Bartz downloaded the database of 4,600 loans—every essay, every neighborhood, every late payment—and started searching for patterns. He identified the 300 most common words in borrowers' essays and correlated them with payment histories. Sure enough, certain words seemed linked to late payments. Among the red flags: need, bills, and business. "Those were all words that reflected that the borrower might be in financial difficulty at the moment," Bartz says. Another one was also, which Bartz theorizes meant that the loan was being used for more than one purpose.

Bartz wasn't the only one poking around in the pixels. Besides providing the data on its customers, LendingClub posted to its Web site the formula it uses to measure default risk and determine the interest rates its borrowers had to pay. Most banks keep this information secret—a perfectly honed algorithm can give them a competitive advantage—but LendingClub open-sourced it and asked readers to submit their own tweaks and improvements. After receiving a slew of suggestions, the site's engineers decided to modify the equation, assigning less weight to debt-to-income ratio, for instance. Other LendingClub lenders downloaded the equation and came up with their own proprietary improvements, devising a better formula so they could cherry-pick borrowers who were wrongly categorized as risky and charge them higher interest rates without worrying about defaults. All this innovation benefited not just individual lenders but the entire ecosystem. LendingClub's default rate is a staggeringly low 2.7 percent (versus nearly 5.5 percent for prime credit cards).

If the financial markets were as open as LendingClub, they would reap similar benefits; the combined efforts and innovation of all investors would make the system as a whole more secure. Tim Bray, an inventor of XML who has been an advocate for XBRL reporting standards, points to political blogger Nate Silver as a helpful model of a citizen-analyst. During the 2008 presidential election, Silver, a baseball statistics whiz, pored over polling data to come up with his own—almost always dead-on—analysis of House, Senate, and presidential races. He was an outsider who manipulated huge quantities of data, allowing him to come to conclusions that had escaped the professional political analysts.

Financial data, says Bray, now director of Web technologies at Sun Microsystems, should draw in the same kind of passionate people who had previously been passive investors. "People care about money," he says. "There's money in money and substantial personal upside to someone who can mine the data and uncover the truth."

The early January light streams through the slanted glass roof of SEC headquarters in Washington, DC, warming the cold marble that covers nearly every surface. Christopher Cox is in his office on the 10th floor, sitting at a glass-topped conference table. He is in a pensive mood. In just one week, he will step down from his post as head of the SEC, a position he has held for three and a half years. Almost everyone sees his tenure as a failure.

Cox came into office proclaiming his intention to protect investors. But he came to realize that the tools he had been given were no longer sufficient. The SEC was great at forcing companies to share financial details, but not so good at figuring out what to do with them. "The SEC was founded on the legal concept of disclosure and transparency," he says. "It was not a technological concept." He flashes a politician's smile, a quick display of blindingly white teeth—cover while he thinks about what comes next. "Today, we have technology that was unimaginable in the early part of the 20th century, that can reify this idea in ways that are far more expansive and consequential."

As Cox sees it, that massive computational power has primarily been used by financial engineers, who create abstract models of how the market should operate and make bets based on those models. "You know Borges, the writer?" Cox asks. "He wrote those fantastical short stories. He has one called On Exactitude in Science." The parable tells of a kingdom obsessed with creating a perfect map of itself—an essentially useless quest that leads them to draw a map that is the same size as the territory it is supposed to represent. Cox sees the story as a metaphor for the modern financial industry, which is so obsessed with modeling the market that it has lost sight of the data beneath those models. But make more data available and you don't need the perfect map. "To the extent that we can atomize what now are these hopelessly complex forms, dense with legalese, and let people have ready means to pull from actual reality what it is that they need, it's no longer a model. It's real."

Cox is now gone and a new team of regulators are walking the marble floors in DC. The old financial system is still in shambles. But a new one will emerge and, like the last, will need to be protected from its own worst instincts. Keeping the rest of us safe can no longer fall to government regulators alone. But if we enable a system in which everyone is a regulator, there just might be enough eyes, enough checks and balances, enough promising DIY economists out there to make sure the financial world doesn't innovate the real world into depression ever again. Brandeis argued that electric lights were the best police force. Now it's time to give everyone a flashlight.