1. E-Fraud: Motives, Techniques, and Research Agenda Presentation at the Second Student Conference of Research in Business April 2008, HEC Montreal Muhammad Aljukhadar PhD Student HEC Montreal

2. From 687,000 Fraud Complaints in 2005 Identity theft complaints 37 % Identity theft complaints 37 % Internet Auctions 12 % Internet Auctions 12 % Foreign Money Offers 8 % Foreign Money Offers 8 % Shop-at-Home/Catalogue Sales 8 % Shop-at-Home/Catalogue Sales 8 % Prizes/Sweepstakes and Lotteries 7 % Prizes/Sweepstakes and Lotteries 7 % Internet Services and Computer Complaints 5 % Internet Services and Computer Complaints 5 % Business Opportunities and Work-at-Home plans 2 % Business Opportunities and Work-at-Home plans 2 % Advance-Fee Loans and Credit Protection 2 % Advance-Fee Loans and Credit Protection 2 % Telephone Services and Other 19 % Telephone Services and Other 19 % - Internet-related complaints accounted for 46 % of all fraud complaints - The percent of Internet-related fraud complaints tripled in three years

3. Examples 3.4 million Bell Canada customers whose personal information was stolen recently 3.4 million Bell Canada customers whose personal information was stolen recently $41 million TJX Inc. (owner of Winners and HomeSense) will pay in a settlement with Visa over a breach that exposed millions of client card numbers; (another $24- million to MasterCard) $41 million TJX Inc. (owner of Winners and HomeSense) will pay in a settlement with Visa over a breach that exposed millions of client card numbers; (another $24- million to MasterCard) 50% of German corporations now employ Chief Privacy Officers (CPO) 50% of German corporations now employ Chief Privacy Officers (CPO)(http://www.theglobeandmail.com/servlet/story/RTGAM.20080409.wgtprivacy10/BNStory/GlobeTQ/home)

4. What is e-Fraud E-fraud is the unlawful and intentional use or deployment of an electronic medium and/or peripheral to make a misrepresentation which causes actual prejudice or which is potentially prejudicial to another. E-fraud is the unlawful and intentional use or deployment of an electronic medium and/or peripheral to make a misrepresentation which causes actual prejudice or which is potentially prejudicial to another. Based on Snyman (2002) definition of fraud

5. E-Fraud exists when: 1. A material false statement 2. A knowledge on the perpetrator’s part that the statement was false when it was uttered. 3. A reliance on the false statement by the victim 4. Resulting damages (Albrecht and Albrecht, 2002) Fraud involve a breach of community standards, also known as “legal policy” (Granova and Eloff, 2004) Fraud involve a breach of community standards, also known as “legal policy” (Granova and Eloff, 2004)

6. Current Academic Work Majority on auction e-Fraud (curry 2001) Majority on auction e-Fraud (curry 2001) Online deception (Grazioli and Jarvenpaa 2003) Online deception (Grazioli and Jarvenpaa 2003) Deception across several studies (Grazioli 2004) Deception across several studies (Grazioli 2004) Pavlou and Gefen (ISR 2005) studied e-fraud as “psychological contract violation” Pavlou and Gefen (ISR 2005) studied e-fraud as “psychological contract violation” Online community can reduce auction e-fraud (Chua et al. 2007 MISQ) Online community can reduce auction e-fraud (Chua et al. 2007 MISQ)

7. Who is affected by e-fraud? Customers are victimized most often. Customers are victimized most often. E-fraud affect many parties. E-fraud affect many parties. Sellers: through lost fees (Kauffman and Wood 2005) ; cheating by false payment (e.g., bad checks) ; lost merchandise; owners of property rights can have their rights diluted by counterfeits; lost customers through heightened perceptions of risk (Grossman and Shapiro 1988a,1988b). Sellers: through lost fees (Kauffman and Wood 2005) ; cheating by false payment (e.g., bad checks) ; lost merchandise; owners of property rights can have their rights diluted by counterfeits; lost customers through heightened perceptions of risk (Grossman and Shapiro 1988a,1988b).

8. Major E-Fraud Techniques Data theft: hackers access secure or non-secure sites, get the data and sell it Data theft: hackers access secure or non-secure sites, get the data and sell it Sniffing: viewing of the information that passes along a network or channel Sniffing: viewing of the information that passes along a network or channel Unauthorized access to password databases: This could be done by insiders, or outsiders through hacking a firewall Unauthorized access to password databases: This could be done by insiders, or outsiders through hacking a firewall Falsified Identity: https:// connection, which indicates a secure server connection. A falsified identity poses a great threat on the safety of an e-banking or e-commerce transaction Falsified Identity: https:// connection, which indicates a secure server connection. A falsified identity poses a great threat on the safety of an e-banking or e-commerce transaction Spoofing: changing the header info in an email message or web request in order to hide identity and make the email appears to be originated from a trusted authority Spoofing: changing the header info in an email message or web request in order to hide identity and make the email appears to be originated from a trusted authority Customer Impersonation: If a customer falsified his or her identity, the business lose money and/or time on responding Customer Impersonation: If a customer falsified his or her identity, the business lose money and/or time on responding False Web Sites: one of the most techniques used in e-fraud and is referred to as ‘bustout’ (Albrecht & Albrecht, 2002) False Web Sites: one of the most techniques used in e-fraud and is referred to as ‘bustout’ (Albrecht & Albrecht, 2002)

9. Auction E-Fraud (adapted from Curry 2001) E-Fraud Type Description Party affected Shilling Sellers confederate bids to drive up price buyer misrepresentation Incorrect item description buyer Fee stacking Hidden costs buyer, auction site Failure to ship Item never sent buyer, auction site Failure to pay Payment never collected seller, auction site Counterfeits/reproductions Counterfeit goods as real Buyer, auction site, company Triangulation Seller sells stolen goods buyer, third party Buy and switch Buyer substitutes delivered item for a refund Seller, auction site Loss/damage claim Buyer claims item was damaged Seller, auction site Shell auction Seller sets up online store to obtain id’s/credit card info Buyer, auction site Illegal activities E-store for illegal activities (money laundering, tax evasion) Auction site, third party

10. Propositions set 1 E-fraud Trust Transaction Intention Transaction Behavior PCV BuyerPCV Seller Profitability (seller; third party) Perceived Risk Price Premium + + _ _ + ++ _ + Vulnerability _ _

11. Propositions set 2 E-fraud Preventive (Why e-fraud occur) Perceived Pressure Perceived Opportunity Rationalization + + +

12. Propositions set 3 e-fraud Consumer Education Anti-scheming techniques Risk Management Managing inside attacks Reactive (how to manage e-fraud Preventive (Why e-fraud occur) Prosecution & law enforcement Perceived Pressure Perceived Opportunity Rationalization + + + _ _ _ _ _

13. Questions? Suggestions?