Financial data processing device, financial data processing method, and financial data processing program

Abstract

To automatically save, by a simple method, cross-sectional data of real-time data related to finance that is updated daily.SOLUTION: A financial data processing apparatus of the present embodiment comprises month-end settlement processing means that executes month-end settlement processing of saving, in a saving table, a management master in which a target year and month, the next execution date, and the number of months of holding are set, the saving table, and cross-sectional data of real-time data related to finance, as month-end data, and in the month-end settlement processing, deletes data before the number of months of holding in the management master as the month-end data at the next execution date in the management master, and adds cross-sectional data obtained by extracting the real-time data updated before the month-end date of the target year and month in the management master.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present invention relates to a financial data processing device, a financial data processing method, and a financial data processing program. [Background technology]

[0002] For example, in the credit management business in the financial industry (for example, credit, financing), it is necessary to manage information such as debtors, contracts, daily transactions, etc. Conventionally, a system relating to credit management business is disclosed in, for example, Patent Document 1. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2015-14857 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the above-mentioned Patent Document 1 does not disclose anything about a simple method for automatically saving cross-sectional data of real-time financial data that is updated daily.

[0005] 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 are capable of automatically saving cross-sectional data of real-time financial data that is updated daily using a simple method. [Means for solving the problem]

[0006] In order to solve the above-mentioned problems and achieve the object, the present invention is a financial data 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, real-time financial data that is updated daily, and a backup table, and is characterized in that the control unit executes a month-end closing process in which cross-sectional data of the real-time data is saved in the backup table as end-of-month data, and in the month-end closing process, the control unit is equipped with a month-end closing processing means 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 that was updated before the end of the month of the target year and month of the management master.

[0007] According to another aspect of the present invention, when the cross-sectional data is added, the month-end closing processing means may recalculate necessary items at that time.

[0008] According to one aspect of the present invention, the management master may further include an execution date, and the month-end closing processing means may update the target year and month of the management master to the next month after executing the month-end closing processing, and may also update the next execution date to the next month plus the date of the execution date of the management master.

[0009] 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.

[0010] In addition, in order to solve the above-mentioned problems and achieve the object, 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, real-time financial data that is updated daily, and an evacuation table, and wherein the control unit executes a month-end closing process in which cross-sectional data of the real-time data is saved to the evacuation 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 that was updated before the end of the month of the target year and month of the management master.

[0011] According to one 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 number of months to be retained are set, real-time financial data that is updated daily, and a backup table, and the control unit executes a month-end closing process in which cross-sectional data of 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, data from the end-of-month data prior to the number of months retained in the management master 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 is added. [Effects of the Invention]

[0012] According to the present invention, it is possible to automatically save cross-sectional data of real-time financial data that is updated daily using a simple method. [Brief explanation of the drawings]

[0013] [Figure 1] FIG. 1 is a diagram for explaining the month-end closing process executed by the financial data processing device of this embodiment. [Figure 2] FIG. 2 is a diagram for explaining the utilization process executed by the financial data processing device of this embodiment. [Figure 3] FIG. 3 is a block diagram showing an example of the configuration of a financial data processing device according to this embodiment. [Figure 4] FIG. 4 is a diagram showing an example of a display screen for performing month-end closing processing. [Figure 5] FIG. 5 is a diagram for explaining the details of the month-end closing process. [Figure 6] FIG. 6 is a diagram for explaining a data image of month-end closing processing when real-time data is used as credit data. [Figure 7] 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. DETAILED DESCRIPTION OF THE INVENTION

[0014] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described in detail with reference to the accompanying drawings. However, the present invention is not limited to the embodiment.

[0015] [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 constantly updated as transactions take place daily (e.g., daily deposit information, overdue information, contract changes, attribute information changes, etc.).

[0016] 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 with having to obtain the data on the same day, as the data changes depending on the transaction, the number of days overdue changes depending on the date, etc. For example, if you want to see 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.

[0017] Therefore, in this embodiment, a system is provided that can automatically save cross-sectional data of real-time financial data (also called "time-series data") that is updated daily, using a simple method.

[0018] 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 refer to the correct cross-sectional information calculated using the same logic as a normal business program later, regardless of the timing of the operation.

[0019] 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 past data is also stored, it can be used in combination (simplifying data analysis).

