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Mining and Linguistically Interpreting Summaries from Surveyed Data Related to Financial Literacy and Behaviour

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Data Management Technologies and Applications (DATA 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 814))

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Abstract

Financial decisions represent important decisions in everyday life, as they could affect the financial well-being of the individuals. These decisions are affected by many factors including level of financial literacy, emotions, heuristics and biases. This paper is devoted to mining and interpreting information regarding effect of financial literacy on individuals’ behaviour (angst, fear, nervousness, loss of control, anchoring and risk taking) from the data surveyed by questionnaire applying linguistic summaries. Fuzzy sets and fuzzy logic allow us to mathematically formalize linguistic terms such as most of, high literacy, low angst and the like, and interpret mined knowledge by short quantified sentences of natural language. This way is suitable for managing semantic uncertainty in data and in concepts. The results have shown that for the majority of respondents having low level of financial literacy, angst and other treats represent serious issues, as expected. On the other hand, about half of respondents with high level of literacy do not consider these treats as significant. This effect is emphasized by the experimenting with socio-demographic characteristics of respondents. This research has also observed problems in applying linguistic summaries on data from questionnaires and suggests some recommendations.

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Notes

  1. 1.

    In the literature, different types of anchor are used. For more information see [5].

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Acknowledgements

This paper is part of a research grant VEGA No. 1/0849/15 entitled Economic and social aspects of the information asymmetry in the insurance market supported by the Ministry of Education, Science, Research and Sport of the Slovak Republic. The authors would especially like to thank Monika Jurkovic̆ová and Erika Pastoráková who collected the data used in this paper.

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Authors and Affiliations

  1. Faculty of Economic Informatics, University of Economics in Bratislava, Dolnozemská cesta 1, Bratislava, Slovakia

    Miroslav Hudec

  2. Faculty of National Economy, University of Economics in Bratislava, Dolnozemská cesta 1, Bratislava, Slovakia

    Zuzana Brokešová

Authors
  1. Miroslav Hudec
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Correspondence to Miroslav Hudec .

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  1. INSTICC, Polytechnic Institute of Setúbal, Setúbal, Portugal

    Joaquim Filipe

  2. University of Coimbra, Coimbra, Portugal

    Jorge Bernardino

  3. RWTH Aachen University, Aachen, Germany

    Christoph Quix

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Hudec, M., Brokešová, Z. (2018). Mining and Linguistically Interpreting Summaries from Surveyed Data Related to Financial Literacy and Behaviour. In: Filipe, J., Bernardino, J., Quix, C. (eds) Data Management Technologies and Applications. DATA 2017. Communications in Computer and Information Science, vol 814. Springer, Cham. https://doi.org/10.1007/978-3-319-94809-6_4

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  • DOI: https://doi.org/10.1007/978-3-319-94809-6_4

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