The Mute Calculus of Distant Algorithms
This blog post is based on research for a forthcoming piece in Coda Story.
What kind of work does a credit score do in the world? And what does it mean to give previously “credit invisible” people a digitally generated financial scorecard?
In countries like Kenya where residents have long been excluded from formal banking, people are now receiving credit scores through the culling of mobile data. This has largely been enabled through the advent of digital credit. Millions of cash-strapped Kenyans have turned to the seductive ease of mobile lending, which was first introduced to the country in 2012. Download an app, fill in some basic personal data, agree to the terms and conditions, and money will appear almost instantaneously in your M-Pesa mobile money wallet.
Companies ranging from multinational telecoms, like Safaricom, to Silicon Valley-based startups, like Tala and Branch, are lining up to offer Kenyans loans at the touch of a button. They have also developed novel ways of assessing people’s credit worthiness.
These algorithms prize various kinds of data: Does this person call their mother? How often do they buy phone credit? Do they make frequent payments with their M-Pesa account? How many followers do they have on Twitter? In a feature on Tala, TechCrunch explains that the company "looks at a customer’s texts and calls logs, merchant transactions, overall app usage and other behavioral data....Based on these pieces of information, its machine learning algorithms evaluate the individual risk and provide instant loans in the range of $10 to $500 to customers."
Proponents argue that such methods enable companies to provide non-collateral loans and offer credit to the "unbanked"--those long excluded from financial services. But talk of financial inclusion tends to silence the background noise: the quiet operations that make these digital apps function.
Mobile technology is not only enabling greater and, in many ways, unprecedented state and corporate surveillance of Kenyan consumer habits in the absence of robust data protection laws. It is also opening people up to the mute calculus of distant algorithms.
Financial inclusion, which rests on the larger fetish for choice and freedom, has opened people up to the depersonalized logic of the algorithm.