JP7795448B2 - Financial data processing device, financial data processing method, and financial data processing program - Google Patents

Description

The present invention relates to a financial data processing device, a financial data processing method, and a financial data processing program.

For example, in the financial industry, debt management operations (e.g., credit, loans) require the management of information such as debtors, contracts, and daily transactions. A conventional system for debt management operations is disclosed, for example, in Patent Document 1.

JP 2015-14857 A

However, the above-mentioned Patent Document 1 does not disclose any simple method for automatically saving cross-sectional data of real-time financial data that is updated daily.

The present invention has been made in consideration of the above, and aims to provide a financial data processing device, a financial data processing method, and a financial data processing program that can automatically and easily save cross-sectional data of real-time financial data that is updated daily.

To solve the above-mentioned problems and achieve the objectives, the present invention provides a financial data processing device equipped with a control unit, which is configured to be able to access a management master in which a target year and month, a next execution date, and a retention period are set, daily updated real-time financial data, and a backup table; and which performs month-end closing processing to save cross-sectional data of the real-time data to the backup table as end-of-month data. During the month-end closing processing, the device is equipped with a month-end closing processing means that, on the next execution date of the management master, deletes end-of-month data from the management master that is older than the retention period, and adds cross-sectional data extracted from real-time data updated before the end of the month of the target year and month of the management master.

Furthermore, according to one aspect of the present invention, when the cross-sectional data is added, the month-end closing processing means may recalculate the necessary items at that time.

Furthermore, according to one aspect of the present invention, an execution date may be set in the management master, and the month-end closing processing means may, after executing the month-end closing processing, update the target year and month of the management master to the next month, and update the next execution date to the next month plus the date of the execution date of the management master.

Furthermore, according to one aspect of the present invention, the real-time data may include debt data, debt transaction data, general debt data, customer information data, general customer data, repayment schedule data, collection performance data, or customer bank information data.

Furthermore, to solve the above-mentioned problems and achieve the objectives, the present invention provides a financial data processing method executed by an information processing device equipped with a control unit, wherein the control unit is configured to be able to access a management master in which a target year and month, a next execution date, and a retention period are set, daily updated real-time financial data, and a backup table; the control unit executes a month-end closing process that saves cross-sectional data of the real-time data to the backup table as end-of-month data; and the month-end closing process includes a month-end closing processing step that, on the next execution date of the management master, deletes data from the end-of-month data that is older than the retention period of the management master, and adds cross-sectional data extracted from real-time data updated before the end of the month of the target year and month of the management master.

According to another aspect of the present invention, there is provided a financial data processing program to be executed by an information processing device having a control unit, wherein the control unit is configured to be able to access a management master in which a target year and month, a next execution date, and a retention period are set, real-time financial data that is updated daily, and a backup table; the control unit executes a month-end closing process in which cross-sectional data from the real-time data is saved to the backup table as end-of-month data; and in this month-end closing process, on the next execution date of the management master, deletes data from the end-of-month data that is older than the retention period of the management master, and adds cross-sectional data extracted from real-time data that was updated before the end of the month of the target year and month of the management master.

The present invention has the advantage of enabling cross-sectional data of real-time financial data that is updated daily to be automatically saved in a simple manner.

FIG. 1 is a diagram for explaining the month-end closing process executed by the financial data processing device of this embodiment. FIG. 2 is a diagram for explaining the utilization process executed by the financial data processing device of this embodiment. FIG. 3 is a block diagram showing an example of the configuration of a financial data processing device according to this embodiment. FIG. 4 is a diagram showing an example of a display screen for performing month-end closing processing. FIG. 5 is a diagram for explaining the details of the month-end closing process. FIG. 6 is a diagram for explaining a data image of month-end closing processing when real-time data is used as credit data. FIG. 7 is a diagram for explaining a data image of month-end closing processing when real-time data is used as bond transaction data.

An embodiment of the present invention will be described in detail with reference to the drawings. However, the present invention is not limited to this embodiment.

[1. Overview]
For example, in the financial industry, in the area of debt management (e.g., credit, loans), a large number of debtors are managed, and information is updated as transactions are made daily (e.g., daily deposit information, overdue information, contract changes, attribute information changes, etc.).

