• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.1269-1275
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• 2021

The phenomenon of money laundering through capital market instruments and various investment instruments in it is a challenge for law enforcement officials, particularly the Corruption Eradication Commission (KPK) in investigating money laundering crimes originating from corruption. This study aims to analyze comprehensively about: (1) implementation of policies on prevention and eradication of money laundering at the KPK in the context of handling money laundering on the capital market; and (2) an effective model for implementing policies to prevent and eradicate money laundering in the KPK in the context of handling money laundering on the capital market. By using a qualitative approach and Interactive Model analysis from Miles and Huberman, it was concluded that the results of the implementation of the policy of preventing and eradicating money laundering at the Corruption Eradication Commission in the context of handling money laundering crimes in the capital market had a positive impact on society, individuals and groups. The theoretical implications of the results of this study are related to the content of policy that is still relevant but for the context of implementation it needs to be refined or reconstructed by adding three elements, namely: communication, monitoring, and evaluation and security.

• Journal of the Society of Disaster Information
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• v.17 no.3
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• pp.600-607
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• 2021

Purpose: The purpose of this study is to examine the path of money laundering of criminal proceeds through cryptocurrency using criminal script analysis and to devise measures to prevent and prevent criminal justice agencies from doing so. Method: Based on the results of a prior study on the profit path of cryptocurrency through money laundering and criminal cases in Korea, the path of money laundering was analyzed using criminal script techniques. Result: Most of the cryptocurrencies that have been launched are converted into criminal proceeds, which are re-launched and cashed or have a vicious cycle of being used as criminal funds are used. According to the script, the route of money laundering is mainly converted to criminal proceeds from cryptocurrency exchanges using anonymity, which is repeated several times, making it very difficult to find the money using cryptocurrency in criminal justice institutions. Conclusion: As the method of money laundering using cryptocurrency is becoming more sophisticated, legal sanctions and preventive institutionalization should be prepared for the prohibition or confiscation of cryptocurrency transactions for money laundering after understanding the flow.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2006.06a
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• pp.294-300
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• 2006

This case study shows constructing the knowledge-based system using a rule-based approach for detecting transactions regarding money laundering in the Korea Financial Intelligence Unit (KoFIU). To better manage the explosive increment of low risk suspicious transactions reporting from financial institutions and to conjugate data converged into the KoFIU from various organizations, the adoption of a knowledge-based system is definitely required. We designed and constructed the knowledge-based system for anti-money laundering by committing experts of each specific financial industry co-worked with a knowledge engineer. The outcome of the knowledge base implementation shows that the knowledge-based system is filtering STRs in the primary analysis step efficiently and so has made great contribution to improve efficiency and effectiveness of the analysis process. It can be said that establishing the foundation of the knowledge base under the entire framework of the knowledge-based system for consideration of knowledge creation and management is indeed valuable.

• IE interfaces
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• v.18 no.3
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• pp.268-276
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• 2005

In recent years, the money Laundering crimes are increasing by means of foreign exchange transactions. Our study proposes four scoring models to provide early warning of the laundering in foreign exchange transactions for both inward and outward remittances: logistic regression model, decision tree, neural network, and ensemble model which combines the three models. In terms of accuracy of test data, decision tree model is selected for the inward remittance and an ensemble model for the outward remittance. From our study results, the accumulated number of transaction turns out to be the most important predictor variable. The proposed scoring models deal with the transaction level and is expected to help the bank teller to detect the laundering related transactions in the early stage.

• Journal of the Society of Disaster Information
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• v.18 no.3
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• pp.600-608
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• 2022

Purpose: The purpose of this study is to examine the types of crimes taking place using NFT in P2E games, and to devise measures to prevent crimes and legal sanctions between the government and companies. Method: In order to classify crime types in the metaverse, crime types were analyzed based on the results of previous studies and current incidents. Results: Most of the crimes taking place through NFTs in P2E games are hacking, money laundering, and copyright issues. Although games are regulated in Korea, these are crimes that can occur if game regulations are loosened in the future. Therefore, crime types were classified into hacking, money laundering, tax evasion, copyright issues, and game speculation, and various cases of damage have already occurred in foreign countries. Conclusion: Currently, no crimes are occurring in Korea due to game regulations, but as seen in foreign cases, large amounts of hacking and money laundering using NFTs are taking place in Korea. this will have to be provided

• The Journal of Bigdata
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• v.1 no.1
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• pp.85-94
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• 2016

Traditional Anti-Money Laundering (AML) software applications monitor bank customer transactions on a daily basis using customer historical information and account profile data to provide a "whole picture" to bank management. With the advent of Big Data, these applications could be benefited from size, variety, and speed of unstructured data, which have not been used in AML applications before. This study analyses the weaknesses of a bank's current AML systems and proposes an AML systems taking advantage of Big Data. For example, early warning of AML risk can be improved by exposing identities and uncovering hidden relationships through predictive and entity analytics on real-time and outside data such as SNS data.

