Guarantee fee revenue forecasting device, guarantee fee revenue forecasting method, and guarantee fee revenue forecasting program

Abstract

To provide a guarantee fee profit predicting device, a guarantee fee profit predicting method and a guarantee fee profit predicting program that enable a prediction for a guarantee fee profit in accordance with a future balance before repayment from information coordinated from a financial agency at a timing at which the contract of a guarantee is settled.SOLUTION: A guarantee fee profit predicting device according to this embodiment includes a control unit. The control unit is accessible to contract data and a guarantee fee managing master. The control unit includes: a guarantee fee calculating unit that calculates a lump-sum guarantee fee based on the contract data and on the guarantee fee managing master; an expanding unit that creates repayment schedule data based on the contract data and on applied-time guarantee contract data; a totalizing unit that calculates a balance cumulative number total from the balance cumulative number for each month in the repayment schedule data; a guarantee annual rate calculating unit that calculates a guarantee annual rate by dividing the lump-sum guarantee fee by the balance cumulative number total; and a predicting unit that predicts the guarantee fee profit based on the balance before repayment for each month in the repayment schedule data, and on the guarantee annual rate of the guarantee contract data.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a guarantee fee revenue prediction device, a guarantee fee revenue prediction method, and a guarantee fee revenue prediction program. [Background technology]

[0002] Traditionally, guarantee companies have received guarantee fees in advance from financial institutions in one lump sum, and the guarantee fee revenue recorded by the guarantee company is determined by dividing it proportionately according to the monthly balance. For example, the monthly balance is determined by file sharing once a month with the guaranteeing financial institution. However, the guarantee fee is calculated based on the actual balance for the most recent month shared monthly by the financial institution, and future guarantee fee revenue cannot be calculated.

[0003] Patent Document 1 discloses a lease installment guarantee system that provides trade credit insurance to installment receivables at the time of a lease installment contract to help guarantee the installment contract, and discloses a configuration in which the trade credit insurance premium is set for the remaining installment receivables at the time of the lease installment contract. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2002-312700 Summary of the Invention [Problem to be solved by the invention]

[0005] However, in the past, there was a problem in that it was not possible to predict guarantee fee revenue based on future pre-repayment balances from the information shared by financial institutions at the time the guarantee contract was finalized.

[0006] The present invention has been made in consideration of the above-mentioned problems, and aims to provide a guarantee fee revenue prediction device, a guarantee fee revenue prediction method, and a guarantee fee revenue prediction program that can predict guarantee fee revenue based on future pre-repayment balances from information shared by financial institutions at the time the guarantee contract is finalized. [Means for solving the problem]

[0007] In order to solve the above-mentioned problems and achieve the object, the guarantee fee revenue forecasting device of the present invention is a guarantee fee revenue forecasting device that includes a control unit, the control unit being able to access contract data including at least customer identification information, loan amount, loan interest rate, first repayment year and month, and final repayment year and month, and a guarantee fee management master in which at least the number of years of borrowing, customer credit information, and guarantee fee per unit yen are set, the control unit being provided with a guarantee fee calculation unit that calculates a lump-sum guarantee fee based on the contract data and the guarantee fee management master, and creates application-time guarantee contract data including at least the guarantee period, guarantee amount, customer credit information, and the lump-sum guarantee fee, and a guarantee fee calculation unit that calculates each month's pre-repayment balance based on the contract data and the application-time guarantee contract data. The system is characterized by comprising: an expansion unit that expands the repayment schedule data and creates scheduled repayment data including at least the number of repayments, the repayment date, the balance before repayment for each month, the number of days elapsed since the last repayment date, and the accumulated balance for each month; a totalization unit that calculates the total accumulated balance from the accumulated balance for each month of the scheduled repayment data; a guaranteed annual rate calculation unit that calculates the guaranteed annual rate by dividing the lump-sum guarantee fee by the total accumulated balance and creates guarantee contract data including at least customer identification information and the guaranteed annual rate; and a prediction unit that predicts guarantee fee revenue based on the balance before repayment for each month of the scheduled repayment data and the guaranteed annual rate of the guarantee contract data, and creates scheduled guarantee fee revenue data including at least the number of repayments and the guarantee fee revenue.

[0008] According to one aspect of the present invention, the guarantee fee per unit yen is a guarantee fee per 1 million yen, and the guarantee fee calculation unit calculates the lump-sum guarantee fee by multiplying the guarantee fee per 1 million yen by the loan amount divided by 1 million.

