JP7560075B2 - Cash management device, cash management method and program - Google Patents

Description

This disclosure relates to a cash management device, a cash management method, and a program.

A cash management system has been proposed in which a cash management server is installed in the central department of a financial institution, and the cash balances at each branch are managed centrally (see, for example, Patent Document 1). The cash management server is connected to the open teller machines installed at each branch via a communication line. The open teller machines store cash and manage its deposits and withdrawals, and also manage the deposits and withdrawals at safes, counter cash machines, and currency exchange machines installed at the branch. In this type of cash management system, the amount of funds required for the next business day is predicted based on the history of cash data, and the cash transport route is calculated based on this predicted amount.

JP 2003-168001 A

However, when transporting cash, it is necessary to use a cash transport vehicle and to have security guards accompany the transport. Therefore, frequent transport of cash is costly. On the other hand, reducing the frequency of cash transport increases the amount of cash on hand at branches, which increases the burden of tasks such as checking the amount of cash on hand at branches.
An object of the present disclosure is to provide a cash management device, a cash management method, and a program that can efficiently manage cash in a store.

According to a first aspect of the present invention, the cash inventory management device includes an acquisition unit that acquires transaction data related to cash transactions in a store, and a calculation unit that calculates, for each of a plurality of transport patterns with different timings for carrying out cash transport, a proposed transport amount, which is the amount of cash to be transported to achieve a cash inventory corresponding to the cash transaction, based on the transaction data.

According to a second aspect of the present invention, a cash management method includes a step in which a cash management device acquires transaction data related to cash transactions in a store, and a step in which the cash management device calculates, for each of a plurality of transport patterns having different timings for carrying out cash transport, a proposed transport amount, which is the amount of cash to be transported to achieve a cash inventory corresponding to the cash transaction, based on the transaction data.

According to a third aspect of the present invention, the program causes a computer to execute a step of acquiring transaction data regarding cash transactions in a store, and a step of calculating, for each of a plurality of transport patterns with different timings for carrying out cash transport, a proposed transport amount, which is the amount of cash to be transported in order to achieve a cash inventory amount corresponding to the cash transaction, based on the transaction data.

According to at least one of the above aspects, the cash management device can efficiently manage the cash balance in the store.

1 is a schematic diagram showing a configuration of a bank system according to a first embodiment. FIG. 4 is a diagram showing an example of transaction data according to the first embodiment; 1 is a schematic block diagram showing the configuration of a cash inventory management device according to a first embodiment. FIG. 10 is a flowchart showing an offset determination process according to the first embodiment. 5 is a flowchart showing a process for comparing a performance transport volume with a proposed transport volume according to the first embodiment; 13 is an example of a first output screen related to a comparison process between a performance transportation volume and a proposed transportation volume according to the first embodiment. 13 is an example of a second output screen related to a comparison process between a performance transportation volume and a proposed transportation volume according to the first embodiment. 10 is a flowchart showing a calculation process of a proposed future transportation volume according to the first embodiment. 10 is a flowchart showing a process for comparing inventory amounts between stores according to the first embodiment. 13 is an example of a similar store search screen according to the first embodiment. FIG. 1 is a schematic block diagram illustrating a configuration of a computer according to at least one embodiment.

First Embodiment
<<Configuration of Bank System 1>>
Hereinafter, the embodiments will be described in detail with reference to the drawings.
FIG. 1 is a schematic diagram showing the configuration of a bank system 1 according to the first embodiment.
The bank system 1 according to the first embodiment has a head office 11 and a plurality of business offices 12. Each business office 12 is provided with a cash processing machine 100 that handles cash transactions such as a counter currency deposit and withdrawal machine (auto cashier) and a currency exchange machine, a teller machine 200 that manages the cash on hand at the business office, and a cash management device 300 that predicts the cash on hand required at the business office and optimizes the cash on hand. The cash processing machines 100, the teller machine 200, and the cash management device 300 are connected to each other via a local network of the business office 12.

In order to keep the cash balance at an appropriate level, each branch 12 transports cash between itself and the head office 11. That is, when a cash shortage is expected due to future cash transactions, the branch 12 receives cash from the head office 11, and when a cash surplus is expected due to future cash transactions, the branch 12 sends cash to the head office 11. Cash transport is carried out by a security company using a cash transport vehicle. Hereinafter, the number or amount of each denomination of cash transported is referred to as the transport volume.

