The Future of Customer Interactions in Financial Services – with Ivan Edwards of Cadence Bank and John Thomas of Uniphore

Riya Pahuja

Riya covers B2B applications of machine learning for Emerj - across North America and the EU. She has previously worked with the Times of India Group, and as a journalist covering data analytics and AI. She resides in Toronto.

The Future of Customer Interactions in Financial Services

This interview analysis is sponsored by Uniphore and was written, edited and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

The intersection of AI and financial services is pushing development of customer experiences to the forefront of leadership agendas. Thanks to growing AI adoption throughout the sector, understanding the customer experience in financial institutions (FIs) has transitioned away from manual workflows. Call centers and other complaint forums are now the domain of financial leaders trying to think of every possible nexus of customer interactions – from physical branches and on to online and mobile experiences –  in terms of new potential ROI to be culled from digitizing the infrastructure and processes therein. 

An article published by the University of California Berkeley provides a thorough summary of how companies are undertaking to improve customer experience and interactions by leveraging AI-driven approaches across sectors. The article cites a 2020 Bain & Company global executive survey finding increased adoption and satisfaction with two dozen data tools for customer experience. That gap in satisfaction grew larger between those FIs leading their markets and those lagging.

Emerj CEO and Head of Research Daniel Faggella recently sat down with Ivan Edwards, Vice President of Virtual Customer Interactions at Cadence Bank and John Thomas, Sales Director at Uniphore, to discuss how the future of customer interactions in financial services and how AI will shape them in the coming future.  

Cadence Bank is a regional banking franchise with over $50 billion in assets and over 350 branch locations across the American South and Texas. Uniphore is an AI vendor specializing in integrating advanced technologies to enhance customer experiences across different industries, utilizing generative-, knowledge- and emotion AI along with workflow automation.

This article analyzes their perspectives and provides executives with the following critical insights from their conversation:

  • Understanding customer sentiment to increase retention: Leveraging AI for real-time sentiment analysis of customer conversations to provide a suitable resolution, improving customer retention. 
  • Enhancing customer support with multimodal self-service: Providing real-time assistance by virtually mirroring or simulating the customer’s interface and guiding them through the steps to address their queries or issues.
  • Prioritizing vendors with robust data protection measures:  Selecting AI vendors with solid data protection measures to maintain control over sensitive information in AI adoption.
  • Justifying AI investments and efficiency: When implementing AI solutions in a regional bank, factors such as regulatory compliance, fraud prevention and operational efficiency become critical considerations for investment in AI.

Guest: Ivan Edwards, Vice President of Virtual Customer Interactions, Cadence Bank 

Expertise: Digital Transformation, Chatbot Development, Digital Strategy

Brief Recognition: Ivan is the Vice President of Virtual Customer Interactions at Cadence Bank, where he leads various departments like voice and non-voice interaction, inbound/outbound contact centers, chat, messaging and bot interactions, as well as the operational and tech teams that support these areas. He has also served at Wells Fargo as Contact Center Manager and Assistant Vice President.

Guest: John Thomas, Sales Director, Uniphore

Expertise: Business development, Customer relationship management, Sales leadership

Brief Recognition: John Thomas is a seasoned sales professional currently serving as the Sales Director at Uniphore, based in Texas, USA. With a strong track record in new business and significant account selling, he has demonstrated expertise in various industries, including BPO, eCommerce, and utility/energy. He graduated from the University of North Texas in 1998. 

Understanding Customer Sentiment to Increase Retention

John begins by explaining the importance of real-time sentiment analysis for organizations, especially banks, in retaining customers. He emphasizes that understanding customer sentiment during positive or negative interactions enables better decision-making. It includes decisions such as waiving fees or addressing specific concerns to enhance customer experience.

He describes Uniphore’s approach, where they provide real-time sentiment information to coach agents during phone calls. For example, if a customer is upset about a fee, the system proactively suggests responses and may automate fee waivers to improve sentiment and overall client satisfaction. It aligns with the long-term strategy of retaining happy clients and increasing customer satisfaction.

