Transforming customer service and engagement
Customer service is another area where AI is expected to make significant strides.
Scott predicts that banks will continue to bring their behind-the-scenes AI work to the forefront of customer interactions.
“Using AI to power customer service chatbots and automate responses to common questions, banks will enable customer service employees to dedicate their time to solving more complex issues that require human interaction,” he says.
This shift towards AI-powered customer service has the potential to improve response times and provide 24/7 support to customers.
By handling routine inquiries and tasks, AI chatbots can free up human customer service representatives to focus on more complex issues that require critical thinking and personalised attention.
Viren Patel, Financial Services Industry Strategist at Workday, predicts that banks will increasingly use advanced Natural Language Processing (NLP) and GPTs to accelerate and grow their customer service capabilities.
“At the frontline, banks will increasingly come to use advanced Natural Language Processing (NLP) and GPTs to accelerate and grow their customer service capabilities,” Viren says.
The use of NLP and GPTs in customer service represents a significant leap forward in banks’ ability to understand and respond to customer queries.
Boosting operational efficiency
The potential for AI to significantly boost productivity in the banking sector is widely recognised.
Prashant cites research from the IBM Institute of Business Value that predicts AI will add a 14% increase to global GDP by 2030, equivalent to a growth of US$15.7tn.
Ryan highlights the potential of AI to take over mundane tasks, freeing up data science teams to focus on more complex problems.
“AI will take over more mundane tasks, like cleaning data,” he says. “Data science teams in banks, freed from monotony, will be able to focus on improving their algorithms.”
This shift in focus has the potential to accelerate innovation in the banking sector, as highly-skilled data scientists can dedicate more time to developing and refining sophisticated AI models that drive business value.
Viren emphasises that AI’s impact extends beyond customer-facing applications: “It can boost real-time decision-making for leaders – for example by highlighting skill gaps within the organisation – alongside enabling better financial planning tools.”
This internal application of AI can help banks operate more efficiently, making better-informed decisions about resource allocation and strategic planning.
link