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In the rapidly evolving landscape of financial services, customer experience has emerged as a critical battleground for differentiation and success. As technology continues to redefine the parameters of service delivery and customer engagement, financial institutions are under increasing pressure to adapt and innovate.
To illustrate the scale of such customer experience problems in the industry even before the overwhelming presence of AI, a pre-pandemic Deloitte survey of over 15,000 customers found the reputation of major banking brands was held in such historically low esteem that nearly half reported they would consider banking services from Amazon. Another quarter said they would consider Facebook banking services.
Anuj Maniar, a Deloitte Principal specializing in financial services, joined Emerj CEO and Head of Research Daniel Faggella on the ‘AI in Business’ podcast to discuss the potential of GenAI’s to reverse these trends back in favor of traditional financial business models.
Throughout their conversation, Anuj emphasizes how generative AI (GenAI) will be instrumental in addressing the challenges and pressures insurers face with increasing customer service expectations. Later, he delves into the need to integrate strategies across communication channels to aid companies in meeting and exceeding ever-evolving benchmarks of customer service.
This article will examine three critical, interrelated takeaways from their discussion:
- Integrating multiple AI capabilities to balance efficiency with customer expectations: Combining GenAI, conversational AI, and basic predictive analytics to identify more clandestine trends in customer expectations and drive associated efficiencies.
- ‘Right Channeling’ communications operations: Strategically selecting and integrating communication channels to align with customer preference signals, ensuring a seamless omnichannel experience that meets rising expectations.
- Proactive back-office operations: GenAI-enhanced copilot technologies are poised to transform back-office operations in after-call work, allowing customer service employees to be proactive in informing customers about bills and payment options, increasing personalized outreach, and reducing associated costs.
Listen to the full episode below:
Guest: Anuj Maniar, Principal, Deloitte Financial Services
Brief Recognition: Anuj has worked as a consultant for over 20 years. Currently heading up Deloitte US’s Customer & Marketing division, his primary goal is assisting companies with developing methods of attracting and retaining customers. He has authored several Deloitte methodologies on the topics of customer analytics, customer experience design, and marketing effectiveness, among others. He holds an MBA in Economics & Strategy from The University of Chicago Booth School of Business.
Skills: Customer experience design, digital transformation, customer analytics, business strategy, marketing strategy
Integrate Multiple AI Technologies to Balance Efficiency with Customer Expectations
Anuj begins the interview by discussing the most common AI in insurance trend he’s seeing of financial leaders attempting to balance customer expectations of service with limited budgets. He lists three technologies that help companies “do more with less” in the long run:
- Conversational AI
- Generative AI
- Predictive analytics
“The biggest trends we’re seeing is that AI and Gen AI are really making an impact on solving an equation … [for] how do I deal with increasing customer expectations with increasing pressure on my budgets? I need to be able to do more with less. And the trends we’re seeing are the adoption of AI to really help solve this equation. Whether it’s in the form of conversational AI, generative AI, or simple, brute force analytics, that tells me more about what customer needs are and how I can solve them efficiently.”
– Anuj Maniar, Principal, Deloitte Financial Services
Some of the improved efficiencies across operations afforded by these three technologies include:
- Reduced costs: Conversational AI (e.g., AI-enhanced virtual assistant platforms) can automate many routine customer inquiries without needing a human agent. Predictive analytics can identify potential customer issues via behavioral analysis and provide proactive solutions, reducing the need for human support and increasing customer satisfaction. GenAI can summarize after-call work, saving time and labor costs.
- Improved customer service: Conversational AI can provide support outside of regular business hours without the need for human agents, lowering support costs and improving the customer service experience. GenAI can create tailored content for proactive outreach (e.g., payment reminders), improving customer satisfaction and loyalty by demonstrating concern for customers’ financial health by reducing late fees.
- Employee enablement: AI tools can provide agents with insights and summaries, getting them up to speed on cases faster and resolving them more effectively. Empowered agents often lead to better customer experiences.
‘Right Channeling’ Communications Operations
In our discussion with Anuj, the most compelling application of AI and GenAI is the strategic integration of communication channels. As mentioned, many eCommerce-adjacent industries with increasingly digital customer experiences are facing pressure to improve customer experience due to trendsetters driving highly tailored customer experiences throughout their systems.
