KR101954131B1 - An unmanned payment system - Google Patents

Abstract

The present invention relates to an unattended payment system capable of notice and convenient payment of taxes and fines. The unattended payment system comprises: an information extraction unit which is linked to an unattended kiosk and extracts personal information of payers, payment history information of payers, and economic index information from a database; a payment pattern analysis unit to estimate expected payment dates of payers based on the extracted payment history information of payers; a personal information analysis unit to generate a new payment pattern to correct the expected payment dates if the extracted payer personal information is changed; an economic incorporation unit to further estimate expected additional payment dates based on the economic index information; and a smart notification unit to notify payers of tax payment in response to the expected payment dates and the expected additional payment dates. The personal information analysis unit includes: an information change reading unit to read items with changed personal information; a correction payment pattern analysis unit to estimate expected change payment dates based on payment history information from time when the personal information is changed if the personal information is changed; and an expected date correction unit to correct the expected payment dates to the expected change payment dates. The economic incorporation unit includes: a growth determination unit to determine whether economic growth exits from an extracted economic index; and an expected additional payment date specifying unit to estimate expected additional payment dates different from the expected payment dates if economic growth is not determined.

Description

AN UNMANNED PAYMENT SYSTEM

TECHNICAL FIELD [0002] The technology disclosed in this specification relates to a payment system, and more particularly, to an unattended payment system capable of noticing taxes and fines and easily paying.

Various systems or methods for efficiently charging and collecting utility bills and taxes have been developed, and in recent years, systems using the Internet or mobile have been developed.

These systems are designed to efficiently handle bills of lading, receipt and inquiries, and administrative tasks for paying bills.

According to Japanese Laid-Open Patent Application No. 2001-142971, a tax information management system for outputting and managing the data of tax offsets is disclosed. According to Japanese Patent Laid-Open No. 2003-203143, A delinquent person management system for performing a management with a computer until a predetermined procedure is performed.

Korean Patent Laid-Open No. 2007-0096568 discloses a system for executing tax notice and settlement through a messenger function of a mobile phone. According to Korean Patent Laid-Open No. 2009-0002113, a taxpayer And provides a method of providing a bill payment account service.

In Korean Patent Registration No. 10-1422562 ("Intelligent Collection Management System"), the personal information of the payment person and the history of the payment from the database storing personal information, address, payment record and consultation contents of the payment person A grouping means for grouping the payer according to the extracted personal information; a weight setting means for assigning a weight to each group based on the payment history information of the payer belonging to each of the grouped groups; A rating determining means for determining a rating of the payer based on the payment history information of the individual payer and the weight of the group to which the payer is assigned; a payment notification means for determining the payment notification method according to the rating of the payer and notifying the payment person It is possible to reduce the occurrence of delinquencies in advance by using the information of the payer or the payment characteristics , There is to provide a convenient and useful payment service technology is disclosed.

The unmanned payment system disclosed in the present specification intends to provide an unattended payment system capable of paying at least notices such as taxes and fines and easy payment.

The unattended payment system disclosed in this specification includes an information extracting unit 100 for extracting personal information of the payment person, payment history information of the payment person, and economic index information from the database 10 in cooperation with an unmanned kiosk, A payment pattern analyzing unit (200) for estimating a payment expectation date of the payment person based on the payment history information of the payment person, and a payment pattern analyzing unit (200) for, when there is a change in the extracted payment person personal information, An analysis unit 300, an economic reflector 500 for further estimating an expected additional payment date based on the economic indicator information, a smart notification unit 500 for making a payment payment notice to the payment person in response to the expected payment date and the additional payment expected date 400, and the personal information analyzing unit 300 includes an information change reading unit 310 for reading an item in which personal information is changed, A correction payment pattern analyzing unit 320 for estimating a change payment expectation date based on the payment history information from when the personal information is changed, and a prospective date correcting unit 330 for correcting the payment expectation date to a change payment expectation date The economic reflection unit 500 includes a growth determination unit 510 for determining whether or not an economic growth has occurred based on the extracted economic indicators, and an additional payment forecasting unit for estimating an expected additional payment date And a determination unit 520.

The personal information analyzing unit 300 may further include a pattern change reading unit 340 for reading a payment date change based on the payment history information of the payment person.

The personal information analyzing unit 300 includes an item-specific pattern setting unit 350 that sets the changed item of the personal information and the estimated date of the change payment as the expected payment date for each item, And an item determiner 360 for reading whether the item is the same as the item of the item.

