JP2013196150A - Pension information management program, pension information management device and pension information management method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a pension information management program or the like capable of quickly and accurately predicting "mathematical debts" or the like even when flexibly reconsidering an assumed interest rate or the like.SOLUTION: In the pension information management program, a computer is made to generate two or more pieces of respectively corresponding previous fixed date reference mathematical debt candidate information using two or more pieces of this fixed date assumed rate candidate information (i, j) of this fixed date on the basis of information associated with subscribers or the like of the previous fixed date, generate two or more pieces of respectively corresponding this fixed date standard premium candidate information using the two or more pieces of this fixed date assumed rate candidate information (i, j) on the basis of the information associated with the subscribers or the like of the previous fixed date, and specify previous fixed date reference input assumed rate corresponding mathematical debt information corresponding to inputted this fixed date input assumed rate information (k) using the two or more pieces of the previous fixed data reference mathematical debt candidate information.

Description

  The present invention relates to, for example, a pension information management program, a pension information management apparatus, and a pension information management method for processing various types of pension information that are information related to benefits and the like that each company should pay to employees in a corporate pension system. Is.

Currently, each company employs a pension system, such as a defined benefit corporate pension system. This defined-benefit corporate pension plan is a pension plan that pays pensions and lump sum benefits calculated according to years of service or salary when employees retire.
For this reason, companies and the like adopting such a system need to accumulate assets for employees and the like in accordance with the rules of the system.
However, since the amount of benefits for employees who will retire in the future is of course undecided at this time, companies are expected to make future payments and accumulate the amount at the present time. We calculate the power, that is, "actuarial debt", and reserve assets for that purpose.
Various proposals have been made for the calculation of the “mathematical debt” (for example, Patent Document 1).

JP 2006-163685 A (summary etc.)

Conventionally, when calculating “actuarial debt” on a settlement date basis, for example, once a year, it is necessary to calculate based on the data (salary, years of service, etc.) of all employees on that settlement date. However, for example, it took about 3 months, depending on the size of the company.
For this reason, it is conceivable to forecast “actuarial debt” on the settlement date in advance, not on the settlement date basis. It is necessary to specify the rate, that is, the “scheduled interest rate”.

However, this planned interest rate shifts to investment products that can be expected to have high investment income with low investment risk in order to respond to the recent highly volatile investment environment, and is linked to the expected long-term return on pension assets. Therefore, since companies etc. which review flexibly increase, it is difficult to specify in advance.
On the other hand, if this “scheduled interest rate” is different, it will be necessary to recalculate the “actuarial debt” of the future settlement date, which requires enormous effort and time.
For this reason, there is a problem that it is difficult to quickly and accurately predict the “actuarial debt” of companies that flexibly review the “scheduled interest rate”.

  Therefore, the present invention provides a pension information management program, a pension information management device, and a pension information management method capable of predicting “actuarial debt” and the like quickly and accurately even when flexibly reviewing a planned interest rate or the like. Objective.

  According to the present invention, according to the present invention, the computer predicts the benefit information that the pension member should receive in the future, and acquires the current fixed day actuarial debt information that is the accumulated amount information to be accumulated on the current fixed date in advance. This is a pension information management program, which is linked to the medium- to long-term expected rate of return information on pension assets on this fixed date based on at least the information related to the subscriber, etc. on the previous fixed date already acquired on the computer. Using the current fixed date scheduled rate candidate information that is the rate candidate information, and generating the previous fixed date reference actuarial debt candidate information that is the candidate information of the accumulated amount information on a plurality of previous fixed dates corresponding to each, at least, Based on information related to subscribers, etc. on the previous fixed date, respond to each of them using the multiple candidate rate information for the fixed date this time Multiple current fixed date standard premium candidate information, which is candidate information for increasing information on the amount of burden from the previous fixed date to the current fixed date, and input the current fixed date, which is the planned interest rate information on the input current fixed date The actuarial debt information corresponding to the previous fixed date standard input interest rate corresponding to the previous fixed date based on the previous fixed date corresponding to the interest rate information is identified by using a plurality of the previous fixed date standard mathematical debt candidate information, and the current fixed date Specified standard interest information corresponding to current fixed date input scheduled interest rate, which is information on the increase in the amount of burden from the previous fixed date to the current fixed date corresponding to the scheduled input interest rate information, using a plurality of current fixed date standard premium candidate information. , At least the previous fixed date reference input interest rate corresponding actuarial debt information, the current fixed date input planned interest rate information, the current fixed date input planned interest rate corresponding standard premium information, and It is configured to generate the current fixed actuarial debt information based on the input benefit information for prediction correction that is the predicted benefit information of the pension and lump sum from the previous fixed date to the current fixed date. Achieved by a characteristic pension information management program.

According to the above configuration, based on the information related to the subscriber, etc. on the previous fixed date that has already been acquired, this fixed date is a plurality of scheduled rate candidate information linked to the medium- to long-term expected rate of return information on pension assets on the fixed date It is configured to generate previous fixed date basis actuarial debt candidate information which is candidate information of the accumulated amount information on a plurality of previous fixed dates corresponding to each of the scheduled daily rate candidate information.
That is, for example, the medium- to long-term expected rate of return information on the final date of this year is predicted within a certain range (for example, 2.0% to 1.5%), and numerical values at both ends of the range are set. 0% and 1.5% are set as “current fixed date scheduled rate candidate information”.
And using these 2.0% and 1.5%, related information such as subscribers on the last fixed date that has already been acquired, for example, the previous fiscal year end (for example, salary of individual subscribers belonging to the pension system) And age, enrollment period, annual information of individual beneficiaries belonging to the pension system, information on personnel such as age, etc.), etc. A certain “last-fixed date standard actuarial debt candidate information” is generated. That is, two pieces of “previous date standard actuarial debt candidate information” are prepared.
It should be noted that the creation of funded amount information based on the subscriber related information is an extremely time-consuming work especially in a large company with a large number of subscribers, and in some cases, it takes about three months.
Accordingly, since it takes a similar amount of time to wait for the current fixed date such as this year's settlement date, this invention takes the expected interest rate (2.0% to 1.5%) on the current fixed date. Based on the related information such as subscribers already acquired on the previous year's closing date using the two scheduled interest rates with a width of Two pieces of information) are generated.

Further, in the above configuration, based on the subscriber related information on the previous fixed date, using a plurality of the current fixed date scheduled rate candidate information, an increase in the amount of burden from the corresponding previous fixed date to the current fixed date It is also configured to generate a plurality of current fixed date standard premium candidate information, which is information candidate information.
That is, for example, using the “current fixed date scheduled rate candidate information” of, for example, 1.5% and 2.0% as described above, calculation is performed based on the related information on the previous fixed date already acquired. For example, “currently determined date standard premium candidate information”, which is candidate information of increase information for one year from the plurality of previous determined dates to the current determined date, for example, the current year's settlement date, is generated.

Further, in the configuration, the actuarial debt information corresponding to the previous fixed date reference input interest rate corresponding to the previous fixed date is the accumulated amount information on the previous fixed date corresponding to the current fixed date input planned interest rate information that is the scheduled interest rate information input on the current fixed date. The plurality of previous fixed date reference actuarial debt candidate information is used for identification.
That is, for example, before the current settlement date, for example, before generation of the current fiscal year settlement date, after generating the previous fixed date basic actuarial debt candidate information, etc., the user of the present invention sets a new predicted value of the “scheduled interest rate”. When acquired, instead of recalculating the "funded amount information" with this new "scheduled interest rate" and related information such as subscribers, it is calculated using the above-mentioned "previous fixed date actuarial debt candidate information" described above. . For example, by performing logarithmic correction calculation, etc., the “funded amount” prediction data (the actuarial debt information corresponding to the expected rate based on the previous fixed date) is acquired for the new “scheduled interest rate”.
Therefore, in order to respond to the recent high-volatility investment environment, companies will shift to investment products that can reduce investment risks and expect high-level investment returns. Even if the “interest rate” is flexibly reviewed, it is not necessary to calculate again based on the “subscriber information” as in the prior art, so that labor can be saved and a quick response can be achieved.

