System and method for providing year-end tax settlement analysis service

Abstract

The present invention provides a system for providing a year-end tax settlement analysis service, and a method using same, the system comprising: a scraping unit for obtaining past year-end tax settlement information and current time financial information of a user from an external system, and generating a basic data set for each deduction item of the past year-end tax settlement information and a basic data set for each deduction item of the current time financial information on the basis of the obtained past year-end tax settlement information and current time financial information of the user; a year-end tax settlement analysis unit for generating deduction item-specific year-end tax settlement analysis information including a deduction amount and a maximum deduction condition amount for each deduction item on the basis of the basic data set for each deduction item of the past year-end tax settlement information; an inference unit for generating deduction item-specific financial consulting information about the user on the basis of the deduction item-specific year-end tax settlement analysis information and the basic data set of the current time financial information; and an output unit for transmitting the deduction item-specific year-end tax settlement analysis information and / or the deduction item-specific financial consulting information to a user terminal and displaying same through the user terminal.

Description

System and method for providing year-end settlement analysis service

[0001] The present invention relates to a system and method for providing a year-end settlement analysis service, and more particularly, to a system and method for providing a year-end settlement analysis service that can provide more accurate year-end settlement prediction information and financial consulting information based on past year-end settlement information and current financial information.

[0002] Year-end tax settlement refers to the procedure by which the National Tax Service settles any overpayment or underpayment of income tax withheld in advance at the end or beginning of each year, additionally collecting any underpaid amount and refunding any overpaid amount.

[0003] Since the year-end settlement conditions for each user are different, such as whether they meet various deduction items and deduction conditions, users need to accurately determine their deduction conditions and predict their financial activities, such as consumption and savings, for the year to maximize their year-end settlement amount.

[0004] However, because tax laws are so complex, it is difficult for users to accurately understand them in advance, making it practically impossible to determine what form of financial activity is desirable at the current point in time.

[0005] [Prior Art Literature]

[0006] Republic of Korea Patent Publication No. 10-2022-0111643 (published on August 9, 2022)

[0007] The purpose of the present invention is to provide a year-end settlement analysis service provision system and method that can provide more accurate year-end settlement prediction information and financial consulting information based on past year-end settlement information and current point-in-time financial information.

[0008] According to one aspect of the present invention, a year-end settlement analysis service providing system is provided, comprising: a scraping unit that obtains a user's past year-end settlement information and current point-in-time financial information from an external system, and generates a basic data set for each deduction item of the past year-end settlement information and the current point-in-time financial information based on the obtained past year-end settlement information and the current point-in-time financial information of the user; a year-end settlement analysis unit that generates year-end settlement analysis information for each deduction item, including a deduction amount and a maximum deduction condition amount for each deduction item, based on the basic data set for each deduction item of the past year-end settlement information; an inference unit that generates financial consulting information for each deduction item for the user based on the basic data set of the year-end settlement analysis information for each deduction item and the current point-in-time financial information; and an output unit that transmits at least one of the year-end settlement analysis information for each deduction item and the financial consulting information for each deduction item to a user terminal so as to be displayed on the user terminal.

[0009] Here, the current financial information may include at least one of bank deposit and loan information, insurance subscription information, credit card-related information, and securities account-related information, which is financial status information that may affect the user's year-end settlement at the current time.

[0010] In addition, the year-end settlement analysis unit may include a deduction amount calculation unit that calculates a deduction amount for each deduction item from a basic data set for each deduction item of past year-end settlement information and generates primary analysis data including the deduction amount; and a deduction amount calculation unit that generates year-end settlement analysis information for each deduction item including the deduction amount and the maximum deduction condition amount that enables the maximum deduction amount based on the primary analysis data.

[0011] In addition, the above-mentioned inference unit may include a year-end settlement analysis model that generates consulting information related to the user's specific details for each deduction item based on year-end settlement analysis information for each deduction item; and a year-end settlement prediction model that generates deduction prediction information for each deduction item based on the year-end settlement analysis information for each deduction item and a basic data set of current point-in-time financial information.

[0012] In addition, the year-end settlement analysis model may be implemented as an artificial intelligence-based model that has been trained in advance to input year-end settlement analysis information for each deduction item and output consulting information related to the user's specific details, and the year-end settlement prediction model may be implemented as an artificial intelligence-based model that has been trained in advance to input year-end settlement analysis information for each deduction item and a basic data set of current financial information and output deduction prediction amount information for the corresponding deduction item and financial activity consulting information related thereto.