[0009] According to one aspect of the present invention, the developing unit calculates the balance product for each month by (the balance before repayment)×(the number of days elapsed)÷365.

[0010] According to one aspect of the present invention, the prediction unit predicts the guarantee fee income for each month by multiplying the balance before repayment for each month by the guaranteed annual rate by 12.

[0011] According to one aspect of the present invention, the customer credit information is a course selected based on the customer's creditworthiness, and the guarantee fee per unit yen is set according to the loan term and the course.

[0012] The guarantee fee revenue prediction method according to the present invention includes the steps of: a guarantee fee revenue prediction device accessing contract data including at least customer identification information, loan amount, loan interest rate, first repayment date, and final repayment date; a step of the guarantee fee revenue prediction device accessing a guarantee fee management master in which at least the number of years of borrowing, customer credit information, and guarantee fee per unit yen are set; a step of the guarantee fee revenue prediction device calculating a lump-sum guarantee fee based on the contract data and the guarantee fee management master, and creating guarantee contract data at the time of application including at least the guarantee period, guarantee amount, customer credit information, and the lump-sum guarantee fee; and a step of the guarantee fee revenue prediction device expanding the balance before repayment for each month based on the contract data and the guarantee contract data at the time of application, and calculating the number of repayments, the repayment date, and the lump-sum guarantee fee. The method includes the steps of: creating scheduled repayment data including at least the balance before repayment for each month, the number of days elapsed since the last repayment date, and the accumulated balance for each month; the guarantee fee revenue prediction device calculating a total accumulated balance from the accumulated balance for each month of the scheduled repayment data; the guarantee fee revenue prediction device calculating the annual guaranteed rate by dividing the lump-sum guarantee fee by the total accumulated balance, and creating guarantee contract data including at least customer identification information and the annual guaranteed rate; and the guarantee fee revenue prediction device predicting guarantee fee revenue based on the balance before repayment for each month of the scheduled repayment data and the annual guaranteed rate of the guarantee contract data, and creating scheduled guarantee fee revenue data including at least the number of repayments and the guarantee fee revenue.

[0013] The guarantee fee revenue forecasting program of the present invention includes the steps of: accessing contract data including at least customer identification information, loan amount, loan interest rate, first repayment date, and final repayment date; accessing a guarantee fee management master in which at least the number of years of borrowing, customer credit information, and guarantee fee per unit yen are set; calculating a lump-sum guarantee fee based on the contract data and the guarantee fee management master; and creating guarantee contract data at the time of application including at least the guarantee period, guarantee amount, customer credit information, and the lump-sum guarantee fee; and expanding the balance before repayment for each month based on the contract data and the guarantee contract data at the time of application, and calculating the number of repayments, the repayment date, and the The system is characterized by executing the following steps: creating scheduled repayment data including at least the balance before repayment for each month, the number of days elapsed since the last repayment date, and the accumulated balance for each month; calculating the total accumulated balance from the accumulated balance for each month of the scheduled repayment data; calculating the annual guaranteed rate by dividing the lump-sum guarantee fee by the total accumulated balance, and creating guarantee contract data including at least customer identification information and the annual guaranteed rate; and predicting guarantee fee revenue based on the balance before repayment for each month of the scheduled repayment data and the annual guaranteed rate of the guarantee contract data, and creating scheduled guarantee fee revenue data including at least the number of repayments and the guarantee fee revenue. [Effects of the Invention]

[0014] According to the present invention, it is possible to predict future guarantee fee income based on the pre-repayment balance from information provided by financial institutions at the time the guarantee contract is finalized. [Brief explanation of the drawings]

[0015] [Figure 1] Figure 1 shows an example of how guarantee fee revenue is recorded in the past. [Figure 2] FIG. 2 is a block diagram illustrating an example of the configuration of a guarantee fee revenue prediction device according to the embodiment. [Figure 3] FIG. 3 is a diagram illustrating an example of contract data according to the embodiment. [Figure 4] FIG. 4 is a diagram illustrating an example of the guarantee fee management master according to the embodiment. [Figure 5] FIG. 5 is a diagram illustrating an example of guarantee contract data at the time of application according to the embodiment. [Figure 6] FIG. 6 is a diagram illustrating an example of repayment schedule data according to the embodiment. [Figure 7] FIG. 7 is a diagram illustrating an example of warranty contract data according to the embodiment. [Figure 8] FIG. 8 is a diagram illustrating an example of guarantee fee income forecast data according to the embodiment. [Figure 9] FIG. 9 is a diagram illustrating an example of a data flow of the guarantee fee income prediction process according to the embodiment. [Figure 10] FIG. 10 is a flowchart illustrating an example of a guarantee fee income prediction process according to the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0016] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described in detail with reference to the accompanying drawings. However, the present invention is not limited to this embodiment.