Further, in the above configuration, the current fixed date input scheduled interest rate corresponding standard premium information, which is the increase information of the burden amount up to the current fixed date corresponding to the current fixed date input scheduled interest rate information, includes a plurality of current fixed date standard premium candidate information. It becomes the structure specified by using.
That is, as described above, for example, when the user of the present invention acquires a predicted value of a new “scheduled interest rate” after generation of “current fixed date standard premium candidate information” or the like before the current fiscal year end date. Does not recalculate the “standard premium” information, which is information on the increase in the amount of one-year burden up to the current fiscal year end, with the new “scheduled interest rate” and subscriber-related information. It is obtained using “current fixed date standard contribution candidate information”. For example, by performing logarithmic correction calculation or the like, the “standard premium” prediction data (current fixed date input standard interest rate corresponding standard interest rate information) for the new “scheduled interest rate” is acquired.
Therefore, as described above, since it is linked to the expected long-term rate of return on pension assets, there is no need to recalculate based on “subscriber information” as in the past, even if the “scheduled interest rate” is flexibly revised. Thus, it is possible to save labor and respond quickly in a short time.

In addition, in the above-described configuration, the actuarial debt information corresponding to the previous fixed date input scheduled interest rate, the current fixed date input planned interest rate information, the current fixed date input planned interest rate corresponding standard interest rate information, and the input from the previous fixed date to the current fixed date. It is configured to generate actuarial debt information for the current fixed date based on the benefit information for forecast correction that is the forecast benefit information for pensions and lump sums.
Therefore, even if the “scheduled interest rate” is changed as described above, it is possible not only to quickly acquire “actual debt information”, which is “actual debt information”, but also to apply this “ Since this fixed-day actuarial debt information is calculated based on “forecast-adjusted benefit information” or the like, it becomes highly accurate “actuarial debt information”.

  As described above, in the above configuration, the generation of “currently determined actuarial debt information” does not take about three months from the settlement date as in the conventional case, and early determination is possible. As a result, the processing is completed at the same time as the corporate accounting, and the general meeting of shareholders can be dealt with early.

  Preferably, on the basis of at least the subscriber related information on the previous fixed date, using the current fixed date scheduled rate candidate information, the increase information of the burden amount from the current fixed date to the next fixed date corresponding to each Generate next multiple fixed date standard premium candidate information that is candidate information, and next fixed date input scheduled interest rate that is information on increase of burden amount from current fixed date to next fixed date corresponding to the current fixed date input planned interest rate information Corresponding standard premium information is specified by using a plurality of next-date fixed date standard premium candidate information.

According to the above-described configuration, based on the subscriber related information on the previous fixed date, the current fixed date scheduled rate candidate information is used, and the corresponding candidate information for increasing the amount of burden from the current fixed date to the next fixed date A plurality of next fixed date standard premium candidate information, which is information, is generated.
In other words, using the “current fixed date scheduled rate candidate information” of 1.5%, 2.0%, etc., calculation based on the related information such as subscribers already acquired on the previous fixed date, for example, the previous fiscal year end Etc. to generate “next determined date standard premium candidate information” which is standard premium information for one year up to a plurality of (for example, two) next year settlement dates. That is, two “next fixed date standard premium candidate information” are prepared.
Note that the creation of standard premium information based on this subscriber-related information is an extremely time-consuming operation, especially in large corporations with a large number of subscribers, and in some cases it takes about three months.
Accordingly, since it takes a similar amount of time to wait for the current fixed date such as this year's settlement date, this invention takes the expected interest rate (2.0% to 1.5%) on the current fixed date. Based on the information related to subscribers, etc. that have already been acquired on the previous fiscal year's closing date using two scheduled interest rates with a width of ) Are generated.

Further, in the above configuration, the next fixed date input scheduled interest rate corresponding standard premium information, which is the increase information of the burden amount from the current fixed date to the next fixed date corresponding to the current fixed date input planned interest rate information, is set to a plurality of the next fixed date standard It is specified by using the premium candidate information.
That is, for example, when the user of the present invention acquires a new predicted value of the “scheduled interest rate” after the generation of “next fixed date standard premium candidate information” or the like before the current fiscal year end date, Rather than recalculating the “standard premium” information, which is information on the increase in the amount of one-year burden up to the next fiscal year's closing date, with the “scheduled interest rate” and related information such as subscribers, It is obtained using “paid candidate information”. For example, by performing logarithmic correction calculation or the like, the “standard premium” prediction data (standard fixed rate information corresponding to the next fixed date input scheduled interest rate) in the new “scheduled interest rate” is acquired.
Therefore, as described above, since it is linked to the expected long-term rate of return on pension assets, there is no need to recalculate based on “subscriber information” as in the past, even if the “scheduled interest rate” is flexibly revised. Thus, it is possible to save labor and respond quickly in a short time.
In addition, “next fixed date standard premium candidate information”, which is information necessary for future pension system management, can be grasped at an early stage.

  Preferably, from the current fixed date to the next fixed date for the salary information based on the input predicted asset amount information that is the predicted value of the asset amount of the current fixed date, the predicted salary amount that is the predicted value of the salary amount, and the depreciable years information The standard charge rate information, which is the rate of increase in the amount of burden on the asset, is generated, and the shortage information generated in relation to the predicted asset amount information and the current fixed date actuarial debt information is input as the current fixed date in the depreciation information Amount of money information to be depreciated evenly on the basis of scheduled interest rate information is generated as special contribution rate information that is rate information for the salary information.

  Preferably, predicted balance sheet information for predicting balance sheet information on the current fixed date based on at least the current fixed actuarial debt information, the predicted asset amount information, the standard premium rate information, and the special premium rate information Is generated.

  According to the above configuration, the predicted balance sheet information for predicting the balance sheet information on the current fixed date is automatically calculated based on the current fixed actuarial debt information, the predicted asset amount information, the standard premium rate information, and the special premium rate information. Therefore, it can be created quickly.

  Preferably, the current fixed date input fixed interest rate information, which is the fixed interest rate information for the current fixed date entered after the arrival of the current fixed date, and the pension and lump sum payment benefits from the previous fixed date input to the current fixed date. Based on the benefit information for fixed correction that is amount information, the final fixed actuarial debt information that is fixed the current fixed actuarial debt information is generated, and the next time based on the fixed date input fixed interest rate information The fixed date input standard interest rate standard premium information is configured to be fixed.

According to the above configuration, the current fixed date input fixed interest rate information, which is the fixed interest rate information on the current fixed date, which is input after the arrival of the current fixed date, and the input pension and lump sum from the previous fixed date to the current fixed date. Based on the defined benefit information, which is defined benefit amount information, the confirmed current fixed actuarial debt information that has been confirmed is generated.
In other words, “the fixed rate information for the fixed rate input”, “the actuarial debt information for the fixed rate input for the fixed rate for the previous fixed date” and “the standard premium information for the fixed rate input for the fixed date for the current fixed date” become the fixed value information. By “amount information”, “benefit information for forecast correction” also becomes a final value.
As a result, the “current fixed actuarial debt information” becomes the fixed value information.
Further, “current fixed date input scheduled interest rate information” becomes a fixed value, and “next fixed date input scheduled interest rate corresponding standard premium information” becomes a fixed value by “current fixed date input fixed interest rate information”.
Therefore, the current fixed date input fixed interest rate information fixed on the current fixed date can be input, and the fixed current fixed date actuarial debt information that is a fixed value can be quickly acquired.
In addition, standard payment information corresponding to the next fixed date input scheduled interest rate can be obtained as a fixed value, which is appropriate data.
Further, in the above configuration, since the predicted value and the final value are calculated with the same logic, if the “adjustment benefit amount” data and the “scheduled interest rate” data are the same input value, the predicted value and The deterministic values match and prediction accuracy improves.
That is, when there is a difference between the predicted value and the final value, it is understood that the cause is a difference from the premise data, and the configuration is easy to deal with.

  Preferably, the fixed asset amount information that is information on the fixed asset amount on the fixed date this time, the fixed salary information that is information on the fixed salary amount, and the fixed depreciation period that are input after the fixed date is reached. The standard premium rate information and the special premium rate information are generated based on fixed depreciation years information which is information of

  Preferably, a balance sheet is generated based on at least the fixed current fixed actuarial debt information, the fixed asset value information, the fixed salary information and the fixed depreciation information.

  According to the above configuration, since the balance sheet is generated based on the confirmed current fixed actuarial debt information, the fixed asset amount information, the fixed salary information, and the fixed depreciation information, a highly accurate balance sheet is created. be able to.