The unattended payment system analyzes the payment pattern of the payment person and estimates the expected payment date, estimates the expected payment date by predicting the state of payment of the payment person through the state of change of the personal information of the payment person and the national economic index, The payment date is corrected in accordance with the change of the personal information of the payer in accordance with the change of the personal information of the payer or the notification of the payment is made at the expected date of payment of additional payment so that the notice of payment is made on the date corresponding to the personal circumstances of the payer through the economic index, , The convenience of taxpayers' tax payment is increased, and the tax payment can be reduced by allowing the tax to be paid before the consumption tax is consumed due to deterioration of the economic situation. .

The unattended payment system can respond in real time to the change of the personal information of the payment person through the pattern change reading unit of the personal information analyzing unit, the pattern setting unit for each item and the item judging unit, so that the payment notice is paid on the best date corresponding to the personal circumstances of the payment person There is an effect that can proceed.

The foregoing provides only a selective concept in a simplified form as to what is described in more detail hereinafter. The present disclosure is not intended to limit the scope of the claims or limit the scope of essential features or essential features of the claims.

1 is a block diagram schematically illustrating the configuration of an unattended payment system according to an embodiment.
2 is a block diagram schematically illustrating a personal information analyzing unit according to an exemplary embodiment of the present invention.
3 is a block diagram schematically illustrating a personal information analyzing unit according to another embodiment.
FIG. 4 is a block diagram schematically illustrating an economic reflector in an embodiment.
5 is a block diagram schematically showing a configuration of an unattended payment system according to another embodiment.

1 is a block diagram schematically illustrating the configuration of an unattended payment system according to an embodiment. 2 is a block diagram schematically illustrating a personal information analyzing unit according to an exemplary embodiment of the present invention. 3 is a block diagram schematically illustrating a personal information analyzing unit according to another embodiment. FIG. 4 is a block diagram schematically illustrating an economic reflector in an embodiment. 5 is a block diagram schematically showing a configuration of an unattended payment system according to another embodiment.

The information extracting unit 100, the payment pattern analyzing unit 200, the personal information analyzing unit 300, and the personal information analyzing unit 300 are operated in cooperation with a kiosk that operates unattended, An economic reflection unit 500, and a smart notification unit 400. [

The payment pattern analyzing unit 200 may include a time limit setting unit 210 and a predicted date designation unit 220.

The personal information analyzing unit 300 may include an information change reading unit 310, a correction payment pattern analyzing unit 320, and an expected correction unit 330.

The personal information analyzing unit 300 may further include a pattern change reading unit 340.

The personal information analyzing unit 300 includes an information change reading unit 310, a correction payment pattern analyzing unit 320 and an item-specific pattern setting unit 350. The personal information analyzing unit 300 includes an item determining unit 360, ).

Hereinafter, a representative embodiment of the unmanned payment system disclosed in the present specification will be described in detail.

The unattended payment system according to an embodiment of the present invention includes an information extraction unit 100 for extracting personal information of a payment person, payment history information of a payment person, and economic index information from a database 10 in cooperation with an unattended kiosk, A payment pattern analyzing unit (200) for estimating a payment expectation date of the payment person based on the extracted payment history information of the payment person, a payment pattern analyzing unit (200) for generating a new payment pattern when the extracted payment person personal information is changed, A personal information analyzing unit 300 for analyzing the economic indicator information, an economic reflector 500 for estimating the expected additional payment date based on the economic indicator information, a smart payment unit 500 for notifying the payment person of the tax payment notice in response to the expected payment date, The personal information analyzing unit 300 may include an information change reading unit 310 for reading items whose personal information has been changed, A payment payment pattern analyzing unit 320 for estimating a change payment expectation date based on the payment history information from when the personal information is changed, and a prospective date correcting unit 330 for correcting the payment expectation date to a change payment expectation date The economic reflection unit 500 includes a growth determination unit 510 for determining whether or not the economic growth has occurred based on the extracted economic indicators, and an additional estimation unit for estimating an expected additional payment date And a payment forecasting unit 520. [

First of all, the unmanned payment system disclosed in this specification allows a payer to pay taxes through a kiosk in accordance with a tax notice to be described below in conjunction with a conventional kiosk (KIOSK).

