Abstract
How are markets possible under conditions of anonymity and lack of repeat dealing? Many scholars consider the problem of fraud as one that must be dealt with by law, but electronic commerce firms treat the problem of online fraud as a business problem, a problem of risk management. This article documents how merchants and financial intermediaries treat fraud as a cost that can be quantified and then minimized. Just as entrepreneurs earn profits by helping meet a previously unmet market demand, entrepreneurs earn profits by helping reduce what could have been considered an unsolved legal problem. Firms have profited by using predictive analytics and various if-then algorithms to help mitigate what might otherwise be an intractable problem and help vastly expand the scope of commerce.
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Notes
Electronic commerce firm Riskified writes, “While every chargeback incurred is painfully noticeable, falsely declined orders mostly go unnoticed and unreported,” and refers to orders that do not take place as an “invisible problem” ( 2015, p. 4).
Card-not-present transactions are those where a customer does not physically hand the card to merchants. That includes mail order, telephone, internet, or recurring purchases. For a discussion of how merchants or banks must bear the cost of card-not-present fraud, see Tu 2013, p. 120.
Among the first authors to talk about how people doing business online rely on extralegal solutions to their problems is Kollock (1999), who describes people building trust online, for example through eBay. Gillette (2001) is among the first authors to talk about how intermediaries help establish trust online. DeGennaro (2006) also provides an excellent analysis of the work of credit card networks to minimize the costs of fraud. Cai and Zhu (2016) discuss how online reputation flows can be clouded by firms posting misleading reviews or masking their identity and propose that blockchain ledger technology can be used to document that a transaction did or did not take place in a way that reviewers describe. Koulu (2016) also suggests that future electronic commerce firms will be able to rely on blockchain technology to mitigate the risks of fraud. When we first started researching this topic in late 2015, blockchain and smart contract technology were being discussed as potentially important ways to reduce fraud but had not been implemented in any serious way compared to today.
To theorists writing in this tradition, markets themselves, and especially technologically advanced markets, cannot exist without government enforcing laws against fraud. Douglass North (1990, pp. 12, 35), for example, argues that “realizing the economic potential of the gains from trade in a high technology world of enormous specialization and division of labor characterized by impersonal exchange is extremely rare, because one does not necessarily have repeated dealings, nor know the other party, nor deal with a small number of other people.” North writes, “The returns on opportunism, cheating, and shirking rise in complex societies. A coercive third party is essential.” James Buchanan and North are among the more famous expositors of this perspective. See Buchanan 1975.
Martin Boyer (2007, p. 481) theorized that when “the proportion of agents that have a low propensity to tell the truth is high,” then “resistance to fraud is futile.” In the 1990s Douglass North and Richard Epstein (1999) predicted that technologically advanced commerce could not expand without effective laws against fraud.
CyberSource (2018c) also recommends that managers create a positive database with known valuable customers put on a white list and a negative database that puts individuals or devices with past problems, such as bad addresses or names, on a gray list or blacklist. Orders from good customers need not go through the same levels of scrutiny as orders from new customers, while customers on a gray list may have their orders turned down or put through extra steps before being processed. For example, the Verified by Visa program requires a purchaser to provide an additional password to help authenticate a transaction, so a hacker with just a stolen credit card number will be thwarted.
In April 2016, Digital Asset Holdings purchased a Swiss smart-contract start-up, Elevence, and its “powerful modeling language capable of expressing any right or obligation, including cash, securities and derivatives, whereby the code defines the considerations between parties, and determines how these contractual relations can evolve over time” (Digital Asset Holdings 2016). Digital Asset Holdings explains the objective: “The primary goal of blockchains with inbuilt Smart Contracts was to create self-enforcing agreements that independently control and automate the exchange of value according to predetermined rules based on predefined inputs.”
Many economists including Luther (2018) have a stricter definition of smart contract to say that it should be only enforced by an algorithm and have no human involvement. We are not particularly devoted to the stricter or looser definition of smart contract, but the person to coin the term, Szabo (1997), describes conditions where a human could judge that a smart contract be not enforced.
“Smart” contracts are only as smart as they are programmed. At a simple level, a smart contract that looks for an NHL score on NBA.com will not work, and at a more complex level, an entity might have some well-programmed smart contracts but remain vulnerable to hackers. An example of a potentially innovative but poorly designed entity relying on smart contracts is an investment fund called The DAO. In June 2016, about a month after it raised the equivalent of $150 million in the cryptocurrency Ether, hackers initiated transactions to take $55 million from it. On the plus side, The DAO’s code specified a 27-day waiting period before funds could be removed, so the sponsors reversed the fraudulent transactions and decided to liquidate the fund and return all the money to its investors. The event, however, showed that the platform was not fully autonomous and independent of human control as many of its early supporters were claiming. The list of problematic smart contracts goes on. In July 2017 hackers identified imperfectly written code in a multi-signature wallet called Parity on the Ethereum platform. Hackers figured out a way to get these multi-signature contracts to reinitialize and then exploit them, and they successfully stole $31 million worth of Ether. In November 2017 a hack led to $156 million worth of Ether in the Parity platform being frozen and made inaccessible, so it is safe to say that in 2018 we are still in the Wild West stage of this new technology. See Zhao 2017.
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Stringham, E.P., Clark, J.R. The crucial role of financial intermediaries for facilitating trade among strangers. Rev Austrian Econ 33, 349–361 (2020). https://doi.org/10.1007/s11138-018-0429-0
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DOI: https://doi.org/10.1007/s11138-018-0429-0
Keywords
- Innovation
- Fraud prevention
- Payment processing
- Credit cards
- Predictive analytics
- Blockchain
- Smart contracts
JEL classification
- G28
- L26
- N20
- P17