[0013] In addition, the above-mentioned year-end settlement prediction model can generate deduction prediction information including information on the predicted amount of deduction that can be deducted this year and financial activity consulting information related to the corresponding deduction item.

[0014] In addition, the above-mentioned inference unit further includes a product recommendation model that generates financial product information related to the deduction item, and the product recommendation model can be trained in advance to output financial product information for the corresponding deduction item by inputting a basic data set of year-end settlement analysis information for each deduction item and current point-in-time financial information.

[0015] Additionally, the year-end settlement analysis model, year-end settlement prediction model, and product recommendation model may also receive the user's personal information.

[0016] In addition, the year-end settlement analysis model, year-end settlement prediction model, and product recommendation model can use income-related information including income statement information among the statement information obtained from the scraping unit as input.

[0017] In addition, the output section can output year-end settlement analysis information and financial consulting information for all deduction items and display them on a user terminal.

[0018] In addition, the above-mentioned inference unit may further include a future financial information prediction unit that generates predicted financial activity information of the user from the present time to the end of the year, and reconstructs the present time financial information by adding the predicted financial activity information to the present time financial information.

[0019] In addition, the future financial information prediction unit may calculate future financial activity information based on the average value of the current financial information for each deduction item of the user from this year to the present, or may calculate future financial activity information based on the average value of the user's financial activity for the same period in the past year.

[0020] In addition, the future financial information prediction unit can predict future financial activity information from past financial activity information of other users who have something in common with the user.

[0021] In addition, the future financial information prediction unit is learned in advance by the user's personal information, year-end settlement analysis information by deduction item, and current point-in-time financial information, and can output future financial activity information by inputting the user's personal information, year-end settlement analysis information by deduction item, and current point-in-time financial information.

[0022] In addition, the system may further include a user data management unit that receives financial data input by a user through a user terminal and transmits the received financial data to a year-end settlement analysis unit and an inference unit.

[0023] Additionally, the user input data may include future financial activity information or income information for this year from the present time to the end of this year.

[0024] According to another aspect of the present invention, a year-end tax settlement analysis service providing method is provided, comprising: a first step of obtaining a user's past year-end tax settlement information and current financial information from an external system when a year-end tax settlement analysis service request signal is received from a user terminal; a second step of generating a basic data set for each deduction item of past year-end tax settlement information and current financial information based on the user's past year-end tax settlement information and current financial information; a third step of generating year-end tax settlement analysis information for each deduction item, including a deduction amount and a maximum deduction condition amount for each deduction item, based on the basic data set for each deduction item of the past year-end tax settlement information; a fourth step of generating financial consulting information for each deduction item for the user based on the basic data set of the year-end tax settlement analysis information for each deduction item and the current financial information; and a fifth step of transmitting the year-end tax settlement analysis information for each deduction item and the financial consulting information for each deduction item to a user terminal, wherein the user terminal displays the received year-end tax settlement analysis information for each deduction item and the financial consulting information.

[0025] According to the present invention, a system and method for providing a year-end settlement analysis service can be provided that can provide more accurate year-end settlement prediction information and financial consulting information based on past year-end settlement information and current financial information.

[0026] In particular, the present invention has the advantage of enabling the user to accurately determine consulting information in advance on how to conduct financial activities to maximize the year-end settlement amount by using an artificial intelligence-based inference model.

[0027] Figure 1 is a drawing showing the connection relationship of the year-end settlement analysis service provision system (100) according to the present invention.

[0028] Figure 2 is a drawing showing an example of the configuration of a system (100).

[0029] Figure 3 shows an example of a basic data set for each deduction item of past year-end settlement information and current point-in-time financial information generated in the scraping unit (110).

[0030] Figure 4 is a drawing showing an example of the configuration of the year-end settlement analysis unit (120).

[0031] Figure 5 shows an example of generating primary analysis data.

[0032] Figure 6 shows an example of year-end settlement analysis information by deduction item.

[0033] Figure 7 is a diagram showing the configuration of the inference unit (130).

[0034] Figure 8 shows an example of consulting information generated from the year-end settlement analysis model (131).

[0035] Figure 9 shows an example of deduction prediction information generated from the year-end settlement prediction model (132).

[0036] Figure 10 shows an example of financial product information generated by a product recommendation model (133).

[0037] Figure 11 shows an example of year-end settlement analysis information and financial consulting information for each deduction item displayed on a user terminal (200) by an output unit (140).

