• The Journal of the Korean life insurance medical association
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• v.24
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• pp.79-96
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• 2005

1. 연구배경과 문제제기 - 보험시장의 환경변화 : 보험업법 개정, 방카슈랑스 도입, 고(高)보장성 생존급부(CI, LTC)상품의 등장, 통신판매 전문보험회사의 설립 허용 - 현행 언더라이팅 시스템의 문제점 : 위험난이도와 판매 채널별 특성이 고려되지 않고 언더라이터에 전건 배정 되어 업무의 효율성이 낮음 - 보험시장의 환경변화에 맞는 EUS(Expert Underwriting System) 도입으로 언더라이팅의 효율성을 증대하고자함 2. 국내/외 생보사 언더라이팅 시스템 현황 비교 및 개선방안 - 국내 언더라이팅 시스템 현황 : 청약서 입력/스캔 후 진단 및 적부 유무(有無)에 따라 자동으로 언더라이터에게 심사가 배정됨 - 미국 언더라이팅 시스템 현황 : EUS에 의한 1차 전산승낙여부 결정 후(後)언더라이터에게 심사가 배정됨 - 위험난이도의 고저(高低)와 관계없이 언더라이터에 배정되는 심사시스템의 문제점을 극복하고 체계적인 위험평가를 위해 EUS도입이 필요함 3. EUS 선행요건 - 고객정보의 확보 - 국내 생보사의 고객정보 수집원 : 청약서, 모집인 보고서, 건강진단서,적부조사, 보험사고정보조회시스템 (ICPS), 고액보험 및 상해보험 중복가입자에 대한 정보 교환제도 - 북미 생보사의 고객정보 수집원 : 청약서, 모집인 보고서, 의사소견서 및 진료기록서, 건강검진, 적부조사, 정보교환제도( 북미보험사간 의료정보 공유-MIB) - 정확한 고객정보의 확보방안 : 법률/제도의 정비, 청약서 질문 내용의 세분화, 의료정보교환제도의 구축 4. EUS 개요 및 현황 - EUS의 정의: 고객의 정보를 입력하여 청약부터 보험증권 발행 단계까지 One-Stop 서비스를 제공하는 것으로 언더라이터가 청약서를 가지고 언더라이팅 하는 것과 동일한 업무를 할 수 있는 전문가 시스템 - EUS의 장점: (1) 비용절감 및 인력의 효율적 활용 (2) 업무별 시스템화 되는 조직속성에 적합함. (3) 언더라이팅 정책이 경영 환경 변화에 대처하는데 신속함 - 국외 EUS 현황 (예: Cologne Re) 및 사례연구 5. 위험분류 및 EUS 개요현황 (언더라이팅 시스템 도입) - 위험관리 선행요건으로 위험요소별 분류가 체계적으로 수립되어야 함. - 데이터웨어하우스 (의사결정을 목적으로 설계된 조회와 분석이 가능한 통합된 정보저장소) 시스템 사용 - EUS 도입을 통한 언더라이팅 프로세스: 데이터마이닝 과정을 통해 "자동승낙, 언더라이터에게 심사배정, 적부의뢰, 진단의뢰, 텔레 언더라이터, 보완지시"등이 결정됨. 6. 판매채널별 EUS 활용방안 - 대면채널: 효용성 높은 정보제공과 정확한 위험분석이 가능한 시스템으로 고(高)보장, 고(高)위험 상품에 대해 언더라이터가 집중 심사 할 수 있게 함. - 방카슈랑스: 3S(간결, 신속, 서비스)의 특성에 맞는 전과정 무인자동심사시스템 - 비대면채널: 판매상품과 타겟시장을 명확히 한 후 도덕적 위험과 재무적 위험에 대한 평가시스템 및 의사결정 시스템을 도입 7. 결론 - EUS 도입의 기대효과 (1) 심사기일의 단축으로 고객만족 실현 (2) 체계적 과학적 리스크 관리로 위험률차익 증대에 기여 (3) 업무효율의 증대와 언더라이터의 역량강화 (4) CRM 활용증대와 모바일 청약시스템 구축의 근간 - EUS 도입시 경제적 법률적 제도적 문제 극복과 생보 업계 공동의 관심과 노력이 필요함 - EUS를 활용하여 종합적.체계적 리스크 관리가 가능한 금융회사로의 경쟁력 향상에 기여함.