  According to the present invention, according to the present invention, pension information management for predicting benefit information to be received in the future by a pension member and generating current fixed actuarial debt information, which is accumulated amount information to be accumulated on the fixed date in advance, is generated. This is a device that is a plurality of candidate rate candidate information linked to the medium- to long-term expected rate of return information on pension assets on this fixed date, based on at least the information related to subscribers etc. on the previous fixed date already acquired Using the fixed date schedule rate candidate information, the previous fixed date standard actuarial debt candidate information that is candidate information of the accumulated amount information on a plurality of previous fixed dates corresponding to each is generated, and at least a subscriber on the previous fixed date Based on the related information, etc., increase the amount of burden from the previous fixed date to the current fixed date by using a plurality of candidate rates for the current fixed date A plurality of current fixed date standard premium candidate information that is candidate information of information is generated, and the accumulated amount information on the previous fixed date corresponding to the current fixed date input planned interest rate information that is the scheduled interest rate information that is input on the current fixed date Specified actuarial debt information corresponding to a certain fixed date based input scheduled interest rate by using a plurality of previous fixed date standard actuarial debt candidate information, and the fixed date from the previous fixed date corresponding to the planned fixed rate input interest rate information The current fixed rate input standard interest rate information corresponding to the current fixed date input information, which is information on the increase in the amount to be paid, is identified by using a plurality of current fixed date standard premium candidate information, and at least the previous fixed date standard input rate corresponding actuarial obligation Information, the current fixed date input scheduled interest rate information, the current fixed date input planned interest rate-related standard premium information, and the input from the last fixed date entered to the current fixed date Beauty is predicted benefits information lump based on the predicted correction benefits information, is accomplished by the current fixed date pension information management apparatus, characterized in that it is configured to generate a mathematical debt information.

  According to the present invention, according to the present invention, pension information management for predicting benefit information to be received in the future by a pension member and generating current fixed actuarial debt information, which is accumulated amount information to be accumulated on the fixed date in advance, is generated. This is a method that is a plurality of candidate rate candidate information linked to medium- to long-term expected rate of return information on pension assets on this fixed date, based on information related to subscribers etc. on the previous fixed date that has already been acquired Using the fixed date schedule rate candidate information, the previous fixed date standard actuarial debt candidate information that is candidate information of the accumulated amount information on a plurality of previous fixed dates corresponding to each is generated, and at least a subscriber on the previous fixed date Based on the related information, etc., increase the amount of burden from the previous fixed date to the current fixed date by using a plurality of candidate rates for the current fixed date A plurality of current fixed date standard premium candidate information that is candidate information of information is generated, and the accumulated amount information on the previous fixed date corresponding to the current fixed date input planned interest rate information that is the scheduled interest rate information that is input on the current fixed date Specified actuarial debt information corresponding to a certain fixed date based input scheduled interest rate by using a plurality of previous fixed date standard actuarial debt candidate information, and the fixed date from the previous fixed date corresponding to the planned fixed rate input interest rate information The current fixed rate input standard interest rate information corresponding to the current fixed date input information, which is information on the increase in the amount to be paid, is identified by using a plurality of current fixed date standard premium candidate information, and at least the previous fixed date standard input rate corresponding actuarial obligation Information, the current fixed date input scheduled interest rate information, the current fixed date input planned interest rate-related standard premium information, and the input from the last fixed date entered to the current fixed date Beauty is predicted benefits information lump based on the predicted correction benefits information, are achieved by the pension information management method characterized in that it is configured to generate the time fixed date mathematical debt information.

  The present invention can provide a pension information management program, a pension information management device, and a pension information management method capable of predicting “actuarial debt” and the like quickly and accurately even when flexibly reviewing a planned interest rate and the like. There are advantages.

It is the schematic which shows the external appearance of the actuarial debt apparatus which is the pension information management apparatus of this invention, for example. It is a schematic block diagram which shows the main structures of the mathematical debt apparatus of FIG. It is a schematic block diagram which shows the outline | summary of the 1st various information storage part shown in FIG. It is a schematic block diagram which shows the outline | summary of the 2nd various information storage part shown in FIG. It is a schematic block diagram which shows the outline | summary of the 3rd various information storage part shown in FIG. It is a schematic block diagram which shows the outline | summary of the 4th various information storage part shown in FIG. It is a schematic block diagram which shows the outline | summary of the 5th various information storage part shown in FIG. It is a schematic block diagram which shows the outline | summary of the 6th various information storage part shown in FIG. It is a schematic flowchart which shows the main operation | movement etc. of the mathematical debt apparatus of FIG. It is another schematic flowchart which shows the main operation | movement etc. of the mathematical debt apparatus of FIG. It is another schematic flowchart which shows the main operation | movement etc. of the mathematical debt apparatus of FIG. It is another schematic flowchart which shows the main operation | movement etc. of the mathematical debt apparatus of FIG. It is a schematic explanatory drawing which shows the "financial settlement environment data" of the "financial settlement environment data storage part" of FIG. It is a schematic explanatory drawing which shows an example of the balance sheet which performed the special premium income present value process. It is a schematic explanatory drawing which shows an example of the balance sheet which performed the reserve fund process separately. It is a schematic explanatory drawing of the process of the mathematical debt apparatus concerning this Embodiment.

Preferred embodiments of the present invention will be described below in detail with reference to the accompanying drawings.
The embodiments described below are preferred specific examples of the present invention, and thus various technically preferable limitations are given. However, the scope of the present invention is particularly limited in the following description. Unless otherwise stated, the present invention is not limited to these embodiments.

FIG. 1 is a schematic diagram showing an appearance of, for example, a mathematical debt apparatus 1 which is a pension information management apparatus of the present invention.
As shown in FIG. 1, the mathematical debt apparatus 1 has a display 2 for displaying various information, and a data input device 3 having a keyboard for inputting various data.
The actuarial debt apparatus 1 is used when operating a pension system, for example, a corporate pension system in a company, specifically a defined benefit corporate pension.
This “defined benefit corporate pension plan” is a pension plan that pays a pension and a lump sum payment calculated according to the length of service, salary, etc., when a company employee (participant in a pension plan) retires.
In this way, the “defined benefit corporate pension plan” is a plan in which the company pays benefits to employees, but since the benefits when an employee retires in the future are uncertain, the company will pay future benefits. The amount to be accumulated at that time, that is, “actuarial debt” is calculated, and assets are pre-paid for this “actual debt”.

In addition, in order to confirm the financial situation of the pension, such as whether the assets accumulated in advance are sufficient or insufficient compared with the actuarial debt, which is the funding target, the corporation should Has been implemented.
In this embodiment, as will be described later, a “balance sheet” used in this “financial settlement” is automatically created.

  In addition, in order to respond to the recent management environment with high volatility (instability), companies have shifted to investment products that can reduce investment risks and expect high investment income when operating pension plans. There is a tendency to flexibly review the “scheduled interest rate” linked to the expected return on investment.

  In other words, the “scheduled interest rate” for each year of pension benefits is not fixed, but will fluctuate every year, so that the “scheduled interest rate” for the forecast year when forecasting “actuarial debt” can be determined quickly and accurately in advance. It has been difficult to predict.

In addition, when calculating “actuarial debt” for the expected year, personnel data, etc., which has already been determined (such as salary and age of individual members belonging to the pension system, membership period, pension system) Calculate based on the “scheduled interest rate” etc. based on the individual beneficiary's annual amount and age, etc., but this personnel data is enormous, especially for large companies, etc. In some cases, it would normally take about three months to calculate “actuarial debt” using the “scheduled interest rate” based on the above.
Therefore, when the “scheduled interest rate” is reviewed, the actuarial debt will be recalculated, and in some cases it would normally take about one month in addition to the above.
Moreover, it was usually announced later than other corporate accounting documents, and it was usually not in time for the announcement of the general meeting of shareholders.

The invention according to the present embodiment solves such a problem, and can predict “actuarial debt” quickly and accurately before the closing date of the financial year to be predicted, and reflects the result of this “mathematical debt”. “Balance sheet” can also be created automatically. In addition, with the arrival of the closing date, these predicted values can be instantly determined.
For this reason, the “Pension Fiscal Financial Results (including Balance Sheet)” of the “Defined Benefit Corporate Pension” can be reported to the General Meeting of Shareholders as a financial report at the same time as other corporate accounting documents.

  This will be specifically described below. 1 has a computer, and has a CPU (Central Processing Unit), a RAM (Random Access Memory), a ROM (Read Only Memory), etc. (not shown), which are connected via a bus or the like. Has been.

  The bus has a function of connecting all devices and is an internal bus having an address bus and a data bus. A CPU or the like performs processing of a predetermined program and controls a ROM and the like connected to a bus or the like. The ROM and the like store various programs and various information. The RAM also has a function as an area for executing the program by comparing the contents of the memory during the program processing.

