JP2021060951A - Borrowing information predicting and cash management information providing apparatus, control method of borrowing information predicting and cash management information providing apparatus, and borrowing information predicting and cash management information providing program - Google Patents

Abstract

To provide a borrowing information predicting and cash management information providing apparatus, etc. capable of automatically providing a user with future borrowing prediction information, etc., by merely a user inputting transaction information of a financial institution.SOLUTION: A borrowing information predicting and cash management information providing apparatus 1 comprises: a financial institute transaction information storage unit 31 for storing financial institute transaction information 31a; a borrowing related item information generating unit 33 extracting borrowing related information from the financial institute transaction information and causing a borrowing related item information storage unit 34 to store it; and overall borrowing arithmetic basic information generating unit 42 for generating overall borrowing arithmetic basic information 43 based on the borrowing related item information. The apparatus predicts and generates overall borrowing information based on the overall borrowing arithmetic basic information.SELECTED DRAWING: Figure 9

Description

The present invention automatically generates future borrowing forecast information and, for example, a borrowing information forecasting and cashing information providing device that automatically generates future cashing information from financial institution transaction information, borrowing information forecasting and cashing information provision. It relates to the control method of the device, the borrowing information forecasting, and the cash flow information providing program.

Conventionally, a business management support system, etc. has been proposed in which the accounting department of a company, etc. can prepare concrete financial statements in accordance with a medium- to long-term plan by simulating its own future income statement, etc. There is.
Further, conventionally, a business management system or the like in which an accounting department or the like of a company or the like can simulate a future profit and loss statement of the company or the like has been proposed (for example, Patent Document 1 or the like).

Japanese Unexamined Patent Publication No. 2016-134053

However, such a business management support system, etc. is a system, etc. that allows a person in charge with accounting knowledge, etc. to create concrete financial statements in the future only by inputting necessary data in predetermined items. Therefore, there is a problem that it is not easy to use for the owners of small stores and the like.
Further, since the above-mentioned simulation device is a device for generating future profit and loss statement data only when a person in charge having accounting knowledge or the like inputs necessary data in a predetermined item or the like. There was a problem that it was not easy to use for the owners of small stores.

Therefore, the present invention can automatically provide the user with forecast information of future borrowing, etc., only by inputting the transaction information of the financial institution, etc., and the user can provide the transaction information of the financial institution, etc. Borrowing information forecasting and financing information providing device, borrowing information forecasting and financing information providing device control method and borrowing information that can automatically provide cash flow information such as future profit and loss statement information to users just by inputting The purpose is to provide forecasting and cash flow information provision programs.

The above object is, in the present invention, a financial institution transaction information storage unit that stores financial institution transaction information, and a borrowing that extracts borrowing-related item information from the financial institution transaction information and stores it in the borrowing-related item information storage unit. It has a related item information generation processing unit and a borrowing overall calculation basic information generation processing unit that generates borrowing overall calculation basic information based on the borrowing related item information, and has an entire borrowing based on the borrowing overall calculation basic information. A deposit / withdrawal item information generation processing unit that predicts and generates information and stores the item information of the financial institution transaction information by dividing it into withdrawal items and deposit items belonging to the profit and loss calculation table, and the deposit items and the above. Cash flow forecast information based on the deposit / withdrawal item forecast information generation processing unit that generates deposit / withdrawal item forecast information for which future withdrawals or deposits are predicted based on the withdrawal item information, and the deposit / withdrawal item forecast information. It has a cash flow forecast information generation processing unit for generating cash flow forecast information and a display unit for displaying the cash flow forecast information, and at least a part of the deposit / withdrawal item forecast information is the withdrawal item information and / or the deposit item. Borrowing information forecasting and borrowing information forecasting characterized in that it is trend information with fluctuation information obtained by adding the fluctuation information of the corresponding month to the forecast information generated based on the trend information obtained by removing the peculiar monthly fluctuation information from the information. Achieved by the cash flow information provider.

According to the above configuration, it has a financial institution transaction information storage unit (for example, a passbook data storage unit) that stores financial institution transaction information (for example, passbook data).
Therefore, for example, financial institution transaction information such as passbook data can be stored.
Further, in the above 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, repayment amount data storage unit and interest data storage unit). be able to.
Further, in the above configuration, based on the borrowing-related item information (for example, repayment amount data, interest data), basic information for calculating the entire borrowing such as annual interest rate data, remaining bond amount data, and remaining repayment period data is generated. be able to.
Therefore, when the deposit / withdrawal item forecast information is trend information with fluctuation information, the forecast is accurate because it is information that takes into account both the trend of change in the entire data and the peculiar fluctuation information such as the month. High deposit / withdrawal item forecast information.

Therefore, based on the basic information of total borrowing calculation such as annual interest rate data, remaining bond amount data, and remaining repayment period data, the total amount of borrowing, monthly repayment amount, repayment period, and other borrowing total information can be accurately predicted. Can be generated.
Further, since the entire borrowing information can be automatically generated from financial institution transaction information such as passbook data, it becomes an extremely easy-to-use device for users such as managers of small stores.

Further, according to the above configuration, item information (for example, deposit / withdrawal, description, etc.) can be obtained from financial institution transaction information (for example, passbook data, etc.), and withdrawal items (for example, personnel expenses, fixed) belonging to the profit and loss calculation table. Expenses, variable expenses, repayments, etc.) and deposit items (for example, sales, etc.) are automatically memorized, and future withdrawals or deposits are predicted based on the information of deposit items and withdrawal items. Gold item forecast information (for example, future labor cost data, etc.) can also be automatically generated.
Then, based on the deposit / withdrawal item forecast information, cash flow forecast information (for example, profit and loss statement information) is generated and the cash flow forecast information is displayed on the display unit, so that the user can cash in the future profit and loss statement and the like. The situation can be obtained easily and without hassle.
Further, according to the above configuration, at least a part of the deposit / withdrawal item prediction information is the tendency information (for example, seasonal index) obtained by removing the monthly peculiar fluctuation information (for example, seasonal index) from the withdrawal item information and / or the deposit item information. For example, it is trend information with fluctuation information (for example, seasonally adjusted future trend value, etc.) in which the fluctuation information of the corresponding month is added to the forecast information generated based on the trend value after removing seasonal fluctuations.
Therefore, when the deposit / withdrawal item forecast information is trend information with fluctuation information, the forecast is accurate because it is information that takes into account both the trend of change in the entire data and the peculiar fluctuation information such as the month. High deposit / withdrawal item forecast information.