When you want to obtain cross-sectional data from a certain point in time in the past for internal analysis or external data sharing, there are issues such as the need to obtain the data on the same day, as the data changes depending on the transaction and the number of days overdue varies depending on the date. For example, if you want to view data from a certain point in time later, after obtaining the data, you have to exclude transaction data from a specific point in time outside the system and perform simulation calculations such as amount calculations.

In this embodiment, therefore, we provide a system that can automatically save cross-sectional data of real-time financial data (also known as "time-series data") that is updated daily using a simple method.

In this embodiment, the calculation logic of the business program can be called, and once the timing is decided, the data at that point can be automatically and collectively consolidated. This makes it possible to later refer to the correct cross-sectional information calculated using the same logic as a normal business program, regardless of the timing of the operation.

Saving and reviewing cross-sectional data has the following advantages:
(1) Batches can be executed overnight, so processing timing is not an issue (same-day processing is not required).
(2) Calculations using the business program eliminate the need for data processing outside the system (improving the accuracy of cross-sectional data).
(3) Since data from past points in time is also stored, it can be used in combination (simplifying data analysis).

An overview of the financial data processing device of this embodiment will be described with reference to Figures 1 and 2. Figure 1 is a diagram for explaining the month-end closing process executed by the financial data processing device of this embodiment. Figure 2 is a diagram for explaining the utilization process executed by the financial data processing device of this embodiment.

In Figure 1, the financial data processing device of this embodiment executes month-end closing processing in accordance with the settings in the management master. By executing month-end closing processing, data at the time of processing is saved to separately stored cross-sectional data. Data that has been updated before the last day of the target month (data to be saved) is extracted, and the data associated with the target is updated to the cross-sectional data. Note that this is executed automatically on the scheduled execution date set in the master, but it can also be executed manually if the scheduled execution date has arrived.

In the example shown in Figure 1, based on the settings in the management master before execution, cross-sectional real-time data is backed up as end-of-month data under the conditions of execution date "2022/10/5", target month "2022/9", and backed-up data retention period "2 months". For end-of-month data, the cross-sectional data for July is deleted and the cross-sectional data for September is added. After execution, the management master is updated.

In Figure 2, the financial data processing device of this embodiment executes utilization processing. Since end-of-month data is stored separately, it can be referenced at any time and utilized for analysis and collaboration. Because the data is consolidated monthly, it is also possible to build processes based on information as of the end of the month, such as batch processing executed monthly.

In the example shown in Figure 2, the utilization process refers to the end-of-month data in various processes, for example (1) extracting it using specified extraction conditions in the data extraction process and outputting it as a file for internal analysis, (2) linking it to external systems on a monthly basis, or (3) utilizing it as the source data for monthly data.

The financial data processing device of this embodiment can be widely applied to businesses that can introduce SLNs (loan management SLNs, installment management SLNs, etc.).

2. Configuration
3 is a block diagram showing an example of the configuration of a financial data processing device 100 according to this embodiment. In FIG. 3, financial data processing device 100 comprises a control unit 102, a communication interface unit 104, a memory unit 106, and an input/output interface unit 108. Each unit of financial data processing device 100 is connected to each other so as to be able to communicate via any communication path.

The communication interface unit 104 communicatively connects the financial data processing device 100 to the network 300 via a communication device such as a router and a wired or wireless communication line such as a dedicated line. The communication interface unit 104 has the function of communicating data with other devices via a communication line. Here, the network 300 has the function of connecting the financial data processing device 100 and the server 200 so that they can communicate with each other, and is, for example, the Internet or a LAN (Local Area Network).

An input device 112 and an output device 114 are connected to the input/output interface unit 108. The output device 114 may be a monitor (including a home television), a speaker, or a printer. The input device 112 may be a keyboard, a mouse, a microphone, or a monitor that functions as a pointing device in conjunction with a mouse. Note that, below, the output device 114 may be referred to as the monitor 114.

The storage unit 106 stores various databases, tables, files, and the like. The storage unit 106 also stores computer programs that work in conjunction with the OS (Operating System) to issue commands to the CPU (Central Processing Unit) to perform various processes. The storage unit 106 can be, for example, a memory device such as RAM (Random Access Memory) or ROM (Read Only Memory), a fixed disk device such as a hard disk, a flexible disk, or an optical disk.

The memory unit 106 includes a management master 106a, a data table 106b, and a backup table 106c.