The teller machine 200 accepts deposit/withdrawal operations by an operator, and accepts deposits and withdrawals of cash held by the teller machine 200 in response to the deposit/withdrawal operations. At this time, the teller machine 200 generates transaction data related to the deposit/withdrawal operations. The teller machine 200 also collects transaction data related to cash transactions from each cash processing machine 100 via the local network. As a result, transaction data related to cash transactions in the entire branch 12 is stored in the internal database of the teller machine 200.
FIG. 2 is a diagram illustrating an example of transaction data according to the first embodiment.
The transaction data includes the transaction date and time, whether it is a deposit or withdrawal, the transaction type, and the transaction amount (number of notes transacted) for each denomination. The transaction data also includes transportation data indicating the amount of money received in relation to cash transportation. The transaction type of the transportation data indicates actual receipt or actual transfer. In other embodiments, the transaction data by the cash handling machine 100 and the transportation data may be managed separately.

<<Configuration of balance management device 300>>
FIG. 3 is a schematic block diagram showing the configuration of the money management device 300 according to the first embodiment.
The cash management device 300 includes an acquisition unit 301 , a prediction unit 302 , an offset determination unit 303 , an input unit 304 , a calculation unit 305 , an evaluation unit 306 , and an output unit 307 .

The acquisition unit 301 acquires transaction data and transportation data from the internal database of the cash register 200.
The prediction unit 302 generates predicted transaction data indicating transaction data for a predetermined future period based on the transaction data acquired by the acquisition unit 301. The prediction unit 302 generates predicted transaction data using a trained model in which coefficients have been determined by learning using, for example, past transaction data acquired by the acquisition unit 301 as a learning dataset. The trained model for generating predicted transaction data may be trained by supervised learning in which, for example, the date, total withdrawal amount, and minimum number of each day in the first period are input samples, and the date, total withdrawal amount, and minimum number of each day in the second period immediately following the first period are output samples. Here, the minimum number refers to the lowest value among the transitions of the difference in the number of transactions due to deposits and withdrawals in one day, that is, the minimum value of cash fluctuation. The date, total withdrawal amount, and minimum number of each day in the second period are examples of predicted transaction data. Examples of the trained model include a random forest model and a neural network model. The trained model has coefficients determined by machine learning and a trained model that is an algorithm.

The offset determination unit 303 determines an offset value of the amount of cash to compensate for the prediction error of the predicted transaction data based on the dispersion of the difference between the actual transaction data acquired by the acquisition unit 301 and the predicted transaction data generated by the prediction unit 302. For example, the offset determination unit 303 calculates the standard deviation σ between the monthly transaction data and the predicted transaction data, and determines the amount of cash equivalent to 3σ as the offset value for that month.

The input unit 304 accepts inputs from user operations. Specifically, the input unit 304 accepts inputs of instructions to compare actual transport volumes with proposed transport volumes, inputs of instructions to calculate proposed future transport volumes, inputs of the timing of cash transport, and inputs of instructions to compare inventory between stores. The actual transport volume is the transport volume indicated by the transport data acquired by the acquisition unit 301.

The calculation unit 305 calculates the amount of cash to be transported at the cash transport timing input to the input unit 304 based on the predicted transaction data predicted by the prediction unit 302. That is, the calculation unit 305 calculates the proposed transport amount. The calculation unit 305 calculates the cash inventory when the cash transport is performed for each of the proposed transport amount and the actual transport amount based on the transaction data acquired by the acquisition unit 301.

The evaluation unit 306 calculates an evaluation value indicating the appropriateness of the proposed transport volume based on the actual transport volume, the proposed transport volume, and the cash inventory when cash transports related to each of the proposed transport volume and the actual transport volume were performed. Examples of evaluation values include inventory reduction rate and transport count reduction rate. The inventory reduction rate is calculated by dividing the difference between the cash inventory based on the actual transport volume and the cash inventory based on the proposed transport volume by the cash inventory based on the actual transport volume. The transport count reduction rate is calculated by dividing the difference between the number of transports related to the actual transport volume and the number of transports related to the proposed transport volume by the number of transports related to the actual transport volume.

The output unit 307 outputs the proposed transport volume, actual transport volume, and cash balance at the time of cash transport relating to each of the proposed transport volume and actual transport volume calculated by the calculation unit 305, as well as the evaluation value calculated by the evaluation unit 306. Examples of output by the output unit 307 include displaying on a display, printing on a sheet, and recording on a storage medium.

