• 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 the Korean Data and Information Science Society
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• v.27 no.4
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• pp.959-967
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• 2016

Distributional assumptions on equity returns play a key role in valuation theories for derivative securities. Elberlein and Keller (1995) investigated the distributional form of compound returns and found that some of standard assumptions can not be justified. Instead, Generalized Hyperbolic (GH) distribution fit the empirical returns with high accuracy. Hu and Kercheval (2007) also show that the normal distribution leads to VaR (Value at Risk) estimate that significantly underestimate the realized empirical values, while the GH distributions do not. We consider saddlepoint approximations to estimate the VaR and the ES (Expected Shortfall) which frequently encountered in finance and insurance as measures of risk management. We supposed GH distributions instead of normal ones, as underlying distribution of linear portfolios. Simulation results show the saddlepoint approximations are very accurate than normal ones.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.3
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• pp.161-170
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• 2015

Recently the fund has been popular for the representative financial investment. In the decision making procedure of the investor about this fund investment, this research analyze how the factor was considered as fund investing behavior. The paper examines investors' risk reduction behavior and fund choice attribution for fund investment behavior, provides insight for marketing strategy in fund market for fund investment behavior. The period for the survey is from December 2014 to January 2015 and analyzed 431 samples of using a fund investor The research results showed that fund distribution, fund literacy and fund performance appeared to be statistically significant variables that positive affected fund investment satisfaction, but fund advertise negative affected fund investment satisfaction. Also, the fund management company, benefit, fund literacy, fund performance, and recommend appeared to be statistically significant variables that positive affected fund investment intention. It is expected that fund marketing strategy based on research return should be established to cope with the fund literacy as well as the fund investing behavior. Concretely to fund investment satisfaction make informed decision in fund performance, fund information provided to investor should be customized to contribute the improvement of overall fund literacy.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.6
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• pp.91-101
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• 2019

Tourism or travel business consists of a set of services for people who visit exotic places. Payment is usually marking the end of the series of activities relating to tourism, and it becomes the linkage for the next activity. With the recent advancement of mobile Fintech technologies, we have learned that more convenient and more secure financial transactions are improving the quality of tourism. It should be noted that tourism counts on information technology heavily in terms of mobile Internet and smart devices use, which yields to a wide business opportunities for Fintech startups. However, payment information has not been highlighted for additional marketing promotion activities. The lack of research into information technology-based business models that extend Fintech services related to payment in venture start-up studies hinders the understanding of the possibility of creating new business through the value creation process after payment. This study attempts to investigate this issue based on the theory of smart tourism and service-dominant logic with developing a new information system. More specifically, marketing promotion activities after payment for Chinese tourists visiting Korea are examined. Specifically, WeChat Pay and instant tax refund service were considered while the system was developed by following desing science research methodology. This study is meaningful in that it finds a new possibility of Fintech business model by applying scientific and academic methods, and it reminds the necessity of service automation system centered on instant tax refund.

• Smart Media Journal
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• v.11 no.3
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• pp.9-17
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• 2022

Algorithmic trading, which uses algorithms to trade financial products, has a problem in that the results are not stable due to many factors in the market. To alleviate this problem, ensemble techniques that combine trading algorithms have been proposed. However, there are several problems with this ensemble method. First, the trading algorithm may not be selected so as to satisfy the minimum performance requirement (more than random) of the algorithm included in the ensemble, which is a necessary requirement of the ensemble. Second, there is no guarantee that an ensemble model that performed well in the past will perform well in the future. In order to solve these problems, a method for selecting trading algorithms included in the ensemble model is proposed as follows. Based on past data, we measure the contribution of the trading algorithms included in the ensemble models with high performance. However, for contributions based only on this historical data, since there are not enough past data and the uncertainty of the past data is not reflected, the contribution distribution is approximated using the Dirichlet distribution, and the contribution values are sampled from the contribution distribution to reflect the uncertainty. Based on the contribution distribution of the trading algorithm obtained from the past data, the Transformer is trained to predict the future contribution. Trading algorithms with high predicted future contribution are selected and included in the ensemble model. Through experiments, it was proved that the proposed ensemble method showed superior performance compared to the existing ensemble methods.