Artificial intelligence and machine learning promise nothing short of a customer experience transformation in retail banking — but the best ideas for their application could fail if projects are not built on firm foundations of clean, accurate and complete data around customers and their behaviors and financial needs.
The focus on customer experience among today’s retail banks and credit unions should hardly be surprising. With financial services becoming even more commoditized, institutions increasingly must battle for consumers’ attention and wallet share against disruptive new market entrants as well as their traditional competitors. More than ever, financial institutions need to find some way to differentiate themselves.
In customer experience terms, AI and machine learning can help marketers in retail banking to predict client needs and deepen relationships. They can do this through more personalizing their approaches, fine-tuning campaigns for maximum effectiveness, targeting consumer segments that represent the best acquisition prospects, and identifying attrition risks and causes.
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