• Journal of Service Research and Studies
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• v.13 no.2
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• pp.130-145
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• 2023

The digital transformation of finance is accelerating, and digital banking has already become a major banking channel. Banks have traditionally placed importance on CRM(Customer Relationship Management) and have tried to retain their loyal customers, who contribute significantly to the bank, such as long-term transactions, holding accounts with a certain balance or more, and holding loans. In this situation, this study exploratorily analyzed the consumer behavior of digital banking deposits in a major bank of Korea(1,145 samples). Statistical analysis was performed using SPSS. The main findings of the study are summarized as follows. It was found that there were differences of consumer behavior in digital banking deposits by generation, and the MZ generation used digital banking more on holidays than other generations. As a result of analyzing the behavior of existing loyal customers and regular customers of digital banking deposit, there was a significant difference in both the amount and period of the deposit. It was confirmed that the existing loyal customers of the bank also engage in consumer behavior that contributes to the bank in digital banking. In addition, the interaction between the customer type and the date of sign up for the deposit period, which is the goal setting of financial consumers, it was found that there was a significant effect. This study empirically analyzed the consumer behavior of digital banking in a situation where decrease of bank branches and encounters with digital banking. The major concepts of the consumer behavior theory are Loyal Customer, Goal Pursuit, and Habit, which were confirmed in an example of digital banking. The results of this study can suggest practical implications for existing banks and Internet-only banks, including the importance of customer management in digital banking.

• Journal of the Korea Society of Computer and Information
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• v.16 no.11
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• pp.123-135
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• 2011

The domestic market of database in Korea is estimated to be over 3.663 trillion won. The data migration is getting to be more important along with the continuous growth of the database industry. g-CRM and private recommending function are examples of the service that can be given through coupling among customer database, product database, geographic information database, and others. The core infrastructure is also the database which is integrated, perfect, and reliable. There are not enough researches on efficient way of data migration and integrating process and investigation of migrated data though trends of database in IT environment as above. In connection with this issue, we have made a model for data migration on scientific and technological contents and suggest the result of data migration process adapting that model. In addition, we verified migration's exhaustiveness, migration's consistency, and migration's coherence for investigation of migrated data and database. From the result, we conclude data migration based on proper model has a significant influence on the database consistency and the data values correctness and is essential to maintain high qualified database.

• Journal of Intelligence and Information Systems
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• v.7 no.2
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• pp.35-49
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• 2001

Over the years, cluster analysis has become a popular tool for marketing and segmentation researchers. There are various methods for cluster analysis. Among them, K-means partitioning cluster analysis is the most popular segmentation method. However, because the cluster analysis is very sensitive to the initial configurations of the data set at hand, it becomes an important issue to select an appropriate starting configuration that is comparable with the clustering of the whole data so as to improve the reliability of the clustering results. Many programs for K-mean cluster analysis employ various methods to choose the initial seeds and compute the centroids of clusters. In this paper, we suggest a methodology to evaluate various clustering programs. Furthermore, to explore the usability of the methodology, we evaluate four clustering programs by using the methodology.

• International Commerce and Information Review
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• v.4 no.2
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• pp.77-96
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• 2002

Through the new round DDA(Doha Development Agenda) negotiations which started in Doha/Qatar conference in November, 2001, service industries have been included in the category of international trades. An electronic commerce cannot be exceptional in this field. The 21st century is largely recognized as the era of globalization, knowledge, and information. To make effective and competitive strategy in this century, it is essentially required to organize Network. OPEN, and FU-PLEX. That is why our government also has been promoting this field since years before, now 10,000,000 people in Korea have joined superhighway internet networks. Korea became the top internet-developed country in the world. As a side-effect of this internet spread into our life, however, there is serious problem we are now faced against. That is the outflow of private information through electronic commerce and other cyber transactions. It has caused many social problems to be rapidly on the rise these days. We are now desperately required to struggle continuously to make a solution for that. Taking the precedent case of Germany and United States which are currently recognized as high-leveled country in protection of private information, we have to come up with legal and technical measures and at the same time, to escalate the social consciousness about private information protection.

