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If I were writing a social network layer to a creditworthiness algorithm, the first thing I'd do is create some kind of taxonomy of friend networks. Got 500+ fr
by byrneseyeview 15y ago
If I were writing a social network layer to a creditworthiness algorithm, the first thing I'd do is create some kind of taxonomy of friend networks. Got 500+ friends? See if the Google results for your name indicate fame (i.e. you show up in title tags on Amazon, IMDB, or the NYT). And bam, reduce the social networks' weighting.
Although I would be willing to bet that a) your fans will have above-average credit scores adjusted for age, and that b) authors whose fans have crappy credit are themselves more likely to have crappy credit.
In the extreme case, if you're a law professor and your FB friends are all attorneys who loved your book, you're probably a good credit. If you wrote a guide to how to fool your parole officer and your FB friends were all fans of your book, your odds of default might be pretty good.
- lurker14 15y agoWhat if you are Adam Sandler or another intelligent, responsible comedian with a base fan base?
- byrneseyeview 15y agoNo heuristic is perfect, but the question is whether this situation is common enough to swamp the general informational effects. So, three possibilities: 1. Adam Sandler will pay a fractionally higher interest rate. 2. The heuristic will route around this situation. 3. Banks that blindly apply this heuristic will lose money on Sandler because they make a comparatively unattractive offer; the bank that lends to him will get higher market share by being less cautious or more careful in this instance. Keep in mind that we're talking about an edge case among edge cases. Authors are a tiny minority of social networking users. And authors whose fandom is a contrarian indicator of their creditworthiness are even rarer. Actually, it would more likely work in the other direction: I bet poets published in the New Yorker have very creditworthy friends and still have trouble paying the rent.