JP6641059B1 - Borrowing information prediction and financing information providing device, borrowing information prediction and financing information providing device control method, borrowing information prediction and financing information providing program - Google Patents

Abstract

An object of the present invention is to provide a borrowing information prediction and funding information providing device that can automatically provide future borrowing prediction information and the like to a user only by inputting transaction information of a financial institution or the like. A financial institution transaction information storage unit that stores financial institution transaction information, and a borrowing related item information generation process that extracts borrowing related item information from the financial institution transaction information and stores the borrowing related item information storage unit in a borrowing related item information storage unit. Unit 33, and a borrowing overall calculation basic information generation processing unit 42 that generates the borrowing overall calculation basic information 43 based on the borrowing related item information, and predicts the entire borrowing information based on the borrowing overall calculation basic information. Borrowing information prediction and financing information providing device 1 generated by using [Selection] Fig. 9

Description

  The present invention automatically generates future borrowing prediction information, and also provides a borrowing information prediction and financing information providing device that automatically generates future financing information from financial institution transaction information, for example, and provides borrowing information prediction and financing information provision The present invention relates to an apparatus control method and a borrowing information prediction and funding information providing program.

Conventionally, there has been proposed a business management support system or the like in which an accounting department or the like of a company or the like can create specific financial statements in accordance with a medium- to long-term plan by simulating the company's future profit and loss statement. I have.
Conventionally, there has been proposed a business management system or the like that allows an accounting department or the like of a company or the like to simulate the company's future profit and loss statement or the like (for example, Patent Document 1).

JP-A-2006-14053

However, such a business management support system, etc., is a system capable of preparing specific future financial statements only when a person having accounting knowledge or the like inputs necessary data for predetermined items. Therefore, there is a problem that it is not easy to use for a manager of a small store or the like.
In addition, the above-described simulation device is a device in which future profit and loss statement data is generated only when a person having accounting knowledge or the like inputs necessary data for a predetermined item or the like, There is a problem that it is not easy to use for managers of small stores and the like.

  Therefore, the present invention can automatically provide a user with prediction information of future borrowing, etc., simply by inputting transaction information of a financial institution or the like, and can provide the user with transaction information of a financial institution, etc. Borrowing information forecasting and financing information providing device that can automatically provide users with financing information such as future profit and loss statement information simply by inputting The purpose of the present invention is to provide a forecast and cash flow information providing program.

  The object of the present invention is to provide a financial institution transaction information storage unit that stores financial institution transaction information, and a borrowing method that extracts borrowing-related item information from the financial institution transaction information and stores the borrowing-related item information storage unit in the borrowing-related item information storage unit. A related item information generation processing unit, and a borrowing entire operation basic information generation processing unit that generates borrowing entire operation basic information based on the borrowing related item information; Information processing unit for predicting and generating information, and storing the item information of the financial institution transaction information in the form of a withdrawal item and a deposit item belonging to a profit and loss account, and storing the deposit item and the deposit item. A cash-in / pay-out item prediction information generation processing unit that generates cash-in / pay-out item prediction information in which future payment or payment is predicted based on the information of the pay-in / out item, and a cash flow based on the cash-in / payout item prediction information. And a display unit for displaying the funding prediction information, wherein at least a part of the deposit / withdrawal item prediction information includes the withdrawal item information and / or the Borrowing information characterized in that the borrowing information is trend information with fluctuation information obtained by adding the fluctuation information of the corresponding month to prediction information generated based on the trend information obtained by removing monthly unique fluctuation information from the payment item information. This is achieved by the prediction and funding information providing device.

According to the above configuration, a financial institution transaction information storage unit (for example, a passbook data storage unit) that stores financial institution transaction information (for example, passbook data) is provided.
Therefore, for example, financial institution transaction information such as passbook data can be stored.
In the above-described configuration, borrowing-related item information such as repayment amount data and interest data is extracted from financial institution transaction information and stored in a borrowing-related item information storage unit (for example, a repayment amount data storage unit and an interest data storage unit). be able to.
Further, in the above configuration, based on the borrowing-related item information (for example, repayment amount data and interest data), the basic borrowing calculation basic information such as annual interest rate data, remaining debt amount data, and remaining repayment period data is generated. be able to.
For this reason, when the deposit / withdrawal item prediction information is the trend information with fluctuation information, the prediction is information that takes into account both the tendency of the change of the entire data and the peculiar fluctuation information of the month or the like. It becomes high deposit / withdrawal item prediction information.

Therefore, based on the basic information on the entire borrowing calculation such as annual interest rate data, remaining debt data, and remaining repayment period data, the total borrowing amount, the repayment amount of each month, and the entire borrowing information such as the repayment period are accurately predicted. Can be generated.
Furthermore, such borrowing entire information can be automatically generated from financial institution transaction information such as passbook data, so that a user or the like such as a manager of a small store or the like can use the device with extremely high usability.

Further, according to the above configuration, item information (for example, deposit / withdrawal, summary, etc.) is converted from financial institution transaction information (for example, passbook data, etc.) to a withdrawal item (for example, personnel cost, fixed cost, etc.) belonging to the income statement. Expenses, variable expenses, repayments, etc.) and deposit items (for example, sales etc.), automatically memorize them, and based on the information of the deposit items and withdrawal items, withdrawal or withdrawal expected to be paid in the future. Gold item prediction information (for example, future labor cost data) can also be automatically generated.
Then, based on the cash-in / pay-out item forecast information, cash-out forecast information (for example, profit and loss statement information, etc.) is generated, and the cash-out forecast information is displayed on the display unit. Can be obtained easily and without trouble.
Further, according to the above configuration, at least a part of the deposit / withdrawal item prediction information includes tendency information (for example, seasonal index or the like) obtained by removing monthly unique fluctuation information (for example, seasonal index) from the withdrawal item information and / or the deposit item information. For example, it is trend information-added trend information (for example, a seasonally adjusted future trend value or the like) in which prediction information generated based on a seasonal variation-removed trend value or the like and the corresponding month's variation information are added.
For this reason, when the deposit / withdrawal item prediction information is the trend information with fluctuation information, the prediction is information that takes into account both the tendency of the change of the entire data and the peculiar fluctuation information of the month or the like. It becomes high deposit / withdrawal item prediction information.

Preferably, it generates warning information on the financial predicted due to variations in the borrowing Nyuzen body information, and outputting.

According to the configuration, warning information about the funds are expected due to variations of refunding Nyuzen body information, for example, it is possible to generate information alerts such that the fluctuations in the share of each bank has occurred, outputs Therefore, it is possible to appropriately notify the user that such a situation will occur.

  Preferably, the borrowing-related item information includes repayment amount information and interest information, the borrowing overall calculation basic information includes annual interest rate information, remaining debt amount information, and remaining repayment period information, and the borrowing overall information includes borrowing information. It is characterized by including amount information of the entire amount, repayment amount information of each month, and repayment period information.

According to the configuration, it is possible to generate the entire borrowing calculation basic information including the annual interest rate information, the remaining debt amount information, and the remaining repayment period information from the borrowing-related item information including the repayment amount information and the interest information.
Then, from the basic borrowing calculation basic information, the entire borrowing information including the total borrowing amount information, the repayment amount information of each month, and the repayment period information can be generated, so that future borrowing information can be accurately predicted. it can.

  Preferably, at least a part of the deposit / withdrawal item prediction information is generated based on moving average processed tendency information obtained by moving average processing of the trend information.