[0038] Figures 12 and 13 illustrate other examples of year-end settlement analysis information and financial consulting information for each deduction item displayed on a user terminal (200) by an output unit (140).

[0039] Figure 14 shows an example of year-end settlement analysis information and financial consulting information for all deduction items displayed on a user terminal (200) by an output unit (140).

[0040] Figure 15 shows the configuration of an inference unit (130-1) according to another embodiment of the present invention.

[0041] Figure 16 shows the configuration of a system (100-1) according to another embodiment of the present invention.

[0042] Figure 17 is a flowchart showing an embodiment of a method for providing a year-end settlement analysis service according to the present invention performed in a system (100, 100-1) as described above.

[0043] Hereinafter, an embodiment of the present invention will be described in detail with reference to the attached drawings.

[0044] Figure 1 is a drawing showing the connection relationship of the year-end settlement analysis service provision system (100) according to the present invention.

[0045] Referring to FIG. 1, a year-end settlement analysis service provision system (100, hereinafter simply referred to as “system (100)”) is connected to a user terminal (200) and an external system (300) via a network.

[0046] The user terminal (200) refers to a conventionally known device such as a computer, a smartphone, a smart pad, etc., and is equipped with an application for performing the service according to the present invention.

[0047] The external system (300) may include the National Tax Service system (310) and the Financial Supervisory Service system (320).

[0048] The National Tax Service system (310) stores the user's past year-end settlement information, and as described below, receives a request signal for the user's past year-end settlement information from the system (100) via an Open API, performs a necessary authentication procedure, and then transmits the user's past year-end settlement information to the system (100).

[0049] The financial settlement system (320) stores the user's current financial information, and also receives a user's current financial information request signal from the system (100) via Open API, performs the necessary authentication procedure, and then transmits the user's current financial information to the system (100).

[0050] Additionally, the external system (300) may further include other agency systems (330). The other agency systems (330) may include, for example, systems such as the Statistics Korea system, the Ministry of Employment and Labor system, etc., which receive information request signals from the system (100) and transmit information corresponding to the information request signals to the system (100).

[0051] The system (100) is combined with a user terminal (200) and an external system (300) to transmit and receive necessary information and provide a year-end settlement analysis service to the user terminal (200).

[0052] Figure 2 is a drawing showing an example of the configuration of a system (100).

[0053] Referring to FIG. 2, the system (100) includes a scraping unit (110), a year-end settlement analysis unit (120), an inference unit (130), and an output unit (140).

[0054] Additionally, the system (100) may include a database (150) that stores various data necessary for implementing the present invention.

[0055] The scraping unit (110) acquires the user's past year-end settlement information and current point-in-time financial information from an external system (300), and performs the function of generating a basic data set for each deduction item based on the acquired user's past year-end settlement information and current point-in-time financial information.

[0056] Past year-end tax settlement information can be obtained from the National Tax Service system (310) of the external system (300). This can be accomplished by transmitting the user's authentication information using the Open API provided by the National Tax Service system (310), performing authentication in the National Tax Service system (310), and then receiving the user's past year-end tax settlement information.

[0057] Here, the past year-end settlement information refers to the user's past year-end settlement information that has been definitively reported to the National Tax Service system (310). For example, the past year-end settlement information may be the user's last year-end settlement information.

[0058] The scraping unit (110) processes and handles raw data of past year-end settlement information, creates a basic data set for each deduction item of past year-end settlement information, and transmits it to the year-end settlement analysis unit (120).

[0059] The scraping unit (110) can extract specification information including at least one of income specification information, tax-exempt and tax-reduced income specification information, settlement specification information, tax amount information, deduction specification information, and detailed deduction specification information from past year-end settlement information, and can create a basic data set for each deduction item of past year-end settlement information based on the extracted specification information.

[0060] The basic data set for each deduction item of the past year-end settlement information generated is transmitted to the year-end settlement analysis department (120).

[0061] Meanwhile, current financial information can be obtained from the financial settlement system (320) of the external system (300). This can also be accomplished by transmitting the user's authentication information using the Open API provided by the financial settlement system (320), performing authentication in the financial settlement system (320), and then receiving the user's current financial information.

[0062] Here, financial information refers to financial status information related to the user, and all financial status information that may affect the user's year-end settlement, and current financial information refers to financial information at the time the financial information is acquired.

[0063] Such current financial information may include at least one of, for example, bank deposit and loan information, insurance subscription information, credit card information, and securities account information.