John also touches upon the broader concept of conversational AI, highlighting that it goes beyond understanding spoken words and text. Uniphore, the company he represents, incorporates verbal and nonverbal communication in their analysis. They have a tool in their portfolio that guides salespeople during phone calls, analyzing sentiment and specific insights, such as moments of inflection, to help improve interactions and provide actionable information for follow-ups and next steps.

Adding to how similar innovations and technology have swept through banking infrastructures the last half decade, Ivan mentioned the ability to connect with a banking agent live at ATMs via video chat. Because customers are interacting with a representative virtually, the bank can offer a more personalized experience while gathering data that makes future interactions more personalized for that specific customer: 

“And one of the things we’re thinking about doing is, let’s say if you have a problem with like your online banking or your mobile app. You do a quick video chat with one of our representatives here in the bank. They can see your screen, you can see their screen, and they can actually navigate you while you see their face. Going back to that more personal live experience.”

-Ivan Edwards, Vice President of Virtual Customer Interactions, Cadence Bank 

Enhancing Customer Support with Multimodal Self-Service

Ivan expands on exciting challenges in addressing customer issues with self-service options and finding innovative ways to assist them. In the process, he mentions that when his own parents call their local bank branch, they often need help with the self-service option and guidance on performing specific actions.

To address this challenge, Ivan shares that his team is exploring new technologies that allow their customer service representatives to mirror the customer’s interface, whether on the desktop version of the website or the mobile app. This means that the bank representatives can guide customers visually by instructing them on where to click or what steps to take, providing real-time assistance.

In response, John discusses a trend he sees in meeting the needs of the demographics accessing these channels while enabling self-service and maintaining high customer satisfaction scores (known throughout service industries as CSAT). He emphasizes the importance of providing a multimodal self-service experience, meeting customers where they want their problems to be solved. It involves allowing them to speak and listen while incorporating visual elements, such as navigation and online interaction.

Prioritizing Vendors with Robust Data Protection Measures

John touches on a common concern among organizations regarding deploying more extensive generative AI solutions into the future. The problem is customers and agents potentially sharing personal and company data when using these models. Many organizations need to be more cautious about ingesting data that could end up in a corpus of responses shared with other entities. As a result, a growing trend exists for large organizations to create their own language models to maintain better control over their data. 

On the other hand, Ivan acknowledges that only some organizations have the resources to build AI capabilities predominantly in-house. For those without such resources, choosing a reliable vendor becomes crucial. He emphasizes the importance of selecting a company that ensures the safety and security of data, as any breach or exposure (even if caused by a vendor) ultimately reflects on the bank itself: 

“Once the bad actors have access to the data, the real concern is this: It’s not that ‘Hey, they’re gonna go set up their own policies for another new regional bank and utilize your policies.’ It’s, ‘Hey, the bad guys are out there and they’re going to understand what it takes to access account information and to transfer funds. They’re going to come back and they’re going to utilize the information that’s been made available to them.'”

-John Thomas, Sales Director, Uniphore

Ivan further notes to John’s point that data breaches in the financial industry often involve breaches at vendors used by financial institutions rather than the institutions themselves.

Justifying AI Investments and Efficiency

Ivan discusses the key considerations, particularly efficiency and scalability, when implementing AI solutions in his organization, specifically a regional bank. He echoes John’s point about the importance of efficiency, highlighting that the investment in AI should be seen as justifiable by all stakeholders. He outlines several factors that justify an investment in AI capabilities:

  1. Regulatory Compliance: If AI implementation reduces the likelihood of regulatory errors, it becomes a valuable investment.
  2. Fraud Prevention: Preventing fraud has a strong ROI as a mature AI use case across retail, eCommerce, financial services and beyond.
  3. Operational Efficiency: The capacity of AI to enhance overall efficiency and streamline processes is crucial, especially for organizations with limited resources.

Ivan emphasizes the challenge regional banks face compared to larger institutions, underscoring that scalability is of utmost importance. Given that his organization is still on-premises and needs to be on the cloud, he highlights the need for solutions that can adapt to his organization’s specific requirements. 

Scalability in partner solutions is essential for his department and the broader Cadence Bank organization, Ivan tells the executive podcast audience. In the process, he must ensure that the chosen AI solution is versatile and can accommodate the parent organization’s evolving needs as well.

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