According to the configuration, at least a part of the deposit / withdrawal item prediction information is moving average processed trend information (for example, for the first three months) obtained by performing moving average processing on trend information (for example, a trend value after removing seasonal fluctuations). Is generated based on the moving average value.
By using the trend information as the moving average processed trend information as a result of the moving average process, the tendency of the change of the entire data can be easily grasped, and the prediction accuracy is improved.

  Preferably, at least a part of the deposit / withdrawal item prediction information is generated based on the overlapped moving average processed tendency information obtained by further performing the moving average processing on the moving average processed tendency information.

According to the above configuration, the moving average processed tendency information (for example, the second three-month moving average value) is further subjected to the moving average processing to the overlapping moving average processed tendency information (for example, the second future trend value or the like). Generated based on
Therefore, it becomes easier to grasp the tendency of the change of the entire data, and the prediction accuracy is further improved.

  Preferably, based on the cash flow prediction information, a warning about a possible increase in demand for funds is output.

  According to the above configuration, a warning regarding an increase in the demand for funds that may occur in the future is output based on the cash flow prediction information. For example, an increase in the demand for funds such as a shortage of a deposit amount or an increase in working capital is predicted. Then, a warning is output and the user is notified.

The object is, in the present invention, storing financial institution transaction information in a financial institution transaction information storage unit, extracting borrowing-related item information from the financial institution transaction information, and storing in the borrowing-related item information storage unit, Based on the borrowing-related item information, borrowing overall calculation basic information is generated, and borrowing overall information is predicted and generated based on the borrowing overall calculation basic information. the item information of the transaction information, and stores the classified into dispensing items and deposit items belonging to the income table, receipt and payment items prediction information generating unit of the equipment is based on the deposited item and information of the dispensing items The cash-out forecast information generation processing unit of the device generates cash-out forecast information based on the cash-in / out item prediction information, and generates cash-out forecast information. Display of The cash flow forecast information is displayed, and at least a part of the deposit / withdrawal item forecast information is based on tendency information obtained by removing monthly unique fluctuation information from the payout item information and / or the deposit item information. This is achieved by a method of controlling a borrowing information prediction and funding information providing apparatus, characterized in that the fluctuation information of a corresponding month is added to the generated prediction information to make the trend information with fluctuation information.

  The object of the present invention is to provide a borrowing information prediction and funding information providing device with a function of storing financial institution transaction information in a financial institution transaction information storage unit, and extracting borrowing related item information from the financial institution transaction information. Function to store the borrowing related item information storage unit based on the borrowing related item information, a function to generate the entire borrowing calculation basic information based on the borrowing related item information, and a function to predict and generate the entire borrowing information based on the borrowing whole calculation basic information A function of storing the item information of the financial institution transaction information in the form of a withdrawal item and a deposit item belonging to a profit and loss statement, and based on the information on the deposit item and the withdrawal item, a future withdrawal or deposit A function of generating forecasted cash-in / pay-out item prediction information, a function of generating cash-out forecast information based on the cash-in / payout item forecast information, and displaying the cash-out forecast information on a display unit No., at least a part of the deposit / withdrawal item prediction information is based on the withdrawal item information and / or the prediction information generated based on the tendency information obtained by removing monthly unique fluctuation information from the deposit item information, This is achieved by a program for providing borrowing information prediction and funding information, wherein a function of adding the fluctuation information of the corresponding month to make trend information with fluctuation information is executed.

  As described above, according to the present invention, it is possible to automatically provide future borrowing prediction information and the like to a user only by the user inputting transaction information of a financial institution or the like. Borrowing information forecasting and financing information providing device that can automatically provide users with financing information such as future profit and loss statement information simply by inputting transaction information such as There is an advantage that a method and a borrowing information forecasting and funding information providing program can be provided.

It is a schematic diagram showing the appearance of the “borrowing information prediction and funding information providing device” according to the embodiment of the present invention. FIG. 2 is a schematic diagram showing a main configuration of a “borrowing information prediction device” portion of the “borrowing information prediction and funding information providing device body” in FIG. 1. FIG. 3 is a schematic block diagram illustrating a main configuration of “first various information storage units 30” to “third various information storage units 50”. FIG. 3 is a schematic block diagram illustrating a main configuration of a first various information storage unit. FIG. 9 is a schematic block diagram illustrating a main configuration of a second various information storage unit. It is a schematic block diagram which shows the main structures of a 3rd various information storage part. It is a schematic flowchart which shows the main operation examples etc. of the borrowing information prediction apparatus 1. It is another schematic flowchart which shows the main operation examples etc. of the borrowing information prediction apparatus 1. It is a schematic explanatory view showing the amount of the entire borrowing amount, which is the entire borrowing information, and information such as the repayment amount and the repayment period of each month. It is the schematic which shows the main structures of the "financing information provision apparatus" part of the "borrowing information prediction and funding information provision apparatus main body" of FIG. FIG. 21 is a schematic block diagram illustrating a main configuration of an “eleventh various information storage unit”. FIG. 35 is a schematic block diagram illustrating a main configuration of a “twelfth various information storage units”. It is a general | schematic block diagram which shows the main structures of "the 13th various information storage part." FIG. 39 is a schematic block diagram illustrating a main configuration of a “fourteenth various information storage units”. FIG. 39 is a schematic block diagram illustrating a main configuration of a “fifteenth various information storage units”. "It is a schematic block diagram showing a main configuration of a sixteenth various information storage unit. FIG. 12 is a schematic explanatory diagram showing a part of “passbook data” stored in a “passbook data storage” in FIG. 11. It is a schematic flowchart which shows a "future sales data" generation process. It is another schematic flowchart which shows a "future sales data" generation process. It is explanatory drawing regarding sales information. FIG. 14 is a schematic explanatory diagram illustrating “seasonal index data” stored in a “seasonal index data storage unit” in FIG. 13. FIG. 9 is a schematic explanatory view showing a characteristic portion of the second embodiment. It is the graph which compared monthly change of "trim average value" and "2nd three-month moving average value."

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings and the like.
Note that the embodiments described below are preferred specific examples of the present invention, and therefore, various technically preferable limitations are added. However, the scope of the present invention particularly limits the present invention in the following description. It is not limited to these embodiments unless otherwise stated.

FIG. 1 is a schematic diagram illustrating an appearance of a “borrowing information prediction and funding information providing device 1” according to an embodiment of the present invention.
As shown in FIG. 1, the present apparatus 1 includes a borrowing information prediction and funding information providing apparatus main body 10, a “display 21” for displaying various information as a display unit, a “keyboard 22” and a “mouse 23” for inputting various information. "Is provided.
Further, the borrowing information prediction and funding information providing apparatus main body 10 includes various data input units 13 for receiving an information recording medium such as a CD and acquiring the data thereof.

  The devices 10 and the like of the “borrowing information prediction and funding information providing device 1” in FIG. 1 are computers, such as a CPU (Central Processing Unit), a RAM (Random Access Memory), a ROM (Read Only Memory), and a hard disk. And are connected via a bus.

  The “borrowing information prediction and financing information providing device 1” according to the present embodiment includes a portion as a “borrowing information prediction device” and a portion as a “borrowing information providing device”. This will be described below in detail by dividing into a portion and a “financing information providing device” portion.

(About "borrowing information prediction device")
By inserting a CD or the like in which a program or the like relating to “borrowing information prediction” according to the present invention is inserted into the various data input units 13 of the present apparatus 1 shown in FIG. 1 ".
Further, the program or the like relating to “borrowing information prediction” according to the present invention may be obtained by the device 1 by wireless communication other than a CD or the like, and may be stored in the borrowing information prediction and funding information providing device body 10 in advance. It does not matter.

