmatched transaction data indicating unmatched transaction data by the first collation by the transaction settlement collation unit 39. Here, the unmatched transaction data is transaction data in which the settlement data corresponding to the transaction data cannot be specified by the first matching.

The unmatched settlement identification unit 43 identifies the unmatched settlement data indicating the unmatched settlement data by the first collation by the transaction settlement collation unit 39. Here, the unmatched settlement data is settlement data in which the transaction data corresponding to the settlement data cannot be specified by the first matching.

The unmatched settlement status generation unit 53 indicates whether or not the unmatched settlement data specified by the unmatched settlement identification unit 41 is associated with the transaction data manually, and the unmatched settlement status data 161 indicates whether or not the unmatched settlement data is associated with the transaction data. To generate.

The unmatched settlement manual processing unit 55 manually associates the unmatched settlement data indicating that the unmatched settlement status data "associates" with the unmatched settlement status generation unit 53. Specifically, the unmatched settlement data indicating that the unmatched settlement status data "associates" and the unmatched transaction data are displayed on the display 122 shown in FIG. 3, and the operator presses the operation unit 123. Use to associate (link).

The receivable bill generation unit 45 generates the receivable bill data 171 based on the settlement data in which the transaction settlement collation unit 39 succeeds in the first collation.
At this time, the unearned bill generation unit 45 manually associates with the unmatched settlement manual processing unit 55 and generates the unearned billing data including the unmatched settlement data.

The billing / payment collation unit 47 secondly collates the plurality of billing data including the receivable billing data 171 generated by the receivable billing generation unit 45 with the plurality of deposit data 173 from the banking system 25.
The second collation is billed using predetermined items such as the kana information set in the customer master, the kana information stored in the learning history master, the transfer requester kana information on the deposit data, and the amount of money. The match / mismatch between the data and the deposit data 173 is collated.

The unmatched transaction status generation unit 49 indicates the unmatched transaction status data 163 indicating the deletion of the unmatched transaction data or the issuance of new billing data corresponding to the unmatched transaction data specified by the unmatched transaction identification unit 41. To generate. Specifically, the unmatched transaction data is displayed on the display 122 shown in FIG. 3, and the operator uses the operation unit 123 to input an instruction as to whether to delete the data or issue a new bill.

The new billing issuance unit 51 issues new billing data based on the unmatched transaction data in which the unmatched transaction status data 163 indicates the issuance of the new billing data in the unmatched transaction status generation unit 49.

FIG. 3 is a hardware configuration diagram for realizing the functions of the verification system 13 described above.
As shown in FIG. 3, the collation system 13 has, for example, an interface 121, a display 122, an operation unit 123, a memory 124, and a processing circuit 125, which are connected via a bus 120.

The interface 121 is used, for example, to communicate with other computers such as the ordering system 11, the storage agency system 23, and the banking system 25.
The display 122 displays various screens provided by the collation program PRG executed by the processing circuit 25.

The operation unit 123 is an operation means such as a keyboard and a mouse.
The memory 124 temporarily stores data used for processing of the collation program PRG executed by the processing circuit 125 and the processing circuit 125.
The processing circuit 125 executes the collation program PRG to control the processing of the counseling support device 1 in an integrated manner.
The processing of the collation system 13 shown in the present embodiment is described in the collation program PRG.

Hereinafter, the flow of the collation process by the collation system 13 will be described.
FIG. 4 is a flowchart for explaining the flow of the collation process by the collation system 13 shown in FIGS. 1 to 3.
Each step will be described.
Step ST1:
Transaction data 141 is input from the ordering system 11 shown in FIG. 1 via the interface 121 shown in FIG.
The transaction data 141 is stored in the memory 124. At this timing, the collation system 13 manages (data storage) the sales related to the transaction data as accounts receivable to the trader (user of the customer terminal 21) related to the transaction.

Step ST2:
Payment data 143 is input from the storage agency system 23 shown in FIG. 1 via the interface 121 shown in FIG.
The payment data 143 is stored in the memory 24.

Step ST3
The transaction settlement collation unit 39 first collates the transaction data input in step ST1 with the settlement data input in step ST2. The first collation is between transaction data and settlement data using a collation key that is freely patterned for each settlement agency, in which multiple items with transaction data and items with settlement data are selected and set. Match match / mismatch.

Step ST4:
The unmatched transaction identification unit 41 identifies unmatched transaction data indicating unmatched transaction data by the first collation by the transaction settlement collation unit 39.
The unmatched settlement identification unit 43 identifies the unmatched settlement data indicating the unmatched settlement data by the first collation by the transaction settlement collation unit 39.