The central challenge for many insurance companies for doing so is that they need to update their legacy, and often decentralized, communications channels. The limitations therein put them at a tremendous disadvantage in meeting customer demands for faster communication across channels.
These difficulties often lead to the following customer service pain points:
- Slow response times: Customers get frustrated when their queries remain unanswered, and claims are slow to process.
- Inconsistent service: Too often, customer experience can vary widely across departments and channels.
- Innovation stagnation: Legacy systems stifle the ability to adopt new technologies and offer innovative services.
To consolidate these often contradictory priorities, Anuj tells the executive podcast audience that he believes leaders need to let go of the status quo approach of trying to fashion each channel to meet all customer needs all at once.
He insists that approach is to overwhelming for leadership and adoption teams to effectively execute over an alternative strategy he refers to as ‘right channeling’:
“[Right channeling] is the pressure that we’re seeing. It’s what’s the right channel, or what’s the right sequence of channels, to serve as a customer’s need. It’s not just make all channels available to serve all types of needs. We’ve had clients that have done things like make a social media channel available in financial services, when from a servicing perspective, you can’t really address a customer’s issue in a social media channel. You then immediately have to switch them.
So the question then is: What is the real channel strategy? Is it going to be an issue that requires a human being, or is it going to be an issue that requires a level of authentication that needs to push out of a social media channel, then orchestrate that for the customer? That’s the pressure we’re seeing.”
– Anuj Maniar, Principal, Deloitte Financial Services
Regarding any potential manual or automated solution, Anuj stresses the importance of:
- Remaining open to any communication solution
- Selecting the right channel or combination of channels for seamless customer communication.
- Recognizing a common misconception that consolidating all channels into a single point of access is not necessarily ideal.
- Doing some weeding out: identifying those channels that should not be integrated or utilized.
Creating the “Right channel,” as Anuj terms it, involves additional steps beyond channel strategy:
- Customer journey mapping: Analyzing and designing customer interactions across touchpoints to ensure a seamless experience.
- Organizational and technical alignment: Unifying communication channels is essential for defragmenting communications across silos and delivering this experience.
- Technology infrastructure: Implementing a robust technical framework to support the transfer of customer data across channels.
Proactive Back-Office Operations
Anuj also emphasizes, that to properly develop such customer-facing AI workflows, it will become increasingly necessary for financial enterprises to incorporate GenAI into more clandestine business operations, especially in areas not directly involving customer interaction. He suggests that GenAI has the potential to significantly improve internal processes, such as after-call tasks and support through copilot platforms that act as “whisper type agents.” Anuj explains that these technologies can transform traditional, reactive back-office functions into proactive enterprise capabilities reducing costs.
He illustrates this point by stating that current procedures for notifying customers about credit card payments and options only occur after a missed payment, leading to financial losses or delayed income for the company.
Anuj proposes using the same previously mentioned combination of three AI technologies to enhance these processes:
- Predictive analytics to identify potential late payments
- Conversational AI to allow agents to receive timely data through a chat interface
- GenAI to customize communication strategies based on individual customer behavior, focusing on empathy and effective persuasion.
Anuj shares a story highlighting how these AI-driven approaches can anticipate why a customer might be calling — such as having several bills due just before receiving their paycheck. With the foresight provided by GenAI, agents can proactively offer flexible payment solutions, addressing customer needs while ensuring revenue streams.
Taking such a proactive approach to channels beyond phones and call centers, Anuj recommends a small – but telling – change in the name for these operations, symbolic of the overall transformation in strategy:
“Instead of using ‘contact center’ or ‘call center’, I would call it our customer experience or customer service organization. That could span the bank branch, the contact center, the ATM, or the insurance agent, the contact center, and the digital experiences we’ve created on the mobile app. That’s what can really unlock the power and value of these technologies. We have to think differently outside of our individual channels. There’s been so much optimization done within each of the individual channels that the future optimization and value are going to come from AI, GenAI, and predictive analytics.”
– Anuj Maniar, Principal, Deloitte Financial Services
