• The Journal of the Korean life insurance medical association
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• v.32 no.2
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• pp.28-32
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• 2013

We studied trends of cardiac valve surgery using insurance data. 368 persons were included our study. We studied whether there are frauds or not. Only 4 cases were done at less than 1year from an insurance contract. We reviewed medical records of all persons. We could find the type of valve disease in 211 cases. The findings are atrial valve 40.1%, mitral valve 34.6% and others 25.3%. When we divided by materials of surgery, mechanical valves were used in 68.8% of men and 70.6% of woman. The main causes of valve disease were infection(55.1%). And degenerative valve disease 32% and congenital valve disease were 13%. We cannot find definite evidence of insurance frauds in the cardiac valve surgery. But there are some limitation in data analysis.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.4
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• pp.89-100
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• 2020

In order to reduce the time and cost used in insurance processing, studies have been actively carried out to apply blockchain smart contract technology to car insurance. However, by using traffic data that is insufficient to prove accidents, existing studies are being exposed to the risk of insurance fraud, such as forgery and overstated damage by malicious insurers. To solve this problem, we propose an accident data-based reliability estimation model by using both various types of data through sensors, RSUs, and IoT devices embedded in automobiles and smart contracts. In particular, the regression model was applied in consideration of the weight estimation according to the type of traffic accident data and the reliability estimation model trained according to various accident situations. The proposed model is expected to effectively reduce fraud and insurance litigation while providing transparency in the insurance process and streamlining it is well.

• The Journal of the Korean life insurance medical association
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• v.28 no.1_2
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• pp.31-35
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• 2009

Background : Many of internists have been working for insurance industry. Insurance medicine is use of medical knowledge for insurance industry. There is social role of insurance medicine in terms of soundness of insurance administration. Recently social role of internists also have been being watched. Although theme of insurance medicine is medical risk selection, insurance claims administration also needs medical experts'opinion. There are not any corroborative study of medical consulting for insurance claims. Among insurance industry, someone called this medical review of insurance claims as 'medical claims review'. Aim : To investigate usefulness of medical review of insurance claims. Design : Questionnaire survey with claim staffs in one of insurance claim adjustment company in Korea. Methods : 265 claim staffs were divided into 4 groups and conducted survey using a questionnaire of 20 questions. Utility score, job satisfaction score, and difficult factors of claims administration were measured. Results : Utility score and job satisfaction score are highest in medical claims review group. The most difficult in claim administration to claim staffs was demonstrated to medical knowledge. Conclusion : Medical review of insurance claims is proved to be worthy. Document-based consulting method, namely medical claims review, is more useful than telephone-based simple query among claim staffs...Subjects of the medical claims review are medical record and it's principle is independent medical examination with evidence-based approach, it also has role of protecting fraud of insurance claims. Two main question types of medical claims review are verification and advice.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.125-131
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• 2021

Detecting fraudulent insurance claims is difficult due to small and unbalanced data. Some research has been carried out to better cope with various types of fraudulent claims. Nowadays, technology for detecting fraudulent insurance claims has been increasingly utilized in insurance and technology fields, thanks to the use of artificial intelligence (AI) methods in addition to traditional statistical detection and rule-based methods. This study obtained meaningful results for a fraudulent insurance claim detection model based on machine learning (ML) and deep learning (DL) technologies, using fraudulent insurance claim data from previous research. In our search for a method to enhance the detection of fraudulent insurance claims, we investigated the reinforcement learning (RL) method. We examined how we could apply the RL method to the detection of fraudulent insurance claims. There are limited previous cases of applying the RL method. Thus, we first had to define the RL essential elements based on previous research on detecting anomalies. We applied the deep Q-network (DQN) and double deep Q-network (DDQN) in the learning fraudulent insurance claim detection model. By doing so, we confirmed that our model demonstrated better performance than previous machine learning models.

• The Journal of Industrial Distribution & Business
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• v.8 no.6
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• pp.25-31
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• 2017

Purpose - This study examines car accidents that occurred in South Korea territory, and analyzes criminal liability of the offender and certain issues of driver's insurance, but a civil liability to the injured is excluded as civil liability belongs to auto insurance. Research design, data, and methodology - With carrying out this research, case study of driver's liability and literature review were adopted throughout. For this, car accidents that occurred in South Korean territory were examined and then criminal liability of the offender and certain issues of driver's insurance were analyzed. Results - From this case study on driver's liability it was found that the offender cannot receive insurance money from the insurer irrespective of the valid drive insurance, if there is no 'bill of agreement of criminal consensus'. This study suggests some ideas, offers suggestions of convenience and assistance of qualified claim staff to overcome a hurdle of drive insurance. Conclusions - As long as the accident is not a fraud and scam by the parties concerned, advance payment of agreement of criminal consensus is required to the insured, the policy holder within the limit of liability of driver insurance, on condition that the drive insurance is valid.

