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A Banking Platform to Leverage Data Driven Marketing with Machine Learning

Payment data is one of the most valuable assets that retail banks can leverage as the major competitive advantage with respect to new entrants such as Fintech companies or giant internet companies. In marketing, the value behind data relates to the power of encoding customer preferences: the better...

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Detalles Bibliográficos
Autores principales: Torrens, Marc, Tabakovic, Amir
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8947041/
https://www.ncbi.nlm.nih.gov/pubmed/35327858
http://dx.doi.org/10.3390/e24030347
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author Torrens, Marc
Tabakovic, Amir
author_facet Torrens, Marc
Tabakovic, Amir
author_sort Torrens, Marc
collection PubMed
description Payment data is one of the most valuable assets that retail banks can leverage as the major competitive advantage with respect to new entrants such as Fintech companies or giant internet companies. In marketing, the value behind data relates to the power of encoding customer preferences: the better you know your customer, the better your marketing strategy. In this paper, we present a B2B2C lead generation application based on payment transaction data within the online banking system. In this approach, the bank is an intermediary between its private customers and merchants. The bank uses its competence in Machine Learning driven marketing to build a lead generation application that helps merchants run data driven campaigns through the banking channels to reach retail customers. The bank’s retail customers trade the utility hidden in its payment transaction data for special offers and discounts offered by merchants. During the entire process banks protects the privacy of the retail customer.
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spelling pubmed-89470412022-03-25 A Banking Platform to Leverage Data Driven Marketing with Machine Learning Torrens, Marc Tabakovic, Amir Entropy (Basel) Article Payment data is one of the most valuable assets that retail banks can leverage as the major competitive advantage with respect to new entrants such as Fintech companies or giant internet companies. In marketing, the value behind data relates to the power of encoding customer preferences: the better you know your customer, the better your marketing strategy. In this paper, we present a B2B2C lead generation application based on payment transaction data within the online banking system. In this approach, the bank is an intermediary between its private customers and merchants. The bank uses its competence in Machine Learning driven marketing to build a lead generation application that helps merchants run data driven campaigns through the banking channels to reach retail customers. The bank’s retail customers trade the utility hidden in its payment transaction data for special offers and discounts offered by merchants. During the entire process banks protects the privacy of the retail customer. MDPI 2022-02-28 /pmc/articles/PMC8947041/ /pubmed/35327858 http://dx.doi.org/10.3390/e24030347 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Torrens, Marc
Tabakovic, Amir
A Banking Platform to Leverage Data Driven Marketing with Machine Learning
title A Banking Platform to Leverage Data Driven Marketing with Machine Learning
title_full A Banking Platform to Leverage Data Driven Marketing with Machine Learning
title_fullStr A Banking Platform to Leverage Data Driven Marketing with Machine Learning
title_full_unstemmed A Banking Platform to Leverage Data Driven Marketing with Machine Learning
title_short A Banking Platform to Leverage Data Driven Marketing with Machine Learning
title_sort banking platform to leverage data driven marketing with machine learning
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8947041/
https://www.ncbi.nlm.nih.gov/pubmed/35327858
http://dx.doi.org/10.3390/e24030347
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