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Money Walks: Implicit Mobility Behavior and Financial Well-Being

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...

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Detalles Bibliográficos
Autores principales: Singh, Vivek Kumar, Bozkaya, Burcin, Pentland, Alex
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4552874/
https://www.ncbi.nlm.nih.gov/pubmed/26317339
http://dx.doi.org/10.1371/journal.pone.0136628
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author Singh, Vivek Kumar
Bozkaya, Burcin
Pentland, Alex
author_facet Singh, Vivek Kumar
Bozkaya, Burcin
Pentland, Alex
author_sort Singh, Vivek Kumar
collection PubMed
description 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 exploration, engagement, and elasticity. Such features yield models that are 30% to 49% better at predicting future financial difficulties than the comparable demographic models.
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spelling pubmed-45528742015-09-10 Money Walks: Implicit Mobility Behavior and Financial Well-Being Singh, Vivek Kumar Bozkaya, Burcin Pentland, Alex PLoS One Research Article 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 exploration, engagement, and elasticity. Such features yield models that are 30% to 49% better at predicting future financial difficulties than the comparable demographic models. Public Library of Science 2015-08-28 /pmc/articles/PMC4552874/ /pubmed/26317339 http://dx.doi.org/10.1371/journal.pone.0136628 Text en © 2015 Singh et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Singh, Vivek Kumar
Bozkaya, Burcin
Pentland, Alex
Money Walks: Implicit Mobility Behavior and Financial Well-Being
title Money Walks: Implicit Mobility Behavior and Financial Well-Being
title_full Money Walks: Implicit Mobility Behavior and Financial Well-Being
title_fullStr Money Walks: Implicit Mobility Behavior and Financial Well-Being
title_full_unstemmed Money Walks: Implicit Mobility Behavior and Financial Well-Being
title_short Money Walks: Implicit Mobility Behavior and Financial Well-Being
title_sort money walks: implicit mobility behavior and financial well-being
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4552874/
https://www.ncbi.nlm.nih.gov/pubmed/26317339
http://dx.doi.org/10.1371/journal.pone.0136628
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