| A Study on Detecting the Linked Accounts by Using Big-Data Analysis |
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Cheol-Won Yang |
| 빅데이터 분석기법을 활용한 연계계좌 데이터 구축에 관한 연구 |
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양철원 |
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단국대학교 |
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| Abstract |
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The most significant feature of recent unfair trade transactions is the increase in the number of suspicious accounts. Despite the fact that the number of unfair transactions investigated by the FSS has decreased every year, the average number of suspicious accounts continues to increase. This means that many unfair trading practices are conducted through multiple linked accounts rather than single accounts. In this study, I develop a linkage index for a pair of accounts, and propose a method of extracting the linked accounts and databaseing them using social network analysis. Since the analysis of the linked account requires a lot of calculation time, the market surveillance organizations can recognize the linked accounts in advance and investigate it when there are abnormal signs in the transaction. In addition, after processing the actual unfair transaction event, they can update the linked account to build a more sophisticated linked account database. This process will further strengthen market surveillance on unfair trade practices. |
| Key Words:
불공정거래,연계계좌,연계지표,사회네트워크 분석,시장감시,Unfair Trade,Linked Accounts,Linkage Index,Social Network Analysis,Market Surveillance |
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