Machine learning and artificial intelligence in consumer banking

Juan M. Huerta and Abhinav Anand

Journal of Digital Banking, 2018, vol. 3, issue 1, 22-32

Abstract: Thanks to the visibility of recent milestones in machine learning (ML) and artificial intelligence (AI), these disciplines have evolved from abstract and theoretical academic disciplines into the business mainstream. This paper provides a description of AI and ML technical underpinnings, limitations and areas of potential future impact in digital banking. It also provides an overview of the most pressing challenges and opportunities in banking, especially as they relate to the most relevant internal stakeholders in consumer banking organisations.

Keywords: machine learning; predictive modelling; decision models; artificial intelligence (search for similar items in EconPapers)
JEL-codes: E5 G2 (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
https://hstalks.com/article/3772/download/ (application/pdf)
https://hstalks.com/article/3772/ (text/html)
Requires a paid subscription for full access.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:aza:jdb000:y:2018:v:3:i:1:p:22-32

Access Statistics for this article

More articles in Journal of Digital Banking from Henry Stewart Publications
Bibliographic data for series maintained by Henry Stewart Talks ().