Preferably, it is characterized in that warning information regarding a fund predicted due to a change in the entire borrowing information is generated and output.

According to the above configuration, it is possible to generate and output warning information about funds that is predicted due to fluctuations in overall borrowing information, for example, alerts that a fluctuation in share of each bank has occurred. 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 total calculation basic information includes annual interest rate information, remaining bond amount information and remaining repayment period information, and the borrowing total information is borrowing. It is characterized by including the amount information of the entire amount, the repayment amount information of each month, and the repayment period information.

According to the above configuration, it is possible to generate basic borrowing calculation information including annual interest rate information, remaining bond amount information and remaining repayment period information from borrowing-related item information including repayment amount information and interest information.
Then, since it is possible to generate total borrowing information including total borrowing amount information, monthly repayment amount information, and repayment period information from this basic borrowing calculation information, it is possible to accurately predict future borrowing information. it can.

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

According to the above configuration, at least a part of the deposit / withdrawal item forecast information is the moving average processed trend information (for example, the first three months) obtained by moving average processing the trend information (for example, the tendency value after removing seasonal fluctuations). It is generated based on the moving average value, etc.).
By making the trend information into the moving average processed trend information obtained by moving average processing in this way, it becomes easier to grasp the tendency of the change of the entire data, and the prediction accuracy is improved.

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

According to the above configuration, the moving average processed trend information (for example, the second 3-month moving average value, etc.) is further converted into the duplicate moving average processed tendency information (for example, the second future trend value, etc.). 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, it is characterized in that a warning regarding a possible increase in demand for funds is output based on the cash flow forecast information.

According to the above configuration, a warning regarding a possible increase in fund demand in the future is output based on the cash flow forecast information, so that an increase in fund demand such as a shortage of future deposit amount or an increase in working capital is predicted. , A warning will be output and the user will be notified.

In the present invention, the above object is to store financial institution transaction information in the financial institution transaction information storage unit, extract borrowing-related item information from the financial institution transaction information, and store it in the borrowing-related item information storage unit. Based on the borrowing-related item information, the borrowing overall calculation basic information is generated, and the borrowing overall information is predicted and generated based on the borrowing overall calculation basic information, and the deposit / withdrawal item information generation processing unit is the financial institution. The item information of the transaction information is separately stored in the withdrawal item and the deposit item belonging to the profit and loss calculation table, and the deposit / withdrawal item prediction information generation processing unit of the apparatus is based on the information of the deposit item and the withdrawal item. Then, the deposit / withdrawal item forecast information for which future withdrawals or deposits are predicted is generated, and the cash flow forecast information generation processing unit of the apparatus generates cash flow forecast information based on the deposit / withdrawal item forecast information, and the apparatus. The cash flow forecast information is displayed on the display unit of, and at least a part of the deposit / withdrawal item forecast information is trend information obtained by removing monthly peculiar fluctuation information from the withdrawal item information and / or the deposit item information. This is achieved by a method of predicting borrowing information and controlling a cash flow information providing device, which is characterized in that the fluctuation information of the corresponding month is added to the forecast information generated based on the above to obtain trend information with fluctuation information.

The above object is, in the present invention, a function of storing financial institution transaction information in a financial institution transaction information storage unit in a borrowing information prediction and cash flow information providing device, and extracting borrowing-related item information from the financial institution transaction information. A function to store the borrowing-related item information storage unit, a function to generate the borrowing-related item information based on the borrowing-related item information, and a function to predict and generate the borrowing-related item information based on the borrowing-related item information. , A function to classify and store the item information of the financial institution transaction information into withdrawal items and deposit items belonging to the profit and loss calculation table, and based on the information of the deposit items and the withdrawal items, future withdrawals or deposits can be made. A function to generate predicted deposit / withdrawal item forecast information, a function to generate cash flow forecast information based on the deposit / withdrawal item forecast information, a function to display the cash flow forecast information on the display unit, the deposit / withdrawal item forecast At least a part of the information is the forecast information generated based on the tendency information obtained by removing the monthly peculiar fluctuation information from the withdrawal item information and / or the deposit item information, and the fluctuation information of the corresponding month. In addition, it is achieved by a borrowing information forecasting and cash flow information providing program, which is characterized in that it is configured to execute a function of trend information with fluctuation information.

As described above, the present invention can automatically provide the user with forecast information of future borrowing, etc., by simply inputting transaction information of the financial institution, etc., and the user can provide the financial institution, etc. Control of borrowing information forecasting and financing information providing device, borrowing information forecasting and financing information providing device that can automatically provide cash flow information such as future profit and loss statement information to users simply by inputting transaction information such as It has the advantage of being able to provide methods and borrowing information forecasting and cash flow information provision programs.

It is the schematic which shows the appearance of the "borrowing information prediction and cash flow information providing apparatus" which concerns on embodiment of this invention. It is a schematic diagram which shows the main structure of the "borrowing information forecasting apparatus" part in the "borrowing information forecasting and cash flow information providing apparatus main body" of FIG. It is a schematic block diagram which shows the main structure of "the first various information storage unit 30" to "the third various information storage unit 50". It is a schematic block diagram which shows the main structure of the 1st various information storage part. It is a schematic block diagram which shows the main structure of the 2nd various information storage part. It is a schematic block diagram which shows the main structure of the 3rd various information storage part. It is a schematic flowchart which shows the main operation example of the borrowing information prediction apparatus 1. It is another schematic flowchart which shows the main operation example of the borrowing information prediction apparatus 1. It is a schematic explanatory diagram which shows information such as the total amount of borrowing which is the total information of borrowing, the repayment amount of each month, and the repayment period. It is a schematic diagram which shows the main structure of the "cashing information providing apparatus" part in "borrowing information forecasting and cashing information providing apparatus main body" of FIG. It is a schematic block diagram which shows the main structure of "the eleventh various information storage part". It is a schematic block diagram which shows the main structure of "12th various information storage part". It is a schematic block diagram which shows the main structure of "thirteenth various information storage part". It is a schematic block diagram which shows the main structure of "14th various information storage part". It is a schematic block diagram which shows the main structure of "15th various information storage part". "It is a schematic block diagram which shows the main structure of the 16th information storage part. It is a schematic explanatory diagram which shows a part of "passbook data" stored in the "passbook data storage part" of FIG. It is a schematic flowchart which shows the "future sales data" generation process. It is another schematic flowchart which shows the process of generating "future sales data". It is explanatory drawing about sales information and the like. It is a schematic explanatory diagram which shows the "seasonal index data" stored in the "seasonal index data storage part" of FIG. It is the schematic explanatory drawing which shows the characteristic part of the 2nd Embodiment. It is a graph comparing the monthly change of "truncated mean value" and "second 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.
Since the embodiments described below are suitable specific examples of the present invention, various technically preferable limitations are attached, but the scope of the present invention particularly limits the present invention in the following description. Unless otherwise stated, the present invention is not limited to these aspects.

