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International Symposium on Ambient Intelligence

ISAmI 2020: Ambient Intelligence – Software and Applications pp 262–266Cite as

New Approach to Recommend Banking Products Through a Hybrid Recommender System

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1239))

Abstract

This research aims to add value in the private banking sector by increasing the sale of financial products to the customer by personalising the recommendation. It proposes a conceptual definition of a new process for private banking when recommending banking products. To this end, a hybrid method of recommending financial products is presented: collaborative filtering combined with content-based filtering. This task involves exploring intelligent algorithms to create the right recommendation for each client. The expected results are the prediction with a high degree of accuracy by integrating a hybrid method that ensures the personalization of products suggested by a bank.

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Notes

  1. 1.

    Fintech Inside-Fintech Spain. http://fintechspain.com/wp-content/uploads/FINTECH-Inside.pdf.

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Acknowledgments

This research is supported by the Ministry of Education of the Junta de Castilla y León and the European Social Fund through a grant from predoctoral recruitment of research personnel associated with the University of Salamanca research project “ROBIN: Robo-advisor intelligent”.

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Authors and Affiliations

  1. BISITE Digital Innovation Hub, University of Salamanca, Edificio Multiusos I+D+I, 37007, Salamanca, Spain

    Elena Hernández Nieves

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  1. Elena Hernández Nieves
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Correspondence to Elena Hernández Nieves .

Editor information

Editors and Affiliations

  1. Departamento de Informática, University of Minho, ALGORITMI Center, Braga, Portugal

    Paulo Novais

  2. DIBRIS, University of Genoa, Genoa, Italy

    Gianni Vercelli

  3. Data Management Group, Technical University of Catalonia, Barcelona, Barcelona, Spain

    Josep L. Larriba-Pey

  4. Department Computer Science and Artificial Intelligence, ETS de Ingenierias Informática y de Telecomunicación, University of Granada, Granada, Spain

    Francisco Herrera

  5. BISITE Research Group, University of Salamanca, Salamanca, Salamanca, Spain

    Pablo Chamoso

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Nieves, E.H. (2021). New Approach to Recommend Banking Products Through a Hybrid Recommender System. In: Novais, P., Vercelli, G., Larriba-Pey, J.L., Herrera, F., Chamoso, P. (eds) Ambient Intelligence – Software and Applications . ISAmI 2020. Advances in Intelligent Systems and Computing, vol 1239. Springer, Cham. https://doi.org/10.1007/978-3-030-58356-9_28

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