  FIG. 2 is a schematic block diagram showing a main configuration of the mathematical debt apparatus 1 of FIG. As shown in FIG. 2, the mathematical debt device 1 has a mathematical debt device control unit 4. The mathematical debt device control unit 4 controls the display 2 and the data input device 3 shown in FIG. "First various information storage unit 10", "second various information storage unit 20", "third various information storage unit 30", "fourth various information storage unit 40", "fifth The “various information storage unit 50” and the “sixth various information storage unit 60” are also controlled.

3 is a schematic block diagram showing an overview of the first various information storage unit 10 shown in FIG. 2, and FIG. 4 is a schematic block diagram showing an overview of the second various information storage unit 20 shown in FIG. FIG. 5 is a schematic block diagram showing an outline of the third various information storage section 30 shown in FIG. 2, and FIG. 6 shows an outline of the fourth various information storage section 40 shown in FIG. It is a schematic block diagram.
7 is a schematic block diagram showing an outline of the fifth various information storage section 50 shown in FIG. 2, and FIG. 8 shows an outline of the sixth various information storage section 60 shown in FIG. It is a schematic block diagram. These contents will be described later.

9 to 12 are schematic flowcharts showing main operations and the like of the mathematical debt apparatus 1 of FIG.
Hereinafter, the operation of the mathematical debt apparatus 1 will be described along with the flowchart of FIG. 9 and the like, and the configurations of FIG. 1 to FIG.

  A user who calculates “mathematical debt” or the like in the mathematical debt apparatus 1 in FIG. 1 creates the following data in advance and stores it in the mathematical debt apparatus 1.

1) Creation and entry of “Last year actuarial debt candidate data” For example, the employee (in the “actual debt” on the settlement date of March 31, 2012, that is, the defined benefit corporate pension plan adopted by the company ( (Participant) predicts the total amount of benefits to be received in the future, and is the accumulated amount information that should be saved in advance (March 31, 2012) in advance (before March 31, 2012). For example, a case where “information actuarial debt” is predicted will be described below.
The user of the mathematical debt apparatus 1 first predicts the fluctuation range of the “scheduled interest rate” on “March 31, 2012” which is the current fixed date of the “current fixed date mathematical debt information”. Assume that the range is 0% and 1.5%, and the actual "scheduled interest rate" falls within this range.
“2.0%” is “this year's upper-limit scheduled interest rate (i)” and “1.5%” is “this year's lower-limit scheduled interest rate (j)”. Is an example.

  And, for example, personnel data (eg, salary and age of individual subscribers belonging to the pension system), which is related information on the subscribers, etc., on the last confirmed date, for example, March 31, 2011, for which data has already been confirmed and acquired. , Based on the enrollment period, the annual amount and age of individual beneficiaries belonging to the pension system, etc. j) "Mathematical debt" is calculated using each of "1.5%".

Specifically, “actuarial debt” using the “maximum expected interest rate (i) of this year” at the end of last year, that is, “fundamental candidate data for the maximum expected interest rate for last year”, for example, “9,325,968 yen” Is calculated. In addition, “actuarial debt” using “this year's lower-limit scheduled interest rate (j)” at the end of last year, that is, “last year's lower-limit planned interest rate corresponding mathematical debt basic candidate data”, for example, “9,900,966 yen” is calculated.
Since these are calculated by using actual last year's personnel data and the like, it may take an enormous amount of time. In this embodiment, such work is performed in advance.
In addition, as long as the “scheduled interest rate” of the “financial date” of the “current fixed actuarial debt information” predicted in the future is between “2.0%” and “1.5%”, The “information” is an amount between “9,325,968 yen” and “9,900,966 yen”.
Note that these are examples of the “basic actuarial debt basic information on the last determined date”.

  Then, these “maximum scheduled interest rate for this year (i)” “2.0%”, “this year's minimum scheduled interest rate (j)” “1.5%”, “the basic candidate for actuarial debt corresponding to the maximum interest rate planned for last year” “9, “325,968 yen” and “last year's minimum expected interest rate corresponding mathematical debt basic candidate data” “9,900,966 yen” are stored in the “financial settlement environment data storage unit 11” of FIG. Specifically, the data is input by using the data input device 3 ”in FIG.

  FIG. 13 is a schematic explanatory view showing “Financial settlement environment data 11a” in “Financial settlement environment data storage unit 11” of FIG. 1. As shown in FIG. Remembered.

2) Creation and input of “Standard Candidate Amount Data for This Year” Next, the user of Mathematical Debt Equipment 1 selects “2.0%” of “Upper Planned Rate of Interest (i) of this Year” and “Lower Planned Rate of Interest of This Year (j)” The amount of pension and lump sum payments to subscribers increased from “April 1, 2011” to “March 31, 2012” using “1.5%” As a result of this, “Standard premium amount”, which is an increase information that increases the burden on the company, is calculated. To do. For example, “231,891 yen” and “252,966 yen”, respectively.
These “standard premium amount candidate data corresponding to the upper limit planned interest rate for this year” and “standard premium amount candidate data corresponding to the lower limit scheduled interest rate for this year” are the “candidate data for this year's standard premium amount”. It has become.

Since these are calculated by using actual last year's personnel data and the like, it may take an enormous amount of time. In this embodiment, such work is performed in advance.
In addition, as long as the “scheduled interest rate” of the “financial date” of the “actual debt information this time” is between 2.0% and 1.5%, "Is an amount between" this year's upper limit planned interest rate corresponding standard multiplying amount candidate data "" 231,891 yen "and" this year lower limit scheduled interest rate corresponding standard multiplying amount candidate data "" 252,966 yen ".

  Then, these “candidate data for standard premiums corresponding to the upper-limit planned interest rate this year” “231,891 yen” and “candidate data for standard premiums corresponding to the lower-limit scheduled interest rate this year” “252,966 yen” are stored in the “Financial settlement environment data storage” of FIG. Part 11 ". Specifically, the data is input by using the data input device 3 ”in FIG.

3) Creation and input of “next year standard premium amount candidate data” Next, the user of actuarial debt device 1 “2.0%” of “this year's upper limit expected interest rate (i)” and “this year's lower limit expected interest rate (j ) ", And the amount of pension and lump sum payments to members during the period from" April 1, 2012 "to" March 31, 2013 " “Standard premium amount” corresponding to the “standard premium amount” corresponding to the increase information that increases the amount of burden on the company, and “standard premium candidate corresponding to the lower limit planned interest rate next year” Data "is calculated. For example, “225,195 yen” and “245,247 yen”, respectively.
These “next year standard premium candidate data” and “next year standard premium candidate data” are the “next year standard premium candidate data”. It is an example.

Since these are calculated by using actual last year's personnel data and the like, it may take an enormous amount of time. In this embodiment, such work is performed in advance.
In addition, as long as the “scheduled interest rate” of the “financial date” of the “actual debt information this time” is between 2.0% and 1.5%, "Is an amount between" upper-term planned interest rate candidate data corresponding to upper-limit planned interest rate for next year "" 225,195 yen "and" candidate data for lower-term planned interest rate corresponding to lower-limit scheduled interest rate "" 245,247 yen ".

  Then, these “next year upper limit scheduled interest rate corresponding standard premium amount candidate data” “225,195 yen” and “next year lower limit scheduled interest rate corresponding standard premium amount candidate data” “245,247 yen” are shown in FIG. The data is stored in the data storage unit 11 ”. Specifically, the data is input by using the data input device 3 ”in FIG.

  This completes the pre-registration of data to be stored in the “financial settlement environment data storage unit 11”. These “last year actuarial debt candidate data” and the like, as described above, require a huge amount of time to be created, but are preferably performed after the last fiscal year's closing date and before the current fiscal year's closing date.

  Next, for example, in the case where the user predicts “actual debt” on the current fiscal year end date (March 31, 2012), that is, “actual debt for the current year”, for example, one month before the closing date in FIG. An example of the operation of the mathematical debt device 1 will be specifically described.

  First, step (hereinafter “ST”) 1 in FIG. 9 is started. That is, “Fundamental data acquisition unit (program) 12 for calculating last year's actuarial debt amount” in FIG. 3 operates, and “Final year maximum expected interest rate (i) (2.0%) from“ Financial settlement environment storage unit 11 ”in FIG. ) "And" Corporate debt candidate data (9,325,968 yen) corresponding to the upper limit planned interest rate for the previous fiscal year "corresponding to this and" Standard candidate amount data (231,891 yen) corresponding to the upper limit expected interest rate this year ", “Yearly upper limit expected interest rate corresponding standard premium amount candidate data (225,195 yen)” is acquired and stored in the “actual debt forecast basic data storage unit 13 of FIG. 3” in FIG.