• Asia pacific journal of information systems
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• v.18 no.1
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• pp.1-23
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• 2008

As managing customer relationship gets more important, companies are strengthening information service using multi-channels to their customers as a part of their customer relationship management (CRM) initiatives. It means companies are now accepting such information services not as simple information -delivering tools, but as strategic initiatives for acquiring and maintaining customer loyalty. In this paper, we attempt to validate whether or not such various information services would impact on organizational performance in terms of CRM strategy. More specifically, our research objective is to answer the next three questions: first, how to construct the instruments to measure not information quality but information service quality?; second, which attributes of information service quality can influence corporate image and customer loyalty?; finally, does each information service type have unique characteristics compared with others in terms of influencing corporate image and customer loyalty? With respect to providing answers to those questions, the previous studies had been limited in that those studies failed to consider the variety of types of information service or restricted the quality of information service to information quality. An appropriate research model answering the above questions should consider the fact that most companies are utilizing multi channels for their information services, and include the recent strategic information service such as customer online community. Moreover, since corporate information service could be regarded as a type of products or services delivered to customer, it is necessary to adopt the criteria for assessing customer's perceived value when to measure the quality of information service. Therefore, considering both multi-channels and multi-traits may enable us to tell the detailed causal routes showing which quality attributes of which information service would affect corporate image and customer loyalty. As information service channels, we include not only homepage and DM (direct mail), which are the most frequently applied information service channels, but also online community, which is getting more strategic importance in recent years. With respect to information service quality, we abstract information quality, convenience of information service, and timeliness of information service through a wide range of relevant literature reviews. As our dependant variables, we consider corporate image and customer loyalty that both of them are the critical determinants of organizational performance, and also attempt to grasp the relationship between the two constructs. We conducted a huge online survey at the homepage of one of representative dairy companies in Korea, and gathered 367 valid samples from 407 customers. The reliability and validity of our measurements were tested by using Cronbach's alpha coefficient and principal factor analysis respectively, and seven hypotheses were tested through performing correlation test and multiple regression analysis. The results from data analysis demonstrated that timeliness and convenience of homepage have positive effects on both corporate image and customer loyalty. In terms of DM, its' information quality was represented to influence both corporate image and customer loyalty, but we found its' convenience have a positive effect only on corporate image. With respect to online community, we found its timeliness contribute significantly both to corporate image and customer loyalty. Finally, as we expected, corporate image was revealed to provide a great influence to customer loyalty. This paper provides several academic and practical implications. Firstly, we think our research reinforces CRM literatures by developing the instruments for measuring information service quality. The previous relevant studies have mainly depended on the measurements of information quality or service quality which were developed independently. Secondly, the fact that we conducted our research in a real situation may enable academics and practitioners to understand the effects of information services more clearly. Finally, since our study involved three different types of information service which are most frequently applied in recent years, the results from our study might provide operational guidelines to the companies that are delivering their customers information by multi-channel. In other words, since we found that, in terms of customer loyalty, the key areas would be different from each other according to the types of information services, our analysis would help to make decisions such as selecting strengthening points or allocating resources by information service channels.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.11a
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• pp.247-256
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• 2000

