• Title/Summary/Keyword: 체납

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A Study on the Effect of Benefit Limit Measure on the likelihood of the late payers of paying missed health insurance premium: The Case of Korea (건강보험료 체납자에 대한 급여제한 사전통지제도의 효과성 분석)

  • Cho, Byong-Hee;Yoo, Taekyun;Yun, Seong-Won
    • Korean Journal of Social Welfare Studies
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    • v.44 no.3
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    • pp.421-450
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    • 2013
  • One of the challenging tasks of the National Health Insurance Corporation(NHIC). the only public insurance institution administrating the Korea's compulsory national health insurance(NHI) system, is to make those NHI beneficiaries who fail to make a scheduled monthly premium payment to pay. For this purpose, the NHIC has been using a measure known as 'Benefit Limit Measure(BLM)' in which those who miss premium payment for six or more month's in total are classified as 'late payer' and are sent warnings and late payer status notices. If the late payers fail to make a full payment of missed premiums even after receiving the written notices, the NHIC can order a temporary seizure of the late payer's property until all missed premiums plus interest are paid. Recently, the BLM has been criticized by the public of its cruel nature, and its effectiveness has been questioned because no empirical evidence has been collected. In this study, the authors using the NHIC data set attempted to analyze the effectiveness of the BLM. Those late payers for whom the BLM was administered were compared to those not in terms of the likelihood of paying missed premium payments with a series of logistic regression analyses models. Data analyses results showed that the likelihood of paying one or more month's unpaid premium of the former group was 14 to 46 times higher than the latter. It, however, was also found that the BLM was only effective to make no more than 12% of the late payers to pay at all. Based on the study findings, the authors made a few recommendations regarding the BLM.

Prediction Model for Unpaid Customers Using Big Data (빅 데이터 기반의 체납 수용가 예측 모델)

  • Jeong, Jaean;Lee, Kyouhwan;Jung, Hoekyung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.7
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    • pp.827-833
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    • 2020
  • In this paper, to reduce the unpaid rate of local governments, the internal data elements affecting the arrears in Water-INFOS are searched through interviews with meter readers in certain local governments. Candidate data affecting arrears from national statistical data were derived. The influence of the independent variable on the dependent variable was sampled by examining the disorder of the dependent variable in the data set called information gain. We also evaluated the higher prediction rates of decision tree and logistic regression using n-fold cross-validation. The results confirmed that the decision tree can find more accurate customer payment patterns than logistic regression. In the process of developing an analysis algorithm model using machine learning, the optimal values of two environmental variables, the minimum number of data and the maximum purity, which directly affect the complexity and accuracy of the decision tree, are derived to improve the accuracy of the algorithm.

리포트 - 2013년도 산재보험료율.바뀌는 제도

  • Jo, Gap-Jun
    • 프린팅코리아
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    • v.12 no.3
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    • pp.74-75
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    • 2013
  • 인쇄업과 경인쇄업의 산재보험료율이 통합돼 같은 요율을 적용받게 되고, 제책업의 요율도 소폭 하락하는 등 2013년의 산재보험료율 부담이 다소 경감됐다. 또한 최저 임금은 280원 인상된 4860원으로 책정됐으며, 지방세 가산세가 최고 40%로 향상되고, 상습 지방세 체납 기준도 2년에서 1년으로 단축됐다.

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A Study on the Late Payment Behavior of the National Health Insurance Contribution (국민건강보험 지역보험료 체납 결정요인 및 체납확률 예측모형)

  • 정우진;이선미;김원훈;신승호;조우현
    • Health Policy and Management
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    • v.13 no.2
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    • pp.85-100
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    • 2003
  • The purpose of this study is to (1) identify socio-demographic, economic, village-effect variables that influence the late payment of the National Health Insurance contribution, (2) to develop the model to predict the probability of a household to make late payment of the contribution. Data is composed of information on 78,858 households, Gangnam branch, National Health Insurance Corporation, as of September 30, 2001. We analyzed the data by using multivariate logistic regressions. The major findings are as follows; (1) an older or female householder whose family consists of smaller number of members is more likely to pay the contribution late than others, (2) as for income, one who belongs to a lower income group or nm a private business tend to pay it late, (3) more attention should be paid to a householders who does not have his/her own house or automobile so as to prevent late payment, (4) lastly, those who live in villages such as Nonhyun-l-dong are less likely to pay the contribution prior to due date.