In addition, from “Financial Results Environment Storage Unit 11”, “Yearly Lower Limit Expected Interest Rate (j) (1.50%)” and the corresponding “Yearly Lower Limit Expected Interest Rate Corresponding Mathematical Debt Basic Candidate Data (9,900,381 Yen)” ”And“ Standard Candidate Amount Candidate Data corresponding to Minimum Expected Interest Rate for This Year (252,966 yen) ”and“ Standard Candidate Amount Candidate Data corresponding to Minimum Expected Interest Rate for Next Year ”(245 and 247 yen) are acquired. The data is stored in the data storage unit 13 ”.

Next, the process proceeds to ST2. In ST2, the message "Please enter the planned interest rate data and the current year's correction benefit data" is displayed on the display 2 of FIG.
In other words, the user of the actuarial debt device 1 predicts the “actual debt” for the current fiscal year (March 31, 2012), which is the “actual debt” for the current fiscal year (March 31, 2012). Ask what you expect to be and ask for its input.

  In the present embodiment, as described above, in order to respond to the recent operation environment with high volatility (unstable), users can expect investment income with low operational risk and high safety when operating the pension system. Given the tendency to shift to investment products and flexibly review the “scheduled interest rate” linked to the medium- to long-term expected return on pension funds, the “scheduled interest rate” can be entered freely when making a forecast. It has become a structure.

  In addition, in order to accurately forecast “actual debt for the current year”, the estimated benefits of the pension and lump sum payments from the previous fiscal year end (April 1, 2011) to the current fiscal year end (March 31, 2012) Since the data is necessary, the input of “current data for the current year correction” that is the predicted data and “the current data for the current correction for prediction” is requested.

Next, the process proceeds to ST3. In ST3, it is determined whether or not “scheduled interest rate data” and “current benefit data for this year” have been input. That is, it is determined whether or not the user has input such data via the data input device 3 in FIG.
If it is determined in ST3 that “scheduled interest rate data” and “current benefit data for this year” have been input, the process proceeds to ST4.

In ST4, the “current year amendment benefit data input processing unit (program) 14” of FIG. 3 operates, and for example, “627,630 yen” is input as the “current year amendment benefit data”. “627,630 yen” is stored in the “basic data storage unit 13 for calculating the current year's actuarial debt amount” in FIG.
For example, when “1.75%” is input as “scheduled interest rate”, “1.75%” is set as “scheduled interest rate (k) (1.75%)” and “actual debt amount, etc. this year” It is stored in the calculation basic data storage unit 13 ”.
Therefore, the “input planned interest rate (k) (1.75%)” is an example of the current scheduled date input scheduled interest rate information.

Next, the process proceeds to ST5. In ST5, the “last year actuarial debt basic data generation processing unit (program) 21” of FIG. 4 operates. First, the “scheduled input interest rate (k ) (1.75%) ”is generated.
That is, as shown in “Financial settlement environment data 11a” in FIG. 13, “actuarial debt” based on last year's personnel data corresponding to “this year's maximum expected interest rate (i)” is Basic candidate data (9,325,968 yen) ". In addition, “actuarial debt” based on last year's personnel data, etc., corresponding to “this year's minimum projected interest rate (j)” is revealed as “last year's minimum expected interest rate corresponding mathematical debt basic candidate data (9,900,381 yen)” ing.
However, in the present embodiment, “actual debt” based on last year's personnel data corresponding to “input expected interest rate (k) (1.75%)” is not actually performed based on last year ’s personnel data, etc. There are already “last year's upper limit planned interest rate corresponding mathematical debt basic candidate data (9,325,968 yen)” and “last year lower limit planned interest rate corresponding mathematical debt basic candidate data (9 , 900,381 yen) ”, and a simple calculation.

That is, for example, the calculation is performed using the “mathematical debt logarithmic correction calculation formula” for obtaining an approximate value of the “mathematical debt logarithmic correction formula data storage unit 22” in FIG.
First, “Mathematical debt logarithm correction calculation formula” has the following formula.
“Last-term expected basic interest rate data corresponding to the upper-limit planned interest rate last year” / “Basic candidate data for the expected lower-term interest rate corresponding to the previous year's minimum interest rate” = {(1+ “Lower-term planned interest rate (j) this year”) / (1+ ” ") ^N
Therefore, when the numerical values of FIG. 13 are applied, for example, 9,325,968 / 9,900,381 = {(1 + 0.015) / (1 + 0.02)} ⁿ , and “n” is obtained.

“Mathematical debt logarithmic correction calculation formula” also includes the following logarithmic correction calculation formula and the like.
“Last term actuarial debt basic data” = “Last term actuarial debt candidate data corresponding to the previous year's upper limit expected interest rate” × {(1+ “This year's upper limit expected interest rate (i)”) / (1+ “Input expected interest rate (k)”)} ⁿ
Accordingly, by performing logarithmic correction calculation using the data of FIG. 13 and these logarithmic correction calculation formulas, etc., the “actual debt information corresponding to the expected rate of input corresponding to the previous fixed date”, for example, Data ", specifically," 9,608,257 yen "can be calculated.

As described above, in the present embodiment, the “maximum scheduled interest rate for the current year (i) (2.0%)” and the “current planned minimum interest rate for the current year (j) (1.5%)” are already used, We have already calculated the basic actuarial debt candidate data (9,325,968 yen) corresponding to the upper limit scheduled interest rate last year and the basic actuarial debt candidate data (9,900,381 yen) corresponding to the lower limit scheduled interest rate last year).
And, “Fundamental actuarial debt basic data” corresponding to the “input planned interest rate (k)”, which is an intermediate value between these “maximum planned interest rate this year (i)” and “this year minimum planned interest rate (j)”, is shown in these figures. Simple logarithmic correction calculation based on 13 “last year's upper limit expected interest rate corresponding mathematical debt basic candidate data (9,325,968 yen)” and “last year lower limit expected interest rate corresponding mathematical debt basic candidate data (9,900,381 yen)” Can be requested.
For this reason, it is not necessary to recalculate last year's actuarial debt basic data based on personnel data, etc. on the last fiscal year-end for each fluctuating “input expected interest rate (k)”. It is possible to quickly respond to the change in the “scheduled interest rate (k)”.

  The “last year actuarial debt basic data (9,608,257 yen)” calculated in this way is stored in the “last year actuarial debt basic data storage unit 23” in FIG.

  Next, the process proceeds to ST6. In ST6, the “current year standard amount forecast data generation processing unit (program) 24” of FIG. 4 operates, and “input expected interest rate (k)” of the “basic data storage unit 13 for calculation of actuarial debt amount etc. of this year” of FIG. “This year's standard premium prediction data”, which is “standard fixed price information corresponding to the current fixed date input scheduled interest rate” corresponding to (1.75%) ”is generated.

That is, as shown in “Financial settlement environment data 11a” in FIG. 13, the “standard amount” based on last year's personnel data corresponding to “this year's upper limit expected interest rate (i)” This is clearly indicated as “paid amount candidate data (231,891 yen)”. Also, the “standard amount” based on last year's personnel data corresponding to “this year's minimum planned interest rate (j)” has become clear as “this year's minimum planned interest rate standard interest amount candidate data (252,966 yen)” Yes.
However, in the present embodiment, the “standard amount” based on last year's personnel data corresponding to “input expected interest rate (k) (1.75%)” is actually based on last year's personnel data, etc. Rather than the “financial settlement environment data storage unit” already stored “candidate data for standard premium amount corresponding to the upper limit planned interest rate for this year (231,891 yen)” and “candidate data for standard premium amount corresponding to the lower limit planned interest rate for this year” (252 , 966 yen) ”, and a simple calculation.

That is, for example, the calculation is performed using the “this year standard multiplied amount logarithmic correction formula data storage unit 35” shown in FIG.
First, “this year's standard multiplying logarithmic correction calculation formula” has the following formula.
“Candidate data for standard premiums corresponding to the maximum planned interest rate for this year” / “Candidate data for standard premiums corresponding to the minimum planned interest rate for this year” = {(1+ “Scheduled interest rate for the current year minimum (j)”) / (1+ ” ")} ^M
Therefore, when applying the numerical values of FIG.
231,891 / 252,966 = {(1 + 0.015) / (1 + 0.02)} ⁿ
And "m" is required.

In addition, “this year's standard multiplying logarithmic correction calculation formula” has the following logarithmic correction calculation formula and the like.
“Current year standard spending amount forecast data” = “Standard multiplying amount candidate data corresponding to current year upper limit planned interest rate” × {(1+ “Current year upper limit scheduled interest rate (i)”) / (1+ “Input scheduled interest rate (k)”)} ^m
Therefore, by performing the logarithmic correction calculation using the data of FIG. 13 and these logarithmic correction calculation formulas, etc., the “standard fixed amount information corresponding to the current fixed date input scheduled interest rate”, for example, “the current year standard multiplied amount forecast” Data ”, specifically,“ 242,185 yen ”can be calculated.