[0020] 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.

[0021] 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 linked to 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 manual execution is also possible if the scheduled execution date has arrived.

[0022] In the example shown in Figure 1, based on the settings of the management master before execution, cross-sectional data of 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, cross-sectional data for July is deleted and cross-sectional data for September is added. After execution, the management master is updated.

[0023] In Figure 2, the financial data processing device of this embodiment executes utilization processing. Since the end-of-month data is stored separately, it can be referenced at any time and utilized for analysis or linkage. Since the data is consolidated monthly, it is also possible to build processes based on the information as of the end of the month, such as batch processing executed monthly.

[0024] 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 in-house analysis, (2) linking it to an external system on a monthly basis, or (3) utilizing it as the source data for monthly data.

[0025] The financial data processing device of this embodiment is widely applicable to businesses that can introduce SLNs (loan management SLNs, installment management SLNs, etc.), for example.

[0026] [2. Configuration] Figure 3 is a block diagram showing an example of the configuration of financial data processing device 100 according to this embodiment. In Figure 3, financial data processing device 100 comprises control unit 102, communication interface unit 104, memory unit 106, and input / output interface unit 108. Each unit of financial data processing device 100 is connected to each other so that they can communicate with each other via any communication path.

[0027] 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 exchanging data with other devices via the 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).

[0028] 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 cooperation with a mouse. Note that hereinafter, the output device 114 may be referred to as the monitor 114.

[0029] Various databases, tables, files, etc. are stored in the storage unit 106. Computer programs that work in conjunction with an OS (Operating System) to issue commands to a CPU (Central Processing Unit) to perform various processes are recorded in the storage unit 106. The storage unit 106 can be, for example, a memory device such as a RAM (Random Access Memory) or a ROM (Read Only Memory), a fixed disk device such as a hard disk, a flexible disk, an optical disk, etc.

[0030] The storage unit 106 includes a management master 106a, a data table 106b, and a save table 106c.

[0031] The management master 106a is a master that sets the conditions for executing the month-end closing process, and can be configured as a table that associates and registers the target year and month, the next execution date, the execution date, and the number of months to retain (see Figure 5(A)).

[0032] The data table 106b is a table for storing real-time financial data.

[0033] The save table 106c is a table for storing end-of-month data. The end-of-month data may include items for save information (target year and month, execution date) and items for real-time data.

[0034] Control unit 102 is a CPU or the like that provides overall control of financial data processing device 100. Control unit 102 has an internal memory for storing control programs such as an OS, programs that define various processing procedures, and required data, and executes various information processing operations based on these stored programs.

[0035] The control unit 102 is configured to be able to access the management master 106a, the data table 106b, the save table 106c, etc. stored in the storage unit 106. The management master 106a, the data table 106b, and the save table 106c may be provided in another location (for example, the server 200) as long as the control unit 102 is able to access them.

[0036] The control unit 102 conceptually includes a data updating unit 102a, a month-end closing processing unit 102b, a data processing unit 102c, and a screen display control unit 102d.

[0037] The data update unit 102a updates the real-time data in the data table 106b in real time.

[0038] The month-end closing processing unit 102b executes month-end closing processing to save the cross-sectional data of the real-time data in the data table 106b to the save table 106c as month-end data, and in this month-end closing processing, on the next execution date of the management master 106a, data older than the number of months retained in the management master 106a for month-end data 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.

[0039] When adding cross-sectional data, the month-end closing processing unit 102b may recalculate necessary items at that time.

[0040] After executing the month-end closing process, the month-end closing processing unit 102b may update the target year and month in the management master 106a to the next month, and may also update the next execution date to the next month plus the execution date of the management master 106a.

[0041] The real-time data may include bond data, bond transaction data, general-purpose bond data, customer information data, general-purpose customer data, repayment schedule data, collection performance data, or customer bank information data. In this case, the month-end closing processing unit 102b saves the bond data, bond transaction data, general-purpose bond data, customer information data, general-purpose customer data, repayment schedule data, collection performance data, or customer bank information data as month-end data.

[0042] Credit data is data that holds credit number, product code, contract date, number of months in arrears, number of days in arrears, etc. Credit transaction data is data that holds credit number, history, transaction, amount received, balance, etc. General credit data is data that holds general items linked to credit (for example, general character 1, general character 2..., general number 1..., general date 1..., etc.). Customer information data is data that holds data about customers (for example, name, kana name, date of birth..., etc.).