FIG. 1 is a schematic view showing the appearance of the “borrowing information prediction and cash flow information providing device 1” according to the embodiment of the present invention.
As shown in FIG. 1, the apparatus 1 includes a borrowing information prediction and cash flow information providing device main body 10, a “display 21” that displays various information as a display unit, a “keyboard 22” and a “mouse 23” that input various information. ".
Further, the borrowing information prediction and cash flow information providing device main body 10 is provided with various data input units 13 that receive an information recording medium such as a CD and acquire the data.

Each device 10 or the like of the “borrowing information prediction and cash flow information providing device 1” in FIG. 1 is a computer, and is a CPU (Central Processing Unit), a RAM (Random Access Memory), a ROM (Read Only Memory), a hard disk, or the like. And are connected via a bus.

Since the "borrowing information prediction and cash flow information providing device 1" of the present embodiment has a part as a "borrowing information prediction device" and a part as a "cash flow information providing device", hereinafter, the "borrowing information prediction device" The part and the "cash flow information providing device" part will be described in detail below.

(About the part as "borrowing information prediction device")
A "borrowing information prediction device" is obtained by inserting a CD or the like in which a program or the like related to the "borrowing information prediction" according to the present invention is stored into various data input units 13 of the device 1 shown in FIG. 1 and reading the data. It functions as "1".
Further, the program or the like related to the "borrowing information prediction" according to the present invention may be acquired by the present device 1 by wireless communication other than a CD or the like, and is stored in advance in the borrowing information prediction and cash flow information providing device main body 10. You can leave it.

FIG. 2 is a schematic diagram showing a main configuration of a portion of the “borrowing information prediction device” of the “borrowing information prediction and cash flow information providing device main body 10” of FIG.
As shown in FIG. 1, the "borrowing information prediction device" portion of the main body 10 has a control unit 11, and the control unit 11 includes a communication device 12 for communicating with an external device such as a display 21 and various data. It is configured to control the input unit 13.
Further, 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.

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

Hereinafter, an operation example of the “borrowing information prediction device” part of the “borrowing information prediction and cash flow information providing device 1” according to the present embodiment will be described.
In the present embodiment, the manager of the A company inputs the financial institution transaction information of the A company, for example, the passbook data into the "borrowing information prediction device and the cash flow information providing device 1" of FIG. The following will be explained as an example of grasping the future borrowing situation of the company and receiving various alerts.

7 and 8 are schematic flowcharts showing a main operation example of the “borrowing information prediction device” portion of the borrowing information prediction and cash flow information providing device 1.
Hereinafter, description will be given with reference to the flowcharts of FIGS. 7 and 8.

First, the manager of company A stores the bankbook data of company A in, for example, a CD or the like, and via the "various data storage units 13" of the "borrowing information prediction and cash flow information providing device main body 10" of FIG. input.
Then, this 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 cash flow information providing device main body 10”.

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

Then, the process proceeds to step 1 (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 of FIG. 3 operates, and the “repayment amount display data storage unit 32” of FIG. 3 is referred to.
"Predetermined repayment amount display data" is stored in the repayment amount display data storage unit 32. For example, "borrowing", "kariire", "financing", "yushi", "certificate loan", "shoshokashitsuke", "certificate lending", "shoukashi", "bill loan", "tegatakashitsuke", "hand lending" , "Tegashi" and other words and names such as financial institution names are stored in advance as "predetermined repayment amount display data".

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

Therefore, the processing unit 33 determines whether or not the display data (wording) of the "summary" of the "passbook data 31a" of FIGS. 3 and 6 corresponds to the predetermined repayment amount display data of FIG. , If applicable, it is the borrowing-related item information, for example, "repayment amount" data, and in association with the withdrawal date data, the borrowing-related item information storage unit, for example, "repayment amount" in FIG. It is stored in the data storage unit 34.

Then, the process proceeds to ST2. In ST2, for example, the interest determination processing unit (program) 36 of FIG. 3, which is a borrowing-related item information generation processing unit, operates, and the display data (wording) of the “summary” of the “passbook data 31a” of FIGS. Determines whether or not the predetermined interest display data stored in the “interest display data storage unit 35” of FIG. 3, for example, “interest” or the like.
Then, if applicable, it is determined that the borrowing-related item information is, for example, "interest" data, and is associated with the withdrawal date data, and is the borrowing-related item information storage unit, for example, "interest data storage" in FIG. It is stored in "Part 37".

As described above, the borrowing information forecasting and cash flow information providing device 1 can acquire "repayment amount data" which is monthly repayment (borrowing) data and monthly interest data.
Then, from these monthly "repayment amount data" and monthly "interest data", it is the borrowing total calculation information necessary for the prediction of borrowing, for example, "one year interest rate data", "remaining bond amount data" and "remaining". Generate repayment period data.

Then proceed to ST3. In ST3, "one-year interest rate data" is generated. Specifically, for example, the “annual interest rate data generation processing unit (program) 42” of FIG. 4, which is the basic information generation processing unit for total borrowing calculation, operates and is stored in the “annual interest rate data calculation storage unit 41” of FIG. Refer to the following formula.
That is, "annual interest rate data = (interest amount for n months-n + interest amount for January) / (repayment amount for n + 1 month) x 12".