The management master 106a is a master that sets the conditions for executing month-end closing processing, and can be composed of a table that associates and registers the target year and month, next execution date, execution date, and number of months to retain (see Figure 5 (A)).

Data table 106b is a table for storing real-time financial data.

The backup table 106c is a table for storing end-of-month data. The end-of-month data may include fields for backup information (target year and month, execution date) and fields for real-time data.

The control unit 102 is a CPU or the like that provides overall control of the financial data processing device 100. The control unit 102 has internal memory for storing control programs such as an OS, programs that define various processing procedures, and required data, and performs various information processing operations based on these stored programs.

The control unit 102 is configured to be able to access the management master 106a, data table 106b, backup table 106c, etc. stored in the memory unit 106. Note that the management master 106a, data table 106b, and backup table 106c may be provided in another location (e.g., server 200) as long as they are accessible by the control unit 102.

Functionally, the control unit 102 comprises a data update unit 102a, a month-end closing processing unit 102b, a data processing unit 102c, and a screen display control unit 102d.

The data update unit 102a updates the real-time data in the data table 106b in real time.

The month-end closing processing unit 102b executes month-end closing processing to back up cross-sectional data of real-time data in the data table 106b to the backup table 106c as end-of-month data. During this month-end closing processing, on the next execution date of the management master 106a, data from the number of months before the end-of-month data retention period in the management master 106a is deleted, and cross-sectional data extracted from real-time data updated before the end of the month of the target year and month in the management master 106a is added.

When adding cross-sectional data, the month-end closing processing unit 102b may recalculate the necessary items at that time.

After performing the month-end closing process, the month-end closing processing unit 102b may update the target year and month of the management master 106a to the next month, and may also update the next execution date to the next month + the execution date of the management master 106a.

The real-time data may include debt data, debt transaction data, general debt data, customer information data, general customer data, repayment schedule data, collection performance data, or customer bank information data. In this case, the month-end closing processing unit 102b saves each of the debt data, debt transaction data, general debt data, customer information data, general customer data, repayment schedule data, collection performance data, or customer bank information data as month-end data.

Credit card data is data that stores credit card number, product code, contract date, number of months in arrears, number of days in arrears, etc. Credit card transaction data is data that stores credit card number, history, transaction, amount received, balance, etc. General credit card data is data that stores general items linked to credit cards (e.g., general character 1, general character 2, etc., general number 1, etc., general date 1, etc.). Customer information data is data that stores data related to customers (e.g., name, kana name, date of birth, etc.).

General customer data is data that holds general items linked to customers (e.g., general character 1, general character 2, ... general number 1 ... general date 1 ... etc.). Scheduled repayment data is data that holds repayment dates and repayment amounts linked to receivables (e.g., scheduled repayment date, repayment amount ... etc.). Collection performance data is data that holds actual collection (repayment) performance linked to scheduled repayment data (e.g., scheduled repayment date, scheduled repayment amount, actual repayment amount ... etc.). Customer bank information data is data that holds information about bank accounts used by customers (e.g., bank code, branch code, account number ... etc.).

The data processing unit 102c executes the utilization process described above and performs various processes on the end-of-month data stored in the backup table 106c, such as data extraction processing, linking with external systems, and monthly data creation processing.

The screen display control unit 102d controls the display of various screens and the acceptance of inputs on the monitor 114.

3. Specific Examples
1 to 7, a specific example of month-end closing processing executed by month-end closing processing unit 102b of control unit 102 of financial data processing device 100 in this embodiment will be described.

(Execution screen)
The month-end closing processing unit 102b automatically executes month-end closing processing on the next execution date set in the management master 106a, but manual execution is also possible if the scheduled execution date has arrived. Figure 4 is a diagram showing an example of the display of the month-end closing processing execution screen. When the operator specifies the target month for this month on the month-end closing processing execution screen and presses the execute button, the month-end closing processing unit 102b executes month-end closing processing. The month-end closing processing execution screen displays the progress of the processing.

(Details of end-of-month closing process)
The month-end closing process will be described in detail with reference to Figure 5. Figure 5 is a diagram for explaining the details of the month-end closing process. The month-end closing processing unit 102b executes month-end closing process to save cross-sectional data of real-time data in the data table 106b to the save table 106c as month-end data, and in this month-end closing process, on the next execution date of the management master 106a, data of the month-end data older than the number of months retained in the management master 106a is deleted, and cross-sectional data extracted from real-time data updated before the end of the month of the target year and month of the management master 106a is added.