As described above, in the present embodiment, the “maximum scheduled interest rate for the current year (i) (2.0%)” and the “current planned minimum interest rate for the current year (j) (1.5%)” are already used, Calculation of the current year's upper limit scheduled interest rate standard premium amount candidate data (231,891 yen) and "this year's lower limit scheduled interest rate standard premium amount candidate data (252,966 yen)" has been completed.
The “annual standard projected amount forecast data” corresponding to the “scheduled input interest rate (k)”, which is an intermediate value between the “annual planned maximum interest rate (i)” and the “current year minimum planned interest rate (j)”, Simple calculation by logarithmic correction calculation based on “Standard Candidate Amount Candidate Data for Current Upper Limit Scheduled Interest Rate (231,891 Yen)” and “Standard Candidate Amount Candidate Data for Lower Expected Interest Rate for This Year (252,966 Yen)” in FIG. Can do.
For this reason, it is not necessary to recalculate the “standard amount forecast data for the current fiscal year” based on the personnel data of the last fiscal year-end for each fluctuating “scheduled input interest rate (k)”. It is possible to quickly respond to the change in the “scheduled interest rate (k)”.

  The “current year standard premium prediction data (231,891 yen)” calculated in this way is stored in the “current year standard premium prediction data storage unit 36” in FIG.

  Next, the process proceeds to ST7. In ST7, the “next year standard multiplied amount prediction data generation processing unit (program) 37” of FIG. 4 operates, and the “input expected interest rate (k ) (1.75%) "corresponding to the next fixed date input scheduled interest rate corresponding standard premium information" is generated.

That is, as shown in “Financial settlement environment data 11a” in FIG. 13, “standard amount” based on last year's personnel data corresponding to “this year's maximum planned interest rate (i)” It is clarified as “standard charge amount candidate data (225,195 yen)”.
In addition, “standard charge” based on last year's personnel data etc. corresponding to “this year's minimum planned interest rate (j)” will be clarified as “next year's minimum planned interest rate standard interest rate candidate data (245,247 yen)” ing.
However, in this embodiment, the “standard amount” based on last year's personnel data corresponding to “scheduled input interest rate (k) (1.75%)” is actually based on last year's personnel data, etc. Rather, the “next year upper limit planned interest rate corresponding standard premium amount candidate data (225,195 yen)” and “next year lower limit scheduled interest rate corresponding standard premium amount candidate data ( 245, 247 yen) "and obtained by simple calculation.

The calculation method is the same method as the calculation method of the above-mentioned “this year standard premium forecast data”, and the calculation formula “this year standard premium logarithm correction calculation formula” is “this year standard premium logarithm correction calculation formula data”. It is stored in the storage unit 35 ”.
The “next-year standard premium prediction data” thus calculated is, for example, “234,994 yen” and is stored in the “next-year standard premium prediction data storage unit 39”.

This completes the acquisition of data that serves as the basis for predicting the amount of “Actual debt for this year”, and the calculation process for “Actual debt for this year” is carried out.
In ST8, the “actual debt amount data generation processing unit (program) 41 of this year” in FIG. 6 operates, and refers to the arithmetic expression stored in the “calculation storage unit 42 for mathematical debt prediction” in FIG.
This arithmetic expression is an arithmetic expression for calculating “actual debt of the current year”, and specifically, is the following expression.
"This year's actuarial debt" = "Last year actuarial debt basic data" + ("Last year actuarial debt basic data" x "Input expected interest rate (k)) +" This year's standard premium forecast data "-" This year's revised benefit "

  In other words, in the “last-year actuarial debt basic data”, which is the “actuarial debt” based on the personnel data of the previous fiscal year corresponding to the “scheduled input interest rate (k) (1.75%)” calculated by the logarithmic correction calculation described above, Calculate the basic “actuarial debt” forecast for the current fiscal year by adding “number of planned basic interest rates (k) (1.75%)” to “last year actuarial debt basic data”. be able to. In addition, this year's standard annual amount forecast data, which is a forecast value for the company's share that increases as a result of adding one year from the last fiscal year's closing date to the current fiscal year's closing date, is added. By subtracting the “annual benefit for this year”, which is the expected value of pension and lump sum payments for one year from the previous fiscal year end date to the current fiscal year end date, the actual “actual debt for the current year” will be reduced.

In addition, “actual debt amount data generation processing unit (program) 41” of this year is “last year mathematical debt basic data storage unit 23” in FIG. 4 “actual debt basic data last year (9,608,257 yen)”, FIG. “Actual interest rate prediction (k) (1.75%)” of “Actual debt forecast basic data storage unit 13 of this year” of “Current year standard premium forecast data storage unit 36” of FIG. Data (242,185 yen) "and" This year's actuarial debt prediction basic data storage unit 13 "in FIG. 3 are referred to as" Amount of benefit for this year (627,630 yen) ".
Then, by substituting these numerical values into the above-mentioned “calculation formula for mathematical debt forecast for the current year”, “actual debt amount data for the current year”, for example, “9,390,956 yen” is calculated, and “actual debt data storage unit for the current fiscal year” is calculated. 43 ".

Next, the process proceeds to ST9. After ST9, based on the “actual debt amount data for the current year” calculated in ST8, “balance sheet” data predicted for the current fiscal year end date is created.
First, in ST9, the message “Please enter the amount of assets, total salary monthly amount, and depreciable years data” is displayed on the display 2 of FIG.
That is, the user of the actuarial debt apparatus 1 is requested to input information on the expected value of “amount of asset”, the expected value of “total monthly salary”, and the “amortization period”.
Then, the process proceeds to ST10. If it is determined in ST10 that "asset amount, total salary monthly amount, depreciable years data" has been input, the process proceeds to ST11.

  In ST11, for example, “asset amount” (input value “8,500,000 yen”) that is the input predicted asset amount information, for example, “total salary monthly amount” (input value) that is the input predicted salary amount. As “100,000 yen”), for example, each prediction data of “depreciable years” (“20 years” as an input value) is stored in the “asset amount storage unit 44” in FIG. Let

Next, the process proceeds to ST12. In ST12, the “next year standard premium rate data generation processing unit (program) 45” of FIG. 6 operates and refers to the calculation formula of the “next year standard premium rate calculation formula data storage unit 51” of FIG.
This arithmetic expression is an arithmetic expression for calculating the “next year standard contribution rate”, and specifically, is the following expression.
“Next year standard premium rate” = “Next year standard premium amount forecast data” / (“Total salary monthly amount” × 12)

In addition, the “next year standard premium rate data generation processing unit (program) 45” displays “next year standard premium amount prediction data (234,994 yen)” in the “next year standard premium amount prediction data storage unit 39” in FIG. In addition, the “total salary monthly amount (100,000 yen)” of the “asset amount storage unit 44” in FIG.
Then, these data are substituted into “next year standard premium rate calculation formula data” to calculate “next year standard premium rate data”, for example, “0.198”, and “next year standard premium rate data storage unit 52”. To remember.

Next, the process proceeds to ST13. In ST13, the “asset shortage determination processing unit (program) 53” of FIG. 7 operates, and the “asset amount (8,500,000 yen)” of the “asset amount storage unit 44” of FIG. It is determined whether or not the “actual debt data of this year (9,390,956 yen)” in the “actuarial debt data storage unit 43” has been reached.
That is, it is determined whether or not the “asset amount” is insufficient with respect to the predicted “actual debt data for the current year”.

If it is determined in ST13 that the “asset amount” is insufficient with respect to the “actual debt data for this year”, it is necessary to obtain the “special contribution rate” that is data for amortizing the shortage. This “special contribution rate” is the rate information for salary information, which is the amount of information that will be depreciated by the planned interest rate information using the amortization years information and the deficit information that occurs due to the relationship between the “amount of assets” and “actual debt data for the current year”. It is what.
Then, since it is necessary to obtain “pension present value data” in order to obtain this “special contribution rate”, the processing is performed in advance.
Specifically, “pension present value data” means to calculate to amortize the principal and interest evenly at the expected interest rate (k) within the input amortization period (p). Has the formula
Assuming v = 1 / (1 + k), the present pension value = (1 + v) / 2 × (1−V ^p ) / (1−v)
Therefore, in ST14, the “pension present value data generation processing unit (program) 54” of FIG. 7 operates, and the “scheduled input interest rate (k) (1)” of the “basic data storage unit 13 for this year's actuarial debt prediction” of FIG. , 75%) ”and“ Amortization years (20 years) ”of“ Asset amount storage unit 44 ”in FIG. 6,“ Pension present value data ”is generated, and“ Pension present value storage unit 55 ”in FIG. To remember.