Then, the processing unit (program) 42 refers to the “repayment amount data storage unit 34” in FIG. 3 and acquires the “n + 1 month repayment amount”, for example, the March repayment amount “6,000 yen”. And substitute.
Also, referring to the "interest data storage unit 37" in FIG. 3, "n + 1 month interest amount" and "n month interest amount", for example, March interest amount (290 yen) and February interest amount (n) 295 yen) is acquired and substituted.
Then, the "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 unit 43”.

In the present embodiment, the interest rate per month is calculated and simply multiplied by 12, but the present invention is not limited to this, and "365 (or 366) ÷ current repayment date from the previous repayment date". It may be calculated as "the 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 exactly if it is linked with the calendar function).

Then, the process proceeds to ST4. In ST4, "n + 1 month remaining bond amount", for example, March remaining bond 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 for total borrowing calculation, operates, and the "remaining bond amount data calculation storage unit 44" of FIG. 4 operates. Refer to the following formula that is stored.
That is, "(n + 1 month remaining bond amount) = (n + 1 month interest amount) ÷ {(n month interest amount-n + 1 month interest amount) ÷ (n + 1 month repayment amount)}.

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

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

Then, 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” of FIG. 5, which is the basic information processing unit for total borrowing calculation, operates, and the “remaining repayment period data calculation storage unit 47” of FIG. 4 operates. Refer to the following formula stored in.
That is, "(n + 1 month remaining bond amount) ÷ (n + 1 month repayment amount)".

Then, the processing unit (program) 51 acquires, for example, the repayment amount of “348,000 yen” in March, which is the “n + remaining bond amount in January” from the “residual bond amount data storage unit” in FIG. ,substitute.
Further, for example, the repayment amount of "6,000 yen" in March, which is the "n + 1 month repayment amount", is acquired from the "repayment amount data storage unit 34" in FIG. 3 and substituted.
Then, the "remaining repayment period data" is obtained and stored in the "remaining repayment period data storage unit 52" of FIG.

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

With the above, "annual interest rate (interest rate) data", "remaining bond amount data" and "remaining repayment period data" can be generated.
Therefore, based on this information, it is possible to obtain information such as the total amount of borrowing in the case of equal repayment of principal, which accounts for the majority of corporate loans, and the repayment amount and repayment period of each month, as shown in FIG. ..
In addition, as shown in FIG. 9, it is also possible to grasp the payment status of the interest rate of the borrowed money.
FIG. 9 is a schematic explanatory diagram showing information such as the total amount of the borrowed amount, which is the total information of the borrowed money, the repayment amount of each month, and the repayment period.

As shown in FIG. 9, the borrowing information prediction and cash flow information providing device 1 accurately predicts the entire borrowing information by simply acquiring the user's passbook data 31a and without having to receive the borrowing details from the user. be able to.
In particular, since the entire borrowing information can be automatically generated from the passbook data 31a or the like, the borrowing information prediction and cash flow information providing device 1 according to the present embodiment is used by the manager or the like of a small store or the like. For those who use it, it will be an extremely easy-to-use device.

Next, the borrowing information prediction and cash flow information providing device 1 is warning information about the fund predicted due to the fluctuation of the entire borrowing information based on the user's "all borrowing information" acquired in the above process. For example, the following alerts are generated as necessary and displayed on the display 21 to notify the user.

(Alerts for fluctuations in the share of borrowing at each bank with which user A company is trading)
As shown in FIG. 9, the borrowing information forecasting and cash flow information providing device 1 can grasp the borrowing amount, the repayment status, etc. of the company A, so that the current and future of each bank with which the company A has a transaction. Information such as the amount of repayment can be obtained.
Therefore, the borrowing information prediction and cash flow information providing device 1 displays the borrowing amount, the borrowing balance, etc. for each bank with which the company is dealing side by side on the display 21 or the like, and when the borrowing amount is biased to a specific bank. Is configured so that the alert can be displayed on the display 21 or the like.

The manager of company A who sees this alert can grasp in advance that the amount of borrowing of the company is biased to a specific bank and there is a possibility that it will be difficult to borrow from another bank in the future.

(Alert of borrowing balance and monthly sales comparison)
The borrowing information forecasting and financing information providing device 1 determines from the information in FIG. 9 and the like whether or not the remaining debt of company A's borrowing is less than 1 times the monthly sales of company A, and is 1 times or less of the monthly sales. When the situation becomes high, an alert is output to the display 21 or the like as it is necessary to raise funds.

That is, as described above, the borrowing information forecasting and cash flow information providing device 1 compares the "remaining bond amount" of company A obtained by calculation with the sales data acquired separately, and the "remaining bond" is "month". When it is determined that the value is 1 times or less of the commercial value, it is considered 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 daily work and cannot confirm accounting information, can know in advance that there is a possibility that a shortage of funds will occur in the near future.

(Comparison of required working capital and alert of borrowing balance)
The borrowing information forecasting and financing information providing device 1 calculates the "required working capital comparison" data, and when the remaining debt of the borrowing falls below, it determines that it is necessary to raise funds and outputs an alert to the display 21 or the like. ..
Here, the "required working capital comparison" data means funds that purchase products, sell them, collect them, and make up for the time lag until the price is paid.
This "required working capital comparison" data tends to increase when the sales of company A are on the increase, and in this embodiment, the borrowing information forecasting and financing information providing device 1 is the balance of the borrowing of company A. In comparison with the above, it is determined that the remaining bonds exceed a predetermined range, and an alert is output to the display 21 or the like as it is necessary to raise funds in a sound manner.

Therefore, even a manager of company A, who is busy with daily work and cannot confirm accounting information, can know in advance that there is a possibility that a shortage of funds will occur in the near future.

Next, the portion of the “borrowing information and cash flow information providing device 1” as the “cash flow information providing device” will be described in detail below.

("First embodiment" for the part as "cash flow information providing device")
The “borrowing information prediction and cash flow information providing device main body 10” shown in FIG. 1 includes various data input units 13 that receive an information recording medium such as a CD and acquire the data.