<Offset Determination Process>
The following describes the operation of the inventory management device 300. The inventory management device 300 determines an offset value for the calculated transportation volume before executing the initial calculation process of the proposed transportation volume. Fig. 4 is a flowchart showing the offset determination process according to the first embodiment.
First, the acquisition unit 301 of the cash management device 300 acquires transaction data for a predetermined period in the past from the cash dispenser 200 (step S1). The period for which transaction data is acquired may be, for example, one year or more. Next, the prediction unit 302 generates predicted transaction data for a plurality of different periods (for example, one month) based on the acquired transaction data (step S2). As described above, the prediction unit 302 generates predicted transaction data for each day for the second period. The offset determination unit 303 compares the predicted transaction data for each day for the plurality of periods generated in step S2 with the actual transaction data for the same day, and calculates the difference (step S3). The offset determination unit 303 determines an offset value for each period (for example, each month) based on the difference between the plurality of predicted transaction data and the actual transaction data (step S4). For example, the offset determination unit 303 calculates the standard deviation σ of the difference between the daily transaction data and the predicted transaction data for each month, and determines the amount of cash equivalent to 3σ as the offset value for that month.

<Comparison of actual transport volume and proposed transport volume>
When the inventory management device 300 receives an input of an instruction to compare the actual transportation volume and the proposed transportation volume from a user, the inventory management device 300 starts a process of comparing the actual transportation volume and the proposed transportation volume.

FIG. 5 is a flowchart showing the process of comparing the actual transportation volume and the proposed transportation volume according to the first embodiment.
The input unit 304 of the cash inventory management device 300 accepts input of a target period for comparison of the transportation amount and a pattern of the timing of cash transportation (step S31). The input unit 304 accepts input of a pattern of the timing of cash transportation, for example, by specifying the number of interval days between transportation timings or one or more days of the week for the transportation timings. The target period is a past period and has a length equivalent to the second period predicted by the prediction unit 302. For example, when the prediction unit 302 predicts transaction data for one month, the length of the target period is one month.

The acquisition unit 301 acquires transaction data and transportation data relating to the target period input in step S31 and a specified prediction period immediately preceding the target period (step S32). For example, when the prediction unit 302 uses one month's worth of transaction data to predict the immediately following one month's worth of transaction data, the acquisition unit 301 acquires transaction data for the target period and the one month immediately preceding the target period. Next, the prediction unit 302 generates predicted transaction data for the target period based on the transaction data for the prediction period acquired in step S32 (step S33).

The calculation unit 305 calculates a proposed transportation amount for the pattern of cash transport timing input in step S31 based on the predicted transaction data generated in step S33 (step S34). For example, the calculation unit 305 calculates the proposed transportation amount in the following procedure. For each cash transport timing specified by the pattern, the calculation unit 305 calculates a sum of the minimum number of bills from the cash transport timing to the next cash transport timing based on the minimum number of bills per day related to the target period indicated by the predicted transaction data. The calculation unit 305 calculates a value obtained by adding the calculated sum of the minimum number of bills to the offset value of the month related to the cash transport timing, as the proposed transportation amount.
Based on the transaction data acquired in step S32, the calculation unit 305 calculates the daily cash balance when cash is transported according to the proposed transportation volume calculated in step S34 (step S35). Hereinafter, the cash balance when cash is transported according to the proposed transportation volume is also referred to as a predicted cash balance value.

Based on the transaction data acquired in step S32, the calculation unit 305 calculates the cash inventory when the cash transport related to the actual transport amount based on the transport data acquired in step S32 is performed (step S36). Hereinafter, the cash inventory when the cash transport related to the actual transport amount is performed is also referred to as the inventory actual value.

The evaluation unit 306 calculates an evaluation value based on the predicted inventory value calculated in step S35 and the actual inventory value calculated in step S36 (step S37). The output unit 307 then outputs a screen displaying the proposed transport volume calculated in step S34, the predicted inventory value calculated in step S35, the actual transport volume based on the transport data acquired in step S32, the actual inventory value calculated in step S36, and the evaluation value calculated in step S37 (step S38).

6 is an example of a first output screen related to a comparison process between a performance transport volume and a proposed transport volume according to the first embodiment. The first output screen is a screen for comparing the transition of the cash balance and the minimum number of bills based on the performance transport volume and the proposed transport volume.
7 is an example of a second output screen related to a comparison process between the actual transport volume and the proposed transport volume according to the first embodiment. The second output screen is a screen for comparing the transition of the transport timing, the transport volume, and the cash inventory based on the actual transport volume and the proposed transport volume.

