Commodify Everything

The new frontiers of commodification and capital accumulation are always uneven, murky, and hard to recognize at their birth. The rise of finance — financialization — is no exception.

Cutting through fuzzy notions that “something structural” has changed, two Australian academics — Mike Rafferty and Dick Bryan — offer a clear-eyed analysis of the frontiers of financial innovation and accumulation along with the mechanisms and instruments of change, particularly the micro and macro manifestations and implications of what the authors dub “risk shifting.”

At the core of Bryan and Rafferty’s argument is the idea that the frontier for financial innovation and accumulation has been shaped and expanded by risk and uncertainty — specifically, how financial markets have been able to develop products to trade risk and uncertainty.

The emergence of tradable products like derivatives — including things like options, swaps, futures, asset-backed securities — and processes such as securitization have been central not only to the explosion of new financial markets and their associated trades but also opens up questions about who is left holding the risks for the system as a whole.

And while these products and processes often appear mystifying, they contain some important unifying features. Many derivatives offer the ability to lock in future prices as a means to manage risk. Take for example a dairy farmer who needs to buy enough feed for the cattle in her care. Since, the price of hay on the market fluctuates on a daily basis, it may skyrocket and put the farmer at risk of bankruptcy. This is where a derivative contract comes in, in this case an option. It gives the farmer the right to buy a set amount of feed at a set price at a set date in the future, safe in the knowledge that she has locked in a certain price for this crucial input.

The key point here is that the value of the option is “derived” from the underlying asset; in this case, cattle feed, while the asset itself remains untraded. And increasingly, for every commodity the cow produces or comes into contact with (milk, the farmer’s tractor, the mortgaged farm itself, etc.) the same process of disassembly and reconfiguration is in play. In this way derivatives, “establish pricing relationships that readily convert between different forms of assets. Derivatives blend different forms of capital into a single unit of measure.”

Financial innovation, allows every production process to be broken down into its constituent elements, converted into an asset stream, reconstituted as a financial product, and made commensurable (and tradable) with everything else.

Take another example. Imagine walking into your nearest mobile phone provider — Verizon for example — and signing up for a new twenty-four month contract. You pay nothing now but over the life of the contract you can expect to pay, say, $1000. The new financial instruments (asset backed securities in this case) allow Verizon (or Vodafone, or AT&T) to sell your future monthly bill repayments to someone on the futures market for less than the $1000, say $900. Why would the mobile phone provider take the smaller $900 in their pocket now and the subsequent blow to their bottom line?

The answer, simply, is risk. For $900 in the here and now Verizon no longer holds the risk of you, the customer, not paying back the $1000 over the 24-month contract. The company who bought access to your repayments now holds the risk of your default. If you fail to make a payment, Verizon still has the $900 in the bank.

In both examples commodities are broken down into their constituent elements which are then converted into asset streams. This means two interrelated things: First, the thing being traded — the key currency determining each transaction — is risk. Why do my future mobile phone repayments cost $900 now? Because that’s the price the market has determined the risk is worth. The farmer and Verizon are trying to manage their risks, to not be exposed to default and failure — to have a safe position in the market. The way to achieve this is to trade in the new financial products.

Second, there is no “outside” this new market in risk. No company, product, or process is untouched by it. Corporations which produce commodities seemingly completely unrelated to finance (such as General Motors) are involved in complicated balance sheet management, creating liquid, securitized asset streams from physical commodities, buying and selling risk on financial markets. The entire productive process is implicated in the financial system in novel ways which are still being made and understood.

The construction company no longer simply trades in bricks and mortar but must have a position on foreign currency fluctuations and mortgage repayments and even the weather. Rafferty and Bryan argue that workers can easily lose out in this game of risk. Where employers or the state once managed risks of sickness or retirement, increasingly it’s up to individuals to “manage” those risks themselves.

Personal Risk Management

What other aspects of our lives are being reworked as risk management practices?

The late Randy Martin, dancer turned academic, and author of Financialization of Daily Life, has posited a “social logic of the derivative,” arguing that “[w]hat we call identity is certainly an attribute of self that gets bundled, valued and circulated beyond an individual person.” Here it is not the underlying asset/person being considered but our constituent elements.

For Deleuze this relationship between (financialized) capital and social control is captured in the notion “dividuation” — instead of a singular identity, articulated through the process of individuation, Delueze sees a separation of the underlying individual and their various attributes, analogous to a financial derivative.

The categories by which people are articulated are those attributes useful to capital — your Amazon book preferences, your credit score, etc. Dividuation “defines and measures an attribute of an individual, and exists discretely from the “underlying” individual from which it is derived … Dividuation serves the purpose of control by being measurably in categories that are functional for capital.” For Deleuze, increasingly we are simply constituted points of data mining searches and computer profiles, divorced from any unitary whole.

And surely Internet dating apps and websites are the proponents of dividuation par excellence. When you look for love (or sex or companionship) online your physical attributes are broken down into their constituent elements (hair color, skin color, body shape), your interests declared and differentiated (basketball, walking, the novels of Balzac) your sexual persuasions and proclivities demanded (gay, straight, polyamorous, BDSM, etc.).

In fact your very choice of dating venue may determine which elements you chose to trade among: Grindr for sexual preference, Tinder for looks, Ashley Madison for extra-marital affairs, Guardian Soulmates for walking and the novels of Balzac. Meanwhile over at eHarmony the whole edifice is gleefully revealed: “we partner people on their behaviors, values, characteristics, and you know the things that matter.”