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

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

11 to 16 are schematic block diagrams showing the main configurations of the "11th various information storage units 130" to the "16th various information storage units 180", respectively. These contents will be described later.

Hereinafter, an operation example of the “cash flow information providing device” part of the “borrowing information prediction and cash flow information providing device 1” according to the present embodiment will be described.
In the present embodiment, the manager of the company A inputs the financial institution transaction information of the company A, for example, the passbook data into the “borrowing information prediction and cash flow information providing device 1” of FIG. In the future, for example, grasping the cash flow situation (lack of funds, etc.) of the next month will be described below as an example.

First, the manager of company A stores the bankbook data of company A in, for example, a CD or the like, and via the "various data storage units 13" of the "borrowing information prediction and cash flow information providing device main body 10" of FIG. input.
Then, this 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 cash flow information providing device main body 10”.

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

The apparatus 1 separately stores the withdrawal items to which the past income statement and the like belong from the passbook data 131a, 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.
Furthermore, based on these "past labor costs,""past fixed costs,""past variable costs,""pastrepayments,""pastsales," etc., in the future, for example, "future labor costs,""future fixed costs," and "future fluctuations" for the following month. Forecast costs, future repayments, future sales, etc.
Hereinafter, each item will be described.

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

For example, among the passbook data 131a in 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 "past personnel". It is stored in the expense data storage unit 133.

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

For example, (40,000 yen (May) + 40,000 yen (June) + 40,000 yen (July)) ÷ 3 = 40,000 yen (estimated value in August) is the "future labor cost" in August. It is stored in the "future labor cost data storage unit 135" as "data".

(About the process of generating "future fixed cost data")
Next, the process of generating "future fixed cost data" will be described below.
First, the deposit / withdrawal item information generation processing unit of the “borrowing information prediction and cash flow information providing device main body 10” of FIG. 11, for example, the “fixed cost judgment acquisition unit (program) 136” operates, and FIGS. 11 and 17 show. A specific description of the passbook data 131a of the "passagebook data storage unit 131" (for example, "for n months of electricity") is determined as a "fixed cost" by machine learning or the like, and the "past fixed cost data storage unit" of FIG. It is stored in 137 ”.

For example, of the passbook data 131a in FIG. 17, "electricity for May" in May is 30,000 yen, "electricity for June" in June is 36,000 yen, and "electricity for July" in July. Data such as 30,000 yen is stored in the "past fixed cost data storage unit 137".

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

For example, (30,000 yen (May) + 36,000 yen (June) + 30,000 yen (July)) ÷ 3 = 32,000 yen (August forecast value) for August deposit / withdrawal item forecast Information, for example, is stored in the "future fixed cost data storage unit 141" as "future fixed cost data".

(About the process of generating "future variable cost data")
Next, the process of generating "future variable cost data" will be described below.
First, the deposit / withdrawal item information generation processing unit of the “borrowing information prediction and cash flow information providing device main body 10” of FIG. 12, for example, the “variable cost judgment acquisition unit (program) 142” operates, and FIGS. 11 and 17 show. Of the passbook data 131a of the passbook data storage unit 131, withdrawals other than fixed costs (excluding repayments for borrowings and loans) are set as "variable costs" and stored in the "past variable cost data storage unit 143" in FIG. To do.

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

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

For example, (60,000 yen (May) + 40,000 (June) + 20,000 yen (July)) ÷ 3 = 40,000 yen (August forecast value) for August deposit / withdrawal item forecast information 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 process of generating "future repayment data" will be described below.
First, the deposit / withdrawal item information generation processing unit of the “borrowing information prediction and cash flow information providing device main body 10” of FIG. 12, for example, the “repayment judgment acquisition unit (program) 146” operates, and the passbooks of FIGS. 11 and 17 are operated. Of the passbook data 131a of the data storage unit 131, the data whose description is "repayment" in the payment column is stored in the "past repayment data storage unit 147" of FIG.

For example, among the passbook data 131a in FIG. 17, data such as 0 yen for May, 6,000 yen for June, and 6,000 yen for July can be obtained from the "past repayment data storage unit 147" in FIG. Remember in.

Next, the deposit / withdrawal item prediction information generation processing unit, for example, the “future repayment data generation processing unit (program) 148” in FIG. 12 operates, and the data (for example, 5) in the “past repayment data storage unit 147” in FIG. Obtained "0 yen" for the month, "6,000 yen" for June, "6,000 yen" for July, etc.), judged that the repayment amount was the same as the previous month, and "future repayment data" for August. Is generated and stored in the “future repayment data storage unit 151” of FIG.

For example, in the above example, since the previous month (July) was 6,000 yen, it was determined that August was also 6,000 yen, and 6,000 yen was set as "future repayment data" for August in FIG. It is stored in the "future repayment data storage unit 51" of.

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

For example, out of the passbook data 131a in FIG. 17, for May, 70,000 yen for "ka) apple", 90,000 yen for "ka) mandarin", 100,000 yen for "ka) banana, etc. Extract the data.
In addition, for June, data such as 80,000 yen for "mosquitoes" and 110,000 yen for "mosquitoes" will be extracted.
Then, for July, data such as 80,000 yen for "ka) mandarin oranges and 90,000 yen for" ka) bananas are extracted and stored in the "past sales data storage unit 153" in FIG.

Then, the process proceeds to ST12. In ST12, the "trim sales average value calculation processing unit (program) 154" of FIG. 13 operates, and the maximum value and the minimum value of the monthly sales data of the "past sales data storage unit 153" of FIG. 13 are removed. , 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 regarding sales information and the like.
The "truncated mean value" stored in the "truncated mean value storage unit 155" of FIG. 13 is calculated as shown in the "truncated mean value" of FIG.
For example, as shown in FIG. 20, the trimmed mean value in July 2016 is 178,000 yen, the trimmed mean value in August is 224,000 yen, the trimmed mean value in September is 173,000 yen, and the like.

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 of each month.

Then, the process proceeds to ST13. In ST13, the “seasonal index data generation processing unit (program) 156” shown in FIG. 13 operates, and is a fluctuation index for each month based on sales data such as monthly trimmed mean values for multiple years in the past, for example, a seasonal index. (Index of sales change in each month) is obtained and stored in the "seasonal index data storage unit 157" of FIG.