[0043] General customer data is data that holds general items linked to customers (for example, General Character 1, General Character 2, ... General Number 1 ... General Date 1 ..., etc.). Scheduled repayment data is data that holds the repayment date and repayment amount linked to the receivable (for example, scheduled repayment date, repayment amount, etc.). Collection record data is data that holds the actual collection (repayment) record linked to the scheduled repayment data (for example, scheduled repayment date, scheduled repayment amount, actual repayment amount, etc.). Customer bank information data is data that holds information about the bank account used by the customer (for example, bank code, branch code, account number, etc.).

[0044] The data processing unit 102c executes the above-mentioned utilization process, and performs various processes on the end-of-month data stored in the save table 106c, such as data extraction process, linkage process with external systems, and monthly data creation process.

[0045] The screen display control unit 102d controls the display of various screens displayed on the monitor 114 and the reception of inputs.

[0046] [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.

[0047] (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.

[0048] (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 process unit 102b executes month-end closing process to save the cross-sectional data of the 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 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.

[0049] Here, a case will be described in which the September 2022 amount is executed on October 5, 2022 based on the pre-execution management master 106a.

[0050] 5A 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, the next execution date, the execution date, and the 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."

[0051] S1: Delete data older than the retention date of the management master 106a. In this example, the retention period is set to "2" (setting to retain two months' worth of data), so data for the last month of the month not exceeding two months prior to the target year and month will be deleted. In this example, data for the two months of 202209 and 202208 will be retained, so data prior to 202207 will be deleted.

[0052] Figure 5(C) is a diagram showing 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 is deleted.

[0053] S2: Back up the data as of the end of the month. Extract real-time data updated before the target end of the month, recalculate necessary items at that time, and add and update them to the end-of-month data. In this example, the target year and month is 202209, so the target end of the month is 2022 / 9 / 30.

[0054] 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. Targets with update times up to the end of the target month (September 30, 2022) are extracted.

[0055] Figure 5(F) shows an example of end-of-month data. The end-of-month data is in a data format that adds items for evacuation information (target year and month, execution date) to the items of real-time data (bond number, product code, contract date, number of months overdue, number of days overdue).

[0056] For example, the real-time "number of days past due" is calculated when a transaction such as a deposit or extraction of past due data occurs. In this example, the deposit was not received on the scheduled date of 7 / 25 / 2022, leaving the item in a past due state. The past due extraction is performed on 9 / 15 / 2022, and the real-time data is updated to the number of days past due of "52 days." Therefore, by recalculating again on 9 / 30 / 2022, the correct cross-sectional data for that time is updated to "67 days."

[0057] S3: Update the status of the management master 106a for the next execution. The "target year and month" of 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."

[0058] (Data Image 1) A data image of month-end closing processing when real-time data is used as bond data will be explained 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, we will explain the case where September 2022 is executed on October 5, 2022 based on the pre-execution management master 106a.

[0059] Fig. 6(A) is a diagram showing an example of the management master 106a before the processing is executed, and Fig. 6(B) is a diagram showing an example of the management master 106a after the processing is executed. After the month-end closing processing, the management master 106a is updated to the next target year, month, and execution date, as shown in Fig. 6(B).

[0060] 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) has fields for bond number, product code, contract date, number of months in arrears, and number of days in arrears.

[0061] As shown in FIG. 6(D), real-time data (credit data) is not updated during month-end closing processing.

[0062] 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 has 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 in arrears, and number of days in arrears).

[0063] As shown in FIG. 6(F), when the month-end closing process is executed, the cross-sectional data for July is deleted from the end-of-month data, and the cross-sectional data for September is added.

[0064] For example, real-time "delinquency information" is calculated when a transaction such as a deposit or delinquent data extraction occurs. In this example, the payment was not received on the scheduled date of 7 / 25 / 2022, leaving the payment in a delinquent state. On 9 / 15 / 2022, delinquency 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 will be updated to "67 days."

[0065] Data newly added 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.

