(An) analytical and empirical analysis of phantom transactions in internet auction

Abstract

Although the internet is useful for transferring information, transactions in internet auctions have a greater information asymmetry than corresponding transactions in traditional environments because current auction market mechanisms allow the seller to remain anonymous and to easily change identities. Internet auction environments make fraud more attractive to offenders because the chance of detection and punishment are decreased. So there are many frauds in internet auctions. One of fraud is a phantom transaction which is a colluding transaction by the buyer and seller to commit illegal discounting of credit card. An illegal discounting of credit card is a fraud that sellers collude with buyers. They pretend to fulfill the transaction paid by credit card, without actual selling products, and seller receives cash from credit card corporations. Then seller lends it out buyer with quite high interest rate whose credit score is so bad that he cannot borrow money from anywhere. In this research, I find the optimal prevention measure which is one of ex-ante regulations in section 3. In section 4, I show how to predict and prevent the phantom transactions in internet auctions. I gather auction data using an Internet-based data collection software agent to find the characteristics of phantom transactions using a logistic model. And in section 5, I examine the effects of changes of parameter value on social welfare and suggest some policy implications.