[0017] [1. Overview] First, an outline of the present invention will be described.

[0018] Figure 1 shows an example of how guarantee fee revenue is traditionally recorded. Every month, financial institutions share information for the previous month, including the repayment period, loan interest rate, loan date, and loan balance, with the guarantee company. Based on the loan balance for the target month shared with them each month by the financial institution, the guarantee company calculates the monthly guarantee fee revenue by multiplying the pre-repayment balance (actual balance) by the guarantee fee rate.

[0019] In order to calculate future guarantee fee revenue, it is necessary to know the monthly balance for future installments as well. However, in most cases, it was not possible to obtain repayment schedules from financial institutions, for example, because financial institutions did not retain such schedules as data. Therefore, until now, guarantee companies only retained balance information for the month provided by financial institutions. In other words, since repayment schedules were not retained, it was only possible to calculate guarantee fee revenue for the most recent month provided by financial institutions.

[0020] The guarantee fee revenue prediction device of this embodiment holds the future planned balance by developing the repayment schedule from the loan amount, repayment period, and interest rate shared by the financial institution when the guarantee contract is finalized.The guarantee fee revenue prediction device of this embodiment then calculates the future guarantee fee revenue from the future planned balance and the annual guarantee rate (= guarantee fee ÷ total balance product).

[0021] According to the guarantee fee revenue prediction device of this embodiment, by developing a repayment schedule based on information received from financial institutions, it is possible to grasp the expected monthly balance and calculate the guarantee fee according to that balance. Since guarantor companies cannot obtain repayment schedules from financial institutions, it has been difficult for them to grasp future revenues, but by developing the repayment schedule, it is possible to simulate future revenues. Understanding future revenues using this simulation function (future prediction function for guarantee fee revenues) is useful for making management decisions.

[0022] [2. Configuration] An example of the configuration of the guarantee fee revenue prediction device 100 according to this embodiment will be described with reference to Fig. 2. Fig. 2 is a block diagram showing an example of the configuration of the guarantee fee revenue prediction device 100.

[0023] The guarantee fee revenue prediction device 100 is a commercially available desktop personal computer. The guarantee fee revenue prediction device 100 is not limited to a stationary information processing device such as a desktop personal computer, but may also be a portable information processing device such as a commercially available notebook personal computer, a PDA (Personal Digital Assistant), a smartphone, or a tablet personal computer.

[0024] The guarantee fee revenue prediction device 100 comprises a memory unit 1, a control unit 2, a communication interface unit 3, and an input / output interface unit 4. Each unit of the guarantee fee revenue prediction device 100 is connected to each other so as to be able to communicate with each other via any communication path.

[0025] Data such as various databases, tables, and files are stored in the storage unit 1. Computer programs that work in conjunction with the OS (Operating System) to issue commands to the CPU (Central Processing Unit) to perform various processes are recorded in the storage unit 1. The storage unit 1 can be, for example, a memory device such as RAM (Random Access Memory) or ROM (Read Only Memory), a fixed disk device such as a hard disk, a flexible disk, or an optical disk.

[0026] The memory unit 1 also stores contract data 1a, guarantee fee management master 1b, application guarantee contract data 1c, repayment schedule data 1d, guarantee contract data 1e, guarantee fee revenue forecast data 1f, etc. Details of the contract data 1a, guarantee fee management master 1b, application guarantee contract data 1c, repayment schedule data 1d, guarantee contract data 1e, and guarantee fee revenue forecast data 1f will be described later with reference to Figures 3 to 8.

[0027] The control unit 2 is a CPU or the like that comprehensively controls the guarantee fee revenue prediction device 100. The control unit 2 has an internal memory for storing control programs such as an OS, programs that define various processing procedures, required data, etc., and executes various information processing based on these stored programs.

[0028] The control unit 2 includes a guarantee fee calculation unit 2a, an expansion unit 2b, a totaling unit 2c, a guarantee annual rate calculation unit 2d, and a prediction unit 2e.

