'Plastic surveillance: Payment cards and the history of transactional data, 1888 to present' by Josh Lauer
in (2020)
Big Data and Society comments
Modern payment cards encompass a bewildering array of consumer technologies, from credit and debit cards to stored-value and loyalty cards. But what unites all of these financial media is their connection to recordkeeping systems. Each swipe sends data hurtling through invisible infrastructures to verify accounts, record purchase details, exchange funds, and update balances. With payment cards, banks and merchants have been able to amass vast archives of transactional data. This information is a valuable asset in itself. It can be used for in-house data analytics programs or sold as marketing intelligence to third parties. This research examines the development of payment cards in the United States from the late 19th century to present, drawing attention to their fundamental relationship to identification, recordkeeping, and data mining. The history of payment cards, I argue, is not just a history of financial innovation and computing; it is also a history of Big Data and consumer surveillance. This history, moreover, provides insight into the growth of transactional data and the datafication of money in the digital economy.
Lerner argues
In 2002, an executive at Canadian Tire, a Toronto-based national retailer, made some surprising discoveries about the store’s credit customers. Close analysis of the store’s card data revealed statistical correlations between how customers used their cards and how they paid their bills. Among other things, the executive learned that customers who purchased bird seed and protective felt pads for the feet of chairs tended to be reliable bill payers. By contrast, those who bought cheap motor oil and chrome skull auto accessories were more likely to miss payments. “If you show us what you buy,” the executive boasted to a New York Times reporter, “we can tell you who you are, maybe even better than you know yourself” (Duhigg, 2009). Several years later, marketing executives at Target, the American mass retailer, were making similar discoveries in a now infamous data-mining program. By linking the store’s guest identification numbers with purchase records, analysts were able to predict which shoppers were pregnant. Transactional data revealed correlations between pregnancy and a variety of purchases, including prenatal vitamin supplements, unscented lotion, and giant bags of cotton balls (Duhigg, 2012).
When these stories broke, they illustrated the startling power of Big Data. While Target’s program attracted media attention and sparked privacy concerns, both cases showed how massive data sets could be mined for hidden behavioral clues and marketing insights. More importantly, they revealed how payment itself—point-of-sale (POS) swipes and card-based online sales—could be leveraged into consumer data programs. These retailers were not alone. During the first decade of the 21st century, payment systems were increasingly viewed as data goldmines. Unlike cash transactions, which produced only anonymous receipts, card payments yielded transactional data attached to specific individuals. This surplus data, merchants discovered, was its own reward. It could be used in-house, as with Canadian Tire and Target, or it could be reassembled, parsed, and sold as marketing intelligence to third parties. Payment cards were not just convenient stand-ins for cash; they were data-harvesting devices.
Reflecting on recent developments in payment systems, anthropologist Bill Maurer (2014) posed a provocative question: “Is there money in credit?” Given the enormous analytical power of Big Data, credit’s informational yield has begun to compete with its value as a source of fees and interest. “Credit’s function,” Maurer mused, “may no longer be as money, but as a means to ever more consumer data” (513). Maurer’s observation points to a radical shift in the business logic of payment. Though money has always been linked to memory via recordkeeping, whether inscribed in tally sticks or account books (Maurer and Swartz, 2017), the records themselves have been subordinate to the value of the commodities, bills, or cash they represent. More recently, however, electronic payment systems have automated money’s recordkeeping function and vastly expanded the volume and granularity of transactional data that is recorded. As Rachel O’Dwyer (2019) argues, this is not simply an elaboration of money’s historical recordkeeping function; it is central to the emergent platform economy, which depends upon the corralling of user interactions so that their behaviors can be collected and monetized. “What is different here,” O’Dwyer writes, “is that … the monetary record becomes a proxy for the intimate secrets and desires of its users” (10).
Building on Maurer and O’Dwyer’s insights, this article examines the long and complex evolution of the payment card’s surveillance function in the United States from the late 19th century to present. Modern payment cards encompass a bewildering array of consumer technologies, from credit and debit cards to stored value cards and loyalty cards. But what unites all of these financial media is their connection to recordkeeping systems. The simplicity of paying with plastic belies the complexity of information-processing infrastructures — the pipes and rails, in industry speak — that make it possible (Gießmann, 2018; Maurer, 2012). Each swipe, for a $4 coffee or a $40,000 wristwatch, sends data hurtling through invisible networks to instantly verify accounts, record purchase details, exchange funds, and update balances. Where cash facilitated “secrecy” and “concealment,” as Georg Simmel (1990: 385) once observed, payment cards demand the opposite: continuous exposure and confession. The history of payment cards, I argue, is not just a history of financial innovation and computing; it is also a history of consumer surveillance.
This history, moreover, provides insight into the proliferation of transactional data in the modern surveillance economy. One of the defining characteristics of computerized information processing is the production of transactional data. The necessity of data “capture” is fundamental to the logic and design of modern computing (Agre, 1994). While electronic computers introduced new possibilities for capturing data, they also expanded the number and variety of data points generated during interactions themselves, including metadata (Schneier, 2015). This particular technological augmentation and related project of datafication (van Dijck, 2014) made it possible to compile more detailed records and ultimately to discover new uses for data, especially uses unrelated to the context of its original collection (Nissenbaum, 2010). The development of late 20th-century data mining and Big Data analysis would depend upon access to such accumulations of repurposed data (Kitchin, 2014; Mayer-Schönberger and Cukier, 2013). Transactional data would not only feed Big Data programs; it provided the building blocks of the modern surveillance economy. This account shows how data “capture,” a philosophical metaphor (Agre, 1994), has become indistinguishable from surveillance: the systematic, real-world collection of information for the purpose of social classification, prediction, and control.
The discovery of transactional data and the rise of surveillance-based business models is often traced to contemporary tech giants. This perspective is exemplified by Zuboff’s (2015, 2019) account of “surveillance capitalism,” a concept that neatly captures the totalizing scale and exorable commercial logic of Big Data aggregators and platforms. For Zuboff (2019), the commodification of untapped transactional data—“behavioral surplus”—began in the early 2000s and can be credited to one company in particular: Google. “The discovery of behavioral surplus markets,” she writes, “marks a critical turning point not only in Google’s biography but also in the history of capitalism” (91). This narrative, however, is misleading. The value of transactional data was recognized much earlier, not by Google, but by other capitalists—namely, credit-granting department stores during the 1920s and credit card companies during the 1970s and 1980s. Both retailers and banks mined their payment records for insight into the buying habits, interests, and future profitability of their customers. The history of payment cards thus reveals the deep roots of surveillance capitalism and efforts to transform data into capital (Sadowski, 2019; West, 2017).
By turning attention back on the payment card, this article examines the fundamental relationship between credit and transactional data, and the historical significance of payment cards as data-capturing technologies both before and after digitalization. Importantly, this account shows how payment systems, with their imperative to record all financial activities, provided a conceptual model for transactional data capture in the modern surveillance economy. Indeed, the inspiration for Google’s data-siphoning programs can be traced to electronic payment systems and their automatic generation of transactional data (Varian, 2010). After reviewing existing surveillance scholarship concerning credit and payment cards, I examine historical linkages between identification and recordkeeping in retail charge systems in the United States during the late 19th and early 20th centuries. I then describe technological changes in American payment card systems between the 1970s and 1990s, when electronic billing and POS systems enabled new forms of transactional data capture and suggested new modes of data monetization. Finally, I connect this history to the development of computerized transactional data, including Google’s pioneering data programs, and long-running privacy concerns surrounding electronic payment systems and their contribution to the intensification of consumer surveillance.
