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Banking and the AI Adoption Bell Curve

Posted on: September 27, 2019 | Posted by: Sona Sharma

The 4 Stages of Adoption of Artificial Intelligence in Banking

Artificial Intelligence (AI) has come a long way since the turn of the century. With Gartner reporting that the number of enterprises implementing AI grew 270% in the last four years alone, segments that were once mostly untouched by AI have begun to explore how the technology can be used to elevate the customer experience. One such notable example is banking. Often outshined by big tech companies when it comes to embracing innovative new technology, many of the world’s most dominant banks have begun to recognize that AI is here to stay, and are determining how it fits into their landscape. Yet, even as some banks forge ahead to make names for themselves in the realm of AI, not all banks are at the same level of adoption. Let’s explore the status of a few industry leaders in relation to the Banking AI Adoption Bell Curve: 

The Conservatives: An AI Awareness

Before action comes awareness. For a number of leading financial institutions, they are ready to embrace AI, but have yet to decide the role it will play. Take U.S. Bank, which operates in 25 states across the U.S., for example. In May of 2017, U.S. Bank announced the creation of a new managerial position—Artificial Intelligence Innovation Leader—to go along with a sizable investment in its artificial intelligence and machine learning research. Such strides indicate an awareness of the important role AI will play in the future of banking; however, a lack of specificity into the role’s function or the initiatives to be launched suggests U.S. Bank is in the early planning stages of AI, rather than serving as a developed leader. For still others, like PNC, conversations on artificial intelligence are primarily confined to the benefit of others investing in AI, with the most prominent internal initiative being a hybrid intelligence program geared to support their environmental performance goals.

For banks in these early stages, it’s clear that artificial intelligence is on their radar, but has not carved out its true place in the organization. Moving forward, these companies will look to others in the industry to determine the must-haves in AI, as well as platforms that can help them close the gap.

The Pragmatists: AI & Security

Far and away, the most notable investment into artificial intelligence in banking has fallen under the category of security. In fact, Risk Forecasting and Monitoring and its related capabilities constitute the largest number of product offering capabilities provided by banks today, coming in at a total of 26.9% of offerings. Such a commitment to customer security and protection can be seen clearly through strategic actions like Citibank’s investment into Feedzai, a global data science company that identifies and prevents fraud in real time.

As cyber threats continue to advance, and consumers become even more concerned about the safety of their money and data in light of major security compromises such as the recent hacking of 100 million Capital One records, there will continue to be a place for AI technology in the fraud prevention sphere of banking; and yet, AI poses potential beyond security alone.

The Early Majority: AI & Efficiency

Newer to the banking world are opportunities for AI technology to improve back end operations for greater cost savings. JPMorgan Chase, an AI leader in banking, has utilized machine learning technology to automate the analysis of legal documents to extract important data points. According to the company, the program, named COiN, can analyze 12,000 contracts with high accuracy in mere seconds, rather than the 360,000 man hours it would historically take—eliminating the considerable risk of error that occurs during manual review and minimizing the wait for customers seeking answers about their applications.

While this program seeks to improve the customer experience through more accurate, more timely responses, it falls short of engaging the customer in a personal, 1:1 manner. It is therefore critical to not only look internally to how AI can improve the operation of banking, but also to look externally to how it can deliver greater benefit to each customer.

The Innovators: AI & Personalization

The banking institutions leading the AI adoption charge have not stopped at their back end—focusing on security or efficiency alone—but rather have brought artificial intelligence technology to the virtual front door by powering  1:1 interactions with customers, driving more personalized, memorable experiences. Some institutions, like Wells Fargo, have focused on AI’s applications to the customer service sphere, bringing an AI-based chat function to Facebook Messenger to deliver in-the-moment insight to customers. Still others, like Bank of America, have brought AI to their mobile app. Erica, Bank of America’s virtual financial assistant, has garnered great success, with over 6 million users and over 35 million completed client requests.

Still, there are more ways that banks can leverage AI to personalize the customer experience. Some include:

  • Leveraging geo-fencing to promote a highly relevant item. For example, if Mary looks online at college financing options one day, and penetrates the geo-fence of her local branch the next day, her bank could send her a notification that bank manager Bob is available for a college financing appointment.
  • Synchronizing devices for seamless form completion. For example, if Tom started to fill out a form on his laptop, but didn’t finish it, he could later receive a push notification on his phone, which he could click to resume filling out the form from where he left off earlier.
  • Activating customer engagement in programs for improved financial performance. For example, if Darrel’s historic spending patterns make him the ideal candidate for a financial tracking program that is offered, a friendly and relevant notification could be enough to encourage his participation.
  • Onboarding new customers through contextualized insight. For example, if Susanne, a prospective new customer, has been searching terms like “no annual fee” and “travel rewards,” the bank could push her an offer for their premium travel credit card when she lands on their website.

While it’s clear that the possibilities surrounding artificial intelligence in banking are endless, they all begin with adopting the right technology. That’s where ZineOne comes in.  Our AI-powered Intelligent Customer Engagement (ICE) platform brings unprecedented 1:1 personalization capabilities to the bank’s front end, elevating the satisfaction of existing customers and driving the acquisition of new customers. Schedule a demo with one of our experts to learn how we’re leading the charge of AI innovation.

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