[0029] The guarantee fee calculation unit 2a calculates the guarantee fee when the application information and loan information are linked from the financial institution to the guarantee fee revenue prediction device 100 of the guarantee company. The application information linked from the financial institution to the guarantee company includes, for example, the customer name, loan date, repayment period, and loan interest rate. Furthermore, the loan information linked from the financial institution to the guarantee company includes, for example, the number of years of loan, course, guarantee amount, number of years of loan, guarantee fee type, and approval / disapproval.

[0030] The method for linking the application information and loan information from the financial institution to the guarantee fee revenue prediction device 100 may be arbitrary. For example, the guarantee fee revenue prediction device 100 may accept the linkage of the application information and loan information through an operation input by an operator. Also, for example, the guarantee fee revenue prediction device 100 may accept the linkage of the application information and loan information through data communication via the network 200.

[0031] First, the guarantee fee calculation unit 2a updates the contract data 1a based on the application information and loan information linked to the guarantee fee revenue prediction device 100 from the financial institution.

[0032] 3 is a diagram showing an example of contract data 1a according to the embodiment. The contract data 1a according to the embodiment includes a customer number, a branch number, a financing date, a financing amount, a financing interest rate, a first repayment date, and a final repayment date.

[0033] The customer number (an example of customer identification information) is a number that identifies a customer. The branch number is a number that identifies multiple pieces of data when there is multiple data identified by the customer number. The loan date is the date on which the loan is executed (the date on which the loan amount is deposited). The loan amount is the amount loaned (loan amount). The loan interest rate (loan interest rate) is the ratio of interest paid to the loan amount (borrowed principal). The first repayment date is the date of the first repayment. The final repayment date is the date of the last repayment.

[0034] Next, the guarantee fee calculation unit 2a calculates the guarantee fee based on the contract data 1a and the guarantee fee management master 1b, and updates the guarantee contract data 1c at the time of application.

[0035] 4 is a diagram showing an example of the guarantee fee management master 1b of the embodiment. The guarantee fee management master 1b of the embodiment is set as a master that holds the guarantee fee per 1 million yen for each loan course and for each loan term. Specifically, the guarantee fee management master 1b of the embodiment includes the loan term, course, guarantee fee type, normal or overage, revision date, and guarantee fee (yen) per 1 million yen.

[0036] The loan term is the number of years indicating the loan period for the loaned funds. The course (an example of customer credit information) is selected based on the creditworthiness of the customer who is providing the guarantee. The set value of the guarantee fee per 1 million yen varies depending on the course. The guarantee fee type indicates a classification of lump sum (lump sum advance guarantee fee) or installment (installment guarantee fee). In the example embodiment, the guarantee fee type is set to "lump sum."

[0037] "Normal" or "Excess" is set to "Normal" or "Excess." "Normal" indicates a guarantee fee for an amount that does not exceed the collateral amount held in the guarantee fee revenue prediction device 100 of the embodiment. "Excess" indicates a guarantee fee for an amount that exceeds the collateral amount held in the guarantee fee revenue prediction device 100 of the embodiment. The revision date is the date on which the data in the guarantee fee management master 1b was revised.

[0038] Guarantee fee (yen) per 1 million (an example of a guarantee fee in yen) is the guarantee fee (yen) per 1 million. The guarantee fee (yen) per 1 million is set according to the loan term and course.

[0039] 5 is a diagram showing an example of guarantee contract data 1c at the time of application according to an embodiment. The guarantee contract data 1c at the time of application according to an embodiment includes the customer number, sub-number, application customer number, acceptance / rejection result, guarantee period, guarantee amount, course, guarantee fee type, and guarantee fee. The customer number and sub-number are the same as those explained in FIG. 3, so their explanation will be omitted. The course and guarantee fee type are the same as those explained in FIG. 4, so their explanation will be omitted.

[0040] The application customer number is a number that identifies the customer applying for a loan. In the example of the application customer number in Figure 5, it is set to the same value as the customer number. The approval / rejection result is set to whether the loan is approved or rejected (OK or NG). The guarantee period is a period equivalent to the loan period described above. The guarantee amount is an amount equivalent to the loan amount (borrowing amount) described above.

[0041] The guarantee fee is calculated as follows: (guarantee fee per 1 million yen) x (loan amount) ÷ 1 million. For example, if the loan amount (loan amount): 30,000,000 yen, loan period: 35 years, course: A, and guarantee fee type: lump sum payment, the guarantee fee is calculated using the following formula based on the guarantee fee management master 1b in Figure 4. 10,000 yen × (30,000,000 yen ÷ 1,000,000) = 300,000 yen (rounded down to the nearest yen)

[0042] Next, the expansion unit 2b expands the repayment schedule based on the contract data 1a and the application guarantee contract data 1c, and creates repayment schedule data 1d (expands the monthly planned balance).

