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THE FUTURE OF CUSTOMER INTERACTIONS IN FINANCIAL SERVICES – WITH IVAN EDWARDS OF
CADENCE BANK AND JOHN THOMAS OF UNIPHORE

Riya PahujaLast updated on January 23, 2024
Last updated on January 23, 2024, published by 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.

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