• Journal of Digital Convergence
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• v.11 no.10
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• pp.593-608
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• 2013

According to increasing number of injury claims, the challenge is reducing investigation of cases of injuries by selecting them more delicately, while also increasing the redemption rates and the amount of restitution. In this regards, we developed the fraud detection model for injury claims of self-employed insured by using decision tree after collecting medical claim data from 2006 to 2011 of the National Health Insurance in Korea. As a result of this model, subject types were classified into 18 types. If applying these types to the actual survey compared with if not applying, the redumption collecting rate will be increasing by 12.8%. Also, the effectiveness of this model will be maximize when the number of claims handlers considering their survey volume and management plans are examined thoroughly.

• Convergence Security Journal
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• v.16 no.6_2
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• pp.53-60
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• 2016

Security measures for the current insurance crime has focused on the capture oriented and reactive response in the screening stage of insurance payments. However, since leaving the damages that can not be healed by post-punishment, it is necessary to take measures to prevent the insurance crimes in advance. In this paper, I would like to try to identify problems through analyzing the characteristics and cases of the insurance crimes, and to present alternatives to it. The problems with the current insurance system that causes the insurance crimes are, First, When signing the insurance contract, it is too inattentive to confirm about the credit status of the policyholder, duplicate join or not, whether voluntarily sign up etc. Second, a thorough investigation or criminal charges in case of insurance accident is not being done properly. Third, information exchange and management to malicious policyholders is not being done properly. Therefore, in order to guard people from insurance crimes, First, it should strengthen the audit of such credit conditions, accident experiences in the insurance contract at the policyholders. Second, we need to block insurance crimes in advance through the continuous upgrades of insurance fraud analysis systems and social network. Third, it is necessary to strengthen the surveillance systems for the insurance crimes by the information sharing.

• 한국IT서비스학회:학술대회논문집
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• 2009.05a
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• pp.357-360
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• 2009

본 연구는 데이터마이닝 기법을 이용하여 건강보험청구료에 있어서 이상정도가 심한 요양기관을 탐지하고, 실제 의료영역에 적용하기 위한 시스템 개발을 목적으로 한다. 현재 건강보험 심사평가원의 이상탐지시스템은 평가대상이 되는 항목을 개별적으로 평가하고, 탐지된 기관의 선정 이유에 대한 근거제시가 부족한 단점을 가지고 있다. 따라서 본 연구에서는 항목을 종합적으로 평가할 수 있는 정량적 지표를 설계하고, 항목들의 상대적 중요도를 파악할 수 있도록 항목들에 대한 가중치 부여한다. 또한 지표에서 얻어진 값으로 등급을 구분하고, 의사결정나무기법(decision tree)를 이용하여 해석력을 높이는 방법을 제시한다.

• Health Policy and Management
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• v.19 no.3
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• pp.109-124
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• 2009

Background: This study aimed to examine whether cases of punishing false claimants threat general physicians to check their medical cost claims with care to avoid being suspected, and identify empirically general deterrence effects of the on-site investigation system in the Korean National Health Insurance. Methods: 800 clinics were selected among a total of 15,443 clinics that had no experience of on-site investigation until June 2007 using a stratified proportional systematic sampling method. We conducted logistic multiple regression to examine the association between factors related to provider's perception of on-site investigation and high level of perceived deterrence referring to fear of punishment after adjusting provider's service experiences and general characteristics. Results: The probability of high perceived deterrence was higher 1.7 times (CI: 1.13-2.56), 2.73 times (CI: 1.68-4.45) each among clinics exchanging the information once or more per year or once or more for 2-3 months than among clinics no exchanging the information about on-site investigation. Also, the probability of high perceived deterrence was higher 2.27 times (CI: 1.28-4.45) among clinics that knows more than 3 health care institutions having experienced an on-site investigation than among clinics knowing no case. Conclusion: A clinic knowing more punishment cases by onsite investigation and exchanging more frequently information about on-site investigation is likely to present high perceived deterrence. This result will provide important information to enlarge preventive effects of on-site investigation on fraud and abuse claims.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.97-108
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• 2001

Frauds detection is a difficult problem, requiring huge computer resources and complicated search activities Researchers have struggled with the problem. Even though a fee research approaches have claimed that their solution is much better than others, research community has not found 'the best solution'well fitting every fraud. Because of the evolving nature of the frauds. a novel and self-adapting method should be devised. In this research a new approach is suggested to solving frauds in insurance claims credit card transaction. Based on evolutionary computing approach, the method is itself self-adjusting and evolving enough to generate a new self of decision-makin rules. We believe that this new approach will provide a promising alternative to conventional ones, in terms of computation performance and classification accuracy.