FIG. 21 is a schematic explanatory view showing “seasonal index data 157a” stored in the “seasonal index data storage unit 157” of FIG.
As shown in FIG. 21, the seasonal index is, for example, "0.85" for January, "0.83" for February, and "0.89" for March. And so on, the "variation index" that shows the fluctuation trend of sales in that month is stored.

Then, the process proceeds to ST14. In ST14, the “monthly trend value generation processing unit (program) 158” of FIG. 13 operates, and with reference to the “truncated mean value storage unit 155” and the “seasonal index data storage unit 157” of FIG. 13, monthly The "truncated mean value" data is divided by the "seasonal index" of the corresponding month to obtain trend information, for example, the "trend value after removing seasonal fluctuations", and the "monthly trend value storage unit 161" in FIG. Remember in.

By dividing the seasonal index by the monthly trimmed mean value in this way, it is possible to grasp the tendency value after removing the seasonal fluctuation.
For example, in the example of FIG. 20, in July 2016, the trimmed mean value is "178,000 yen" and the seasonal index is "1.08", so the "monthly trend value" of sales is "165". And in August. “249”, “164” in September, etc., and these “monthly tendency values” are stored in the “monthly tendency value storage unit 161” of FIG.

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

Specifically, in the example of FIG. 20, the "monthly trend value" in July 2016 is "165" and the "monthly trend value" in August is "249", so from July to August. The change in the tendency value of is "1.5 times". Therefore, the "future trend value prediction data generation processing unit (program) 162" in FIG. 14 operates, and the monthly trend value "146" in July 2017 is multiplied by "1.5 times" to be obtained in August 2017. The "future trend value""219" is obtained and stored in the "future trend value storage unit 163" of FIG.
As a result, the "future trend value" in August 2017 is predicted to be, for example, "219" and will be stored.
In addition, this "future trend value" is an example of "prediction information generated based on trend information".

Then, 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. 14 operates. Is multiplied by the "seasonal index (for example, August, 0.9)" of the corresponding "seasonal index storage unit" to generate a "seasonally adjusted future trend value", and the "seasonally adjusted future trend value storage unit" is generated. It is stored in "165".
That is, the "future trend value" obtained in ST15 only shows the trend value for the entire year, and does not take into account the fluctuation information peculiar to each month. Therefore, in this process, by multiplying the seasonal index of the month, the monthly tendency value considering the seasonal index is obtained, and the reliability of the value is improved.

Specifically, by multiplying "219", which is the "future trend value" of the above example, by the seasonal index "0.9" in August, it is trend information with fluctuation information, for example, "seasonally adjusted future trend". The "value" of "197" is obtained and stored in the "seasonally adjusted future trend value storage unit 165" of FIG.

With the above, the forecast values for withdrawals such as "future labor costs", "future fixed costs", "future variable costs" and "future repayments" in September 2017, and the forecast values for sales, "seasonally adjusted" The completed future trend value ”is obtained and stored by the present device 1.
Therefore, as follows, the "Profit and Loss Statement" data for September 2017 is forecast by ST17.
In ST17, the cash flow forecast information generation processing unit of FIG. 14, for example, the “future profit / loss statement generation processing unit (program) 166” operates, and the “future labor cost data storage unit 135” of 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. To do.

Then, the processing unit 166 uses "future labor cost data" (August, 40,000 yen), "future fixed cost data" (August, 32,000 yen), and "future variable cost" in the storage unit 135, etc. 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, "future profit and loss statement" data, which is "cash flow forecast information" for August 2017, is generated and stored in the "future profit and loss statement storage unit 167" of FIG.

With the above, in the future, for example, "income statement" data for August 2017 will be generated and stored.
And, this "income statement" data is forecast data that considers the annual trend value and the seasonal index of the month to be forecast, especially the forecast of "sales" data, and the trend of the change of the whole annual sales and the corresponding Since the data includes both unique seasonal indexes such as the month, it is highly accurate forecast data.
In addition, this "income statement" data is automatically classified into each item such as "personnel cost", "fixed cost", "variable cost", "repayment" and "sales" just by inputting passbook data etc. Along with the creation, the "income statement" data, which is a future forecast, is also generated, so that the user can easily grasp the "cash flow status".

Further, in the present embodiment, the “income statement” data for August 2017 can be generated in this way, and the “income statement” data can be displayed on the display 21 of FIG. 1 as needed. it can. Therefore, the user can easily grasp the future cash flow situation and the like by visually recognizing the display 21.
Specifically, for example, the user can grasp in advance the shortage of deposits in August 2017.

Further, in the present embodiment, as described above, since the future "income statement" data can be predicted, various alerts that are warnings regarding the increase in the demand for funds that may occur in the future can be output. ing.

Since the alert of the present embodiment includes the "first financing examination alert", the "second financing examination alert", and the "tax payment preparation alert", each of them will be described below.

(About the first funding review alert output process)
The "first fund procurement examination alert generation processing unit (program) 171" of FIG. 15 operates, and the forecast of the passbook is made within a set plurality of months with reference to the "future income statement storage unit 167" of FIG. It is determined whether or not the amount is less than the set amount, and if it is determined that the amount is less than the set amount, the "first financing consideration alert" is output to the display 21 or the like.
Therefore, when the estimated amount of money in 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 funding review alert output process)
The "Second Funding Examination Alert Generation Processing Unit (Program) 172" in Fig. 15 operates, and refers to past withdrawal data, etc. to determine whether the withdrawal amount has exceeded the same month last year for multiple consecutive months. However, when it exceeds the limit, it is determined that an increase in working capital needs is expected, 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 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, refers to past withdrawal data, deposit data, etc., and determines whether or not the withdrawal is less than the deposit for multiple months. , "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 company's sales increase, it generally requires increased working capital, and if it does not borrow, cash will decrease. For this reason, it is possible that there will be a shortage of cash at the timing of subsequent tax payments.
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" for the part as "cash flow information providing device")
The present embodiment differs in that the "future trend value" relating to the sales of the first embodiment described above is further processed, but since many other configurations are common to the first embodiment, Hereinafter, the differences will be mainly described, and the configurations and the like common to the first embodiment are designated by the same reference numerals and the description thereof will be omitted.