FIG. 2 is a schematic diagram showing a main configuration of a “borrowing information prediction device” portion of the “borrowing information prediction and funding information providing device body 10” in FIG.
As shown in FIG. 1, the “borrowing information prediction device” portion of the main body 10 includes a control unit 11. The control unit 11 includes a communication device 12 for communicating with an external device such as a display 21 and various data. The input unit 13 is controlled.
The display 21, the keyboard 22, and the mouse 23 are communicably connected to the communication device 12.
Further, the control unit 11 also controls the first various data storage units 30, the second various data storage units 40, and the third various data storage units 50 shown in FIG.

  FIGS. 3 to 5 are schematic block diagrams showing main configurations of the “first various information storage units 30” to “third various information storage units 50”, respectively. These contents will be described later.

Hereinafter, an operation example of the “borrowing information prediction device” of the “borrowing information prediction and funding information providing device 1” according to the present embodiment will be described.
In the present embodiment, the manager of the company A inputs the bankbook information, which is the financial institution transaction information of the company A, for example, to the “borrowing information prediction device and the funding information providing device 1” in FIG. The following describes an example of grasping the future borrowing status and receiving various alerts.

FIG. 7 and FIG. 8 are schematic flowcharts showing main operation examples and the like of the “borrowing information prediction device” portion of the borrowing information prediction and funding information providing device 1.
Hereinafter, description will be given along the flowcharts of FIGS. 7 and 8.

First, the manager of the company A stores the passbook data of the company A in, for example, a CD or the like, via the “various data storage unit 13” of the “borrowing information prediction and funding information providing apparatus main body 10” in FIG. input.
Then, the passbook data is stored in, for example, the “passbook data storage unit 31” which is the financial institution transaction information storage unit of FIG. 3 of the “borrowing information prediction and funding information providing device main body 10”.

FIG. 6 is a schematic explanatory diagram showing a part of, for example, “passbook data 31a” which is the financial institution transaction information stored in the “passbook data storage unit 31” in FIG.
As shown in FIG. 6, the passbook data 31a includes item information of the financial institution transaction information of the passbook of the company A, for example, the date of deposit / withdrawal, the distinction of deposit or withdrawal, their summary, the amount, and the like. include.

Next, the process proceeds to step (hereinafter referred to as “ST”) 1. In ST1, the borrowing-related item information generation processing unit, for example, the repayment amount determination processing unit (program) 33 in FIG. 3 operates and refers to the “repayment amount display data storage unit 32” in FIG.
In the repayment amount display data storage unit 32, “predetermined repayment amount display data” is stored. For example, "borrowing", "calling", "financing", "Yushi", "certificate lending", "show loan", "certificate lending", "show cash", "bill lending", "Tagataka Shitsuke", "hand lending" , "Tegashi", names of financial institutions, etc. are stored in advance as "predetermined repayment amount display data".

  The storage unit 32 also stores information indicating that when the display data such as these words includes “excluded display data” such as “interest”, it is not determined to be “repayment amount”. .

  Accordingly, the processing unit 33 determines whether or not the display data (text) of the “summary” of the “passbook data 31a” in FIGS. 3 and 6 corresponds to the predetermined repayment amount display data in FIG. If applicable, the borrowing-related item information is determined to be, for example, “repayment amount” data, and the borrowing-related item information storage unit is associated with the withdrawal date data, for example, “repayment amount” in FIG. The data is stored in the data storage unit 34 ".

Next, the process proceeds to ST2. In ST2, the borrowing-related item information generation processing unit, for example, the interest determination processing unit (program) 36 in FIG. 3 operates, and the display data (text) of “Summary” of the “passbook data 31a” in FIGS. 3 and 6. Is the predetermined interest display data stored in the “interest display data storage unit 35” in FIG. 3, for example, “interest” or the like.
Then, if applicable, it is determined as borrowing-related item information, for example, “interest” data, and is associated with the withdrawal date data, and the borrowing-related item information storage unit, for example, “interest data storage” in FIG. Section 37 ".

As described above, the borrowing information prediction and financing information providing device 1 can acquire “repayment amount data”, which is monthly repayment (borrowing) data, and monthly interest data.
Next, from the monthly “repayment amount data” and the monthly “interest data”, the total borrowing calculation information required for the borrowing forecast, for example, “one year interest rate data”, “remaining debt amount data” and “remaining debt amount data” Repayment period data ”is generated.

Then, the process proceeds to ST3. In ST3, "one-year interest rate data" is generated. More specifically, the borrowing entire calculation basic information generation processing unit, for example, the “annual interest rate data generation processing unit (program) 42” in FIG. 4 operates and is stored in the “annual interest rate data operation storage unit 41” in FIG. Refer to the following equation.
That is, “annual interest rate data = (interest amount in n month−interest amount in n + 1 month) ÷ (repayment amount in n + 1 month) × 12”.

Then, the processing unit (program) 42 refers to the “repayment data storage unit 34” in FIG. 3 and obtains the “repayment amount in n + 1 month”, for example, the repayment amount in March “6,000 yen”. And assign.
Also, referring to the “interest data storage unit 37” in FIG. 3, “interest amount in (n + 1) month” and “interest amount in n month”, for example, interest amount in March (290 yen) and interest amount in February ( 295 yen) and substitute it.
Then, “annual interest rate data” is obtained and stored in the “annual interest rate data storage unit 43” of FIG.

In the above example, {(interest amount in February (295 yen)) − (interest amount in March (290 yen))}
(March repayment amount (6000 yen)) × 12, the annual interest rate data becomes “1%”, and this “1%” is stored in the “annual interest rate data storage section 43”.

  In the present embodiment, the interest rate per month is calculated and simply multiplied by 12. However, the present invention is not limited to this, and “365 (or 366) ÷ the date from the previous repayment date to the current repayment date It may be calculated as "number of days" (if the end of the month is a holiday, it will be repaid on the previous business day, so it can be calculated strictly in cooperation with the calendar function).

Next, the process proceeds to ST4. In ST4, the “n + 1 month remaining debt amount”, for example, the March remaining debt amount is generated. Specifically, for example, the “remaining bond amount data generation processing unit (program) 45” of FIG. 4 which is the basic information processing unit of the entire borrowing operation operates, and the “remaining bond amount data calculation storage unit 44” of FIG. Refer to the stored equation below.
That is, “(n + 1 month remaining debt) = (n + 1 month interest) ÷ ｛(n month interest−n + 1 month interest) ÷ (n + 1 month repayment) 済.

Then, the processing unit (program) 45 obtains, for example, the repayment amount of “n + 1 month”, for example, the repayment amount of “6,000 yen” in March from the “repayment amount data storage unit 34” in FIG. substitute.
Also, referring to the “interest data storage unit 37” in FIG. 3, “interest amount in (n + 1) month” and “interest amount in n month”, for example, interest amount in March (290 yen) and interest amount in February ( 295 yen) and substitute it.
Then, “March remaining bond amount annual interest rate data” is obtained and stored in the “Remaining bond amount data storage unit 46” in FIG.

  In the above example, the amount of interest in March (290 yen) ÷ ｛(the amount of interest in February (295 yen) -the amount of interest in March (290 yen)) ÷ the amount of repayment in March (6000 yen)｝ , "The amount of remaining bonds in March" is "348,000 yen".

Next, the process proceeds to ST5. In ST5, “remaining repayment period data” of the borrowed money is generated.
Specifically, for example, the “remaining repayment period data generation processing unit (program) 51” in FIG. 5 which is the borrowing entire calculation basic information processing unit operates, and the “remaining repayment period data operation storage unit 47” in FIG. The following equation stored in "."
That is, “(n + 1 month remaining debt) 額 (n + 1 month repayment)”.