[0066] (Data image 2) With reference to Figure 7, we will explain the data image of month-end closing processing when real-time data is used as bond transaction data. Figure 7 is a diagram for explaining the data image of month-end closing processing when real-time data is used as bond transaction data. Here, we will explain the case where the September 2022 amount is executed on October 5, 2022 based on the management master 106a before execution. The data example of the management master 106a is the same as that of Figure 6.

[0067] 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) has the following fields: bond number, history, transaction, deposit amount, and balance.

[0068] As shown in FIG. 7(B), real-time data (bond transaction data) is not updated during month-end closing processing.

[0069] Figure 7(C) is a diagram showing an example of month-end data before processing is executed. Figure 7(D) is a diagram showing an example of month-end data after processing is executed. The month-end 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).

[0070] As shown in FIG. 7(F), when the month-end closing process is executed, the cross-sectional data for July is deleted from the end-of-month data, and the cross-sectional data for September is added.

[0071] Data newly added 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.

[0072] As explained above, according to this embodiment, a management master 106a is provided in which the target year and month, the next execution date, and the 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. In 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 for the end-of-month data 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.

[0073] [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.

[0074] Furthermore, this embodiment can contribute to reducing waste and promoting paperless and electronic systems, thereby contributing to the achievement of SDGs Goals 12, 13, and 15.

[0075] Furthermore, this embodiment can contribute to strengthening control and governance, which can contribute to the achievement of Goal 16 of the SDGs.

[0076] 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.

[0077] 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.

[0078] Furthermore, the processing procedures, control procedures, specific names, information including parameters such as registered data and search conditions for each process, screen examples, and database configurations shown in this specification and drawings can be changed as desired unless otherwise specified.

[0079] Furthermore, with regard to financial data processing device 100, the components shown in the figures are functional concepts, and do not necessarily have to be physically configured as shown in the figures.

[0080] For example, all or any part of the processing functions of 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 financial data processing device 100 as needed. That is, a computer program for issuing instructions to the CPU in cooperation with the OS and performing various processes is recorded in a storage unit such as a ROM or HDD (Hard Disk Drive). This computer program is executed by being loaded into RAM, and cooperates with the CPU to form the control unit.

[0081] This computer program may also be stored in an application program server connected to financial data processing device 100 via any network, and all or part of it may be downloaded as needed.

[0082] Furthermore, the program for executing the processes described in this embodiment may be stored in a non-transitory computer-readable recording medium or configured as a program product. Here, the term "recording medium" includes any "portable physical medium" such as a memory card, a Universal Serial Bus (USB) memory, a Secure Digital (SD) card, a flexible disk, a magneto-optical disk, a ROM, an Erasable Programmable Read Only Memory (EPROM), an Electrically Erasable and Programmable Read Only Memory (EEPROM (registered trademark)), a Compact Disk Read Only Memory (CD-ROM), a Magneto-Optical disk (MO), a Digital Versatile Disk (DVD), and a Blu-ray (registered trademark) disc.

[0083] Furthermore, a "program" is a data processing method written in any language or description method, regardless of the format, such as source code or binary code. Note that a "program" is not necessarily limited to a single structure, but also includes a structure that is distributed as multiple modules or libraries, or a structure that achieves its function by cooperating with a separate program, such as an OS. Note that the specific configuration 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 configurations and procedures.

[0084] The various databases stored in the memory unit are storage means 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 providing websites.

[0085] Furthermore, 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 connected to any peripheral device. Furthermore, financial data processing device 100 may be realized by installing software (including programs or data, etc.) that causes such device to perform the processing described in this embodiment.

[0086] Furthermore, the specific form of distribution and integration of the devices is not limited to that shown in the drawings, and all or part of them can be configured by functionally or physically distributing and integrating them in any unit depending on various additions or functional loads. In other words, the above-described embodiments can be implemented in any combination, or embodiments can be implemented selectively. [Explanation of symbols]

[0087] 100 Financial data processing device 102 Control section 102a Data update section 102b Month-end closing processing section 102c Data processing section 102d Screen display control unit 104 Communication interface unit 106 Storage section 106a Management Master 106b Data Table 106c Evacuation Table 108 Input / Output Interface Section 112 Input Device 114 Output Device 300 Network

Claims

1. 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 month-end data of the extracted cross-sectional data to the save table, and deleting the month-end 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.

2. 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.

3. 2. The financial data processing device according to claim 1, wherein 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.

4. 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 the 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.

5. 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 the 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.

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