[0043] 6 is a diagram showing an example of repayment schedule data 1d according to the embodiment. The example in FIG. 6 shows a case where the repayment schedule is developed under the following loan conditions: Loan amount: 30,000,000 yen Financing date: January 10, 2022 Repayment period: 35 years Loan interest rate: 0.5% Lump sum guarantee fee: 300,000 yen

[0044] The repayment schedule data 1d in this embodiment includes the number of repayments, repayment date, monthly repayment amount, principal payment, interest payment, balance before repayment, balance after repayment, number of days elapsed, and cumulative balance. The number of repayments is the number of repayments. The repayment date is the date on which the repayment is made. The monthly repayment amount is the monthly repayment amount. The principal payment is the amount of the monthly repayment amount that corresponds to the principal. The interest payment is the amount of the monthly repayment amount that corresponds to the interest.

[0045] The pre-payment balance is the balance before the monthly payment. The pre-payment balance is used, for example, to calculate the balance multiplier and guarantee fee income. The post-payment balance is the balance after the monthly payment. The number of days elapsed is the number of days since the last payment.

[0046] The balance product is the balance product for the number of repayments, and is calculated by (balance before repayment) x (number of days elapsed) ÷ 365. For example, the balance product for the first repayment is calculated using the following formula. 30,000,000 yen x 31 ÷ 365 = 2,547,945 (rounded down to the nearest yen)

[0047] Next, the totaling unit 2c calculates the total balance accumulated amount from the repayment schedule data 1d. In the example of Figure 6, the total balance accumulated amount is 541,855,226 yen.

[0048] Next, the annual guarantee rate calculation unit 2d calculates the annual guarantee rate by dividing the lump-sum guarantee fee in the guarantee contract data 1c at the time of application (Figure 5) and the total balance accumulated value calculated by the totaling unit 2c from the repayment schedule data 1d (Figure 6), and updates the guarantee contract data 1e.

[0049] 7 is a diagram showing an example of guarantee contract data 1e according to an embodiment. The guarantee contract data 1e according to an embodiment includes customer N, branch number, application customer No., acceptance / rejection result, guarantee period, guarantee amount, course, guarantee fee type, and guarantee fee rate. The customer N, branch number, application customer No., acceptance / rejection result, guarantee period, guarantee amount, course, and guarantee fee type are the same as those explained in FIG. 5, so explanations will be omitted.

[0050] The guarantee fee rate is a value calculated by (lump sum guarantee fee) / (total balance product). For example, in the examples of Figures 5 and 6, the annual guarantee rate is calculated using the following formula. (Guaranteed annual rate) = (lump sum guarantee fee) ÷ (total balance) =300,000 ÷ 541,855,226 ≒0.05537% (rounded up to the sixth decimal place)

[0051] Next, the prediction unit 2e predicts (expands) future profits from the monthly pre-repayment balance and the guaranteed annual interest rate, and creates the guarantee fee profit schedule data 1f.

[0052] Figure 8 is a diagram showing an example of guarantee fee revenue forecast data 1f according to an embodiment. The guarantee fee revenue forecast data 1f according to an embodiment includes the number of repayments, repayment date, monthly repayment amount, principal paid, interest paid, balance before repayment, balance after repayment, number of days elapsed, cumulative balance, annual guarantee rate, and guarantee fee revenue. The number of repayments, repayment date, monthly repayment amount, principal paid, interest paid, balance before repayment, balance after repayment, number of days elapsed, and cumulative balance are the same as those explained in Figure 6, so their explanation will be omitted. Furthermore, the annual guarantee rate is the same as that explained in Figure 7, so its explanation will be omitted.

[0053] Guarantee fee income is calculated by multiplying the balance before repayment each month by the annual guaranteed rate and dividing that by 12. For example, in the case of the first repayment, the guarantee fee income is calculated using the following formula: (Guarantee fee income) = (Balance before repayment each month) × (Guaranteed annual rate) ÷ 12 =30,000,000×0.05537%÷12 =1,384.25 ≒1,385 (rounded up to the nearest whole number)

[0054] In addition, if the contract is renewed, such as with partial early repayment, the repayment pattern will be re-developed each time and the correct guarantee fee income will be recalculated.