Then, the processing unit (program) 51 acquires, for example, the repayment amount of “348,000 yen” in March, which is “the remaining bond amount in the (n + 1) month”, from the “remaining bond amount data storage unit” in FIG. ,substitute.
Also, for example, the repayment amount of “n + 1 month”, for example, the repayment amount of “6,000 yen” in March is acquired from the “repayment amount data storage unit 34” in FIG.
Then, “remaining repayment period data” is obtained and stored in “remaining repayment period data storage unit 52” in FIG.

  In the above example, “the amount of remaining bonds in March (348,000 yen) ÷ the amount of repayment in March (6,000 yen)”, and the “remaining repayment period data” is “58 months”.

As described above, “annual interest rate (interest rate) data”, “remaining bond amount data”, and “remaining repayment period data” can be generated.
Therefore, based on these information, information such as the total amount of borrowing in the case of equal repayment of principal, which accounts for the majority of corporate loans, the amount of repayment in each month, the repayment period, etc. can be obtained as shown in FIG. .
Further, as shown in FIG. 9, it is possible to grasp the payment status of the interest rate of the borrowed money.
FIG. 9 is a schematic explanatory diagram showing the amount of the entire borrowed amount, which is the entire borrowed amount information, and information such as the repayment amount and repayment period of each month.

As shown in FIG. 9, the borrowing information prediction and funding information providing device 1 accurately obtains the entire borrowing information without acquiring the borrowing content from the user only by acquiring the user's passbook data 31 a. be able to.
In particular, since the entire borrowing information can be automatically generated from the passbook data 31a and the like, the borrowing information prediction and funding information providing device 1 according to the present embodiment is used by managers of small-scale stores and the like. Is extremely convenient for the user.

  Next, the borrowing information prediction and funding information providing apparatus 1 is warning information on funds predicted based on a change in the entire borrowing information based on the user's “all borrowing information” acquired in the above-described process. For example, the following alerts are generated as needed and displayed on the display 21 to notify the user.

(Alert alerts you to changes in the borrowing share of each bank with which your company A is trading)
As shown in FIG. 9, the borrowing information prediction and financing information providing device 1 can grasp the borrowing amount and the repayment status of the A company, so that the current and future Information such as the amount of repayment can be obtained.
Therefore, the borrowing information prediction and funding information providing apparatus 1 displays the borrowing amount and the borrowing balance of each bank with which the company is trading on the display 21 or the like, and when the borrowing amount is biased to a specific bank. Is configured so that an alert can be displayed on the display 21 or the like.

  The manager or the like of the company A who visually recognizes the alert can know beforehand that the borrowed amount of the company is biased to a specific bank, and that borrowing from another bank may become difficult in the future.

(Remaining debt of borrowed money and alert on monthly sales)
The borrowing information forecasting and funding information providing device 1 determines whether the remaining debt of the borrowing of the company A is less than or equal to 1 time compared to the monthly business of the A company based on the information in FIG. In this case, an alert is output to the display 21 or the like when it becomes necessary to raise funds.

  That is, as described above, the borrowing information prediction and funding information providing device 1 compares the “remaining debt amount” of the company A obtained by calculation with the sales data acquired separately, and determines that the “remaining debt” is “monthly”. When it is determined that the value is less than or equal to 1 times the quotient, it is determined that there is a high possibility that a shortage of funds will occur in the near future, and an alert is output to the display 21 or the like.

  Therefore, even a manager of Company A who is busy with his daily work and cannot check the accounting information can be informed in advance that there is a possibility of a shortage of funds in the near future.

(Alert for required working capital and borrowed debt)
The borrowing information prediction and financing information providing device 1 calculates “required working capital comparison” data, and when the remaining debt of the borrowed money falls short, determines that financing is necessary, and outputs an alert to the display 21 or the like. .
Here, the “required working capital comparison” data refers to funds for purchasing and selling products, collecting the products, and compensating for a time lag from when payment is made.
The “required working capital comparison” data tends to increase when the sales of the company A are increasing. In the present embodiment, the borrowing information prediction and financing information providing device 1 determines that the remaining debt of the borrowing of the company A is When it is determined that the number of remaining debts exceeds a predetermined range by comparison, an alert is output to the display 21 or the like, indicating that there is a need for sound funding.

  Therefore, even a manager of Company A who is busy with his daily work and cannot check the accounting information can be informed in advance that there is a possibility of a shortage of funds in the near future.

  Next, the portion of the "borrowing information and funding information providing device 1" as the "financing information providing device" will be described in detail below.

("1st Embodiment" about the part as "financing information providing apparatus")
The “borrowing information prediction and funding information providing apparatus main body 10” shown in FIG. 1 includes various data input units 13 for receiving an information recording medium such as a CD and acquiring the data.

Therefore, by inserting a CD or the like in which a program related to “financing information provision” is stored in the various data input units 13 of the present apparatus 1 shown in FIG. 1 and reading the data, “borrowing information prediction and funding information provision It functions as "the device 1".
Further, the program or the like relating to “financing information provision” may be acquired by the device 1 by wireless communication other than a CD or the like, or may be stored in the borrowing information prediction and funding information providing device body 10 in advance. Absent.

FIG. 10 is a schematic diagram showing a main configuration of the “borrowing information prediction and funding information providing device body 10” of the “borrowing information prediction and funding information providing device 1” in FIG.
As shown in FIG. 1, the main body 10 includes a control unit 111, and the control unit 111 controls a communication device 12 for communicating with an external device such as a display 21 and various data input units 13. ing.
The display 21, the keyboard 22, and the mouse 23 are communicably connected to the communication device 12.
Further, the control unit 111 includes an eleventh various data storage unit 130, a twelfth various data storage unit 140, a thirteenth various data storage unit 150, a fourteenth various data storage unit 160, and a fifteenth various data storage unit 130 illustrated in FIG. The various data storage unit 170 and the sixteenth various data storage unit 180 are also controlled.

  FIGS. 11 to 16 are schematic block diagrams showing main configurations of the “eleventh various information storage units 130” to “the sixteenth various information storage units 180”, respectively. These contents will be described later.

Hereinafter, an operation example of the “financing information providing device” portion of the “borrowing information prediction and funding information providing device 1” according to the present embodiment will be described.
In the present embodiment, the manager of the company A inputs the bankbook transaction information of the company A, for example, passbook data to the “borrowing information prediction and funding information providing device 1” in FIG. In the future, for example, the following description will be given by taking an example of grasping the funding situation (lack of funds, etc.) in the next month.

First, the manager of the company A stores the passbook data of the company A in, for example, a CD or the like, via the “various data storage unit 13” of the “borrowing information prediction and funding information providing apparatus main body 10” in FIG. input.
Then, the passbook data is stored in, for example, the "passbook data storage unit 131" which is the financial institution transaction information storage unit of FIG. 11 of the "borrowing information prediction and funding information providing apparatus body 10".

FIG. 17 is a schematic explanatory diagram showing a part of “passbook data 131a” stored in “passbook data storage 131” in FIG.
As shown in FIG. 17, the passbook data 131a includes item information of the financial institution transaction information of the passbook of the company A, for example, the date of deposit / withdrawal, the distinction of deposit or withdrawal, their summary, the amount, and the like. include.

The present apparatus 1 classifies and stores, from the passbook data 131a, withdrawal items to which a past profit and loss statement or the like belongs, for example, "past labor cost", "past fixed cost", "past variable cost", "past repayment" and the like. At the same time, past payment items such as "past sales" are also stored separately.
In addition, based on these past labor costs, past fixed costs, past variable costs, past repayments, past sales, etc., in the future, for example, the next month's future labor costs, future fixed costs, future Predict expenses, future repayments, future sales, etc.
Hereinafter, each item will be described.