  For example, “pension present value” when “planned interest rate (k) (1.75%)” and “depreciable years (20 years)” is “16.899947”.

Next, the process proceeds to ST15. In ST15, the “special premium data generation processing unit (program) 56” in FIG. 7 operates and refers to the arithmetic expression of the “special premium rate arithmetic expression storage unit 57”.
This arithmetic expression is an arithmetic expression for calculating the “special contribution rate”, specifically, the following expression.
"Special premium rate" = ("Actual debt amount for this fiscal year"-"Asset amount") / (12 x "Monthly salary" x "Pension present value")

In addition, the “special premium data generation processing unit (program) 56” displays “actual debt amount data (9,390,956 yen)” of “actual debt data storage unit 43” of FIG. “Asset amount (8,500,000 yen)” and “Total salary monthly amount (100,000 yen)” in “Amount storage unit 44” and “Pension present value (16 .89947) ”.
Then, these data are substituted into the “special premium rate calculation formula” to obtain “special premium data (0.044)” and are stored in the “special premium data storage unit 61”.

Next, the process proceeds to ST16. In ST16, the “special premium income present value including balance sheet creation processing section (program) 62” of FIG. 8 operates, and the difference data between the “actual debt amount of this year” and the “asset amount” is expressed as “special premium income present value”. "Debt account" and stored in the "balance sheet data storage unit 63" in FIG.
FIG. 14 is a schematic explanatory diagram illustrating an example of a balance sheet on which special premium income present value processing has been performed.
The “balance sheet data storage unit 63” in FIG. 8 stores the “balance sheet” data shown in FIG.

  As described above, in this embodiment, the predicted “actual debt amount this year” and “asset amount” are compared, and when the asset amount is small, the “special contribution rate” is automatically obtained and the result is taken into account. Thus, since the balance sheet is created, the mathematical debt device 1 is extremely easy for the user to use.

On the other hand, when the “asset amount” exceeds the “actual debt amount for this year” in ST13, the process proceeds to ST17. In ST17, the “separate reserve inclusion balance sheet creation processing unit (program) 63” of FIG. 8 operates, and the difference data between “actual debt amount of this year” and “asset amount” is set as “separate reserve fund”. Debt account ”and stored in the“ balance sheet data storage unit 64 ”.
FIG. 15 is a schematic explanatory diagram illustrating an example of a balance sheet that has been separately funded.
The “balance sheet data storage unit 64” in FIG. 6 stores the “balance sheet” data shown in FIG.

  In this way, in this embodiment, the predicted “actual debt amount this year” and “asset amount” are compared, and when the asset amount is large, “separate reserve fund” is automatically obtained and the results are taken into account. Thus, since the balance sheet is created, the mathematical debt device 1 is extremely easy for the user to use.

FIG. 16 is a schematic explanatory diagram of processing of the mathematical debt apparatus 1 according to the present embodiment.
The data before “N−1 months” in FIG. 16 corresponds to the case of the above-described embodiment. In this way, “actual debt for the current year” can be predicted by entering “scheduled interest rate (k)”, “adjustment benefits for the current year”, etc. You can also forecast “the premium rate”, “the next year's special premium rate” and “the balance sheet for the current year”.
In addition, this prediction may be performed not only for one month of the current fiscal year but also multiple times, such as five months ago, as shown in FIG. 16, and in that case, the result can be obtained easily and quickly. Can do.
In addition, when this calculation is performed after the closing date of the current year, as shown in FIG. 16, the fixed rate input interest rate information for the current fixed date, for example, the fixed “planned input rate (k)” or the fixed correction benefit For example, when the finalized “current amount correction benefit data”, which is amount information, is input, the calculated value is also the final fixed day actuarial debt information, for example, “actual debt of the current year” as the final value.
Further, since “assets amount”, “total salary monthly amount”, “depreciable years”, etc. shown in FIG. 16 are not predicted values but fixed values, the resulting “balance sheet” is also data based on fixed values.

Therefore, the “actual debt of the current year” information, which is a fixed value, can be quickly acquired by inputting the fixed value data on the closing date of the current year.
As described above, in the present embodiment, since the predicted value and the final value are calculated with the same logic, the data for the “annual benefit payment amount” and the “scheduled interest rate (k)” data are the same. If it is an input value, the predicted value and the determined value match, and the accuracy of prediction is improved.
That is, when there is a difference between the predicted value and the final value, it is understood that the cause is a difference from the premise data, and the configuration is easy to deal with.
Needless to say, the present invention is not limited to the above-described embodiment.

DESCRIPTION OF SYMBOLS 1 ... Mathematical debt apparatus, 2 ... Display, 3 ... Data input device, 4 ... Mathematical debt apparatus control part, 10 ... 1st various information storage part, 11 ... Financial settlement Environmental data storage unit, 11a ... Financial settlement environmental data, 12 ... Fundamental data acquisition unit for last year's actuarial debt amount calculation (program), 13 ... Basic data storage unit for mathematical debt prediction of this year, 14 ... This year's correction benefit data input processing unit (program), 20 ... second various information storage unit, 21 ... last year actuarial debt basic data generation processing unit (program), 22 ... mathematical debt logarithm correction Calculation formula data storage unit, 23 ... last year actuarial debt basic data storage unit, 24 ... current year standard amount forecast data generation processing unit (program), 30 ... third various information storage unit, 35 ...・ This year's standard Amount logarithm correction calculation formula data storage unit, 36 ... current year standard multiplied amount prediction data storage unit, 37 ... next year standard multiplied amount prediction data generation processing unit (program), 39 ... next year standard multiplied amount prediction Data storage unit 40... Fourth various information storage unit 41... This year's actuarial debt amount data generation processing unit (program) 42... This year's actuarial debt data storage unit, 44 ... Asset amount storage unit, 45 ... Next year standard premium rate data generation processing unit (program), 50 ... Fifth various information storage unit, 51 ... Next year standard premium rate calculation formula data storage unit, 52 ... Next year standard premium rate data storage unit, 53 ... Asset shortage judgment processing unit (program), 54 ... Pension present value data generation processing unit (program) ), 55 years Current value storage unit 56... Special premium data generation processing unit (program) 57. Special premium rate calculation formula storage unit 60. Sixth various information storage unit 61. Special premium data Storage unit, 62 ... Special premium income present value including balance sheet creation processing unit (program), 63 ... Separately funded balance sheet creation processing unit (program), 64 ... Balance sheet data storage Part

That is, for example, the calculation is performed using the “mathematical debt logarithmic correction calculation formula” for obtaining an approximate value of the “mathematical debt logarithmic correction formula data storage unit 22” in FIG.
First, “Mathematical debt logarithm correction calculation formula” has the following formula.
“Last-term expected basic interest rate data corresponding to the upper-limit planned interest rate last year” / “Basic candidate data for the expected lower-term interest rate corresponding to the previous year's minimum interest rate” = {(1+ “Lower-term planned interest rate (j) this year”) / (1+ ” ]) } ^N
Therefore, when the numerical values of FIG. 13 are applied, for example, 9,325,968 / 9,900,381 = {(1 + 0.015) / (1 + 0.02)} ⁿ , and “n” is obtained.

That is, for example, the calculation is performed using the “this year standard multiplied amount logarithmic correction formula data storage unit 35” shown in FIG.
First, “this year's standard multiplying logarithmic correction calculation formula” has the following formula.
“Candidate data for standard premiums corresponding to the maximum planned interest rate for this year” / “Candidate data for standard premiums corresponding to the minimum planned interest rate for this year” = {(1+ “Scheduled interest rate for the current year minimum (j)”) / (1+ ” ")} ^M
Therefore, when applying the numerical values of FIG.
231,891 / 252,966 = {(1 + 0.015) / (1 + 0.02)} ^m
And "m" is required.