[0055] Returning to Fig. 1, the communication interface unit 3 communicatively connects the guarantee fee revenue prediction device 100 to the network 200 via a communication device such as a router and a wired or wireless communication line such as a dedicated line. The communication interface unit 3 has a function of communicating data with other devices via the communication line. Here, the network 200 has a function of connecting the guarantee fee revenue prediction device 100 and other devices so that they can communicate with each other, and is, for example, the Internet or a LAN (Local Area Network).

[0056] An input device 110 and an output device 120 are connected to the input / output interface unit 4. The input device 110 may be a keyboard, a mouse, a microphone, or a monitor (including a touch panel) that cooperates with the mouse to realize a pointing device function. The output device 120 may be a monitor (including a touch panel), a speaker, or a printer. The output device 120 outputs, for example, the results of processing by the control unit 2.

[0057] FIG. 9 is a diagram showing an example of the data flow of the guarantee fee revenue prediction process of the embodiment. First, based on the loan course and number of years entered on the application screen, the guarantee fee (normal guarantee fee) per 1 million yen is obtained from the guarantee fee management master 1b, and the guarantee fee (lump sum guarantee fee) is calculated. For example, the guarantee fee is calculated as (normal guarantee fee per 1 million yen) x (loan amount below the collateral valuation amount) ÷ 1 million. Then, the guarantee fee calculation unit 2a updates the application time guarantee contract data 1c.

[0058] Next, the expansion unit 2b expands the repayment schedule based on the application information and loan information linked from the financial institution to create repayment schedule data 1d. Next, the totaling unit 2c sums up the balance products of the repayment schedule data 1d to calculate the total balance product.

[0059] Next, the annual guarantee rate calculation unit 2d calculates the annual guarantee rate from the guarantee fee (lump sum guarantee fee) in the guarantee contract data 1c at the time of application and the total balance accumulated amount calculated by the totaling unit 2c from the repayment schedule data 1d, and updates the guarantee contract data 1e.

[0060] Next, the prediction unit 2e calculates the guarantee fee income for each month to simulate future guarantee fee income. In other words, since the guarantee fee income prediction device 100 of the embodiment holds the pre-repayment balance (planned balance) for each month, it is possible to simulate future guarantee fee income according to the planned balance.

[0061] 10 is a flowchart showing an example of a guarantee fee revenue forecasting process according to an embodiment. First, the guarantee fee calculation unit 2a calculates a lump-sum guarantee fee from the contract data 1a and the guarantee fee management master 1b, and creates the application guarantee contract data 1c including at least the guarantee period, the guarantee amount, the course (an example of customer credit information), and the lump-sum guarantee fee (step S1).

[0062] Next, the expansion unit 2b expands the unpaid balance for each month based on the contract data 1b and the guarantee contract data 1c at the time of application, and creates repayment schedule data 1d including at least the number of repayments, the repayment date, the unpaid balance for each month, the number of days since the last repayment date, and the accumulated balance for each month (step S2). Next, the totaling unit 2c calculates the total accumulated balance from the accumulated balance for each month in the repayment schedule data 1d (step S3).

[0063] Next, the annual guarantee rate calculation unit 2d calculates the annual guarantee rate by dividing the lump-sum guarantee fee by the total balance product, and creates guarantee contract data 1e containing at least the customer identification information and the annual guarantee rate (step S4). Next, the prediction unit 2e predicts the guarantee fee revenue for each month based on the pre-repayment balance for each month in the repayment schedule data 1d and the annual guarantee rate in the guarantee contract data 1e, and creates guarantee fee revenue schedule data 1f containing at least the number of repayments and the guarantee fee revenue (step S5).

[0064] As described above, according to the embodiment of the guarantee fee revenue prediction device 100, it is possible to predict guarantee fee revenue based on the future pre-repayment balance from information shared by financial institutions at the time the guarantee contract is finalized.

[0065] [3. Contribution to the United Nations-led Sustainable Development Goals (SDGs)] This embodiment can contribute to improving business efficiency and promoting appropriate management decisions by companies, thereby contributing to the achievement of SDGs Goals 8 and 9.

[0066] Furthermore, this embodiment can contribute to reducing waste and promoting paperless and electronic systems, thereby contributing to the achievement of SDGs Goals 12, 13, and 15.

[0067] Furthermore, this embodiment can contribute to strengthening control and governance, which can contribute to the achievement of Goal 16 of the SDGs.

[0068] 4. Other Embodiments The present invention may be implemented in various different embodiments other than those described above within the scope of the technical concept set forth in the claims.