Here, we will explain the case where the September 2022 amount is executed on October 5, 2022, based on the pre-execution management master 106a.

Figure 5 (A) is a diagram showing an example of data in the management master 106a. The management master 106a has fields for the target year and month, next execution date, execution date, and number of months to retain. In the example shown in the figure, the target year and month are set to "202209," the next execution date to "2022/10/5," the execution date to "5," and the number of months to retain to "2."

S1: Delete data older than the retention date of the management master 106a.
In this example, the retention period is set to "2" (two months' worth of data is retained), so data for the last month of the month that is not two months prior to the current target month will be deleted. In this example, two months' worth of data, 202209 and 202208, will be retained, so data prior to 202207 will be deleted.

Figure 5 (C) shows an example of end-of-month data. End-of-month data is in a data format that adds items for the target year and month and execution date to the real-time data items. As shown in Figure 5 (D), the cross-sectional data for July in the end-of-month data will be deleted.

S2: Save the data as of the end of the target month.
Real-time data updated before the end of the month is extracted, and any necessary items are recalculated at that time, and added to the end-of-month data to update it. In this example, the target year and month is 202209, so the target end of the month is 2022/9/30.

Figure 5 (E) is a diagram showing an example of real-time data. The real-time data includes fields such as credit number, product code, contract date, number of months in arrears, and number of days in arrears. Items with update times up to the end of the target month (September 30, 2022) are extracted.

Figure 5 (F) shows an example of end-of-month data. End-of-month data is in a data format that adds items for evacuation information (target year and month, execution date) to real-time data items (bond number, product code, contract date, number of months overdue, number of days overdue).

For example, the real-time "number of days overdue" is calculated when a transaction such as a deposit or extraction of overdue data occurs. In this example, the deposit was not made on the scheduled date of 7/25/2022, leaving the transaction in a delinquent state. On 9/15/2022, overdue extraction was performed, and the real-time data was updated to the number of days overdue of "52 days." Therefore, by recalculating again on 9/30/2022, the correct cross-sectional data for that time is updated to "67 days."

S3: Update the status of the management master 106a for the next execution.
The "target year and month" in the management master 106a is updated to the next month, and the "next execution date" is updated to the date of the next month plus the execution date. Figure 5 (B) is a diagram showing an example of the management master 106a after the update. As shown in the figure, the target year and month has been updated from "202209" to "202210," and the "next execution date" has been updated from "2022/10/5" to "2022/11/5."

(Data image 1)
A data image of month-end closing processing when real-time data is used as bond data will be described with reference to Figure 6. Figure 6 is a diagram for explaining a data image of month-end closing processing when real-time data is used as bond data. Here, a case where September 2022 is executed on October 5, 2022 based on the pre-execution management master 106a will be described.

Figure 6 (A) shows an example of the management master 106a before processing is executed, and Figure 6 (B) shows an example of the management master 106a after processing is executed. After month-end closing processing, the management master 106a is updated to the next target year, month, and execution date, as shown in Figure 6 (B).

Figure 6 (C) is a diagram showing an example of real-time data (bond data) before processing is executed. Figure 6 (D) is a diagram showing an example of real-time data (bond data) after processing is executed. The real-time data (bond data) includes fields for bond number, product code, contract date, number of months overdue, and number of days overdue.

As shown in Figure 6 (D), real-time data (receivables data) is not updated during month-end closing processing.

Figure 6 (E) is a diagram showing an example of end-of-month data before processing is executed. Figure 6 (F) is a diagram showing an example of end-of-month data before processing is executed. The end-of-month data includes fields for the target year and month, execution date, and real-time data (bond data) fields (bond number, product code, contract date, number of months overdue, and number of days overdue).

As shown in Figure 6 (F), when the month-end closing process is executed, the end-of-month data is deleted from the July cross-sectional data and added to the September cross-sectional data.

For example, real-time "delinquency information" is calculated when a transaction such as a deposit or the extraction of delinquent data occurs. In this example, the deposit was not made on the scheduled date of 7/25/2022, resulting in a delinquent status. On 9/15/2022, delinquency extraction was performed, and the real-time data was updated to the number of days delinquent "52 days." Therefore, by recalculating again on 9/30/2022, the correct cross-sectional data for that time is updated to "67 days."