(About the “future labor cost data” generation process)
First, the “personnel cost judgment acquisition unit (program) 132” of FIG. 11 which is a deposit / withdrawal item information generation processing unit operates, and the transfer data from the company A to the individual is equal to or more than a predetermined number, and the date and time sunrise data exists. In the case of 17, the withdrawal data such as “salary” on May 25, 2017 is stored as “personnel cost” in the “past personnel cost data storage unit 133” in FIG.

  For example, in the passbook data 131a of FIG. 11, data such as "salary" of 40,000 yen in May, "salary" of 40,000 yen in June, and "salary" of 40,000 yen in July are referred to as "past person records". Cost data storage unit 133 ".

  Next, for example, the "future labor cost data generation processing unit (program) 134" of FIG. 11 which is a deposit / withdrawal item prediction information generation processing unit operates, and the data of the "past labor cost data storage unit 133" (for example, May) "40,000 yen", "40,000 yen" in June, "40,000 yen" in July, etc.), and an average value is obtained. For example, “future labor cost data” is generated and stored in the “future labor data storage unit 135” in FIG.

  For example, (40,000 yen (May) + 40,000 yen (June) + 40,000 yen (July)) / 3 = 40,000 yen (predicted value in August) The data is stored in the “future labor cost data storage unit 135” as “data”.

(About the "Fixed future cost data" generation process)
Next, the “future fixed cost data” generation process will be described below.
First, for example, the “fixed cost judgment acquisition unit (program) 136” which is a deposit / withdrawal item information generation processing unit of the “borrowing information prediction and funding information providing apparatus body 10” in FIG. A specific summary of the passbook data 131a in the "passbook data storage unit 131" (for example, "for n months of electricity") is determined as "fixed cost" by machine learning or the like, and the "past fixed cost data storage unit" in FIG. 137 ".

  For example, of the passbook data 131a in FIG. 17, 30,000 yen for “Electric May” in May, 36,000 yen for “Electric June” in June, and “Electric July” in July Is stored in the “previous fixed cost data storage unit 137”.

  Next, for example, a “future fixed cost data generation processing unit (program) 138” of FIG. 11 which is a deposit / withdrawal item prediction information generation processing unit operates, and data of the “past fixed cost data storage unit 137” of FIG. "30,000 yen" in May, "36,000 yen" in June, "30,000 yen" in July, etc.), and the average value is obtained. The “future fixed cost data” is generated and stored in the “future fixed cost data storage unit 141” in FIG.

  For example, (30,000 yen (May) + 36,000 yen (June) + 30,000 yen (July)) ÷ 3 = 32,000 yen (August forecast value) For example, the information is stored in the “future fixed cost data storage unit 141” as “future fixed cost data”.

(About the “Future variable cost data” generation process)
Next, the “future variable cost data” generation process will be described below.
First, for example, the “variable cost judgment acquisition unit (program) 142” which is a deposit / withdrawal item information generation processing unit of the “borrowing information prediction and funding information providing device main body 10” of FIG. Of the passbook data 131a of the passbook data storage unit 131, withdrawals other than fixed costs (however, excluding repayment of borrowings and loans) are set as "variable costs" and stored in the "past variable cost data storage unit 143" of FIG. I do.

  For example, in the passbook data 131a of FIG. 17, a total of 60,000 yen of 10,000 yen for "ka) carrot and 50,000 yen for" ka) cabbage for the month for May, and " Data such as “f) cabbage” 40,000 yen, and “f) carrot” 20,000 yen for July are stored in the “past variable cost data storage unit 143” in FIG. 12.

  Next, for example, a “future variable cost data generation processing unit (program) 144” in FIG. 12 which is a deposit / withdrawal item prediction information generation processing unit operates, and data in the “past variable cost data storage unit 143” in FIG. , "60,000 yen" in May, "40,000 yen" in June, "20,000 yen" in July, etc.), and the average value is obtained. “Future variable cost data” is generated and stored in the “future variable cost data storage unit 145” in FIG.

  For example, (60,000 yen (May) + 40,000 (June) + 20,000 yen (July)) ÷ 3 = 40,000 yen (August forecast value) For example, it is stored in the “future variable cost data storage unit 145” as “future variable cost data”.

(About the process of generating “future repayment data”)
Next, the “future repayment data” generation step will be described below.
First, for example, a “repayment determination acquisition unit (program) 146” which is a deposit / withdrawal item information generation processing unit of the “borrowing information prediction and funding information providing apparatus body 10” in FIG. 12 operates, and the passbook in FIG. 11 and FIG. In the payment column of the passbook data 131a of the data storage unit 131, the summary “repayment” data is stored in the “past repayment data storage unit 147” of FIG.

  For example, in the passbook data 131a of FIG. 17, data of 0 yen for May, 6,000 yen for June, 6,000 yen for July, etc. is stored in the “past repayment data storage unit 147” of FIG. To memorize.

  Next, for example, the “future repayment data generation processing unit (program) 148” of FIG. 12 which is a deposit / withdrawal item prediction information generation processing unit operates, and the data of the “past repayment data storage unit 147” of FIG. "0 yen" for the month, "6,000 yen" for June, "6,000 yen" for July, etc.), the repayment amount is determined to be the same as the previous month, and the "future repayment data" for August Is generated and stored in the “future repayment data storage unit 151” in FIG.

  For example, in the above example, since the previous month (July) is 6,000 yen, it is determined that August is also 6,000 yen, and 6,000 yen is used as the “future repayment data” of August in FIG. In the “future repayment data storage unit 51”.

(About the process of generating “future sales data”)
Next, a process of generating “future sales data” will be described below.
FIG. 18 and FIG. 19 are schematic flowcharts showing the “future sales data” generation process.
Hereinafter, the generation process of “future sales data” will be described with reference to the flowcharts of FIGS.
First, in ST11, for example, the “sales determination acquisition unit (program) 152” which is the deposit / withdrawal item information generation processing unit in FIG. 11 operates, and the passbook data 131a in the “passbook data storage unit 131” in FIGS. 11 and 17. , All payments other than “certificate loan” are set as “sales” and stored in the “past sales data storage unit 153” in FIG.

For example, in the passbook data 131a in FIG. 17, 70,000 yen for “ka) apple, 90,000 yen for“ ka) mandarin ”, and 100,000 yen for“ ka) banana ”for the month of May. Extract data.
In addition, data of 80,000 yen for “Ka) apple” and 110,000 yen for “Ka) orange” for June are extracted.
Then, as the data for July, data such as 80,000 yen for “ka) orange” and 90,000 yen for “ka) banana” are extracted and stored in the “past sales data storage unit 153” of FIG.

  Next, the process proceeds to ST12. In ST12, the “trim sales average value calculation processing unit (program) 154” in FIG. 13 operates, and removes the maximum value and the minimum value from the monthly sales data in the “past sales data storage unit 153” in FIG. Then, the average of the remaining sales values is obtained and stored in the “trim sales average value storage unit 155” of FIG.

FIG. 20 is an explanatory diagram related to sales information and the like.
The “trim average value” stored in the “trim average sales value storage unit 155” in FIG. 13 is calculated as shown in “trim average value” in FIG.
For example, as shown in FIG. 20, the average trim value in July 2016 is 178,000 yen, the average trim value in August is 224,000 yen, and the average trim value in September is 173,000 yen.

  As described above, in the present embodiment, the reliability of the average value can be improved by not including the abnormal value in the calculation of the average of the sales value for each month.