The output unit 307 switches between, for example, a first output screen shown in FIG. 6 and a second output screen shown in FIG.
The first output screen includes a first actual result graph showing the actual changes in the cash amount and the minimum number of bills for the target period, a first forecast graph showing the changes in the cash amount and the minimum number of bills based on the proposed transport volume for the target period and the predicted withdrawal number based on the predicted transaction data, an income/expense graph showing the actual changes in the number of transactions for the target period, and a cash reduction rate as an evaluation value. By visually checking the first output screen, the user can consider the cash reduction rate due to the proposed transport volume and the validity of the proposed transport volume. In addition, in the first forecast graph, if the minimum number of bills does not exceed the predicted withdrawal number to which an offset is added for each day, it can be seen that the proposed transport volume will not cause a depletion of cash amount.

The second output screen includes a second actual result graph showing the actual trends in cash on hand, the number of bills currently sent, and the number of bills currently received for the target period, a second forecast graph showing the actual trends in cash on hand, the number of bills currently sent, and the number of bills currently received based on the proposed transportation volume for the target period, a balance graph showing the actual trends in the number of transactions for the target period, and the reduction rate of the number of bills currently sent and the reduction rate of the number of bills currently received as evaluation values. By visually checking the second output screen, the user can consider the appropriateness of the frequency of cash transport.

The input unit 304 of the cash management device 300 can accept input of other cash transport timings after calculating the proposed transport amount based on the cash transport timing input in step S1 in the above process. In this case, the cash management device 300 calculates the proposed transport amount based on the cash transport timing in steps S31 to S39 described above. That is, the cash management device 300 can calculate the proposed transport amount for each of multiple transport patterns with different cash transport timings. This allows the user to consider the appropriate cash transport timing for each store.

《Calculation process for future proposed transportation volume》
After the user considers the appropriate cash transport timing for each store in the above-mentioned process of comparing the actual transport volume and the proposed transport volume, the user operates the cash management device 300 and inputs an instruction to calculate the proposed future transport volume.
When the inventory management device 300 receives an instruction to calculate the future proposed transportation volume, the inventory management device 300 starts the calculation process of the future proposed transportation volume.

FIG. 8 is a flowchart showing the calculation process of the proposed future transportation volume according to the first embodiment.
The input unit 304 of the cash management device 300 accepts input of the timing of cash transport (step S61). The acquisition unit 301 acquires the transaction data and transport data for a predetermined prediction period immediately before the current time input in step S61 (step S62). Next, the prediction unit 302 generates predicted transaction data for a target period based on the transaction data for the prediction period acquired in step S62 (step S63).

The calculation unit 305 calculates the proposed transportation amount at the cash transportation timing input in step S61 based on the predicted transaction data generated in step S63 (step S64). Then, the output unit 307 outputs a screen displaying the proposed transportation amount calculated in step S64 (step S65).
This allows the user to determine the timing of cash transport in the store and the amount to be transported at each timing.

<Comparison of inventory between stores>
However, it may be difficult for users to recognize whether the cash balance of the managed store is an appropriate amount. This is because the size and number of transactions vary depending on the location and customers of each store, and the amount of cash that needs to be secured varies. Therefore, the cash management device 300 according to this embodiment presents the user with the relative appropriateness of the cash balance by comparing the cash balance of the target store with other stores that have similar conditions.

FIG. 9 is a flowchart showing a process for comparing inventory amounts between stores according to the first embodiment.
FIG. 10 shows an example of a similar store search screen according to the first embodiment.
When the cash management device 300 receives an input of an instruction to compare cash between stores by a user's operation, the input unit 304 displays a similar store search screen as shown in FIG. 10 on the display and receives input of narrowing down conditions for stores to be compared (step S91). The similar store search screen includes a target store setting button B1, a narrowing down condition setting button B2, a similar store display button B3, and a store list L. The input unit 304 receives input of narrowing down conditions by pressing the narrowing down condition setting button B2. Examples of categories of narrowing down conditions include total withdrawal amount, total deposit amount, total cash, average number of banknotes deposited, average number of banknotes withdrawn, average number of coins deposited, average number of coins withdrawn, average closing time, average closing time, number of operators, number of transactions, etc. Note that the multiple stores are classified in advance into five levels (L1 to L5 in the example shown in FIG. 10) for each category, and the cash management device 300 stores the classes in advance as tag data. At this time, the user can view each category class related to the target store by pressing the setting button B1 for the target store and inputting the ID of the target store into the cash management device 300.