Step ST5:
The unmatched settlement status generation unit 53 indicates whether or not the unmatched settlement data specified by the unmatched settlement identification unit 41 is associated with the transaction data manually, and the unmatched settlement status data 161 indicates whether or not the unmatched settlement data is associated with the transaction data manually. To generate.
The unmatched transaction status generation unit 49 indicates the unmatched transaction status day indicating the deletion of the unmatched transaction data or the issuance of new billing data corresponding to the unmatched transaction data specified by the unmatched transaction identification unit 41. Generate 163 data.

Step ST6:
The unmatched settlement manual processing unit 55 manually associates the unmatched settlement data indicating that the unmatched settlement status data "associates" with the unmatched settlement status generation unit 53.

Step ST7:
The receivable bill generation unit 45 generates the receivable bill data 171 based on the settlement data in which the transaction settlement collation unit 39 succeeds in the first collation.
At this time, the unearned bill generation unit 45 manually associates with the unmatched settlement manual processing unit 55 and generates the unearned billing data 171 including the unmatched settlement data.
The collation system 13 manages (data storage) the receivables related to the receivable billing data 171 as receivables for the bank system 25 (bank) that issued the corresponding settlement data.

Step ST8:
The billing / payment collation unit 47 secondly collates the plurality of billing data including the receivable billing data 171 generated by the receivable billing generation unit 45 with the plurality of deposit data 173.

Step ST9:
The new billing issuance unit 51 issues new billing data based on the unmatched transaction data in which the unmatched transaction status data 163 indicates the issuance of the new billing data in the unmatched transaction status generation unit 49.

The functions shown in FIGS. 3 and 4 of the collation system 13 focus on general payment management including ordinary transfer, and at the same time, collectively process miscalculation management of payment information using these payment agents, and are in operation at your company. By creating data linked to the core system and accounting system of, it can play a new role as a credit management system that can flexibly respond to new payment methods using payment agents.

According to the collation system 13, it is possible to automatically collate the payment details information with the company's order / sales and shipping information and manage the miscalculation.
Further, even when there are both transactions (BtoB) with the customer terminal 21 and transactions (BtoC) with the storage agency system 23, the credit management can be appropriately performed.
Furthermore, even if it is necessary to manage the status of the company's order information before settlement / settlement / payment collection due to auditing before listing, it can be dealt with appropriately. Furthermore, the settlement result can be automatically journalized to rationalize the man-hours for creating accounting journals.

Hereinafter, the second collation (application processing) performed by the billing / payment collation unit 47 shown in FIG. 2 will be described in detail.
The billing / payment collation unit 47 secondly collates the plurality of billing data including the receivable billing data 171 generated by the receivable billing generation unit 45 with the plurality of deposit data 173.

The billing payment collation unit 47 includes a batch application processing unit 251, an individual application processing unit 252, a learning history processing unit 253, and a due date cash processing unit 254. The batch application processing unit 251 includes an overpayment display processing unit 251a, an error adjustment processing unit 251b, and a collation order setting processing unit 251c. The individual application processing unit 252 includes an error adjustment processing unit 252a, an application simulation processing unit 252b, and an advance payment processing unit 252c.

Next, the details of the collation program PRG stored in the program storage unit 25 will be described with reference to the drawings.
FIG. 5 is a functional block diagram related to the batch application process of the billing / payment verification unit 47 shown in FIG.
FIG. 6 is a table for explaining the batch clearing process shown in FIG.
FIG. 7 is a table for explaining the setting of the collation order of the present embodiment.

The batch application processing unit 251 collates the billing data (accounts receivable billing data 171 and the like) with the deposit data 173 based on a preset collation order. As shown in FIG. 6, the billing data in the batch clearing process includes, for example, information on the billing destination code (customer code), the billing destination name (customer name), and the billing amount. .. The invoice issuance destination code is a code assigned to each invoice issuance destination. The invoice issuance destination name is the name of the invoice issuance destination (customer). The information included in the billing data in the batch application process may be appropriately selected by the user.

The deposit data 173 in the batch application process includes information on the transfer requester name (invoice issuance destination katakana name), the deposit amount, the fee burden, and the application balance. The transfer requester name (invoice issuance destination katakana name) is a katakana display of the invoice issuance destination name. The fee burden is information about the person who bears the transfer fee. In other words, the fee burden is information on whether the other party (customer) bears the transfer fee or whether the company bears the transfer fee. The balance of application represents the difference (unpaid amount) between the billed amount and the deposited amount. The information included in the deposit data 173 in the batch application process may be appropriately selected by the user.