오늘날의 기업은 상품을 판매하는 것 뿐만 아니라 기업의 신용과 이미지를 위해 그 상품에 대한 사후처리(After Service) 업무에 많은 투자를 하고 있다. 이러한 양질의 사후서비스를 고객에게 공급하기 위해서는 많은 인력을 합리적으로 관리해야 하고 요청되는 고장수리 서비스 업무를 빠르게 해결하기 위해서는 업무를 인력들에게 합리적으로 배정을 하고 회사의 비용을 최소화하면서 정해진 시간에 요청된 작업을 처리하기 위해서는 인력들에게 작업을 배정하고 스케줄링하는 문제가 발생된다. 본 논문에서는 이러한 문제를 해결하기 위해 화학계기의 A/S 작업을 인력에게 합리적으로 배정하는 스케줄링 시스템에 관한 연구이다. 먼저 스케줄링 모델을 HP 사의 화학분석 및 시스템을 판매, 유지보수 해 주는 "영진과학(주)"회사의 작업 스케줄을 분석하여 필요한 도메인과 고객서비스전략과 인력관리전략에서 제약조건을 추출하였고 여기에 스케줄링 문제를 해결하기 위한 방법으로 제약만족문제(CSP) 해결기법인 도메인 여과기법을 적용하였다. 도메인 여과기법은 제약조건에 의해 변수가 갖는 도메인의 불필요한 부분을 여과하는 것으로 제약조건과 관련되어 있는 변수의 도메인이 축소되는 것이다. 또한, 스케줄링을 하는데에 있어서 비용적인 측면에서의 스케줄링방법과 고객 만족도에서의 스케줄링 방법을 비교하여 가장 이상적인 해를 찾는데 트래이드오프(Trade-off)를 이용하여 최적의 해를 구했으며 실험을 통해 인력에게 더욱 효율적으로 작업들을 배정 할 수 있었고 또한, 정해진 시간에 많은 작업을 처리 할 수 있었으며 작업을 처리하는데 있어 소요되는 비용을 감소하는 결과를 얻을 수 있었다. 검증하였다.를, 지지도(support), 신뢰도(confidence), 리프트(lift), 컨빅션(conviction)등의 관계를 통해 다양한 방법으로 모색해본다. 이 연구에서 제안하는 이러한 개념계층상의 흥미로운 부분의 탐색은, 전자 상거래에서의 CRM(Customer Relationship Management)나 틈새시장(niche market) 마케팅 등에 적용가능하리라 여겨진다.선의 효과가 나타났다. 표본기업들을 훈련과 시험용으로 구분하여 분석한 결과는 전체적으로 재무/비재무적 지표를 고려한 인공신경망기법의 예측적중률이 높은 것으로 나타났다. 즉, 로지스틱회귀 분석의 재무적 지표모형은 훈련, 시험용이 84.45%, 85.10%인 반면, 재무/비재무적 지표모형은 84.45%, 85.08%로서 거의 동일한 예측적중률을 가졌으나 인공신경망기법 분석에서는 재무적 지표모형이 92.23%, 85.10%인 반면, 재무/비재무적 지표모형에서는 91.12%, 88.06%로서 향상된 예측적중률을 나타내었다.ting LMS according to increasing the step-size parameter $\mu$ in the experimentally computed. learning curve. Also we find that convergence speed of proposed algorithm is increased by (B+1) time proportional to B which B is the number of recycled data buffer without complexity

• Journal of Digital Convergence
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• v.13 no.1
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• pp.383-396
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• 2015

This study aims to identify factors related to rescreening the private health screening center. Data from private health screening center with seven district centers were analyzed. The number of subjects was 70,250 from 2008 through 2015. Socio-demographic characteristics, morbidity, history, physical measurement, laboratory test, and health behavior factors were analyzed the association with health rescreening using chi-square test and negative binominal regression. 19.2% of subjects were recheck their health status on each year from 2008 to 2012. The socio-demographic characteristics related to reuse private health screening center were male, 30-40 aged, Daegu, Gwangju, Jeonnam and Gyeongnam region residents. And overweight and pre-hypertension were also factors association with number of using the private health screening program. People who control their health risk factors such as alcohol intake, smoking and mental health and execute physical exercise tend to use health screening program regularly. Our finding suggest that customer relationship management can execute and private health screening center enable their strategic plan based on data-evidence.

