Financial Inclusion is important but hard. We study Mexican bank's incursion into lending to borrowers with little or no formal credit history. We document that after 2 years of getting a credit card cumulative delinquency is 27pp and exit is 33pp. Ex-ante we can predict at most 1\% of the variance in profits. Using an 8-arm randomized experiment we show that this risk cannot be mitigated by lowering interest rates or increasing minimum payments. Treatments effects are smaller an order of magnitude smaller than baseline exit and delinquency. This also suggests moral hazard is low, possibly because conditions in the informal loan markets are much worse, which we document.
In the digital economy, user data is typically treated as capital created by corporations observing willing individuals. This neglects users' role in creating data, reducing incentives for users, distributing the gains from the data economy unequally and stoking fears of automation. Instead treating data (at least partially) as labor could help resolve these issues and restore a functioning market for user contributions, but may run against the near-term interests of dominant data monopsonists who have benefited from data being treated as "free". Countervailing power, in the form of competition, a data labor movement and/or thoughtful regulation could help restore balance.