After the narrowing down conditions are input, when the input unit 304 accepts the pressing of the Display Similar Stores button B3, the output unit 307 outputs a list L of stores that meet the input conditions (step S92). In addition to the store ID, the store list L displays the category class related to the conditions not set in step S91. This allows the user to confirm the difference between the stores narrowed down by the narrowing down conditions and the target store. The input unit 304 accepts the selection of one store from the list L of stores from the user (step S93). Next, the acquisition unit 301 acquires transaction data and transportation data from the cash dispenser 200 of the store selected in step S92 (step S94). Next, the calculation unit 305 calculates the trends in the actual transportation volume and cash on hand for the other stores based on the acquired transaction data and transportation data (step S95). Then, the output unit 307 outputs the calculated trends in the actual transportation volume and cash on hand for the other stores (step S96).

By comparing the trends in actual transport volumes and cash balances for other stores, which are output under similar conditions as the target store, with those of the target store, users can examine the appropriateness of the relative number of transports and cash balances.

<Action and Effects>
As described above, according to the first embodiment, the cash management device 300 acquires transaction data regarding cash transactions in a store, and calculates a proposed transportation amount for each of a plurality of transportation patterns that have different timings for transporting cash.
This allows users to consider appropriate transportation patterns within a store and efficiently manage cash on hand at the store.

Here, a use case of the cash management device 300 according to the first embodiment will be described. To transport cash, a cash transport vehicle must be used, and security guards must be present to perform security duties. Therefore, transporting cash is costly. Furthermore, if the amount of cash on hand at a branch is large, the burden of tasks such as checking the amount of cash on hand at the branch increases. Therefore, the user has the cash management device 300 calculate the proposed transport amount for multiple transport patterns with different transport times. This allows the user to consider a transport pattern that balances the costs of transport and the costs of managing the cash on hand at the branch. In other words, by using the cash management device 300, the user can identify a transport pattern that minimizes the sum of the costs of transport and the costs of managing the cash on hand.

The cash management device 300 also generates predicted transaction data indicating the amount of cash involved in future cash transactions based on the transaction data, and calculates a proposed transport amount based on the amount of cash involved in the predicted transaction data. This allows the user to determine an appropriate transport amount based on the predicted future cash transactions.

The cash inventory management device 300 also identifies the minimum value of daily cash fluctuations based on the predicted transaction data, and calculates the proposed transport volume by adding an offset value to this minimum value. This allows the cash inventory in the store to be optimized while compensating for errors contained in the predicted transaction data. In this embodiment, the offset is determined based on the degree of dispersion of the difference between the predicted transaction data and the actual transaction data. This allows the cash inventory management device 300 to determine an appropriate offset value that can compensate for errors.

In addition, the cash inventory management device 300 calculates an evaluation value that indicates the appropriateness of the proposed transport volume. This allows the user to recognize the degree to which the cash inventory will be optimized by adopting the proposed transport volume.

Other Embodiments
Although one embodiment has been described in detail above with reference to the drawings, the specific configuration is not limited to the above, and various design changes are possible. That is, in other embodiments, the order of the above-mentioned processes may be changed as appropriate. Also, some of the processes may be executed in parallel.
The cash management device 300 according to the embodiment described above may be configured by a single computer, or may be configured by distributing the configuration of the cash management device 300 among multiple computers, and the multiple computers may cooperate with each other to function as the cash management device 300. In this case, some of the computers constituting the cash management device 300 may be mounted inside the cash register 200, and other computers may be provided outside the cash register 200.

In addition, the inventory management device 300 according to the above embodiment allows the user to consider appropriate transportation timing based on the proposed transportation volume, but this is not limited to this in other embodiments. For example, the inventory management device 300 according to other embodiments may automatically calculate transportation timing using an optimization algorithm using gradient descent, a genetic algorithm, or the like, and present it to the user.

The cash management device 300 according to the embodiment described above calculates the minimum number of bills per day and calculates the proposed transport volume based on this, but is not limited to this. For example, the cash management device 300 according to another embodiment may directly calculate the minimum number of bills between the cash transport timing and the next cash transport timing and calculate the proposed transport volume based on this.