Then, the batch application processing unit 251 automatically identifies the unpaid billing data and the paid billing data among the plurality of billing data (collective clearing process). For example, as shown in item number "1" shown in FIG. 6, the amount billed to "A Co., Ltd." is "279,000" and the amount deposited from "A Co., Ltd." is "200,000". In this case, the process of setting the remaining amount of application to "79,000" is executed. That is, the batch application processing unit 251 automatically identifies the unpaid amount "79,000" and the deposited amount "200,000" among the billed amount "279,000". Alternatively, for example, as shown in item number "4" shown in FIG. 6, the billing amount for "D Co., Ltd." is "31,500", and the deposit amount from "D Co., Ltd." is "31,500". In some cases, the process of setting the remaining amount of application to "0" is executed. That is, the batch application processing unit 251 applies the entire amount "31,500" of the billed amount "31,500" as if it was paid from D Co., Ltd.

Here, as described above with respect to FIG. 5, the batch application processing unit 251 has a collation order setting processing unit 251c. The collation order setting processing unit 251c sets the collation order for at least one of the invoice issuance destination code, the learning history, the dedicated deposit account, and the invoice issuance destination katakana name, and executes the batch application process. (Collation order setting process). That is, the batch application process has a collation order setting process.

As shown in FIG. 7, in the present embodiment, the order (collation order) in which the batch application processing unit 251 executes the collation process between the billing data and the deposit data 173 is the billing destination code and the learning history. , Dedicated deposit account and invoice issuance destination Kana name, set for at least one of them. The dedicated deposit account is an account assigned to each invoice issuer. The details of the learning history will be described later.

The order of the collation items (collation logic name) and the presence / absence of use are set appropriately by the user. In the example shown in FIG. 7, the collation process using the invoice issuance destination code, the learning history, the dedicated deposit account, and the invoice issuance destination katakana name is executed in this order. Further, in the example shown in FIG. 7, the invoice issuance destination code, the learning history, the dedicated deposit account, and the invoice issuance destination katakana name are all used in the collation process.

As described above with respect to FIG. 5, the batch application processing unit 251 has an overpayment display processing unit 251a. The overpayment display processing unit 251a determines the total amount of the deposited amount and the billing data when the amount of the paid billing data related to the billing destination is larger than the total amount of the plurality of billing data related to the billing destination. The difference between and is displayed as an overpayment (overpayment display processing). That is, the batch application process has an overpayment display process. For example, as in the item number "6" shown in FIG. 6, when the deposit amount "234,280" from "F Co., Ltd." is larger than the billing amount "232,000" for "F Co., Ltd." , The overpayment display processing unit 251a displays the overpayment (for example, minus display) with the application balance as "-2,280".

Further, as described above with respect to FIG. 5, the batch application processing unit 251 has an error adjustment processing unit 251b. The error adjustment processing unit 251b determines that the difference between the total amount of the plurality of billing data related to the billing destination and the amount of the paid billing data related to the billing destination is within a preset error amount. It is assumed that the total amount of billing data is the same as the amount already paid, and the application processing is performed (error adjustment processing). That is, the batch clearing process has an error adjustment process. For example, as shown in item number "3" shown in FIG. 6, when the fee burden is not the other party (C Co., Ltd.) but "in-house", the remaining amount of application "525" is a preset fee. If it is within the error amount, the error adjustment processing unit 251b determines that the application balance "525" is a fee error, and considers that the total amount of billing data is the same as the amount already paid and applies it. Perform processing.

FIG. 8 is a table for explaining the individual application processing of the present embodiment.
FIG. 9 is a table for explaining the setting of billing data in the individual application processing of the present embodiment.
FIG. 10 is a table for explaining the setting of the deposit data 173 in the individual application processing of the present embodiment.
The tables shown in FIGS. 9 and 10 may be used for setting the billing data and the deposit data 173 in the batch application process described above with respect to FIG.

The individual application processing unit 252 manually identifies the unpaid billing data and the paid billing data among the plurality of billing data remaining without clearing in the batch clearing process described above with respect to FIG. (Individual application processing). The billing data in the individual application process is, for example, information on the billing destination code (customer code), the billing destination name (customer name), the billing date, the scheduled payment date, and the billing amount. including. The deposit data 173 in the individual application process includes information on the transfer requester name (invoice issuance destination katakana name), the deposit date, and the deposit amount.