  Next, the process proceeds to ST13. In ST13, the “seasonal index data generation processing unit (program) 156” of FIG. 13 operates, and based on sales data such as monthly average trim values for a plurality of years in the past, for example, a seasonal index, (An index of change in sales in each month) is obtained and stored in the “seasonal index data storage unit 157” in FIG.

FIG. 21 is a schematic explanatory diagram showing “seasonal index data 157a” stored in “seasonal index data storage unit 157” of FIG.
As shown in FIG. 21, the seasonal index is, for example, “0.85” for the January seasonal index, “0.83” for the February seasonal index, and “0.89” for the March seasonal index. And the like, and the “fluctuation index” indicating the fluctuation tendency of the sales in the month is stored.

  Next, the process proceeds to ST14. In ST14, the “monthly trend value generation processing unit (program) 158” of FIG. 13 operates, and referring to the “trim sales average value storage unit 155” and the “seasonal index data storage unit 157” of FIG. By dividing the “trim average value” data by the “season index” of the corresponding month, a trend information, for example, “trend value after removing seasonal fluctuation” is obtained, and the “trend value storage unit 161” in FIG. To memorize.

As described above, by dividing the seasonal index by the monthly trim average value, the tendency value after removing the seasonal variation can be grasped.
For example, as shown in the example of FIG. 20, in July 2016, the average trim value is “178 thousand yen” and the seasonal index is “1.08”, so the “monthly trend value” of the sales is “165”. And August. “249”, September is “164”, etc., and these “monthly trend values” are stored in the “monthly trend value storage unit 161” in FIG.

Next, the process proceeds to ST15. In ST15, the “future trend value prediction data generation processing unit (program) 162” in FIG. 14 operates, and based on the “monthly trend value” in the “monthly trend value storage unit 161” in FIG. It is generated and stored in the “future tendency value storage unit 163” in FIG.
That is, in this step, for example, from the “monthly trend value after removing seasonal fluctuations” shown in FIG. 20, the future “monthly trend value”, for example, the “monthly trend value” of “August 2017” not yet stored in FIG. The trend value is predicted.

Specifically, in the example of FIG. 20, since the “monthly trend value” of July 2016 is “165” and the “monthly trend value” of August is “249”, it is changed from July to August. Is 1.5 times. For this reason, the “future trend value prediction data generation processing unit (program) 162” in FIG. 14 operates to “1.5 times” the monthly trend value “146” in July 2017, and The “future tendency value” “219” is obtained and stored in the “future tendency value storage unit 163” in FIG.
As a result, the “future tendency value” of August 2017 is predicted to be, for example, “219” and stored.
The “future trend value” is an example of “prediction information generated based on trend information”.

Next, the process proceeds to ST16. In ST16, the “seasonally adjusted future trend value generation processing unit (program) 164” of FIG. 14 operates, and the “future trend value (for example, August, 219)” of the “future trend value storage unit 163” of FIG. Is multiplied by the “seasonal index (for example, August, 0.9)” of the corresponding “seasonal index storage unit” to generate a “seasonally adjusted future tendency value storage unit”. 165 ".
That is, the “future trend value” obtained in ST15 merely indicates the trend value of the entire year, and does not take into account the fluctuation information unique to each month. Therefore, in this process, the seasonal index of the month is multiplied to obtain a monthly trend value in consideration of the seasonal index, thereby increasing the reliability of the numerical value.

  Specifically, “219” which is the “future trend value” in the above example is multiplied by the seasonal index “0.9” in August, and the trend information with fluctuation information, for example, “seasonally adjusted future trend” The value “197” as the “value” is obtained and stored in the “seasonally adjusted future tendency value storage unit 165” in FIG.

As described above, in the future, for example, in September 2017, the forecast value regarding withdrawal such as “future labor cost”, “future fixed cost”, “future variable cost”, “future repayment” and the like, and the “seasonal adjustment” The future tendency value ”is obtained and stored by the present apparatus 1.
Therefore, the “income statement” data for September 2017 is predicted in ST17 as follows.
In ST17, for example, the “financial income statement generation processing unit (program) 166” which is the funding prediction information generation processing unit in FIG. 14 operates, and the “future personnel cost data storage unit 135” in FIG. See “Future fixed cost data storage unit 141”, “Future variable cost data storage unit 145” in FIG. 12, “Future repayment data storage unit 151” in FIG. 13, and “Seasonally adjusted future trend value storage unit 165” in FIG. I do.

  The processing unit 166 stores “future personnel cost data” (August, 40,000 yen), “future fixed cost data” (August, 32,000 yen), “future variable costs” in the storage unit 135 and the like. For example, based on "data" (August, 40,000 yen), "future repayment data" (August, 6,000 yen), "seasonally adjusted future trend value" (August, 197,000 yen), etc. , For example, “Finance Profit and Loss Statement” data of August 2017, for example, “Future Profit and Loss Statement” data is generated and stored in “Future Profit and Loss Statement Storage Unit 167” in FIG.

As described above, the “income statement” data of, for example, August 2017 is generated and stored in the future.
The “income statement” data is a forecast data in which the forecast of the “sales” data is a forecast value in consideration of the annual trend value and the forecasted seasonal index of the month. Since the data takes into account both the unique seasonal indices such as the month, it is highly accurate prediction data.
In addition, by simply inputting passbook data etc., this “income statement” data is automatically classified into items such as “personnel costs”, “fixed costs”, “variable costs”, “repayment” and “sales”. The “finance statement” data, which is the future forecast, is also generated, so that the user can easily grasp the “financing status”.

Further, in the present embodiment, as described above, the “income statement” data of August 2017 is generated, and this “income statement” data can be displayed on the display 21 of FIG. 1 as necessary. it can. For this reason, the user can easily grasp the future funding situation and the like by visually checking the display 21.
Specifically, for example, the user can grasp in advance the shortage of the deposit in August 2017 and the like.

  In addition, in the present embodiment, as described above, since the future “income statement” data can be predicted, it is possible to output various alerts that are warnings about a possible increase in the demand for funds in the future. ing.

  The alerts of the present embodiment include a “first financing review alert”, a “second financing review alert”, and a “tax payment preparation alert”, and each of them will be described below.

(About the first financing review alert output process)
The “first financing examination alert generation processing unit (program) 171” in FIG. 15 operates and refers to the “future profit and loss statement storage unit 167” in FIG. 14 to predict the passbook within a set plurality of months. It is determined whether or not the amount is less than the set amount. If it is determined that the amount is less than the set amount, a “first financing consideration alert” is output to the display 21 or the like.
Therefore, when the estimated amount of the passbook is less than the set amount, an alert is output, so that the user can be made aware of the estimated amount.

(About the second financing review alert output process)
The “second financing examination alert generation processing unit (program) 172” of FIG. 15 operates to determine whether or not the withdrawal amount has exceeded the same month of the previous year for a plurality of consecutive months by referring to past withdrawal data and the like. If it exceeds, it is determined that the increased working capital needs are predicted, and a “second financing alert” is output to the display 21 or the like.
Therefore, when an increase in working capital needs is predicted, an alert is output, so that the user can be made aware of the prediction.

(About tax payment preparation alert output process)
The “tax payment preparation alert generation processing unit (program) 173” in FIG. 15 operates to determine whether or not the state where the amount of payment is smaller than the amount of payment has continued for a plurality of months by referring to the past payment data and payment data. , "Tax payment preparation alert" is output to the display 21 or the like.
Therefore, when the user needs to prepare for tax payment, an alert is output in advance.

For example, when the sales of the company increase, an increased working capital is generally required, and if no borrowing is performed, cash will decrease. For this reason, cash may run short at the timing of tax payment after that.
Therefore, in order to avoid such a situation, an alert is output to the effect that a cash flow plan in consideration of tax payment is required.