The information extracting unit 100 is configured to extract the personal information of the payment person, the payment history information of the payment person, and the economic indicator information from the database 10. The personal information of the payer and the payment history information of the payer are read out from the database 100 in which the personal information of the payer, address, payment record, consultation contents, and the like are stored, and text mining Information is extracted. The economic index information refers to various economic growth rates disclosed by various organizations such as the IMF, ADB, and the Bank of Korea, and extracts the tabular index information stored in the database 10. The personal information is information on the gender, age, address, residence type, marital status (married / married), property and income status, workplace information and the like of the payment person, and the payment history information includes payment date, payment method, The number of days in arrears, the frequency of delinquencies, the reasons for delinquencies, and the status of payments. Here, the housing type largely means an apartment, a multi-family house, a multi-family house, and the present state of payment means the state of payment such as health insurance premium and national tax. The information extracting unit 100 may collect and extract more accurate information in cooperation with a geographic information system such as a GIS (Geographic Information System). In addition, the extracted personal information and payment history information can be classified and coded to facilitate management.

The payment pattern analyzing unit 200 is configured to estimate the payment expected date of the payment person based on the extracted payment history information of the payment person. The payment pattern analyzing unit 200 includes a time setting unit 210 for setting a time limit by an administrator. The payment pattern analyzing unit 200 includes an estimation date designation unit 220 for estimating an average date of the payment dates included in the payment history information within a set period of time and designating the average day as a payment expected date.

For example, when the administrator sets the recent three-year period through the setting section 210, the average value (date) of the date of payment for the last three years of the payer is extracted. And the estimated average value is estimated as a predicted payment date by the determination unit 220. The payment pattern analyzing unit 200 estimates the situation where the payment person can actually pay through the payment history.

The personal information analyzing unit 300 is configured to analyze the new payment pattern to correct the expected payment date when there is a change in the extracted payment person's personal information. The personal information analyzing unit 300 may roughly include the information change reading unit 310, the correction payment pattern analyzing unit 320 and the expected correction unit 330. [

The information change reading unit 310 reads the item whose personal information has been changed.

When the personal information is changed, the correction payment pattern analyzing unit 320 generates a new payment pattern based on the payment history information from the time when the personal information is changed, and estimates the change payment expectation date.

For example, if there is a change in the personal information of the payer (such as the work information directly connected to the payer's income) in March 2017, a new payment pattern based on the payment history information from March 2017 to the present is created, Estimate the average payment date based on the payment pattern as the expected change payment date.

The predicted date correcting unit 330 corrects the expected payout date to the expected payment due date by the corrected payment pattern analyzer 320.

For example, the predicted date correcting unit 330 may calculate the estimated date of the estimated payment date through the payment pattern analyzer 200 described above by using the corrected payment pattern analyzer 320 described above, Change to the date. The personal information analyzing unit 300 estimates the payment date of the payer according to the personal circumstances, that is, the personal information, by estimating the change of the personal information with the personal circumstances of the payer, . Further, it is also possible to determine whether the variation of the payment date is temporary or continuing through the information change reading unit 310. [

As shown in FIG. 4, the economic reflector 500 may roughly include a growth determination unit 510 and an additional payment expectation determination unit 520.

The growth determining unit 510 determines whether the economic growth is possible based on the economic indicator information extracted from the database 10.

For example, the growth decision unit 510 may compute information on the economic growth rate included in the economic indicator information extracted by the information extraction unit 100 to derive an average growth rate, And if it is - the value, it is judged that economic growth is impossible. In other words, the economic growth is estimated to be the increase or decrease in the income of the payer or the fund. Furthermore, the economic growth rate can be judged based on the rise rate versus the growth rate of a specific period.

If it is determined that the economic growth is not judged through the growth decision unit 510, the additional payment forecasting unit 520 estimates the additional payment expected date of the date that is different from the expected payment date.

The economic reflection unit 500 has an effect of predicting the economic situation of the taxpayer and encouraging the payment, so that the tax payment can be made before the purchase of the luxury goods even if the payer's economic situation is bad.

The smart notification unit 400 is configured to notify the payment person in response to the expected payment date. The smart notification unit 400 notifies the payment person of the payment of the tax in correspondence with the estimated payment date and the estimated additional payment date.

Meanwhile, the smart notification unit 400 may notify the estimated payment date through the payment pattern analyzing unit 200, notify the estimated payment date through the personal information analyzing unit 300, And can be repeatedly notified according to the revised payment expected date.

The unmanned payment system described above can not only respond to the complainant's complaints but also analyzes the payment pattern of the payment person and estimates the expected payment date according to the change of the personal information of the payment person and the national economic index By predicting the pensioner's economic situation and estimating the expected additional payment date, the estimated payment date is corrected in accordance with the change in the personal information of the payer, or the payment notification is made at the expected payment date, If payment notice is made on the date corresponding to the circumstances, the convenience of the taxpayers' payment of tax is increased and the tax payment can be reduced by making the tax to be paid before the consumption tax is consumed due to deterioration of the economic situation There is an effect.