The information included in the billing data in the individual application process may be appropriately selected by the user. Specifically, the order and presence / absence of use of the information included in the billing data in the individual clearing process may be appropriately performed by the user. In the example shown in FIG. 9, the billing category, the positive / negative of the billing balance, the absolute value of the billing balance (planned payment amount), the scheduled payment date, the billing date, and the invoice issuance destination code (customer code). All information about, due date cash schedule flags, and is used as billing data in the individual clearing process in this order.

The information included in the deposit data 173 in the individual application process may be appropriately selected by the user. Specifically, the order and presence / absence of use of the information included in the deposit data 173 in the individual application processing may be appropriately performed by the user. In the example shown in FIG. 10, the offset data, the positive / negative of the deposit balance, the deposit date, the name of the transfer requester (invoice issuance destination Kana name), the destination bank, the destination branch, the absolute value of the deposit balance, and so on. All information about the deposit classification and is used as deposit data 173 in the individual application process in this order.

For example, in the item number "3" shown in FIG. 6, among the billed amount "10,500", the unpaid amount "525" and the deposited amount "9,975" are automatically specified by the batch application process. Has been done. In this case, the entire amount of the billed amount "10,500" is not specified as the deposit amount. Therefore, in the batch clearing process, the billing data related to "C Co., Ltd." is not cleared and remains.

Therefore, as shown in FIG. 8, regarding the item number “3” shown in FIG. 6, the individual application processing unit 252 uses the unpaid billing data and the paid billing among the plurality of billing data. The data and can be identified manually. Specifically, the individual clearing processing unit 252 selects the billing data to be cleared within the range of the deposit amount "9,975" from the plurality of billing data of items Nos. 1 to 3 shown in FIG. It can be selected manually.

At this time, the learning history processing unit 253 (see FIG. 5) learns the pattern that has been erased in the individual clearing process, saves it as a learning history, and reflects the saved learning history in the batch clearing process (see FIG. 5). Learning history processing). That is, in the batch application process described above with respect to FIG. 6, the learning history saved in the learning history process is referred to and used for collation between the billing data and the deposit data 173. For example, when clearing is performed in the individual clearing process, the invoice issuance destination code (see FIG. 9), the transfer requester name (see FIG. 10), the destination bank (see FIG. 10), and the destination branch (see FIG. 10). The collation history between at least one of the above is saved as a learning history. Then, the saved learning history becomes the target of the collation process in the batch clearing process.

In the example shown in FIG. 8, the learning history processing unit 253 has a pattern of billing data in which the billing data is cleared within the range of the deposit amount “9,975” from the plurality of billing data of items Nos. 1 to 3. And save it as a learning history. Then, the learning history processing unit 253 reflects the saved learning history in the batch clearing process described above with respect to FIG.

According to the collation program PRG according to the present embodiment, the learning history process is executed. Therefore, when the batch application process and the individual application process are executed, the billing data and the deposit data 173 are collated in the batch application process. The accuracy of the program will gradually improve. Thereby, it is possible to improve the efficiency and the accuracy in the collation processing of the plurality of billing data and the plurality of deposit data 173.

Further, as described above with respect to FIG. 5, in the batch application process, an overpayment display process of displaying as an overpayment is executed when the amount of the billed data that has been paid is larger than the total amount of the plurality of billing data. Therefore, the user can efficiently grasp that there was an overpayment.

Here, as described above with respect to FIG. 5, the individual application processing unit 252 has an advance payment processing unit 252c. The advance payment processing unit 252c determines the difference between the paid amount and the total amount of the billing data when the amount of the paid billing data related to the billing destination is larger than the total amount of the plurality of billing data related to the billing destination. Is processed as an advance payment (advance payment processing).

For example, in the item number "6" shown in FIG. 6, of the billed amount "232,000", the unpaid amount "-2,280" and the deposited amount "234,280" are automatically applied by the batch application process. Has been identified. In this case, since the deposit amount "234,280" is larger than the billing amount "232,000", the billing data related to "F Co., Ltd." is not cleared and remains in the batch clearing process. .. In this case, the advance payment processing unit 252c can process the difference (overpayment amount) "2,280" between the amount already paid and the total amount of billing data as the advance payment. As a result, in the next collation process, the advance payment and the billing data can be collated.