• Journal of Fashion Business
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• v.7 no.1
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• pp.38-54
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• 2003

This study looked into the present status of e-mail marketing, which is conducted in local Internet fashion shopping malls and is being used as a one-to-one marketing method in the e-CRM concept so as to establish an effective e-mail marketing policy by grasping problems based on the current status and by presenting solutions to the problems. This study analyzed the e-mail letters received during a certain period of time by 30 professional Internet fashion shopping malls of with famous goods, brands and non-brands. Four individuals subscribed to shopping mall through the procedure for membership applying for e-mail services. The analysis showed that there were no shopping malls that were doing a differentiated e-mail marketing among Internet shopping malls. As for time factor, they were sending e-mail letters irregularly regardless of a certain cycle. And as for visual factor, they didnt have any standard for the content of the mail. As for content factor, the contents of their mail were not differentiated and all the same. The comparison of fashion malls showed that the brand shopping malls were the most active in e-mail marketing. On the basis of the problems, the direction for the effective e-mail marketing of Internet shopping malls are presented as follows: First, individualized contents fitting for customers should be developed, and differentiated mailing services should be provided thereby. Second, each shopping mall should make periodic tests of mailing to find out the optimal time and day to provide e-mail services to the customers at the designated time. Third, e-mail should be differentiated fitting for the website according to a certain on a certain standard for visual effects and the identity of shopping mall should be established. Firth, in the contents of e-mail, the image and message elements should be properly harmonized and creative policies should be made with interactive or recreational elements. Fifth, a homepage policy which can satisfy customers demand for information when the e-mail is clicked on..

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.137-148
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• 2014

Recommender system has become one of the most important technologies in e-commerce in these days. The ultimate reason to shop online, for many consumers, is to reduce the efforts for information search and purchase. Recommender system is a key technology to serve these needs. Many of the past studies about recommender systems have been devoted to developing and improving recommendation algorithms and collaborative filtering (CF) is known to be the most successful one. Despite its success, however, CF has several shortcomings such as cold-start, sparsity, gray sheep problems. In order to be able to generate recommendations, ordinary CF algorithms require evaluations or preference information directly from users. For new users who do not have any evaluations or preference information, therefore, CF cannot come up with recommendations (Cold-star problem). As the numbers of products and customers increase, the scale of the data increases exponentially and most of the data cells are empty. This sparse dataset makes computation for recommendation extremely hard (Sparsity problem). Since CF is based on the assumption that there are groups of users sharing common preferences or tastes, CF becomes inaccurate if there are many users with rare and unique tastes (Gray sheep problem). This study proposes a new algorithm that utilizes Social Network Analysis (SNA) techniques to resolve the gray sheep problem. We utilize 'degree centrality' in SNA to identify users with unique preferences (gray sheep). Degree centrality in SNA refers to the number of direct links to and from a node. In a network of users who are connected through common preferences or tastes, those with unique tastes have fewer links to other users (nodes) and they are isolated from other users. Therefore, gray sheep can be identified by calculating degree centrality of each node. We divide the dataset into two, gray sheep and others, based on the degree centrality of the users. Then, different similarity measures and recommendation methods are applied to these two datasets. More detail algorithm is as follows: Step 1: Convert the initial data which is a two-mode network (user to item) into an one-mode network (user to user). Step 2: Calculate degree centrality of each node and separate those nodes having degree centrality values lower than the pre-set threshold. The threshold value is determined by simulations such that the accuracy of CF for the remaining dataset is maximized. Step 3: Ordinary CF algorithm is applied to the remaining dataset. Step 4: Since the separated dataset consist of users with unique tastes, an ordinary CF algorithm cannot generate recommendations for them. A 'popular item' method is used to generate recommendations for these users. The F measures of the two datasets are weighted by the numbers of nodes and summed to be used as the final performance metric. In order to test performance improvement by this new algorithm, an empirical study was conducted using a publically available dataset - the MovieLens data by GroupLens research team. We used 100,000 evaluations by 943 users on 1,682 movies. The proposed algorithm was compared with an ordinary CF algorithm utilizing 'Best-N-neighbors' and 'Cosine' similarity method. The empirical results show that F measure was improved about 11% on average when the proposed algorithm was used