• Information Systems Review
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• v.22 no.4
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• pp.135-161
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• 2020

With the growth of blockchain and cryptocurrency-related markets, cryptocurrency exchanges are growing as a new industry. However, as the legal and regulatory definitions of cryptocurrencies are still in progress, unlike existing industrial groups, they are not under the supervision of regulatory agencies. As a result, users (i.e., cryptocurrency investors) have suffered two types of damage that could occur from hacking and other accidents on the exchanges. One type of the damage is the loss of assets caused by the extortion of personal information or account and the other is the damage from users who might be involved in external frauds. Both are analyzed in comparison with existing operators whose functions are like the exchanges. The results of this study show that membership (KYC: Know Your Client), log-in, and additional authentication in transactions are on the similar level to those of the operators while the fraud detection system (FDS) and anti-money laundering (AML) of fiat currencies and cryptocurrencies need rapid improvement.

• Journal of Intelligence and Information Systems
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• v.14 no.2
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• pp.179-192
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• 2008

This case study shows constructing the knowledge-based system using a rule-based approach for detecting illegal transactions regarding money laundering in the Korea Financial Intelligence Unit (KoFIU). To better manage the explosive increment of low risk suspicious transactions reporting from financial institutions, the adoption of a knowledge-based system in the KoFIU is essential. Also since different types of information from various organizations are converged into the KoFIU, constructing a knowledge-based system for practical use and data management regarding money laundering is definitely required. The success of the financial information system largely depends on how well we can build the knowledge-base for the context. Therefore we designed and constructed the knowledge-based system for anti-money laundering by committing domain experts of each specific financial industry co-worked with a knowledge engineer. The outcome of the knowledge base implementation, measured by the empirical ratio of Suspicious Transaction Reports (STRs) reported to law enforcements, shows that the knowledge-based system is filtering STRs in the primary analysis step efficiently, and so has made great contribution to improve efficiency and effectiveness of the analysis process. It can be said that establishing the foundation of the knowledge base under the entire framework of the knowledge-based system for consideration of knowledge creation and management is indeed valuable.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.3
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• pp.1-9
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• 2017

Recently, Bitcoin which is digital currency and cryptocurrency is getting worldwide attention since Bitcoin has an ability to replace legal tender unlike other existing cyber currency. Especially, most Bitcoin trading is done between two traders such as P2P method and it does not require a third-party to make sure reliability and it records every transaction details, so it is more transparent then traditional financial trade, so the number of users is increasing. However, Bitcoin, which has been recognized for transparency, confidentiality and stability among traders has recently been threatened by illegal transactions such as money laundering and the attack on the exchange. These threats to Bitcoin are becoming social problems. At first, it seems that most of the digital currency is difficult to get hacked due to the Blockchain technology. However, threats such as digital money leaks by user account hacking and paralyzing the servers are increasing. In this paper, it will examine the features of the Bitcoin and the threatening elements to secure marketability of digital currency such as Bitcoin and receive more interest from public in domestic. The paper will examine the problems of Blockchain technology on speculative transactions and fraudulent behavior by analyzing the problems of Bitcoin transaction. Lastly, it will propose ways to make transparent and secure digital currency transactions.

• Journal of Internet Computing and Services
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• v.19 no.5
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• pp.1-11
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• 2018

The Blockchain is a technique that prevents data from being manipulated and guarantees the integrity and reliability of the data by all participants in the network jointly owning and validating the data. Since the Blockchain characterized by security, scalability and transparency, it is used in a variety of fields including logistics, distribution, IoT and healthcare, including remittance. In particular, there is a growing interest in smart contract that can create different forms of contracts and automate implementation based on Blockchain. Smart Contract can be used to pre-programme contracts and are implemented immediately when conditions are met. As a result, digital data can be more reliable. In this paper, we are conducting a study on the smart contract design as a way to solve such problems as illegal misuse of funds on virtual currency, which has become an issue recently. Through this process, we applied the customer identification and money laundering prevention process using smart contract, and then check the possibility of preventing money laundering and propose the ASM (AML SmartContract Mechant) design.