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Mobile Phone Usage Data for Credit Scoring

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Databases and Information Systems (DB&IS 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1243))

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Abstract

The aim of this study is to demostrate that mobile phone usage data can be used to make predictions and find the best classification method for credit scoring even if the dataset is small (2,503 customers). We use different classification algorithms to split customers into paying and non-paying ones using mobile data, and then compare the predicted results with actual results. There are several related works publicly accessible in which mobile data has been used for credit scoring, but they are all based on a large dataset. Small companies are unable to use datasets as large as those used by these related papers, therefore these studies are of little use for them. In this paper we try to argue that there is value in mobile phone usage data for credit scoring even if the dataset is small. We found that with a dataset that consists of mobile data based only on 2,503 customers, we can predict credit risk. The best classification method gave us the result 0.62 AUC (area under the curve).

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Author information

Authors and Affiliations

  1. Tallinn University of Technolgoy, Akadeemia tee 15a, 12618, Tallinn, Estonia

    Henri Ots & Innar Liiv

  2. Warsaw School of Economics, aleja Niepodległości 162, 02-554, Warszawa, Poland

    Diana Tur

Authors
  1. Henri Ots
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  2. Innar Liiv
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  3. Diana Tur
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Corresponding author

Correspondence to Henri Ots .

Editor information

Editors and Affiliations

  1. Department of Computer Systems, Tallinn University of Technology, Tallinn, Estonia

    Tarmo Robal

  2. Department of Software Science, Tallinn University of Technology, Tallinn, Estonia

    Hele-Mai Haav

  3. Department of Software Science, Tallinn University of Technology, Tallinn, Estonia

    Jaan Penjam

  4. Institute of Computer Science, University of Tartu, Tartu, Estonia

    Raimundas Matulevičius

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Ots, H., Liiv, I., Tur, D. (2020). Mobile Phone Usage Data for Credit Scoring. In: Robal, T., Haav, HM., Penjam, J., Matulevičius, R. (eds) Databases and Information Systems. DB&IS 2020. Communications in Computer and Information Science, vol 1243. Springer, Cham. https://doi.org/10.1007/978-3-030-57672-1_7

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  • DOI: https://doi.org/10.1007/978-3-030-57672-1_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-57671-4

  • Online ISBN: 978-3-030-57672-1

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