What Does the Future of AI in Banking Look Like?

Immediate and Personalized Money Management Solutions

Natural language processing is used by AI chatbots — including Bank of America’s Erica, HDFC Bank’s Eva and TD Bank’s Clari — to help with basic transactions or provide appropriate solutions to various consumer inquiries, such as account balance information.

With its speech, textual data analysis, and predictive analytics capabilities, NLP can navigate human emotion and interpret consumer sentiment while simultaneously analyzing consumer data and performing personalized risk assessments. Bank customers can get 24/7 service from a chatbot or an AI-powered banker and can expect to receive swift financial counsel based on their money history, risk tolerance, and financial goals. 

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Personalized Savings and Investment Recommendations

Asset managers can use NLP to uncover potential investment opportunities by using AI to predict stock market performance and conduct semi-log optimal portfolio optimization. They can also manage downside risks and monitor the impact of rapidly evolving financial markets to guide their clients in real time.

However, future bank customers won’t need an asset manager to access personalized savings and investment recommendations. Instead, they will use NLP-powered transactional bots that serve as financial advisers. These bots will help customers manage savings, investments and other financial plans.

Already, the technology has shown impressive results. The downloadable app Cleo, for instance, is a personal financial assistant currently helping over 3.1 million users effectively budget and save in alignment with their personal financial goals.

And it’s working: 78 percent of users report a decrease in financial worry thanks to AI. With JPMorgan Chase developing a ChatGPT-like AI service to help customers select investments, it’s only a matter of time before digital financial advisers become routine.

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Automated and Anticipatory Decision-Making

Just as NLP is helping banks automate and anticipate money management solutions unique to the customer, high-performance computing is driving AI and predictive decision-making for banks. These supercomputing solutions makes it possible for AI to anticipate and automate document processing, particularly in acquisition and servicing, such as loan underwriting. This not only lowers operating costs for banks, but also accelerates the speed at which customers receive their financial information.

AI Is Paving the Way for a Seamless Omnichannel Experience

AI will provide the speed and agility needed to onboard customers to a variety of technology platforms. The transition so far has proved to be smooth and scalable as customers reap the benefits of an omnichannel experience, unaffected by staffing shortages or significant wait time.

From powering visualization technologies, such as dashboards, to engaging with users 24/7 via NLP chatbots, AI will be pivotal to creating a unified, personalized experience across banking platforms. Whether in person or online — or even while switching between devices or apps —customers can expect a consistent banking experience.

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Smart Ways to Implement AI into Your Banking Business

Many financial institutions don’t have the resources to employ the data scientists needed to maintain AI tools. But building out a full AI team in-house isn’t necessary to start implementing AI technology. CDW offers professional and consulting services to help banks build out AI capabilities without having to make costly staffing investments, combining technology from recognized AI leaders with full-scale services to help banks get up and running with AI.