Further, as described above with respect to FIG. 5, in the batch application process, when the difference between the total amount of the plurality of billing data and the amount of the billed data that has been paid is within a preset error amount, a plurality of cases. An error adjustment process is executed in which the total amount of the billing data and the amount of the billed data that has been paid are regarded as the same amount and the application processing is performed. That is, when the application balance "525" in the batch application process is within the preset fee error amount, the error adjustment processing unit 251b determines that the application balance "525" is the fee error. Then, as shown in FIG. 8, the application balance "525" in the batch application process is processed as a fee "525" in the individual application process. Therefore, the application processing is executed assuming that the total amount of the billing data is the same as the amount already paid. According to this, the billing data related to "C Co., Ltd." is cleared more reliably in the batch clearing process, and it is possible to prevent the billing data from remaining unprocessed. Therefore, the clearing process is executed with higher accuracy.

Further, as described above with respect to FIG. 5, the collation order in the batch application process is the dedicated deposit account assigned to each invoice issuance destination, the invoice issuance destination code, the learning history, and the invoice issuance destination kana name. And, it is set for at least one of. Therefore, the user can change the collation order among the dedicated deposit account, the invoice issuance code, the learning history, and the invoice issuance katakana name, and appropriately select whether to use or not to use the collation item. It is possible to improve the efficiency and accuracy of the collation process in the batch clearing process.

FIG. 11 is a table for explaining the consumption simulation process of the present embodiment.
As described above with respect to FIG. 5, the individual application processing unit 252 has an application simulation processing unit 252b. When the total amount of the plurality of billing data related to the billing destination does not match the amount of the paid billing data related to the billing destination, the application simulation processing unit 252b deposits from the total amount of the plurality of billing data. Detects combinations that match the completed amount and lists them as candidates (consumption simulation processing). That is, the individual clearing process has a clearing simulation process.

For example, in the item number "2" shown in FIG. 6, of the billed amount "2,685,000", the unpaid amount "155,000" and the deposited amount "2,530,000" are collectively applied. It is automatically identified by processing. In this case, the entire amount of the billed amount "2,685,000" is not specified as the deposit amount. Therefore, in the batch clearing process, the billing data related to "B Co., Ltd." is not cleared and remains.

Therefore, as shown in FIG. 11, the individual clearing processing unit 252 executes the individual clearing process for the item number “2” shown in FIG. At this time, the application simulation processing unit 252b detects a combination that matches the deposited amount from the total amount of the plurality of billing data and lists it as a candidate. In the example shown in FIG. 11, the deposit amount “1,000,000”, “637,000”, “500,000”, “393,000”, and “155,000” are selected from among the plurality of billing amounts “1,000,000”, “637,000”, “500,000”, and “155,000”. The combinations "1,000,000", "637,000", "500,000" and "393,000" that match "2.53 million" are listed as candidates. If there is no problem with the listed candidates, the user can perform the erasure by performing a predetermined operation such as pressing a predetermined button.

According to this, the user can efficiently perform the application processing if there is no problem in the result of the application simulation process. Further, since the application simulation processing unit 252b lists the combination as a candidate, the combination can be appropriately rearranged in the individual application process. As a result, the efficiency of the collation process can be improved.

FIG. 12 is a table illustrating the due date cash processing of the present embodiment.
As described above with respect to FIG. 1, the program storage unit 25 has a due date cash processing unit 254. When the information regarding the due date cash payment notification 7 (see FIG. 1) is input, the due date cash processing unit 254 collates the billing data with the deposit data 173, performs the application processing, and notifies the due date cash payment notification 7 by the payment notification 7. Automatically generate new billing data with the due date as the due date (due cash processing).

For example, as shown in FIG. 12, when the payment notice 7 for the invoice 31 on the invoice date "March 10" arrives on April 30, the application processing with the collection category set to "cash due date". Is executed. That is, in the first collation process between the billing data and the deposit data 173, the balance of the accounts receivable amount (billing amount) is reduced.

Further, new billing data with the scheduled payment date notified by the payment notification 7 (July 31 in the example shown in FIG. 12) as the due date and the collection category as "transfer" is automatically generated. Then, the second collation process of the billing data and the deposit data 173 (cash transfer data) is executed. In this way, the clearing process is executed twice, the collection date of the payment notification 7 and the scheduled payment date (due date) notified by the payment notification 7. Therefore, it is possible to improve the efficiency and accuracy of the collation process.

The embodiment of the present invention has been described above. However, the present invention is not limited to the above embodiment, and various modifications can be made without departing from the scope of claims. The configuration of the above embodiment may be partially omitted or may be arbitrarily combined so as to be different from the above.