("Second embodiment" regarding the portion as "financing information providing device")
This embodiment is different from the first embodiment in that the “future tendency value” regarding the sales in the first embodiment is further processed. However, since many other configurations are common to the first embodiment, Hereinafter, differences will be mainly described, and configurations and the like common to the first embodiment will be denoted by the same reference numerals and the description thereof will be omitted.

In the first embodiment described above, the “monthly trend value” is obtained in ST14 of FIG. 18, and the “future trend value” is generated based on the “monthly trend value” in ST15. However, in this embodiment, There is a great difference in that a “three-month moving average” process is further performed twice (3 × 3 moving average) from the “monthly tendency value”, and then a “second future tendency value” is obtained.
The details will be described below.

First, ST11 to ST14 of FIG. 18 for generating future sales data are the same as those in the first embodiment.
Also, the method of calculating data on personnel expenses, fixed costs, variable costs, repayments, etc. relating to withdrawals is common to the first embodiment.
Hereinafter, the processing after the processing of ST14 is described.

In ST14 of FIG. 18, the “monthly trend value” after removing the seasonal variation is stored in the “monthly trend value storage unit 161” of FIG. 14, and then the “first three-month moving average processing unit (program) 174” of FIG. The “monthly trend value” of each month in the “monthly trend value storage unit 161” of FIG. 14 is added to the value of one month before and after that, divided by 3, and the “moving for the first three months” of that month is added. The “average value” is obtained and stored in the “first three-month moving average value storage unit 175” in FIG.
The “first three-month moving average value” is an example of the moving average processed tendency information.

FIG. 22 is a schematic explanatory view showing a characteristic portion of the second embodiment.
As shown in FIG. 22, by performing the “first three-month moving average” process on the monthly trend values, as shown in FIG. 22, “191” is given in July 2016, “193” is given in August, and September is given in FIG. Are “186” and the like, and these are “first moving average values”.

Next, the “second three-month moving average processing unit (program) 176” of FIG. 15 operates, and the “first three-month moving average value” of each month in the “first three-month moving average storage unit 175”. , And the values for the preceding and succeeding months are added and divided by 3 to obtain a “second three-month moving average value” for the month and store it in the “second three-month moving average value storage unit 177”.
Then, the “second moving average value” in FIG. 22 is obtained. That is, in the present embodiment, the “three-month moving average” is performed twice (3 × 3 moving average) to obtain a numerical value that makes it easy to grasp the overall tendency value.
The “second three-month moving average value” is an example of the overlapping moving average processed tendency information.

FIG. 23 is a graph comparing the monthly changes in the “trim average value” and the “second three-month moving average value”.
As shown in FIG. 23, by performing the “3 × 3 moving average” processing as in the present embodiment, the data becomes more easily grasped the tendency.

  Next, the “second future trend value prediction data generation processing unit (program) 181” in FIG. 16 operates, and the “second three-month moving average value storage unit 177” in FIG. Based on the “three-month moving average value”, a “second future tendency value” is generated and stored in the “second future tendency value storage unit 182” in FIG.

For example, the “second three-month moving average” from July to August 2016 changes from “183” to “190” in FIG. 22 and is about 1.04 times.
For this reason, the “second future trend value prediction data generation processing unit (program) 181” in FIG. 16 similarly multiplies “159” in July 2017 by 1.04 times, and calculates the expected sales value in August. Is calculated as “165”, and this value is stored in the “second future tendency value storage unit 182” as the “second future tendency value”.

  Next, the “second seasonally adjusted future trend value generation processing unit (program) 183” in FIG. 16 operates to correspond to the “second future trend value” in the “second future trend value storage unit 182”. The “seasonally adjusted second future trend value” is generated by multiplying the “seasonal index” of the “seasonal index storage unit 157” in FIG. 184 ".

For example, by multiplying the above-mentioned “165”, which is the “second future trend value”, by the seasonal index “0.9” in August, a “seasonally adjusted future trend value” (149) is obtained to be 149,000 yen. Is stored in the “seasonally adjusted second future trend value storage unit 184” in FIG. 16 as the “seasonally adjusted second future trend value” for August.
In this step, the predicted sales value is accurately estimated from both the trend value and the seasonal adjustment factor.

Next, a step of predicting the “income statement” is performed.
Specifically, the “second future profit and loss statement generation processing unit (program) 185” in FIG. 16 operates, and the “future personnel cost data storage unit 135” in FIG. 11 and the “future fixed cost data storage unit 135” in FIG. 12, “future variable cost data storage unit 145” in FIG. 12, “future repayment data storage unit 151” in FIG. 13, and “seasonally adjusted second future trend value storage unit 184” in FIG. 16.
Then, “future labor cost data” (August, 40,000 yen), “future fixed cost data” (August, 32,000 yen), “future variable cost data” (August, 40,000 yen), Based on the “future repayment data” (August, 6,000 yen) and the “seasonally adjusted second future trend value” (August, 149,000 yen), the “second future The “income statement” data is generated and stored in the “second future income statement storage unit 186” in FIG.

  As described above, in the present embodiment, unlike the first embodiment, the processing of “3 × 3 moving average” is added to calculate the expected value of sales, so that the present embodiment is different from the first embodiment. More irregular factors can be removed, and the determination can be made based on the leveled tendency value (second future tendency value).

The present invention is not limited to the above-described first and second embodiments, but includes the following configurations.
For example, when basic data such as passbook data is scarce and the seasonal index cannot be obtained by calculation, for example, when there is only data for one year, the above-mentioned “3-month moving average (data for one month before and after the month concerned) , A method of averaging data for three months before the month, a method of averaging data for three months after the month, etc.)).

Further, the “trend value” may be obtained by “3 × 3 moving average” in the second embodiment.
Further, even when there is missing data in the passbook data or the like, the configuration may be such that the “monthly trend value” or the like is obtained by supplementing the data with the above “3 month moving average” or “3 × 3 moving average”.

  In the present embodiment described above, the case where the present invention is realized as an apparatus has been described as an example. However, the present invention is not limited to this, and a magnetic disk (floppy (registered) (Trademark) disk, hard disk, etc.), optical disk (CD-ROM, DVD, etc.), magneto-optical disk (MO), semiconductor memory, and other storage media.

  The storage medium may be any storage medium that can store the program and that can be read by a computer. The storage format of the storage medium is not particularly limited.

  Also, an OS (Operating System) running on the computer based on an instruction of a program installed in the computer from the storage medium, MW (Middleware) such as database management software, network software, etc. realize the present embodiment. May be partially executed.

  Further, the storage medium in the present invention is not limited to a medium independent of a computer, but also includes a storage medium in which a program transmitted via a LAN, the Internet, or the like is downloaded and stored or temporarily stored.

  Further, the computer according to the present invention only needs to execute each processing in the present embodiment based on a program stored in a storage medium, and may be a device including one personal computer or the like, or a plurality of devices connected to a network. System or the like.

  Further, the computer in the present invention is not limited to a personal computer, but also includes an arithmetic processing unit, a microcomputer, and the like included in an information processing device, and is a general term for a device and a device capable of realizing the functions of the present invention by a program. ing.

