Authors :
Tayyab Muhammad; Stephanie Ness; Mykola Volkivskyi; Yulu Gong
Volume/Issue :
Volume 9 - 2024, Issue 2 - February
Google Scholar :
http://tinyurl.com/2p8skyej
Scribd :
http://tinyurl.com/5n6zr44n
DOI :
https://doi.org/10.5281/zenodo.10707332
Abstract :
The use of Artificial Intelligence (AI) and
Machine Learning (ML) within the Banking sector has
dramatically transformed the industry in recent times. AI
has catalyzed new advancements on both the back and
front ends of financial operations. This article seeks to
explore the significant impact of artificial intelligence
within the banking industry. It will look at how these
abilities further drive efficiency, allowing professionals in
the industry to enhance the experience for their customer
base. It will explore different use cases within the space
and paint a picture for the future as computational
intelligence continues to hold a key role in decision-making
where accuracy is increasingly important. The banking
industry has traditionally been an area conservative about
the implementation of new technology due to security
implications. However, this has begun to change as the
banking industry begins to consolidate these technologies
can provide an advantage in the market and catch the eye
of a public who is using traditional banks less and opting
to reside with tech and fin tech companies. Understanding
what AI and ML are is key to getting what these
technologies are about. This paper provides multiple real-
world examples of how machine learning is likely to upend
banking. By ingesting files and recognizing patterns, ML
algorithms help banks predict behavior and make choices
that will help redefine what banking is in the modern age.
The use of Artificial Intelligence (AI) and
Machine Learning (ML) within the Banking sector has
dramatically transformed the industry in recent times. AI
has catalyzed new advancements on both the back and
front ends of financial operations. This article seeks to
explore the significant impact of artificial intelligence
within the banking industry. It will look at how these
abilities further drive efficiency, allowing professionals in
the industry to enhance the experience for their customer
base. It will explore different use cases within the space
and paint a picture for the future as computational
intelligence continues to hold a key role in decision-making
where accuracy is increasingly important. The banking
industry has traditionally been an area conservative about
the implementation of new technology due to security
implications. However, this has begun to change as the
banking industry begins to consolidate these technologies
can provide an advantage in the market and catch the eye
of a public who is using traditional banks less and opting
to reside with tech and fin tech companies. Understanding
what AI and ML are is key to getting what these
technologies are about. This paper provides multiple real-
world examples of how machine learning is likely to upend
banking. By ingesting files and recognizing patterns, ML
algorithms help banks predict behavior and make choices
that will help redefine what banking is in the modern age.