Computer Configuration
FIG. 11 is a schematic block diagram illustrating a configuration of a computer according to at least one embodiment.
The computer 90 comprises a processor 91 , a main memory 92 , a storage 93 , and an interface 94 .
The above-mentioned money management device 300 is implemented in a computer 90. The operations of each of the above-mentioned processing units are stored in the form of a program in a storage 93. The processor 91 reads the program from the storage 93, loads it in the main memory 92, and executes the above-mentioned processing in accordance with the program. The processor 91 also secures storage areas in the main memory 92 corresponding to each of the above-mentioned storage units in accordance with the program. Examples of the processor 91 include a CPU (Central Processing Unit), a GPU (Graphic Processing Unit), and a microprocessor.

The program may be for realizing part of the functions to be performed by the computer 90. For example, the program may be for performing the functions by combining with other programs already stored in the storage or by combining with other programs implemented in other devices. In other embodiments, the computer 90 may be provided with a custom LSI (Large Scale Integrated Circuit) such as a PLD (Programmable Logic Device) in addition to or instead of the above configuration. Examples of PLDs include PAL (Programmable Array Logic), GAL (Generic Array Logic), CPLD (Complex Programmable Logic Device), and FPGA (Field Programmable Gate Array). In this case, some or all of the functions realized by the processor 91 may be realized by the integrated circuit. Such integrated circuits are also included as examples of processors.

Examples of storage 93 include a magnetic disk, a magneto-optical disk, an optical disk, and a semiconductor memory. Storage 93 may be an internal medium directly connected to the bus of computer 90, or an external medium connected to computer 90 via interface 94 or a communication line. In addition, when this program is distributed to computer 90 via a communication line, computer 90 that receives the program may expand the program into main memory 92 and execute the above-mentioned processing. In at least one embodiment, storage 93 is a non-transitory tangible storage medium.

The program may be for realizing part of the above-mentioned functions. Furthermore, the program may be a so-called differential file (differential program) that realizes the above-mentioned functions in combination with another program already stored in storage 93.

1...Bank system 11...Head office 12...Business office 100...Cash processing machine 200...Teller 300...Inventory management device 301...Acquisition unit 302...Prediction unit 303...Offset determination unit 304...Input unit 305...Calculation unit 306...Evaluation unit 307...Output unit

Claims (8)

an acquisition unit that acquires transaction data regarding cash transactions at the target store and at least one comparison store narrowed down from the plurality of stores according to the narrowing down conditions;
a calculation unit that calculates the trends in actual transportation volume and cash in handover amount for the target store and the comparison store based on the transaction data;
an output unit that outputs the transition of the actual transportation amount and the cash amount for the target store and the comparison target store;
A cash management device comprising: The inventory management device of claim 1, wherein the narrowing conditions include at least one of the following categories per unit period: total withdrawal amount, total deposit amount, total inventory amount, average number of banknotes deposited, average number of banknotes withdrawn, average number of coins deposited, average number of coins withdrawn, number of operators, and number of transactions. The plurality of stores are pre-classified according to the category,
The cash management device according to claim 2 , wherein the output unit displays a class of the category related to the target store. The cash management device according to claim 3 , wherein the output unit outputs a list of stores that meet the narrowing conditions, and further outputs to the list of stores classes of categories related to conditions not set in the narrowing conditions. The cash inventory management device of claim 1, wherein the calculation unit calculates a proposed transportation amount, which is the amount of cash to be transported in order to achieve a cash inventory corresponding to the cash transaction, for each of a plurality of transportation patterns having different timings for carrying out cash transportation, based on the transaction data of the target store. a prediction unit that generates predicted transaction data indicating an amount of cash involved in future cash transactions based on the transaction data of the target store;
The cash inventory management device according to claim 5 , wherein the calculation unit calculates the proposed transportation amount based on an amount of cash related to the predicted transaction data. A step in which the computer acquires transaction data regarding cash transactions at the target store and at least one comparison store narrowed down from the plurality of stores using the narrowing-down conditions;
The computer calculates the trends of actual transportation volume and cash in handover amount for the target store and the comparison store based on the transaction data;
a step of outputting the transition of the actual transportation volume and the cash amount for the target store and the comparison target store by the computer ;
A method for managing inventory. On the computer,
acquiring transaction data regarding cash transactions at the target store and at least one comparison store narrowed down from among the plurality of stores using the narrowing-down conditions;
calculating a transition of actual transportation volume and cash in hand for the target store and the comparison store based on the transaction data;
outputting the transition of the actual transportation volume and the cash amount for the target store and the comparison store;
A program for executing.

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