[0064] The scraping unit (110) creates a basic data set of current point-in-time financial information including at least one of bank deposit and loan information, insurance subscription information, credit card-related information, and securities account-related information from current point-in-time financial information, which is raw data, and transmits it to the inference unit (130).

[0065] Figure 3 shows an example of a basic data set for each deduction item of past year-end settlement information and current point-in-time financial information generated in the scraping unit (110).

[0066] Figure 3 (A) shows the basic data set when the deduction item among the past year-end settlement information is a credit card. Since the user used two credit cards, the basic data set for the deduction item credit card includes two basic data sets for each credit card.

[0067] As illustrated, the basic data set may include card identification information, handling institution information, deductible amount information, monthly usage information, and other usage information.

[0068] In addition, (B) of FIG. 3 shows a basic data set for credit card-related information among the current point-in-time financial information, and since the user used two credit cards, it also includes two basic data sets for each credit card.

[0069] As illustrated, the basic data set may include card identification information, handling institution information, usage amount information, and data date information.

[0070] The year-end settlement analysis unit (120) performs a function of generating year-end settlement analysis information for each deduction item, including the deduction amount and maximum deduction condition amount for each deduction item, based on the basic data set for each deduction item of past year-end settlement information transmitted from the scraping unit (110).

[0071] Figure 4 is a drawing showing an example of the configuration of the year-end settlement analysis unit (120).

[0072] Referring to FIG. 4, the year-end settlement analysis unit (120) includes at least one year-end settlement analysis unit (121 to 123) for each deduction item.

[0073] In Fig. 4, for the convenience of explanation, a total of three deduction items (deduction items A, B, and C) are shown, but this is only an example, and in reality, each year-end settlement analysis section is included for all deduction items subject to deduction in the year-end settlement.

[0074] The year-end settlement analysis section (121-123) by deduction item includes a deduction target amount calculation section (1211) and a deduction amount calculation section (1212).

[0075] Although the data used may differ depending on the deduction item, the basic principle is the same. Therefore, in the following, deduction item A will be assumed to be a “credit card” and the analysis data generation unit (121) for this will be explained as an example.

[0076] The deduction amount calculation unit (1211) calculates the deduction amount for each deduction item from the basic data set for each deduction item of the past year-end settlement information, and creates primary analysis data including the deduction amount.

[0077] The deduction target amount calculation unit (1211) references the deduction rules for each deduction item based on the tax law of the year in which the year-end settlement is made in the database (150), calculates the deduction target amount for each deduction item, and creates primary analysis data including the deduction target amount.

[0078] Figure 5 shows an example of generating primary analysis data.

[0079] The left side of Fig. 5 shows the basic data set in the case where the deduction item is a credit card among the past year-end settlement information generated by the scraping unit (110) as described above. The basic data set may include card identification information, handling agency information, deduction target amount information, monthly usage information, and other usage information.

[0080] The right side of Figure 5 shows the primary analysis data generated based on the basic data set for these deductible item credit cards.

[0081] Referring to this, since the deduction amount in the credit card deduction rule is the total credit card usage amount minus other usage amounts, it can be seen that the remaining amount of 14,500,000 won, which is the amount minus other usage amounts from the usage amounts of the two credit cards, was calculated as the deduction amount.

[0082] The primary analysis data including the deductible amount calculated in this way is transmitted to the deductible amount calculation unit (1212).

[0083] The deduction amount calculation unit (1212) generates year-end settlement analysis information for each deduction item, including the deduction amount and the maximum deduction condition amount that enables the maximum deduction amount, based on the primary analysis data calculated in the deduction target amount calculation unit (1211).

[0084] Figure 6 shows an example of year-end settlement analysis information by deduction item.

[0085] Referring to Figure 6, year-end settlement analysis information by deduction item may include information on deduction target amount, deduction amount information, and maximum deduction condition amount information.

[0086] The deductible amount (KRW 14,500,000) can be obtained from the primary analysis data described above. The deductible amount is KRW 675,000, indicating that KRW 675,000 was deducted from the credit card deductible item.

[0087] Additionally, the maximum deduction condition amount refers to the maximum amount a user can deduct for a deduction item. In the example of Figure 6, it can be seen that the maximum deduction can be received only if a credit card is used for 10,000,000 won. The maximum deduction condition amount can be calculated by referencing the deduction rules for each deduction item described above in the database (150).

[0088] The deduction amount calculation unit (1212) generates year-end settlement analysis information for each deduction item, including the deduction amount and maximum deduction condition amount, and transmits it to the inference unit (130).