In the first embodiment described above, the "monthly trend value" was obtained in ST14 of FIG. 18, and in ST15, the "future trend value" was generated based on this "monthly trend value". The difference is that the "monthly trend value" is further subjected to the "3-month moving average" process twice (3 x 3 moving average), and then the "second future trend value" is obtained.
Hereinafter, a detailed description will be given.

First, ST11 to ST14 in FIG. 18 for generating future sales data are common to the first embodiment.
In addition, the method of calculating data on personnel costs, fixed costs, variable costs, repayments, etc. related to withdrawals is also common to the first embodiment.
Hereinafter, the processing after the processing of ST14 is completed will be described.

In ST14 of FIG. 18, after storing the "monthly tendency value" after removing the seasonal fluctuation in the "monthly tendency value storage unit 161" of FIG. 14, the "first 3-month moving average processing unit (program) 174" of FIG. 15 Is activated, and the "monthly tendency value" of each month of the "monthly tendency value storage unit 161" in FIG. 14 and the values of the months before and after that are added and divided by 3, and the "first 3 months movement" of the month is performed. The "average value" is obtained and stored in the "first 3-month moving average value storage unit 175" of FIG.
This "first 3-month moving average value" is an example of the moving average processed trend information.

Further, FIG. 22 is a schematic explanatory view showing a characteristic portion of the second embodiment.
As shown in FIG. 22, by processing the monthly trend value by the "first 3-month moving average", as shown in FIG. 22, July 2016 is "191", August is "193", and September. Is "186" and the like, and these are the "first moving average values".

Next, the "second 3-month moving average processing unit (program) 176" of FIG. 15 operates, and the "first 3-month moving average value" of each month of the "first 3-month moving average value storage unit 175" operates. , And the values of one month before and after that are added and divided by three to obtain the "second three-month moving average" of the month, which is stored in the "second three-month moving average storage unit 177".
Then, it becomes the "second moving average value" of FIG. That is, in the present embodiment, by performing the "3-month moving average" twice (3 x 3 moving average), a numerical value that makes it easy to grasp the overall tendency value is obtained.
This "second 3-month moving average value" is an example of the overlapping moving average processed trend information.

FIG. 23 is a graph comparing the monthly changes of the “truncated mean value” and the “second three-month moving average value”.
As shown in FIG. 23, by performing the "3 × 3 moving average" process as in the present embodiment, the data is easier to grasp the tendency.

Next, the "second future trend value prediction data generation processing unit (program) 181" of FIG. 16 operates, and the "second second" of each month of the "second three-month moving average value storage unit 177" of FIG. A "second future trend value" is generated based on the "three-month moving average value" and stored in the "second future trend value storage unit 182" of FIG.

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

Next, the "second seasonally adjusted future trend value generation processing unit (program) 183" of FIG. 16 operates, and corresponds to the "second future trend value" of the "second future trend value storage unit 182". Multiply the "seasonal index" of the "seasonal index storage unit 157" of FIG. 13 to generate a "seasonally adjusted second future trend value", and generate a "seasonally adjusted second future trend value storage unit" of FIG. 184 ”is stored.

For example, the above-mentioned "165", which is the "second future trend value", is multiplied by the August seasonal index "0.9" to obtain the "seasonally adjusted future trend value" (149), which is 149,000 yen. Is stored in the “seasonally adjusted second future trend value storage unit 184” of FIG. 16 as the “seasonally adjusted second future trend value” in August.
In this process, the forecasted sales value is accurately estimated from both the trend value and the seasonally adjusted factors.

Then, the step of predicting the "income statement" is executed.
Specifically, the "second future profit and loss statement generation processing unit (program) 185" of FIG. 16 operates, the "future labor cost data storage unit 135" of FIG. 11, and the "future fixed cost data storage" of FIG. Refer to “Unit 141”, “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.
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 "Future repayment data" (August, 6,000 yen) and "Seasonally adjusted second future trend value" (August, 149000 yen), etc., "Second future" in August 2017 The "profit and loss statement" data is generated and stored in the "second future profit and loss statement storage unit 186" of 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 sales value, and therefore, as compared with the first embodiment. More irregular factors are removed, and the judgment can be made based on the leveled tendency value (second future tendency value).

The present invention is not limited to the above-described first embodiment and second embodiment, but also includes the following configurations.
For example, when there is little basic data such as passbook data 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)" , The method of averaging the data of the three months before the month, the method of averaging the data of the three months after the month, etc.) ”may be used to obtain the trend value.

Further, the "trend value" may be obtained from the "3 × 3 moving average" of the second embodiment.
Further, even when there is missing data in the passbook data or the like, the data may be supplemented with the above-mentioned "3-month moving average" or "3 × 3 moving average" to obtain the "monthly trend value" or the like.

In the present embodiment described above, the case where it is realized as an apparatus has been described as an example, but the present invention is not limited to this, and as a program that can be executed by a computer, a magnetic disk (floppy (registered)). It may be stored and distributed in a storage medium such as a disk (trademark), a hard disk, etc.), an optical disk (CD-ROM, DVD, etc.), a magneto-optical disk (MO), or a semiconductor memory.

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

Further, in order to realize this embodiment, an OS (operating system) running on the computer based on instructions of a program installed on the computer from a storage medium, MW (middleware) such as database management software and network software, etc. You may execute a part of each process of.

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

Further, the computer in the present invention may be a device consisting of one personal computer or the like, or a plurality of devices may be connected to a network, as long as each process in the present embodiment is executed based on a program stored in a storage medium. It may be a 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, etc. included in an information processing device, and is a general term for devices and devices capable of realizing the functions of the present invention by a program. ing.