The unattended payment system can respond in real time to the change of the personal information of the payment person through the pattern change reading unit of the personal information analyzing unit, the pattern setting unit for each item and the item judging unit, so that the payment notice is paid on the best date corresponding to the personal circumstances of the payment person There is an effect that can proceed.

2, the personal information analyzing unit 300 configured by the information change reading unit 310, the correction payment pattern analyzing unit 320, and the expected correction unit 330 includes a pattern change reading unit 340 May be further included.

The pattern change reading unit 340 reads the change of the payment pattern based on the payment history information of the payment person. The pattern change reading unit 340 will be described in more detail, based on the payment history information, whether the payment date paid recently is paid on a date different from the expected payment date.

The information change reading unit 310 of the personal information analyzing unit 300 including the pattern change reading unit 340 reads the item whose personal information is changed when the payment pattern is changed. When the personal information is changed, the correction payment pattern analyzing unit 320 estimates the change payment expectation date based on the payment history information from the time when the personal information is changed. The expected date correcting unit 330 corrects the expected date of payment to the expected date of payment.

The personal information analyzing unit 300 described above can preferentially extract personal circumstances that substantially affect the payment date of the payment person. The personal information analyzing unit 300 can extract the personal circumstances that substantially affect the change in the payment date from the personal information, so that it is possible to carry out the notification closer to the personal circumstances of the payer.

3, the personal information analyzing unit 300 configured by the information change reading unit 310, the correction payment pattern analyzing unit 320, and the expected correction unit 330 includes a pattern setting unit 350 for each item, And an item judging unit 360. [0040]

The item-by-item pattern setting unit 350 sets the changed item of the personal information through the information change reading unit 310 and the estimated change payment due date through the correction payment pattern analyzing unit 320 described above And stores it in the database 10.

The item judging unit 360 reads whether the item whose personal information is changed is the same as the item of the estimated payment date for each item.

The information extracting unit 100 further extracts the information on the expected payment due to each item. If the items for which the personal information is changed are the same, the predicted date correcting unit 330 corrects the expected payment date to the expected change payment date.

When the payment person pays the payment in 20 days with the estimated payment date estimated through the payment pattern analyzer 200 described above being 15 days, the information change reading unit 310 The changed personal information (work information) and the payment date are read out.

Then, the item judging unit 360 reads whether the item is the same as the item of the estimated payment date for each item. If the item is not the item of the same personal information (workplace information), the items of personal information A new payment pattern is generated from the day on which the workplace information is changed, and the estimate of the change payment is estimated.

Then, the item-specific pattern setting unit 350 stores in the database 10 the estimated payment date for each item including the changed personal information item (workplace information) and the estimated change payment date corresponding to the item, 330) to finally correct the expected payment date.

On the other hand, when the estimated payment date for each item in the workplace information is stored in the database 10, the item determination unit 360 corrects the estimated payment date based on the estimated change payment date stored in the item determination unit 360.

The expected date of payment for change included in the estimated payment date for each item described above is -5 days, which is the difference value between 20 days and 15 days. In other words, the expected date for payment of change is the day after subtracting 5 days from the previous expected payment date.

As another example, the estimated change payment date can be estimated based on the pay day included in the work information when the item of work information is changed.

The personal information analyzing unit 300 including the item-by-item pattern setting unit 350 and the item judging unit 360 can easily estimate the estimated change-due date only with changed items of the personal information. The personal information analyzing unit 300 has an effect that it is possible to estimate the payment expected date with a sufficiently high accuracy because the payment history information used in the correction payment pattern analyzing unit 320 is not sufficient.

The pattern change reading unit 340, the item-specific pattern setting unit 350, and the item determining unit 360 may be combined.

The unattended payment system with reference to FIG. 5 according to another embodiment may further include a grouping unit 600. FIG.

The grouping unit 600 groups the personal information extracted by the information extracting unit 10 by the payer. Specifically, group the payer by gender, age, address, residential type, marital status, and workplace of personal information. Furthermore, they may be grouped by the same payment date of the payment history information.

Meanwhile, the smart notification unit 400 of the present embodiment may change the notification count for each group.

The unattended payment system including the grouping unit 600 may further include a weight setting unit 700 as shown in FIG.

The weight setting unit 700 assigns appropriate weights based on the payment history information of the payer who belongs to each group generated by the grouping. That is, the delinquent characteristics are analyzed for each group, and a weight is given according to the result.