[0089] The inference unit (130) performs the function of generating financial consulting information for each deduction item for the user based on the basic data set of year-end settlement analysis information for each deduction item and current point-in-time financial information.

[0090] Here, year-end settlement analysis information for each deduction item is generated and transmitted from the year-end settlement analysis unit (120), and the basic data set of current point-in-time financial information is transmitted from the scraping unit (110).

[0091] Figure 7 is a diagram showing the configuration of the inference unit (130).

[0092] Referring to FIG. 7, the inference unit (130) may include a year-end settlement analysis model (131), a year-end settlement prediction model (132), and a product recommendation model (133).

[0093] The year-end settlement analysis model (131) performs the function of generating consulting information related to the user's specific details for each deduction item based on the year-end settlement analysis information for each deduction item.

[0094] To perform these functions, the year-end tax settlement analysis model (131) can be implemented as an artificial intelligence (AI)-based model. For example, the year-end tax settlement analysis model (131) can be implemented as a neural network model based on deep learning. In this case, the year-end tax settlement analysis model (131) can be trained in advance to input year-end tax settlement analysis information for each deduction item and output consulting information related to the user's specific needs.

[0095] Figure 8 shows an example of consulting information generated from the year-end settlement analysis model (131).

[0096] Referring to Figure 8, it can be seen that a total of three pieces of consulting information were generated, and consulting information 1 outputs that the amount used on a deductible credit card has decreased compared to the average for other months. This is because the year-end settlement analysis model (131) automatically determined and outputted a special feature that the average amount used has decreased compared to other months in the user's year-end settlement analysis information for each deductible item.

[0097] Additionally, Consulting Information 2 outputs information related to the special feature that the total usage amount has decreased compared to the past usage amount of the user before last year, and Consulting Information 3 outputs information related to the special feature that the average usage amount is lower compared to that of other users of the same age as the user.

[0098] The year-end settlement prediction model (132) performs the function of generating deduction prediction information for each deduction item based on the year-end settlement analysis information for each deduction item and the basic data set of current point-in-time financial information.

[0099] Here, the deduction forecast information includes information on the deduction forecast amount that can be deducted this year and financial activity consulting information related to the deduction item.

[0100] To perform these functions, the year-end tax settlement prediction model (132) may also be implemented as an artificial intelligence model, for example, a neural network model based on deep learning. In this case, the year-end tax settlement prediction model (132) may be trained in advance to input year-end tax settlement analysis information for each deduction item and a basic data set of current financial information, and output deduction prediction amount information for the corresponding deduction item and related financial activity consulting information.

[0101] In this case, it is desirable for the year-end settlement prediction model (132) to also receive the user's personal information.

[0102] Figure 9 shows an example of deduction prediction information generated from the year-end settlement prediction model (132).

[0103] Referring to Figure 9, three deduction forecasts were output for the deduction item credit card. Deduction forecast information 1 indicates that the predicted amount a user can deduct this year for the deduction item credit card is KRW 675,000.

[0104] Additionally, Deduction Forecast Information 2 indicates that the maximum deduction amount, which allows for maximum deductions based on credit card, debit card, and cash receipt usage, has already been achieved for the deductible credit card. Therefore, it can be seen that the financial consulting information was generated and output to advise users to minimize credit card usage and increase debit card and cash receipt usage.

[0105] In addition, it can be seen that Deduction Forecast Information 3 provides financial consulting information to achieve the maximum deduction amount (KRW 3,000,000) for the remainder of the year in relation to the deduction item credit card, and provides an increase in the amount of debit card and cash receipt usage by KRW 12,300,000.

[0106] The product recommendation model (133) performs the function of generating financial product information related to deduction items.

[0107] The product recommendation model (133) can know the information of the credit card currently being used by the user for the deduction item credit card, and can therefore provide credit card information that can provide better benefits to the user in addition to the credit card.

[0108] To perform these functions, the product recommendation model (133) may also be implemented as an artificial intelligence model, such as a neural network model based on deep learning. In this case, the product recommendation model (133) may be trained in advance to output financial product information for each deduction item, using a basic data set of year-end settlement analysis information for each deduction item and current financial information.

[0109] Figure 10 shows an example of financial product information generated by a product recommendation model (133).

[0110] Referring to Figure 10, it can be seen that when the same amount is used, information about another credit card with better conditions, such as annual fees or points, is output compared to the credit card the user is currently using.