And this is where the matching potential of supply and demand comes into its own. You submit these constituent elements into a patented algorithm to be “matched.” And just like contemporary financial markets, the sophistication of the trademarked algorithm is a selling point in itself — with Eharmony offering “29 Key Dimensions that are crucial for relationship success” compared to OKCupid’s algorithm magic:  “Algorithms, formulas, heuristics — we do a lot of crazy math stuff to help people connect faster.” Whatever the brand, the veneration of a particular algorithm or method is par for the course.

And just like the derivatives market, the only way to ensure a “successful” outcome is to continually participate; to trade, to take multiple positions in the market, to hedge your risk, to be constantly active. To only engage in a single conversation with a sole potential suitor is a dangerous game. And so you sit and swipe, and sit and swipe, engaged in an elaborate system of matching, risking, and hedging. And as a result of all this trading the algorithm improves; your chances of a better match improve: “So when you head out on an eHarmony date, you know it will give you butterflies not awkward silences.”

And just like Verizon trading away repayments, the promise of Internet dating is that it is actually possible to remove risk and, instead, lock in certainty — to know and to be sure.

The perverseness of the logic here is that the only way to have as much upside risk as possible (more potential good outcomes than bad) is to continually go back to the well. The idea of hedging so prevalent in financial rhetoric is apt here — to remove as much downside risk as possible, to open up the future to good outcomes solely.

And so just like a foreign exchange futures trader you become implicated in a systemic logic that promotes the dismantling of things into their constituent elements, demands a calculative agenda of commensurability, and rewards the individual management of risk.

Whose fault is it but yours if you fail at Internet dating? You must have done it wrong. Or maybe you put all your eggs in one basket. And so in our online pursuit of love we are unwittingly cast into what Bryan and Rafferty have dubbed, “capital’s risk project,” whereby “the incorporation of financial ways of thinking and acting — often without us knowing it — sees competition and the pricing of everything becoming normalized.”

Love in the Age of Big Data

Looking back out again, on an industry level, Internet dating apps and websites are also major players in the field of “big data” — the collection of large amounts of data on users. Big data is increasingly commodified and disseminated in ways useful for capital.

The digital collection of information from places like match.com happens automatically, with platforms recording information not only offered up directly by users but also about their behavior on the site itself. Christian Rudder of OKCupid fame claims he can “lay bare vanities and vulnerabilities that were perhaps until now just shades of truth,” while over at EHarmony they bleat that more than 19 million people have filled in their online questionnaire.

But beyond the creepy and conspiratorial (or not) claims about big data, it is the logic of the derivative that unites individuals, industries, and the economy as a whole: When your personal information or information about your behavior is sold for marketing or another purpose, it is not the individual person that is being sold but your constituent elements; your interests, characteristics, communications, behaviors, and habits.

Individual profiles may be constructed but data points far outweigh actual individuals; your interests and proclivities are packaged up and sold as asset streams on yet another marketplace that is increasingly coming to resemble the particularities of financial markets.

And here we come to the crux of the matter. Why does all this matter at all?

Fans of Internet dating will point to the happily married couple at the end of the table and challenge you to say ill of the thing that brought them together. But the point is not to cast aspersion on the love borne from Internet dating or smart phone apps, but to see Internet dating as part of a broader project of the financialized self.

So just as capital has developed the financial products to trade in, and profit from, risk, so too, does it have an interest in measuring and managing risk across the entirety of the system that is composed of individuals.

It is not just a matter of companies selling big data but also studying it. Our individual riskiness is constantly assessed through our inputs (social media, Internet dating, census data) to determine the likelihood of our defaults on loan repayments, our job prospects, our political proclivities etc. Think Fitbits and your health information, collected and disseminated.

Internet dating has turned social relationships — which were once seen as part of the public good and defined by their use value (meeting people, finding partners, sharing photos, etc.) — into financialized commodities. And capital’s risk project is now central to these relationships, both in terms of providing the quantitative data for systemic risk measurement and assessment, and simultaneously promoting a discourse of individual participation in risk hedging behaviors.

The square is circled when we realize that for banks, too, our happily ever after is good business.

Economists in a working paper for the Federal Reserve Board have been examining “the role that credit scores have in predicting the stability and potential longevity of a relationship that’s starting to get serious.” They found that those with higher credit ratings were more likely to be in a stable relationship, that “credit scores are indicative of trustworthiness in general, and couples with a mismatch in credit scores are more likely to see their relationships end for reasons not directly related to their use of credit.”

This kind of information is crucial for banks and lenders making decisions about where to lend money and analysis of their own exposures to potential risks. Couples from different socioeconomic backgrounds are more risky proposition according to this research. Will your next dating app contain a credit-rating filter?

Are we happy to have the palpations of our heart reduced to a strategy of risk management and traded according to an increasingly sophisticated algorithm which also harvests our data?

As Croatian philosopher Srecko Horvat argues in The Radicality of Love, falling in love occurs on that revolutionary plane of the imagination: Love renders the ability “to see another person, to relate to another being, and vice versa, to relate to themselves meaningfully though the other person.”

A financialized love seems devoid of love’s power — its inexplicability, its inherent, unavoidable risks, its immeasurability in a world increasingly systemically reliant on such measurement.

The answer, surely, as always, is to imagine something different. To, as it were, swipe left.