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

DESCRIPTION OF SYMBOLS 1 ... Borrowing information prediction and financing information provision apparatus 10 ... Borrowing information prediction and financing information provision apparatus main body, 11 ... Control part, 12 ... Communication device, 13 ... Various data input parts, Reference numeral 21 ... display, 22 ... keyboard, 23 ... mouse, 30 ... first various data storage units, 31 ... passbook data storage unit, 31a ... passbook data, 32 ... Repayment amount display data storage unit, 33 ... Repayment amount judgment processing unit (program), 34 ... Repayment amount data storage unit, 35 ... Interest display data storage unit, 36 ... Interest judgment processing unit (program ), 37: interest data storage unit, 40: second various data storage unit, 41: annual interest data calculation storage unit, 42: annual interest data generation processing unit (program), 43 ..Annual interest rate data , 44 ... Remaining bond amount data calculation storage unit, 45 ... Remaining bond amount data generation processing unit (program), 46 ... Remaining bond amount data storage unit, 47 ... Remaining repayment period data calculation Storage unit, 50: third various data storage unit, 51: remaining repayment period data generation processing unit (program), 52: remaining repayment period data storage unit, 130: eleventh Various data storage units, 131: passbook data storage unit, 132: personnel cost judgment acquisition unit (program), 133: past personnel cost data storage unit, 134: future personnel cost data generation processing unit ( 135) Future personnel cost data storage unit, 136 ... Fixed cost judgment acquisition unit (program), 137 ... Past fixed cost data storage unit, 138 ... Future fixed cost data generation processing unit ( Program), 140 .. Twelfth various data storage units, 141 ... future fixed cost data storage unit, 142 ... variable cost judgment acquisition unit (program), 143 ... past variable cost data storage unit, 144 ... future Variable cost data generation processing unit (program), 145: future variable cost data storage unit, 146: repayment judgment acquisition unit (program), 147 ... past repayment data storage unit, 148 ... future repayment data Generation processing unit (program), 150: thirteenth various data storage unit, 151: future repayment data storage unit, 152: sales determination acquisition unit (program), 153: past sales data storage unit 154: Trim sales average value calculation processing unit (program), 155: Trim sales average value storage unit, 156 ... Seasonal index data generation processing unit (program), 157 ... Seasonal index data storage unit, 158: monthly trend value generation processing unit (program), 160: fourteenth various data storage unit, 161: monthly trend value storage unit, 162: future trend value prediction Data generation processing unit (program), 163: future trend value storage unit, 164: seasonal adjusted future trend value generation processing unit (program), 165: seasonally adjusted future trend value storage unit, 166 ..Future profit and loss statement generation processing unit (program), 167: future profit and loss statement storage unit, 170: fifteenth various data storage unit, 171: first financing examination alert generation processing unit (Program), 172: Second financing examination alert generation processing unit (program), 173: Tax payment preparation alert generation processing unit (program), 174: First three-month moving average Management unit (program), 175: first three-month moving average value storage unit, 176: second three-month moving average processing unit (program), 177: second three-month moving average value Storage unit, 180 ... 16th various data storage unit, 181: second future trend value prediction data generation processing unit (program), 182 ... second future trend value storage unit, 183 ... Second seasonally adjusted future trend value generation processing unit (program), 184: seasonally adjusted second future trend value storage unit, 185: second future income statement generation processing unit (program) , 186... Second future income statement storage unit.

Claims (8)

A financial institution transaction information storage unit for storing financial institution transaction information,
A borrowing related item information generation processing unit that extracts borrowing related item information from the financial institution transaction information and stores it in the borrowing related item information storage unit;
Based on the borrowing-related item information, a borrowing entire operation basic information generation processing unit that generates borrowing entire operation basic information,
Predicting and generating borrowing overall information based on the borrowing overall calculation basic information,
Based on the information of the deposit and withdrawal item information generation processing unit, which stores the item information of the financial institution transaction information as a withdrawal item and a deposit item belonging to a profit and loss calculation table, and the deposit item and the withdrawal item. A deposit / withdrawal item prediction information generation processing unit that generates deposit / withdrawal item prediction information in which future withdrawals or deposits are predicted, and a cash flow prediction information generation processing unit that generates funding prediction information based on the deposit / withdrawal item prediction information. And a display unit for displaying the cash flow forecast information, wherein at least a part of the deposit / withdrawal item forecast information is unique variation information for each month from the withdrawal item information and / or the deposit item information. A borrowing information prediction and funding information providing apparatus, characterized in that the information is trend information with fluctuation information obtained by adding the fluctuation information of a corresponding month to prediction information generated based on the tendency information from which the borrowing information has been removed. The borrowing generates warning information about the expected funds due to variations in Nyuzen body information, borrowing information prediction and financing information providing apparatus according to claim 1, characterized in that the output. The borrowing-related item information includes repayment amount information and interest information,
The borrowing total calculation basic information includes annual interest rate information, remaining debt amount information and remaining repayment period information,
3. The borrowing information prediction and funding information providing apparatus according to claim 1, wherein the borrowing entire information includes amount information of the entire borrowing amount, repayment amount information of each month, and repayment period information.   4. The method according to claim 1, wherein at least a part of the deposit / withdrawal item prediction information is generated based on moving average processed trend information obtained by performing a moving average process on the trend information. 5. The borrowing information prediction and cash flow information providing device described in the above.   The borrowing according to claim 4, wherein at least a part of the deposit / withdrawal item prediction information is generated based on the overlapped moving average processed tendency information obtained by further performing the moving average processing on the moving average processed tendency information. Information prediction and funding information providing device.   The borrowing information prediction and the financing information provision according to any one of claims 1 to 5, wherein a warning regarding a possible increase in the future funding demand is preferably output based on the financing prediction information. apparatus. The financial institution transaction information is stored in the financial institution transaction information storage unit,
Extracting borrowing-related item information from the financial institution transaction information and storing it in the borrowing-related item information storage unit;
Based on the borrowing related item information, generate borrowing entire calculation basic information,
Predicting and generating borrowing overall information based on the borrowing overall calculation basic information,
A deposit / withdrawal item information generation processing unit stores the item information of the financial institution transaction information divided into a withdrawal item and a deposit item belonging to a profit and loss calculation table, and the deposit / withdrawal item prediction information generation processing unit of the device, based on the deposit item and information of the dispensing items to generate a receipt and payment items prediction information withdrawal or payment in the future is predicted, funding prediction information generating unit of the equipment is pre-filled dispensing items prediction information Based on the cash flow forecast information, the cash flow forecast information is displayed on a display unit of the device, and at least a part of the deposit / withdrawal item forecast information is obtained from the payout item information and / or the deposit item information. Borrowing information prediction and funding information, characterized in that the fluctuation information of the corresponding month is added to the prediction information generated based on the tendency information from which the peculiar fluctuation information for each month has been removed, and the tendency information with fluctuation information is obtained. Offer Method of controlling the location A function of storing the financial institution transaction information in the financial institution transaction information storage unit in the borrowing information prediction and funding information providing device,
A function of extracting borrowing related item information from the financial institution transaction information and storing it in the borrowing related item information storage unit;
Based on the borrowing related item information, a function to generate borrowing entire calculation basic information,
A function of predicting and generating the entire borrowing information based on the entire borrowing calculation basic information,
A function of storing the item information of the financial institution transaction information separately in a withdrawal item and a deposit item belonging to a profit and loss statement,
A function of generating deposit / withdrawal item prediction information in which future withdrawal or deposit is predicted based on the information on the deposit item and the withdrawal item,
A function of generating cash flow prediction information based on the deposit / withdrawal item prediction information,
A function of displaying the cash flow forecast information on a display unit, and at least a part of the deposit / withdrawal item forecast information is a trend information obtained by removing monthly unique fluctuation information from the payout item information and / or the deposit / withdrawal item information. Borrowing information prediction and funding information providing program, wherein a function of adding the fluctuation information of the corresponding month to the prediction information generated based on .

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