Reporting about large-scale finance decisions is difficult for any journalist—but a team of German investigative reporters has crowdsourced a major investigative story revealing flaws in a closely guarded credit scoring algorithm.
Most citizens in Germany have a Schufa score, which is something like the FICO score in the US. Various bits of consumer data are put through a proprietary algorithm and out comes a risk assessment score indicating credit worthiness. The scores are used to inform financial decisions in all kinds of contexts: from banking and insurance to real estate rentals and other service contracts. But you don’t have to look very hard to find cracks in the accuracy of the scores. Anecdotal reports of discrepant scores, as well as a general lack of transparency and explanation around how the proprietary system operates, raise questions.
Late last November, the results of an almost year-long investigation into Schufa were published by Der Spiegel and the Bavarian Public Broadcaster. The investigation is an example of algorithmic accountability reporting: an attempt to uncover the power wielded by algorithmic decision-making systems and shed light on their biases, mistakes, or misuse. Algorithmic accountability entails understanding how and when people exercise power within and through an algorithmic system, and on whose behalf. Some outlets are introducing coverage that amounts to an emerging algorithms beat, oriented around reverse engineering, auditing, and otherwise critiquing algorithms in society.
I spoke to data journalist Patrick Stotz at Der Spiegel about his team’s process for getting the story. Two nonprofits, the Open Knowledge Foundation and Algorithm Watch, initially partnered to collect data. They crowdsourced thousands of personal credit reports from consumers, which were then passed on to and analyzed en masse by investigative journalists.
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Source: What a report from Germany teaches us about investigating algorithms – Columbia Journalism Review