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Money Walks: Implicit Mobility Behavior and Financial Well-Being

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  • Vivek Kumar Singh
  • Burcin Bozkaya
  • Alex Pentland

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 exploration, engagement, and elasticity. Such features yield models that are 30% to 49% better at predicting future financial difficulties than the comparable demographic models.

Suggested Citation

  • Vivek Kumar Singh & Burcin Bozkaya & Alex Pentland, 2015. "Money Walks: Implicit Mobility Behavior and Financial Well-Being," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-17, August.
    • Handle: RePEc:plo:pone00:0136628
    DOI: 10.1371/journal.pone.0136628
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    References listed on IDEAS

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    Cited by:

    1. Saiz, Albert & Salazar-Miranda, Arianna, 2023. "Understanding Urban Economies, Land Use, and Social Dynamics in the City: Big Data and Measurement," IZA Discussion Papers 16501, Institute of Labor Economics (IZA).
    2. Chi Ming Chen & Geoffrey Kwok Fai Tso & Kaijian He, 2024. "Quantum Optimized Cost Based Feature Selection and Credit Scoring for Mobile Micro-financing," Computational Economics, Springer;Society for Computational Economics, vol. 63(2), pages 919-950, February.
    3. Mahendru, Mandeep & Sharma, Gagan Deep & Pereira, Vijay & Gupta, Mansi & Mundi, Hardeep Singh, 2022. "Is it all about money honey? Analyzing and mapping financial well-being research and identifying future research agenda," Journal of Business Research, Elsevier, vol. 150(C), pages 417-436.
    4. Cagan Urkup & Burcin Bozkaya & F Sibel Salman, 2018. "Customer mobility signatures and financial indicators as predictors in product recommendation," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-18, July.
    5. Rishav Raj Agarwal & Chia-Ching Lin & Kuan-Ta Chen & Vivek Kumar Singh, 2018. "Predicting financial trouble using call data—On social capital, phone logs, and financial trouble," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-17, February.

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