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The Role of AI in Banking


Even before the pandemic, banks were undergoing dramatic transformation. In fact, according to the Bain report, as many as 80% of banks in the Americas and Europe were planning changes to their branch networks, including closing or redesigning locations. Many consolidated branches, while others shifted to a hub-and-spoke model. Still others tested and deployed interactive video tellers to address their need to minimize staffing in the branch.

Then the pandemic pushed even more customers to mobile banking, as the non-digitally inclined were persuaded to change their behaviors for health and safety reasons. In April and May, branch traffic dropped 30% compared to previous years. While simple on-site banking transactions have declined, the types of customer transactions that remain are complex. Plus, customers have higher expectations. All of this is a challenge for branches with far fewer resources.

Yet there are also opportunities now for the bank branch to deliver tremendous value to customers. Those who have answered this call have accelerated technology deployments from years down to weeks, enabling customers to enjoy the increased efficiency that comes with new solutions.. 

For example, mobile appointment scheduling is being used to reduce the number of people in a branch at any given time. This allows employees to prepare so that a customer can walk in safely and complete their business without having to wait.

Many technologies rely on the more mature application of artificial intelligence (AI), which was initially used simply to automate back office functions and paperwork. Today, AI is used in solutions like Wells Fargo’s “Advance Listening” capability that engages Natural Language Processing (NLP) to analyze customer communications across all channels (email, text, phone, online, etc.) and prompt employees on how to best service customer needs. The application also helps Wells Fargo monitor employee compliance with bank policies. Bank of America’s “Erica” is an AI-enabled chatbot that also uses NLP to serve 16.7 million customers. And, TD Bank purchased an AI tech company to leverage its ability to analyze data and predict customer needs and identify fraud.

What’s Lies Beneath the Digital Experience?

The more digitally “capable” a bank becomes, however, the more it needs to assess its underlying network infrastructure. One common mistake across all industries is the failure to consider holistically what is required to create the digital experience. For example, an enterprise will commit enormous time and resources to identify which AI-enabled clienteling solution to deploy, with little time spent scrutinizing the network it will depend on. The result can be slow or timed out transactions, and an overall poor experience for both the customer and the employee. This often happens when existing T1/MPLS don’t provide nearly enough bandwidth. But the answer isn’t necessarily to add more T1/MPLS (which can be cost-prohibitive), or to turn to alternative broadband solutions (which may be congestion prone and pose meaningful cybersecurity risks).

Instead, a better option is for banks to leverage the same types of artificial intelligence used to create added value digital experiences, to solve network performance issues! Hughes has already seen AI’s impact in our own operations. Since deploying our AI for IT Operations (AIOps) technology last year, we have saved customers thousands of hours in headaches and hassles through pre-emptive mitigation techniques—anticipating and solving network problems before they might otherwise occur. Other intelligent solutions to address broadband congestion problems include our Hughes Managed Software Defined Wide Area Network (SD-WAN) technologies, which transform ordinary broadband connections into enterprise grade WAN connections.

Innovative network solutions can remedy a variety of challenges facing the small branch and enable the distributed enterprise to deliver a consistent digital banking experience to all customers, regardless of location. These are just a few reasons it makes sense for banks to step back to assess their network infrastructure as they roll-out more AI-enabled applications. Doing so will pay dividends in the end!