[0111] Meanwhile, it is desirable that the year-end settlement analysis model (131), year-end settlement prediction model (132), and product recommendation model (133) implemented as artificial intelligence models also receive user personal information such as the user's gender, age, occupation, workplace, and address.

[0112] Additionally, the year-end settlement analysis model (131), year-end settlement prediction model (132), and product recommendation model (133) can use the specification information acquired from the scraping unit (110) as input. For example, among the specification information, at least one of income-related information, such as income specification information, tax-exempt and tax-reduced income specification information, etc., can be used as input for each model.

[0113] Meanwhile, the output unit (140) performs a function of transmitting at least one of the year-end settlement analysis information and financial consulting information for each deduction item generated by the inference unit (130) to the user terminal (200) and displaying it through the user terminal (200).

[0114] Figure 11 shows an example of year-end settlement analysis information and financial consulting information for each deduction item displayed on a user terminal (200) by an output unit (140).

[0115] Referring to Figure 11, it can be seen that the deductible amount is "17,622,637 won" as the year-end settlement analysis information for each deductible item for the deductible credit card, and the financial consulting information as described above is displayed below it.

[0116] Additionally, the amount of use corresponding to the financial consulting information is displayed in a graph at the bottom to help users understand intuitively.

[0117] In the above, credit cards were explained as a deduction item, but the basic principles are the same for other deduction items, so year-end settlement analysis information and financial consulting information for each deduction item can be printed and displayed in the same way.

[0118] Figures 12 and 13 illustrate other examples of year-end settlement analysis information and financial consulting information for each deduction item displayed on a user terminal (200) by an output unit (140).

[0119] Figure 12 shows the year-end settlement analysis information and financial consulting information for each deduction item of personal pension savings when the deduction item is guaranteed insurance, and Figure 13 shows the year-end settlement analysis information and financial consulting information for each deduction item of personal pension savings.

[0120] Referring to FIGS. 12 and 13, the specific consulting information is slightly different from that in FIG. 11, where the deduction item is a credit card, but the basic principle of providing the deduction target amount and consulting information that can maximize the deduction amount is the same.

[0121] Meanwhile, the output unit (140) can output year-end settlement analysis information and financial consulting information for all deduction items and display them through the user terminal (200).

[0122] Figure 14 shows an example of year-end settlement analysis information and financial consulting information for all deduction items displayed on a user terminal (200) by an output unit (140).

[0123] Referring to Figure 14, it can be seen that the deduction amount (refund amount) information is displayed for all deduction items, and financial consulting information is printed below it.

[0124] Figure 15 shows the configuration of an inference unit (130-1) according to another embodiment of the present invention.

[0125] The inference unit (130-1) of FIG. 15 is the same as the inference unit (130) of FIG. 6, but differs in that it further includes a future financial information prediction unit (134).

[0126] The future financial information prediction unit (134) performs the function of generating forecast information on the user's financial activities from the present time to the end of this year.

[0127] Since year-end settlement is performed based on financial activities from January 1 to December 31 of each year, for example, if the year-end settlement analysis service according to the present invention is performed on October 15, the current financial information from January 1 to October 15 of this year can be used, but the financial information from October 16 to December 31 cannot be used.

[0128] Therefore, the future financial information prediction unit (134) predicts financial activity information occurring from the present time to the end of this year, and reconstructs the present time financial information by adding the predicted financial activity information to the present time financial information.

[0129] In addition, each of the year-end settlement analysis model (131), year-end settlement prediction model (132), and product recommendation model (133) operates as described above using the reconstructed current point-in-time financial information.

[0130] The future financial information prediction unit (134) can generate financial activity prediction information in the following manner.

[0131] First, we can calculate the average value of the current financial information for each deduction item from January 1st of this year to the present, and then calculate future financial activity information based on this.

[0132] Alternatively, you can average a user's financial activity for the same period in past years and use that as a basis to calculate future financial activity information.

[0133] Another approach is to predict future financial activity based on the past financial activity of other users who share similar characteristics. For example, one method might be to identify users with similar personal information, obtain their financial activity data for the past three years, and then calculate the average of that data.

[0134] These functions can also be implemented as artificial intelligence models, such as neural network models based on deep learning. In this case, the future financial information prediction unit (134) is trained in advance based on user personal information, year-end settlement analysis information by deduction item, and current financial information, and can output future financial activity information by taking user personal information, year-end settlement analysis information by deduction item, and current financial information as input.

[0135] Figure 16 shows the configuration of a system (100-1) according to another embodiment of the present invention.