Data that becomes eligible between the end of the previous target month (August 2022) and the end of this target month (September 2022) will be added to the backup target. Data after the end of the current target month will not be included.

(Data image 2)
A data image of month-end closing processing when real-time data is used as bond transaction data will be explained with reference to Figure 7. Figure 7 is a diagram for explaining a data image of month-end closing processing when real-time data is used as bond transaction data. Here, a case where September 2022 is executed on October 5, 2022 based on the pre-execution management master 106a will be explained. An example of data in the management master 106a is the same as that in Figure 6.

Figure 7 (A) is a diagram showing an example of real-time data (bond transaction data) before processing is executed. Figure 7 (B) is a diagram showing an example of real-time data (bond transaction data) after processing is executed. The real-time data (bond transaction data) includes the following fields: bond number, history, transaction, deposit amount, and balance.

As shown in Figure 7 (B), real-time data (bond transaction data) is not updated during month-end closing processing.

Figure 7 (C) is a diagram showing an example of end-of-month data before processing is executed. Figure 7 (D) is a diagram showing an example of end-of-month data after processing is executed. The end-of-month data includes fields for the target year and month, execution date, and real-time data (bond transaction data) fields (bond number, history, transaction, deposit amount, and balance).

As shown in Figure 7 (F), when the month-end closing process is executed, the end-of-month data is deleted from the July cross-sectional data and added to the September cross-sectional data.

Data that becomes eligible between the end of the previous target month (August 2022) and the end of this target month (September 2022) will be added to the backup target. Data after the end of the current target month will not be included.

As explained above, this embodiment uses a management master 106a in which the target year and month, next execution date, and number of months to be retained are set, and a month-end closing process is executed in which cross-sectional data of real-time financial data is saved as end-of-month data in a save table 106c. During this month-end closing process, on the next execution date of the management master 106a, data older than the number of months retained in the management master 106a is deleted, and cross-sectional data extracted from real-time data updated before the end of the month of the target year and month of the management master 106a is added. Therefore, it is possible to automatically save cross-sectional data of real-time financial data that is updated daily using a simple method.

[4. Contribution to the United Nations-led Sustainable Development Goals (SDGs)]
This embodiment can contribute to improving business efficiency and promoting appropriate management decisions by companies, thereby contributing to the achievement of SDGs Goals 8 and 9.

Furthermore, this embodiment can contribute to reducing waste and promoting paperless and electronic systems, thereby contributing to SDGs goals 12, 13, and 15.

Furthermore, this embodiment can contribute to strengthening control and governance, thereby contributing to Goal 16 of the SDGs.

5. Other Embodiments
The present invention may be implemented in various different embodiments other than those described above within the scope of the technical concept set forth in the claims.

For example, among the processes described in the embodiments, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically using known methods.

In addition, the processing procedures, control procedures, specific names, registered data for each process, information including parameters such as search conditions, screen examples, and database configurations shown in this specification and drawings may be changed as desired unless otherwise specified.

Furthermore, with regard to the financial data processing device 100, the components shown in the figure are functional concepts and do not necessarily have to be physically configured as shown.

For example, all or any part of the processing functions of the financial data processing device 100, particularly the processing functions performed by the control unit, may be implemented by a CPU and a program interpreted and executed by the CPU, or may be implemented as hardware using wired logic. The program is recorded on a non-transitory, computer-readable recording medium containing programmed instructions for causing the information processing device to execute the processes described in this embodiment, and is mechanically read by the financial data processing device 100 as needed. That is, a computer program is recorded in a storage unit such as a ROM or HDD (Hard Disk Drive) that works with the OS to issue commands to the CPU and perform various processes. This computer program is executed by being loaded into RAM, and works with the CPU to form the control unit.

In addition, this computer program may be stored on an application program server connected to the financial data processing device 100 via any network, and all or part of it may be downloaded as needed.

In addition, the program for executing the processing described in this embodiment may be stored on a non-temporary computer-readable recording medium, or may be configured as a program product. Here, this "recording medium" includes memory cards, USB (Universal Serial Bus) memories, SD (Secure Digital) cards, flexible disks, magneto-optical disks, ROMs, EPROMs (Erasable Programmable Read Only Memory), EEPROMs (registered trademark) (Electrically Erasable and Programmable Read Only Memory), CD-ROMs (Compact Disk Read Only Memory), MOs (Magneto-Optical disks), DVDs (Digital Versatile Disks), and more. This includes any "portable physical media" such as a Blu-ray Disc (registered trademark) and a Blu-ray (registered trademark) Disc.