Using Video Function of Smart Phone Number plate recognition & Real-time Inquiry System (스마트폰의 영상기능을 이용한 차량 번호판 인식 및 실시간 조회 시스템)

  • Park, Min-Sung;Woo, Jong-Seong;Kim, Gwan-Hyung;Sin, Dong-Seok
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.10a
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    • pp.111-112
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    • 2013
  • 본 논문에서는 최근 증가하고 있는 차량의 질서 위반 행위 및 과태료 체납, 대포차 등에 대한 문제를 보다 효율적으로 해결하기 위하여 이동이 간편한 스마트 기기를 통하여 차량의 번호판을 인식하고 관리할 수 있는 시스템을 제시하고자 한다. 영상 촬영 기능과 데이터 전송 기능을 가지고 있는 휴대용 단말기를 소지한 사용자가 자동차의 번호판을 촬영했을 시 자동차 번호판을 인식하고 촬영된 영상과 차량 번호에 대한 데이터를 원격지 서버로 전송하여 차량 소유자에 대한 과태료 체납여부, 위반행위 등을 조회하여 해당 차량에 대한 정보 등을 신속하게 확인하고 현장에서 복합적으로 대응할 수 있는 시스템을 개발하고자 한다. 본 논문에서 제시할 주요한 기능은 영상처리를 통한 차량 번호판 인식과 인식된 차량 번호 정보와 번호판 영상 정보를 원격지 서버로 전송하여 정보를 관리 할 수 있는 시스템을 제시하고자 한다.

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2007년 한국오리협회 정기총회 및 워크샵 개최

  • Korea Duck Association
    • Monthly Duck's Village
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    • s.45
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    • pp.90-93
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    • 2007
  • 지난 2월 27일, 본 회에서는 사육, 부화, 계열 및 유통분과 회원들이 한 자리에 모인 가운데 회원간 단합과 오리산업의 발전을 도모하기 위해 이틀간 합동 워크샵을 개최하였다. 이번 워크샵에서는 각 분과별 회비 납부 기준, 2005년 새끼오리 판매부문 미거출 회비문제 처리방안, 회비 장기체납회원 처리문제 및 이사정수조정 건 등, 협회 내 근본적 문제를 허심탄회하게 논의하는 데 중점을 두고 논의된 사항을 이사회와 정기총회를 거쳐 의결하는 순으로 진행되었다. 워크샵 진행 내용은 다음과 같다.

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Categorized the Contribution evasion through Health Insurance contribution evasion expected model (건강보험 체납예측모형을 통한 체납세대의 유형화 및 특성)

  • 이애경;최인덕
    • Health Policy and Management
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    • v.14 no.2
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    • pp.78-98
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    • 2004
  • The purpose of this study was to categorize the contribution evasion and develop the expected models for contribution arrears in National Health Care System. The modified logistic regression model in non-payments was used as logistic regression model based on the statistical method. By using this model, we arranged non-payment types and typical branches those are appeared by statistical technique. First fact, sex and age branches those are able to take a part in economy had effect mostly. Also they had difference in non-payment probability by existence of their incomes and property. Especially people who didn't have their own house and car were appeared in high non-payment probability, disease and reduction characteristic(rare diseases, reduction of seniors, handicaps, numbers of medical treatments) didn't effect much in probability. The reason for some characteristic of non-payment which is higher than the correct threshold value of Logistic Regression Model (a suggested model for predicting non-payment)'s distribution of probability was mostly moral hazard. Living difficulty was the bigger reason for non-payment, but moral slackening was the bigger reason for non-payment. But it is careless to decide that moral hazard is just the reason, there is a necessity to examine on the side of sociology based in family. By the reason, the member's non-payment reason can be classified by economy, population, and psychology, but there was a comprehension that losing of work desire could be one reason. So we analyzed informations for composition of family of members. In conclusion, we grasped that family conflict makes non-payment and conversion of member in the National Basic Livelihood Protection System difficult.

Issues and Perception on Management Fee and Rental Payment Overdue of Permanent Rental Housing Residents (영구임대주택 입주자의 관리비 및 임대료 체납 실태와 의식)

  • Kim,, Young-Joo;Kim, Young-Tae
    • Journal of the Korean housing association
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    • v.18 no.5
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    • pp.73-84
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    • 2007
  • Permanent rental housing, the construction of which was strongly financed by the central government, is regarded as a social housing for those who fall within the lowest income bracket. Differing from "public rental housing", offered to tenants for sale after a five year rental period, this type of housing is intended for rental use on a long-tenn basis. At present, about 190,000 permanent rental housing units exist in Korea. According to a statistics, 15.6% of its residents did not pay their management fee and rental payment in 4 or more months in 2005, which places stress on the housing management. Based on the "eviction condition" stipulated in the tenancy agreement for permanent rental housing, a householder owning assets or a vehicle which is not used as his means of living, who is overdue with his management fee and rental payment for a long time, may be evicted from the house. However, there are many conflicts and problems between administrators/housing managers and residents in the process of enforcing this regulation. The purpose of this study is to explore the key issues associated with the present situation and the reasons why so many management fee and rental payment for permanent rental housing are overdue. For the purpose of research, data were collected from 10,990 permanent rental housing residents nationwide via a questionnaire survey in February 2007. One third of the respondents had an experience of more than 2 months overdue since they have moved in current residence. For further analysis, the respondents were divided into three groups, based on their working ability. The major finding showed that the group of respondents who have working ability required a more practical plan, such as employment, to have a sustainable life, while the other group of no labor force indicated a need for more housing allowance from the government. To suggest more specific alternatives for the subject of housing payment overdue, further comparison study should be performed between the residents of permanent rental housing and other low income tenants in private housing sector.