[0136] The system (100-1) of FIG. 16 is identical to the system (100) of FIGS. 1 to 14, but differs in that it further includes a user data management unit (160).

[0137] The user data management unit (160) receives financial data input by the user through the user terminal (200) and performs the function of transmitting the received financial data to the year-end settlement analysis unit (120) and inference unit (130).

[0138] User input data may include future financial activity information from the present time to the end of the year. As described above, future financial activity information may be predicted by the future information prediction unit (134), but this information may also be input by the user.

[0139] Additionally, user-entered data can include this year's income information. While last year's income information can be obtained from past year-end tax settlement information, changes in this year's income cannot be obtained from past year-end tax settlement information. Therefore, this information can be obtained from the user.

[0140] Additionally, user input data may include personal information about the user. For example, information such as a change in address or job title may be collected from the user.

[0141] This user input data is transmitted to the year-end settlement analysis unit (120) and the inference unit (130), and the year-end settlement analysis unit (120) and the inference unit (130) perform the operations described above by taking the user input data into consideration together.

[0142] Figure 17 is a flowchart showing an embodiment of a method for providing a year-end settlement analysis service according to the present invention performed in a system (100, 100-1) as described above.

[0143] Referring to FIG. 17, first, when the system (100) receives a request signal for a year-end settlement analysis service according to the present invention from a user terminal (200) (S100), it transmits a request signal for past year-end settlement information of the corresponding user to the National Tax Service system (310) and receives past year-end settlement information of the corresponding user (S110, S120).

[0144] Additionally, the system (100) requests the current financial information of the user from the financial settlement system (320) and receives the current financial information of the user (S130, S140).

[0145] Next, the scraping unit (110) of the system (100) generates a basic data set for each deduction item of the past year-end settlement information and the present point-in-time financial information based on the acquired past year-end settlement information and the present point-in-time financial information of the user as described above (S150).

[0146] And, as described above, the year-end settlement analysis unit (120) of the system (100) generates year-end settlement analysis information for each deduction item, including the deduction amount and maximum deduction condition amount for each deduction item, based on the basic data set for each deduction item of past year-end settlement information (S160).

[0147] Next, the inference unit (130) of the system (100) generates financial consulting information for each deduction item for the user based on the basic data set of year-end settlement analysis information for each deduction item and current point-in-time financial information, as described above (S170).

[0148] And, the output unit (140) of the system (100) transmits year-end settlement analysis information and financial consulting information for each deduction item to the user terminal (200) (S180), and the user terminal (200) displays the received year-end settlement analysis information and financial consulting information for each deduction item on the display unit as described above (S190).

[0149] Although the present invention has been described above with reference to preferred embodiments according to the present invention, the present invention is not limited to the above embodiments, and various modifications and variations are of course possible within the scope of the present invention as understood by the attached claims and drawings.

[0150] For example, although not shown, the system (100, 100-1) may include a chatbot model based on artificial intelligence and may provide appropriate financial consulting information in response to year-end tax settlement-related questions received from users.

[0151] In addition, although not included in the city, it may further include a claim processing unit that can process year-end tax settlement reports, tax correction reports, etc. to the National Tax Service system (310) upon request from a user.

Claims

1. As a year-end settlement analysis service provision system, A scraping unit that obtains the user's past year-end settlement information and current point-in-time financial information from an external system, and creates a basic data set for each deduction item of the past year-end settlement information and current point-in-time financial information based on the obtained user's past year-end settlement information and current point-in-time financial information; A year-end settlement analysis unit that generates year-end settlement analysis information for each deduction item, including the deduction amount and maximum deduction condition amount for each deduction item, based on the basic data set for each deduction item of the above-mentioned past year-end settlement information; An inference unit that generates financial consulting information for each deduction item for the user based on the basic data set of year-end settlement analysis information for each deduction item and current financial information; and An output section that transmits at least one of the year-end settlement analysis information by deduction item and financial consulting information by deduction item to the user terminal and displays it through the user terminal. A system for providing year-end settlement analysis services including:

2. In claim 1, A year-end settlement analysis service providing system, characterized in that the current financial information is financial status information that can affect the user's year-end settlement at the current time, and includes at least one of bank deposit and loan information, insurance subscription information, credit card-related information, and securities account-related information.