If it is determined in ST13 that the “asset amount” is insufficient with respect to the “actual debt data for this year”, it is necessary to obtain the “special contribution rate” that is data for amortizing the shortage. This “special contribution rate” is the rate information for salary information, which is the amount of information that will be depreciated by the planned interest rate information using the amortization years information and the deficit information that occurs due to the relationship between the “amount of assets” and “actual debt data for the current year”. It is what.
Then, since it is necessary to obtain “pension present value data” in order to obtain this “special contribution rate”, the processing is performed in advance.
Specifically, “pension present value data” means to calculate to amortize the principal and interest evenly at the expected interest rate (k) within the input amortization period (p). Has the formula
Assuming v = 1 / (1 + k), the present pension value = (1 + v) / 2 × (1− v ^p ) / (1−v)
Therefore, in ST14, the “pension present value data generation processing unit (program) 54” of FIG. 7 operates, and the “scheduled input interest rate (k) (1)” of the “basic data storage unit 13 for this year's actuarial debt prediction” of FIG. , 75%) ”and“ Amortization years (20 years) ”of“ Asset amount storage unit 44 ”in FIG. 6,“ Pension present value data ”is generated, and“ Pension present value storage unit 55 ”in FIG. To remember.

On the other hand, when the “asset amount” exceeds the “actual debt amount for this year” in ST13, the process proceeds to ST17. In ST17, the “separate reserve inclusion balance sheet creation processing unit (program) 63” of FIG. 8 operates, and the difference data between “actual debt amount of this year” and “asset amount” is set as “separate reserve fund”. Debt account ”and stored in the“ balance sheet data storage unit 64 ”.
FIG. 15 is a schematic explanatory diagram illustrating an example of a balance sheet that has been separately funded.
The “balance sheet data storage unit 64” in FIG. 8 stores data of “balance sheet” shown in FIG.

Claims (9)

A pension information management program for causing a computer to predict benefit information to be received in the future by a pension member and to obtain current fixed actuarial debt information, which is accumulated information to be accumulated on the fixed date in advance,
This fixed date is a set of candidate rate information linked to medium- to long-term expected rate of return information on pension assets on the fixed date, based on information related to subscribers etc. on the fixed date that has already been acquired on the computer. Using the planned rate candidate information, the previous fixed date basis actuarial debt candidate information that is candidate information of the accumulated amount information on a plurality of previous fixed dates corresponding to each is generated,
At least the candidate information of the increase information of the burden amount from the previous fixed date to the current fixed date corresponding to each of the current fixed date scheduled rate candidate information based on the subscriber related information on the previous fixed date To generate multiple current date standard premium candidate information
Input the actuarial debt information corresponding to the previous fixed date based scheduled interest rate that is the accumulated amount information on the previous fixed date corresponding to the current fixed date input planned interest rate information that is the current scheduled interest rate information on the current fixed date. Identified by using daily basis actuarial debt candidate information,
The current fixed date input scheduled interest rate corresponding standard premium information that is an increase information of the amount of burden from the previous fixed date corresponding to the current fixed date input scheduled interest rate information to the current fixed date is used by using a plurality of current fixed date standard premium candidate information To identify
At least the previous fixed date basis input interest rate corresponding actuarial debt information, the current fixed date input planned interest rate information, the current fixed date input planned interest rate corresponding standard premium information, and the input from the previous fixed date to the current fixed date And a pension information management program characterized in that the current fixed actuarial debt information is generated on the basis of predicted correction benefit information which is predicted benefit information of a lump sum. At least, based on the subscriber related information on the previous fixed date, using the current fixed date scheduled rate candidate information, the candidate information of the increase information of the burden amount from the current fixed date to the next fixed date corresponding to each Generate multiple next fixed date standard premium candidate information,
The next fixed date input scheduled interest rate corresponding standard premium information, which is the increase information of the burden amount from the current fixed date to the next fixed date corresponding to the current fixed date input scheduled interest rate information, using a plurality of the next fixed date standard premium candidate information The pension information management program according to claim 1, characterized by:   Based on the predicted asset amount information that is the predicted value of the asset amount on the current fixed date, the predicted salary amount that is the predicted value of the salary, and the depreciable years information, the amount of burden from the current fixed date to the next fixed date for the salary information Standard premium rate information that is an increase rate information of the current amount, and shortage information that occurs due to the relationship between the predicted asset amount information and the current fixed actuarial debt information is input to the current fixed date input scheduled interest rate information with the depreciation information 3. The pension information management program according to claim 2, wherein the amount information for amortization of principal and interest is generated as special contribution rate information that is rate information for the salary information.   Based on at least the current fixed actuarial debt information, the predicted asset amount information, the standard premium rate information, and the special premium rate information, predicted balance sheet information for predicting balance sheet information on the current fixed date is generated. The pension information management program according to claim 3.   The current fixed date input fixed interest rate information, which is the fixed interest rate information entered on the current fixed date entered after the arrival of the current fixed date, and the fixed benefit information for the pension and lump sums from the previous fixed date entered to the current fixed date. Based on certain fixed benefit information, the final fixed actuarial debt information that is the fixed fixed actuarial debt information is generated, and the next fixed date is calculated based on the fixed fixed rate input fixed interest rate information. The pension information management program according to claim 1 or 2, wherein the standard premium candidate information is determined.   The fixed asset amount information that is information on the fixed asset amount on the fixed date this time, the fixed salary information that is information on the fixed salary amount, and the information on the fixed depreciation period that is input after the arrival of the fixed date this time. The pension information management program according to any one of claims 3 to 5, wherein the standard premium rate information and the special premium rate information are generated based on certain fixed depreciation years information.   6. The balance sheet is generated based on at least the fixed current actuarial debt information, the fixed asset amount information, the fixed salary information and the fixed depreciation information. 6. The pension information management program described in 6. A pension information management device that predicts benefit information that a pension member should receive in the future and generates current fixed actuarial debt information that is accumulated amount information to be accumulated on the fixed date in advance,
At least the scheduled rate candidate for the current fixed date that is the multiple planned rate candidate information linked to the medium- to long-term expected rate of return information for the plan assets on the fixed date based on the information related to the subscribers etc. already acquired on the previous fixed date Using the information to generate previous fixed date basis actuarial debt candidate information that is candidate information of the accumulated amount information on a plurality of previous fixed dates corresponding to each,
At least the candidate information of the increase information of the burden amount from the previous fixed date to the current fixed date corresponding to each of the current fixed date scheduled rate candidate information based on the subscriber related information on the previous fixed date Generate multiple current fixed date standard premium candidate information
Input the actuarial debt information corresponding to the previous fixed date based scheduled interest rate that is the accumulated amount information on the previous fixed date corresponding to the current fixed date input planned interest rate information that is the current scheduled interest rate information on the current fixed date. Identified by using daily basis actuarial debt candidate information,
The current fixed date input scheduled interest rate corresponding standard premium information that is an increase information of the amount of burden from the previous fixed date corresponding to the current fixed date input scheduled interest rate information to the current fixed date is used by using a plurality of current fixed date standard premium candidate information To identify
At least the previous fixed date basis input interest rate corresponding actuarial debt information, the current fixed date input planned interest rate information, the current fixed date input planned interest rate corresponding standard premium information, and the input from the previous fixed date to the current fixed date The pension information management device is configured to generate the current fixed actuarial debt information based on the predicted correction benefit amount information which is the predicted benefit amount information of the lump sum. A pension information management method for predicting benefit information to be received in the future by a pension member and generating current fixed actuarial debt information which is accumulated amount information to be accumulated on the fixed date in advance,
At least the scheduled rate candidate for the current fixed date that is the multiple planned rate candidate information linked to the medium- to long-term expected rate of return information for the plan assets on the fixed date based on the information related to the subscribers etc. already acquired on the previous fixed date Using the information to generate previous fixed date basis actuarial debt candidate information that is candidate information of the accumulated amount information on a plurality of previous fixed dates corresponding to each,
At least the candidate information of the increase information of the burden amount from the previous fixed date to the current fixed date corresponding to each of the current fixed date scheduled rate candidate information based on the subscriber related information on the previous fixed date Generate multiple current fixed date standard premium candidate information
Input the actuarial debt information corresponding to the previous fixed date based scheduled interest rate that is the accumulated amount information on the previous fixed date corresponding to the current fixed date input planned interest rate information that is the current scheduled interest rate information on the current fixed date. Identified by using daily basis actuarial debt candidate information,
The current fixed date input scheduled interest rate corresponding standard premium information that is an increase information of the amount of burden from the previous fixed date corresponding to the current fixed date input scheduled interest rate information to the current fixed date is used by using a plurality of current fixed date standard premium candidate information To identify
At least the previous fixed date basis input interest rate corresponding actuarial debt information, the current fixed date input planned interest rate information, the current fixed date input planned interest rate corresponding standard premium information, and the input from the previous fixed date to the current fixed date And the pension information management method, wherein the current fixed actuarial debt information is generated based on the predicted correction benefit information which is the predicted benefit information of the lump sum.

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