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

1 ... Borrowing information prediction and cash flow information providing device, 10 ... Borrowing information prediction and cash flow information providing device main body, 11 ... Control unit, 12 ... Communication device, 13 ... Various data input units, 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 units, 41 ... Annual interest rate data calculation storage unit, 42 ... Annual interest rate data generation processing unit (program), 43.・ ・ Annual interest rate data storage unit, 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 units, 51 ... Remaining repayment period data generation processing unit (program), 52 ... Remaining repayment period data storage unit, 130・ ・ ・ 11th various data storage unit, 131 ・ ・ ・ passbook data storage unit, 132 ・ ・ ・ labor cost judgment acquisition department (program) 133 ・ ・ ・ past labor cost data storage unit, 134 ・ ・ ・ future personnel Expense data generation processing unit (program), 135 ... Future labor cost data storage unit, 136 ... Fixed cost judgment acquisition unit (program), 137 ... Past fixed cost data storage unit, 138 ... Fixed in the future Cost data generation processing unit (program), 140 ... 12th 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 ... 13th various data storage units, 151 ... Future repayment data storage unit, 152 ... Sales judgment 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 ... 14th various data storage units, 161 ... Monthly trend value storage unit, 162 ... Future trend value prediction Data generation processing unit (program), 163 ... Future trend value storage unit, 164 ... Seasonally 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 ・ ・ ・ 15th various data storage units, 171 ・ ・ ・ 1st fund raising examination alert generation processing unit (Program), 172 ... Second funding review alert generation processing unit (program), 173 ... Tax payment preparation alert generation processing unit (program), 174 ... First three-month mobile average processing unit (program) Program), 175 ... 1st 3-month moving average value storage unit, 176 ... 2nd 3-month moving average processing unit (program), 177 ... 2nd 3-month moving average value storage unit, 180 ... 16th various data storage units, 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 profit and loss statement generation processing unit (program), 186.・ ・ Second future profit and loss statement storage unit.

Claims (8)

The financial institution transaction information storage unit that stores 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.
It has a borrowing total calculation basic information generation processing unit that generates borrowing total calculation basic information based on the borrowing related item information.
Overall borrowing calculation Based on the basic information, the entire borrowing information is predicted and generated, and
Based on the deposit / withdrawal item information generation processing unit that divides and stores the item information of the financial institution transaction information into the withdrawal items and the deposit items belonging to the profit and loss calculation table, and the information of the deposit items and the withdrawal items. A deposit / withdrawal item forecast information generation processing unit that generates deposit / withdrawal item forecast information for which future withdrawals or deposits are predicted, and a cash flow forecast information generation processing unit that generates cash flow forecast information based on the deposit / withdrawal item forecast information. And a display unit that displays the cash flow forecast information, and at least a part of the deposit / withdrawal item forecast information is peculiar monthly fluctuation information from the withdrawal item information and / or the deposit item information. A borrowing information forecasting and cash flow information providing device, characterized in that it is trend information with fluctuation information obtained by adding the fluctuation information of the corresponding month to the forecast information generated based on the trend information obtained by removing the above. The borrowing information forecasting and financing information providing device according to claim 1, wherein warning information regarding a fund predicted due to a change in the entire borrowing information is generated and output. The borrowing-related item information includes repayment amount information and interest information.
Basic information on total borrowing calculation includes annual interest rate information, remaining bond amount information and remaining repayment period information.
The borrowing information forecasting and cash flow information providing device according to claim 1 or 2, wherein the borrowing total information includes the total amount information of the borrowing amount, the repayment amount information of each month, and the repayment period information. The item according to any one of claims 1 to 3, wherein at least a part of the deposit / withdrawal item prediction information is generated based on the moving average processed trend information obtained by moving the trend information. Described borrowing information forecasting and cash flow information providing device. The borrowing according to claim 4, wherein at least a part of the deposit / withdrawal item forecast information is generated based on the duplicate moving average processed tendency information obtained by further moving averaging the moving average processed tendency information. Information forecasting and cash flow information providing device. Preferably, the borrowing information forecast and the cash flow information provision according to any one of claims 1 to 5, wherein a warning regarding a possible increase in fund demand in the future is output based on the cash flow forecast information. apparatus. Store financial institution transaction information in the financial institution transaction information storage unit,
Borrowing-related item information is extracted from the financial institution transaction information and stored in the borrowing-related item information storage unit.
Based on the borrowing related item information, the basic information of the entire borrowing calculation is generated.
Overall borrowing calculation Based on the basic information, the entire borrowing information is predicted and generated, and
The deposit / withdrawal item information generation processing unit stores the item information of the financial institution transaction information by dividing it into withdrawal items and deposit items belonging to the profit and loss calculation table, and the deposit / withdrawal item prediction information generation processing unit of the device stores the item information. Based on the information of the deposit item and the withdrawal item, the deposit / withdrawal item prediction information for which future withdrawal or deposit is predicted is generated, and the cash flow forecast information generation processing unit of the apparatus generates the deposit / withdrawal item prediction information. The cash flow forecast information is generated based on the above, the cash flow forecast information is displayed on the display unit of the device, and at least a part of the deposit / withdrawal item forecast information is from the withdrawal item information and / or the deposit item information. Borrowing information forecast and cash flow information, which is characterized by adding the fluctuation information of the corresponding month to the forecast information generated based on the trend information obtained by removing the peculiar fluctuation information of each month to obtain the trend information with fluctuation information. Control method of the provider A function to store financial institution transaction information in the financial institution transaction information storage unit in the borrowing information forecasting and cash flow information providing device.
A function that extracts borrowing-related item information from the financial institution transaction information and stores it in the borrowing-related item information storage unit.
A function to generate basic information for total borrowing calculation based on the borrowing-related item information,
A function that predicts and generates overall borrowing information based on the above basic borrowing calculation information,
A function to store the item information of the financial institution transaction information by dividing it into withdrawal items and deposit items belonging to the profit and loss statement.
A function to generate deposit / withdrawal item prediction information for which future withdrawals or deposits are predicted based on the information of the deposit items and the withdrawal items.
A function to generate cash flow forecast information based on the deposit / withdrawal item forecast information,
The function of displaying the cash flow forecast information on the display unit, at least a part of the deposit / withdrawal item forecast information, is the tendency information obtained by removing the monthly peculiar fluctuation information from the withdrawal item information and / or the deposit item information. Borrowing information forecasting and cash flow information provision program, which is characterized in that it is configured to execute a function of adding the fluctuation information of the corresponding month to the forecast information generated based on the above to obtain trend information with fluctuation information. ..

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