A "program" is a data processing method written in any language or description method, and may be in any format, such as source code or binary code. It should be noted that a "program" is not necessarily limited to a single structure, but also includes a distributed structure consisting of multiple modules or libraries, or a structure that achieves its function by working in conjunction with a separate program, such as an OS. The specific structure and reading procedure for reading a recording medium in each device shown in the embodiments, as well as the installation procedure after reading, can use well-known structures and procedures.

The various databases stored in the memory unit are storage devices such as memory devices such as RAM and ROM, fixed disk devices such as hard disks, flexible disks, and optical disks, and store various programs, tables, databases, and web page files used for various processes and website provision.

Furthermore, the financial data processing device 100 may be configured as an information processing device such as a known personal computer or workstation, or may be configured as such an information processing device to which any peripheral device is connected. Furthermore, the financial data processing device 100 may be realized by installing software (including programs or data, etc.) that causes the device to perform the processing described in this embodiment.

Furthermore, the specific form of distribution and integration of the devices is not limited to that shown in the figures, and all or part of them can be functionally or physically distributed and integrated in any unit depending on various additions or functional loads. In other words, the above-mentioned embodiments may be implemented in any combination, or embodiments may be implemented selectively.

REFERENCE SIGNS LIST 100 Financial data processing device 102 Control unit 102a Data update unit 102b Month-end closing processing unit 102c Data processing unit 102d Screen display control unit 104 Communication interface unit 106 Storage unit 106a Management master 106b Data table 106c Save table 108 Input/output interface unit 112 Input device 114 Output device 300 Network

Claims (5)

A financial data processing device having a control unit,
The control unit
The management master with the target year and month, next execution date, and retention period set,
Real-time data on financial information updated daily , including the date and time of the update ,
a save table for extracting cross-sectional data from the real-time data and saving end-of-month data obtained by adding items of the target year and month and the next execution date of the management master to the extracted cross-sectional data ;
It is configured to be accessible to
A financial data processing device characterized by comprising a month-end closing processing means for extracting cross-sectional data of real-time data updated before the end of the month of the target year and month of the management master on the next execution date of the management master, adding the end-of-month data of the extracted cross-sectional data to the save table, and deleting the end-of-month data prior to the number of months held by the management master from the save table on the next execution date of the management master. The management master further includes an execution date set therein,
The financial data processing device according to claim 1, characterized in that, after executing the month-end closing processing, the month and year in the management master are updated to the next month, and the next execution date is updated to the next month plus the execution date of the management master. The financial data processing device of claim 1, characterized in that the real-time data includes bond data, bond transaction data, general bond data, customer information data, general customer data, repayment schedule data, collection performance data, or customer bank information data. A financial data processing method executed by an information processing device having a control unit, comprising:
The control unit
The management master with the target year and month, next execution date, and retention period set,
Real-time data on financial information updated daily , including the date and time of the update ,
a save table for extracting cross-sectional data from the real-time data and saving end-of-month data obtained by adding items of the target year/month and execution date of the management master to the extracted cross-sectional data ;
It is configured to be accessible to
The control unit executes
A financial data processing method characterized by including a month-end closing processing step for extracting cross-sectional data of real-time data updated before the end of the month of the target year and month of the management master on the next execution date of the management master, adding the end-of-month data of the extracted cross-sectional data to the backup table, and performing month-end closing processing to delete the end-of-month data prior to the number of months retained by the management master from the backup table. A financial data processing program to be executed by an information processing device having a control unit,
The control unit
The management master with the target year and month, next execution date, and retention period set,
Real-time data on financial information updated daily , including the date and time of the update ,
a save table for extracting cross-sectional data from the real-time data and saving end-of-month data obtained by adding items of the target year/month and execution date of the management master to the extracted cross-sectional data ;
It is configured to be accessible to
The control unit
A financial data processing program for executing a month-end closing processing step that extracts cross-sectional data of real-time data updated before the end of the month of the target year and month of the management master on the next execution date of the management master, adds the end-of-month data of the extracted cross-sectional data to the backup table, and performs month-end closing processing that deletes end-of-month data from the backup table prior to the number of months the management master is retained.