Money Walks: Implicit Mobility Behavior and Financial Well-Being
Identifieur interne : 000023 ( Main/Exploration ); précédent : 000022; suivant : 000024Money Walks: Implicit Mobility Behavior and Financial Well-Being
Auteurs : Vivek Kumar Singh [États-Unis] ; Burcin Bozkaya [Turquie] ; Alex Pentland [États-Unis]Source :
- PLoS ONE [ 1932-6203 ] ; 2015.
Abstract
Traditional financial decision systems (e.g. credit) had to rely on explicit individual traits like age, gender, job type, and marital status, while being oblivious to spatio-temporal mobility or the habits of the individual involved. Emerging trends in geo-aware and mobile payment systems, and the resulting “big data,” present an opportunity to study human consumption patterns across space and time. Taking inspiration from animal behavior studies that have reported significant interconnections between animal spatio-temporal “foraging” behavior and their life outcomes, we analyzed a corpus of hundreds of thousands of human economic transactions and found that financial outcomes for individuals are intricately linked with their spatio-temporal traits like
Url:
DOI: 10.1371/journal.pone.0136628
PubMed: 26317339
PubMed Central: 4552874
Affiliations:
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Le document en format XML
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<front><div type="abstract" xml:lang="en"><p>Traditional financial decision systems (e.g. credit) had to rely on explicit individual traits like age, gender, job type, and marital status, while being oblivious to spatio-temporal mobility or the habits of the individual involved. Emerging trends in geo-aware and mobile payment systems, and the resulting “big data,” present an opportunity to study human consumption patterns across space and time. Taking inspiration from animal behavior studies that have reported significant interconnections between animal spatio-temporal “foraging” behavior and their life outcomes, we analyzed a corpus of hundreds of thousands of human economic transactions and found that financial outcomes for individuals are intricately linked with their spatio-temporal traits like <italic>exploration</italic>
, <italic>engagement</italic>
, and <italic>elasticity</italic>
. Such features yield models that are 30% to 49% better at predicting future financial difficulties than the comparable demographic models.</p>
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