[0069] For example, among the processes described in the embodiments, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically using known methods.

[0070] Furthermore, the processing procedures, control procedures, specific names, information including parameters such as registered data and search conditions for each process, screen examples, and database configurations shown in this specification and drawings can be changed as desired unless otherwise specified.

[0071] Furthermore, with regard to the guarantee fee revenue prediction device 100, the components shown in the figure are functional concepts, and do not necessarily have to be physically configured as shown in the figure.

[0072] For example, all or any part of the processing functions of the guarantee fee revenue prediction device 100, particularly the processing functions performed by the control unit 2, may be implemented by a CPU and a program interpreted and executed by the CPU, or may be implemented as hardware using wired logic. The program is recorded on a non-transitory computer-readable recording medium containing programmed instructions for causing an information processing device to execute the processes described in this embodiment, and is mechanically read by the guarantee fee revenue prediction device 100 as needed. That is, a computer program for providing instructions to the CPU in cooperation with the OS and performing various processes is recorded in a storage unit such as a ROM or HDD (Hard Disk Drive). This computer program is executed by being loaded into RAM, and cooperates with the CPU to form the control unit.

[0073] In addition, this computer program may be stored in an application program server connected to the guarantee fee revenue prediction device 100 via any network, and all or part of it may be downloaded as needed.

[0074] Furthermore, the program for executing the processes described in this embodiment may be stored in a non-transitory computer-readable recording medium or configured as a program product. Here, the term "recording medium" includes any "portable physical medium" such as a memory card, a Universal Serial Bus (USB) memory, a Secure Digital (SD) card, a flexible disk, a magneto-optical disk, a ROM, an Erasable Programmable Read Only Memory (EPROM), an Electrically Erasable and Programmable Read Only Memory (EEPROM (registered trademark)), a Compact Disk Read Only Memory (CD-ROM), a Magneto-Optical disk (MO), a Digital Versatile Disk (DVD), and a Blu-ray (registered trademark) disc.

[0075] Furthermore, a "program" is a data processing method written in any language or description method, and does not matter whether it is in the form of source code or binary code. Note that a "program" is not necessarily limited to a single structure, but also includes a structure that is distributed as multiple modules or libraries, or a structure that achieves its function by cooperating with a separate program, such as an OS. Note that the specific configuration and reading procedure for reading a recording medium in each device shown in this embodiment, as well as the installation procedure after reading, can use well-known configurations and procedures.

[0076] The various databases stored in the memory unit 1 are storage means such as memory devices such as RAM and ROM, fixed disk devices such as hard disks, flexible disks, and optical disks, and store various programs, tables, databases, and web page files used for various processes and providing websites.

[0077] The guarantee fee revenue prediction device 100 may be configured as an information processing device such as a known personal computer or workstation, or may be configured as the information processing device to which any peripheral device is connected. The guarantee fee revenue prediction device 100 may be realized by installing software (including programs or data, etc.) that causes the device to realize the processing described in this embodiment.

[0078] Furthermore, the specific form of distribution and integration of the devices is not limited to that shown in the drawings, and all or part of them can be configured by functionally or physically distributing and integrating them in any unit depending on various additions or functional loads. In other words, the above-described embodiments can be implemented in any combination, or embodiments can be implemented selectively. [Industrial Applicability]

[0079] The present invention is useful in credit guarantee operations for loans from financial institutions, such as housing loans. [Explanation of symbols]

[0080] 100 Guarantee fee revenue forecasting device 1 Storage section 1a Contract Data 1b Guarantee fee management master 1c Guaranteed contract data at the time of application 1d Repayment schedule data 1e Warranty contract data 1f Guarantee fee revenue forecast data 2. Control Unit 2a Memory control unit 2b Setting section 2c Changes 3. Communication interface section 4 Input / Output Interface Section 110 Input Device 120 Output Device 200 Network

