Democratizing Machine Learning Algorithms for Integrated Data-Sharing
The Tango of AI and Big Data
Transforming the Art Museum in the 21st Century.
Explainable AI And The Future Of Machine Learning
Optimal Healthcare Strategy Design In The Digital Era
Ingrid Vasiliu-Feltes, Chief Quality And Innovation Officer, Mednax
Machine Learning And Its Potential Disruptions And Transformations
Sangeeta Edwin, Vice President, Data, Analytics & Insights, Rockwell Automation
AI Summers And Winters And What They Teach Us About The Future
Andreas Merentitis, Director Of Data Science (Global), Olx Group
Artificial Inteligence And The Lost Art Of Auscultation
Edward Kersh, Medical Director, Sutter Care
Thank you for Subscribing to CIO Applications Weekly Brief

Four Benefits of Artificial Intelligence and Machine learning in Banking

Artificial intelligence in banking helps clients evaluate the vast amount of information, from the user’s request in social networks to make informed and safe decisions.
Fremont, CA: Artificial intelligence and machine learning in banking offer many opportunities for personalization, data analysis, tasks solving abilities, and also reasonable costs for implementation.
The widespread rise in the importance of artificial intelligence and machine learning for banking has strong foundations as the technologies offer new and useful benefit.
Here are four benefits of artificial intelligence and machine learning in banking:
A Cutting Edge Advantage:
Machine learning in banks have the capability to make users more competitive according to the task they want to solve.
Banks used to evaluate data with less access to information such as when a client comes with a request to issue a loan, the decision was made only based on the statement of income, current assets and liabilities of the client, and the credit history. Today, artificial intelligence in banking helps clients evaluate the vast amount of information, from the user’s request in social networks to make informed and safe decisions.
Better Security:
Artificial intelligence in banking can be implemented in various ways to achieve higher security. Credit card fraud detection implementing machine learning has become a common application of the technology, and innovative cameras with face recognition can identify if a client has wrong intentions by judging the facial expressions.
Costs Cut:
Artificial intelligence and machine learning can help cut costs for banks and financial institutions based on how these technologies are used. Integrating robo-advisors in the support team can help reduce the cost of staff maintenance.
See Also:
I agree We use cookies on this website to enhance your user experience. By clicking any link on this page you are giving your consent for us to set cookies. More info
Featured Vendors
-
Jason Vogel, Senior Director of Product Strategy & Development, Silver Wealth Technologies
James Brown, CEO, Smart Communications
Deepak Dube, Founder and CEO, Datanomers
Tory Hazard, CEO, Institutional Cash Distributors
Jean Jacques Borno, CFP®, Founder & CEO, 1787fp
-
Andrew Rudd, CEO, Advisor Software
Douglas Jones, Vice President Operations, NETSOL Technologies
Matt McCormick, CEO, AddOn Networks
Jeff Peters, President, and Co-Founder, Focalized Networks
Tom Jordan, VP, Financial Software Solutions, Digital Check Corp
Tracey Dunlap, Chief Experience Officer, Zenmonics