1 ... Transaction system 11 ... Ordering system 21 ... Customer terminal 23 ... Storage agency system 25 ... Banking system 39 ... Transaction settlement collation unit 41 ... Unmatched transaction identification unit 43 ... Unverified settlement identification unit 45 ... Unearned bill generation unit 47 ... Billing payment verification unit 49 ... Unverified transaction status generation unit 51 ... New billing issuance unit 53 ... Unverified settlement status generation unit 55 ... Unverified settlement manual processing unit 141 ... Transaction data 143 ... Settlement data 171 ... Receivable billing data 173 ... Payment data 251 ... Batch application processing unit 251a ... Overpayment display processing unit 251b ... Error adjustment processing unit 251c ... Collation order setting processing unit 252 ... Individual application processing unit 252a ... Error adjustment processing unit 252b ... Application simulation processing unit 252c ... Advance payment processing unit 253 ... Learning history processing unit 254 ... Due date cash processing unit

Claims (11)

The transaction settlement matching process, which performs the first matching between the transaction data and the settlement data,
The unmatched transaction identification process for identifying the unmatched transaction data indicating the unmatched transaction data by the first matching, and the unmatched transaction identification process.
An unmatched settlement specifying step for identifying unmatched settlement data indicating the unmatched settlement data by the first matching, and
A receivable bill generation step of generating receivable billing data based on the settlement data that succeeded in the first collation, and
A collation characterized in that a computer is made to execute a plurality of billing data including the unpaid billing data generated in the receivable billing generation step and a billing deposit collation step for performing a second collation with the plurality of deposit data. program. Unmatched transaction status generation step of generating unmatched transaction status data indicating deletion of the unmatched transaction data or issuance of new billing data corresponding to the unmatched transaction data specified in the unmatched transaction specifying process. The collation program according to claim 1, wherein the computer is further executed. A new billing issuance process for issuing new billing data based on the unmatched transaction data in which the unmatched transaction status data generated in the unmatched transaction status generation step indicates the issuance of the new billing data is performed on the computer. The collation program according to claim 2, which is further executed. Wherein for said unreconciled payment data specified in uncollated settlement specific process, produce unmatched settlement status that generates unreconciled settlement status data indicating whether the manual transaction data to the MiTeru if settlement data association The collation program according to any one of claims 1 to 3, wherein the computer further executes the process. Unmatched settlement manual that performs manual association processing based on the unmatched settlement data that indicates that the unmatched settlement status data generated in the unmatched settlement status generation process is manually associated with transaction data. The collation program according to claim 4, wherein the computer further executes the processing step. The claim 5 is described in claim 5, wherein the unearned bill generation step generates the unearned bill data including the unpaid bill corresponding to the unmatched settlement data manually associated in the unmatched settlement manual processing step. Matching program. Transaction data input process for inputting the transaction data from the ordering system.
The collation program according to any one of claims 1 to 6, wherein when the transaction data is input, the sales related to the transaction data are managed as accounts receivable to the ordering party related to the transaction. The collation program according to any one of claims 1 to 7, wherein the receivables related to the receivable bill data generated in the receivable bill generation step are managed as receivables for the settlement institution that issued the settlement data. The billing payment verification process is
A batch that collates the billing data with the deposit data based on a preset collation order and automatically identifies the unpaid billing data and the paid billing data among the plurality of billing data. Apply processing and
An individual application process for manually identifying the unpaid billing data and the paid payment data among the plurality of billing data remaining without being cleared in the batch application process.
A learning history process in which a pattern that has been erased in the individual clearing process is learned and saved as a learning history, and the saved learning history is reflected in the batch clearing process.
The collation program according to any one of claims 1 to 8, wherein the computer is executed. When the information regarding the due date cash payment notification is input, the billing data and the payment data are collated and the application process is performed, and new billing data with the scheduled payment date notified by the payment notification is automatically generated. The collation program according to any one of claims 1 to 9, wherein the computer further executes the due date cash processing generated in the above. The transaction settlement matching process, which performs the first matching between the transaction data and the settlement data,
The unmatched transaction identification process for identifying the unmatched transaction data indicating the unmatched transaction data by the first matching, and the unmatched transaction identification process.
An unmatched settlement specifying step for identifying unmatched settlement data indicating the unmatched settlement data by the first matching, and
A receivable bill generation step of generating receivable billing data based on the settlement data that succeeded in the first collation, and
A computer programmatically executes a plurality of billing data including the unpaid billing data generated in the receivable billing generation step and a billing deposit collation step for performing a second collation with the plurality of deposit data. Characteristic data matching method.

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