For example, it is possible to give a relatively high weight to addressees with a high average value and a relatively low weight to addressees with a low average value by averaging delinquent recipients' delinquencies, delinquent days, and delinquency frequency by grouped address. As another example, in the case of payment history information such as the reason for delinquency of a payer, a relatively high weight is given to a reason for which delinquency is unlikely to be solved, and a relatively low weight can be given for a reason likely to solve delinquency have. For such weighting, the statistical theory of RFM (Recency, Frequency, Monetary) can be applied.

In assigning the weights in this way, not only the individual payment characteristics of the payment person but also the external conditions such as the living environment are used together, so that the possibility of delinquent payment of the payment person can be determined more accurately and precisely.

As shown in FIG. 5, the unattended payment system including the weight setting unit 700 may further include a rating determination unit 800. FIG.

On the other hand, the rating determination unit 800 determines the rating of the payer based on the payment history information of the payer and the weight of the group to which the payer belongs. More specifically, the rating decision unit 800 assigns a basic grade score to the payer according to the amount of delinquency, the number of delinquent days, and the repayment frequency from the payment history information, and assigns the weight of each group to which the payer belongs to the basic score The final grade score of the payer is calculated. The grade of the payer is determined according to the calculated final grade score.

The level of the payer can be set to an appropriate number as needed. For example, a lower level means a loyal taxpayer and a higher level means a malicious delinquent.

Meanwhile, the smart notification unit 400 according to the present embodiment may change the notification count for each rank.

The unattended payment system described in connection with the various embodiments is only for the convenience of explanation, and various components may be combined in various combinations.

On the other hand, it may be constituted by one conventional server having an input / output device, or may be dispersed in a plurality of servers. In this embodiment, one server is used. This server always communicates with the database 10 to read out the information on the payer-related information of the database 10 that is continuously updated.

While the present invention has been described with reference to the preferred embodiments described above and the accompanying drawings, it is to be understood that the invention may be practiced otherwise than as specifically described herein. Accordingly, the scope of the disclosure herein is defined by the appended claims, and is not to be construed as limited to the specific embodiments described herein.

10: Database
100: Information extracting unit
200: payment pattern analysis section
210:
220: anticipated government
300: Personal Information Analysis Department
310: information change reading unit
320: correction payment pattern analysis unit
330: The expected date and time
340: Pattern change reading unit
350: Item-specific pattern setting unit
360: Item judging unit
400: Notification section
500: Economic reflection department
510: growth decision unit
520: Expected payment plan
600:
700: Weight setting unit
800:
900: Kiosk

Claims (3)

In a payment system linked to a kiosk,
An information extraction unit (100) for extracting economic indicator information including personal information of the payment person, payment history information of the payment person and information on the economic growth rate from the database (10);
A payment pattern analyzing unit (200) for estimating an average date of the payment date included in the payment history information of the extracted payment person as the expected payment date of the payment person;
A personal information analysis unit (300) for generating a new payment pattern and correcting the expected payment date when the extracted payment person individual information is changed;
An economic reflector 500 for further estimating the estimated additional payment based on the economic indicator information extracted by the information extracting unit 100;
And a smart notification unit (400) for notifying the payment person of payment of the tax in correspondence with the expected payment date and the estimated additional payment date,
The personal information analyzing unit 300 includes an information change reading unit 310 for reading an item in which personal information has been changed, and payment information for the work information of the personal information from the point of time when the pay day is changed when the pay day is changed. A correction payment pattern analyzing unit 320 for estimating an average date of a payment date included in the history information as a change payment expectation date, and an expected date correcting unit 330 for correcting the expected payment date to a change payment expectation date,
The economic reflection unit 500 includes a growth determination unit 510 for determining whether or not the economic growth has occurred based on the extracted economic indicators, and an additional payment forecasting unit for estimating an expected additional payment date Including the subsystem 520,
The payment date of the payment person is estimated based on the personal circumstances and the unattended payment can be made through the kiosk according to the payment details of the tax that has been estimated, system. The method according to claim 1,
The personal information analysis unit 300
And a pattern change reading unit (340) for reading a payment date change based on the payment history information of the payment person. The method according to claim 1,
The personal information analysis unit 300
And an item-specific pattern setting unit (350) for setting the changed item of the personal information and the estimated date of the change payment as the expected payment date for each item,
And an item judging section (360) for reading whether the item whose personal information has changed is the same as the item of the estimated payment date for each item.

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