Claims

1. A guarantee fee revenue prediction device including a control unit, The control unit contract data including at least customer identification information, loan amount, loan interest rate, first repayment date, and final repayment date; The guarantee fee management master in which at least the loan term, customer credit information, and guarantee fee per unit yen are set is accessible; The control unit a guarantee fee calculation unit that calculates a lump-sum guarantee fee based on the contract data and the guarantee fee management master, and creates guarantee contract data at the time of application that includes at least the guarantee period, the guarantee amount, the customer credit information, and the lump-sum guarantee fee; an expansion unit that expands the balance before repayment for each month based on the contract data and the guarantee contract data at the time of application, and creates repayment schedule data that includes at least the number of repayments, the repayment date, the balance before repayment for each month, the number of days that have passed since the last repayment date, and the cumulative balance for each month; a totaling unit that calculates a total balance product from the balance product of each month of the repayment schedule data; a guarantee annual rate calculation unit that calculates the guarantee annual rate by dividing the lump-sum guarantee fee by the total balance product and creates guarantee contract data that includes at least customer identification information and the guarantee annual rate; a prediction unit that predicts guarantee fee income based on the balance before repayment for each month of the repayment schedule data and the annual guarantee rate of the guarantee contract data, and creates guarantee fee income schedule data that includes at least the number of repayments and the guarantee fee income; A guarantee fee revenue prediction device comprising:

2. The guarantee fee per unit yen is the guarantee fee per 1 million yen, The guarantee fee revenue prediction device of claim 1, characterized in that the guarantee fee calculation unit calculates the lump-sum guarantee fee by (guarantee fee per 1 million yen) x (the loan amount) ÷ 1 million.

3. 3. The guarantee fee revenue prediction device according to claim 1, wherein the expansion unit calculates the balance product for each month by (the balance before repayment) x (the number of days elapsed) ÷ 365.

4. The guarantee fee revenue prediction device described in claim 1 or 2, characterized in that the prediction unit predicts the guarantee fee revenue for each month by (the balance before repayment for each month) x (the annual guarantee rate) ÷ 12.

5. The customer credit information is a course selected according to the customer's creditworthiness, 3. The guarantee fee revenue prediction device according to claim 1, wherein the guarantee fee per unit yen is set according to the number of years of the loan and the course.

6. a step in which the guarantee fee revenue prediction device accesses contract data including at least customer identification information, loan amount, loan interest rate, first repayment date, and final repayment date; a step in which the guarantee fee revenue prediction device accesses a guarantee fee management master in which at least the number of years of borrowing, customer credit information, and guarantee fee per unit yen are set; The guarantee fee revenue prediction device calculates a lump-sum guarantee fee based on the contract data and the guarantee fee management master, and creates guarantee contract data at the time of application that includes at least the guarantee period, the guarantee amount, customer credit information, and the lump-sum guarantee fee; The guarantee fee revenue prediction device develops the balance before repayment for each month based on the contract data and the guarantee contract data at the time of application, and creates repayment schedule data including at least the number of repayments, the repayment date, the balance before repayment for each month, the number of days elapsed since the last repayment date, and the cumulative balance for each month; a step in which the guarantee fee income prediction device calculates a total balance accumulation figure from the balance accumulation figure for each month of the repayment schedule data; the guarantee fee revenue prediction device calculates an annual guarantee rate by dividing the lump-sum guarantee fee by the total balance product, and creates guarantee contract data including at least customer identification information and the annual guarantee rate; The guarantee fee income prediction device predicts the guarantee fee income based on the balance before repayment for each month of the repayment schedule data and the annual guarantee rate of the guarantee contract data, and creates guarantee fee income schedule data including at least the number of repayments and the guarantee fee income; A method for predicting guarantee fee revenue, comprising:

7. On the computer, accessing contract data including at least customer identification information, loan amount, loan interest rate, first repayment date, and final repayment date; A step of accessing a guarantee fee management master in which at least the loan term, customer credit information, and guarantee fee per unit yen are set; A step of calculating a lump-sum guarantee fee based on the contract data and the guarantee fee management master, and creating guarantee contract data at the time of application that includes at least the guarantee period, the guarantee amount, the customer credit information, and the lump-sum guarantee fee; A step of expanding the balance before repayment for each month based on the contract data and the guarantee contract data at the time of application, and creating repayment schedule data including at least the number of repayments, the repayment date, the balance before repayment for each month, the number of days elapsed since the last repayment date, and the cumulative balance for each month; A step of calculating a total balance accumulated amount from the balance accumulated amount for each month of the repayment schedule data; a step of calculating the annual guarantee rate by dividing the lump-sum guarantee fee by the total balance product, and creating guarantee contract data including at least customer identification information and the annual guarantee rate; A step of predicting guarantee fee income based on the balance before repayment for each month of the repayment schedule data and the annual guarantee rate of the guarantee contract data, and creating guarantee fee income schedule data including at least the number of repayments and the guarantee fee income; Guarantee fee revenue forecasting program to carry out.

Images