3. In claim 1, The above year-end settlement analysis department, A deduction amount calculation unit that calculates the deduction amount for each deduction item from the basic data set for each deduction item of the past year-end settlement information and creates primary analysis data including the deduction amount; and A deduction amount calculation unit that generates year-end settlement analysis information for each deduction item, including the deduction amount and the maximum deduction condition amount that enables the maximum deduction amount, based on the above primary analysis data. A year-end settlement analysis service providing system characterized by including:

4. In claim 1, The above reasoning part is, A year-end settlement analysis model that generates consulting information related to the user's specific details for each deduction item based on year-end settlement analysis information for each deduction item; and A year-end settlement prediction model that generates deduction prediction information for each deduction item based on the year-end settlement analysis information for each deduction item and the basic data set of current financial information. A year-end settlement analysis service providing system characterized by including:

5. In claim 4, The above year-end settlement analysis model is implemented as an artificial intelligence-based model that has been trained in advance to input year-end settlement analysis information by deduction item and output consulting information related to the user's specific details. The above year-end settlement prediction model is a year-end settlement analysis service providing system characterized in that it is implemented as an artificial intelligence-based model that has been trained in advance to input year-end settlement analysis information for each deduction item and a basic data set of current financial information, and output deduction prediction amount information for the corresponding deduction item and financial activity consulting information related thereto.

6. In claim 4, The above year-end settlement prediction model is a year-end settlement analysis service providing system characterized by generating deduction prediction information including information on the deduction prediction amount that can be deducted this year and financial activity consulting information related to the corresponding deduction item.

7. In claim 4, The above reasoning part is, Product recommendation model that generates financial product information related to deduction items Including more, The above product recommendation model is a year-end settlement analysis service providing system characterized by being trained in advance to output financial product information for each deduction item by inputting year-end settlement analysis information for each deduction item and a basic data set of current financial information.

8. In claim 7, A year-end settlement analysis service providing system characterized in that the above year-end settlement analysis model, year-end settlement prediction model, and product recommendation model also receive the user's personal information.

9. In claim 8, A year-end settlement analysis service providing system characterized in that the year-end settlement analysis model, year-end settlement prediction model, and product recommendation model use income-related information including income statement information among the statement information obtained from the scraping unit as input.

10. In claim 1, A year-end settlement analysis service providing system characterized in that the above output section outputs year-end settlement analysis information and financial consulting information for all deduction items and displays them through a user terminal.

11. In claim 1, A year-end settlement analysis service providing system characterized in that the above-mentioned inference unit further includes a future financial information prediction unit that generates a user's financial activity prediction information from the present time to the end of the year, and reconstructs the present time financial information by adding the predicted financial activity information to the present time financial information.

12. In claim 11, The above future financial information prediction unit calculates future financial activity information based on the average value of the current point-in-time financial information of each deduction item from this year to the present of the user, or calculates future financial activity information based on the average value of the user's financial activity for the same period in the past year. A year-end settlement analysis service providing system.

13. In claim 11, A year-end settlement analysis service providing system characterized in that the above future financial information prediction unit predicts future financial activity information from past financial activity information of other users who have something in common with the user.

14. In claim 11, The above future financial information prediction unit is a year-end settlement analysis service providing system characterized in that it learns in advance by user personal information, year-end settlement analysis information by deduction item, and current point-in-time financial information, and outputs future financial activity information by taking user personal information, year-end settlement analysis information by deduction item, and current point-in-time financial information as input.

15. In claim 1, A year-end settlement analysis service providing system further comprising a user data management unit that receives financial data input by a user through a user terminal and transmits the received financial data to a year-end settlement analysis unit and an inference unit.

16. In claim 15, A year-end settlement analysis service providing system, characterized in that the above user input data includes future financial activity information or this year's income information from the present time to the end of this year.

17. As a method of providing year-end settlement analysis services, When a year-end settlement analysis service request signal is received from a user terminal, the first step is to obtain the user's past year-end settlement information and current financial information from an external system; A second step of generating a basic data set for each deduction item of past year-end settlement information and present point-in-time financial information based on the past year-end settlement information and present point-in-time financial information of the above user; A third step of generating year-end settlement analysis information for each deduction item, including the deduction amount and maximum deduction condition amount for each deduction item, based on the basic data set for each deduction item of the above-mentioned past year-end settlement information; A fourth step of generating financial consulting information for each deduction item for the user based on the basic data set of year-end settlement analysis information for each deduction item and current financial information; and Step 5: Sending year-end settlement analysis information for each deduction item and financial consulting information for each deduction item to the user terminal Including, A method for providing a year-end settlement analysis service, characterized in that the user terminal displays year-end settlement analysis information and financial consulting information for each of the received deduction items.

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