Banking

4 Ways Retail Banks & Lenders Can Emerge Victorious in the Amazon, Uber, Netflix Era

5 mins read
December 12, 2018
By
Total Expert

Customer expectations are changing faster than ever in the era of Uber, Amazon and Netflix. These disruptors continually raise the bar by relentlessly simplifying and personalizing customer experiences. People now expect these experiences with all companies they use, and they can easily shop around at any point in any transaction to find a provider who meets their expectations.

No banker or mortgage lender is immune. As many as 5.6 million Americans plan to switch banks this year – a significant jump from years past – in search of better, faster service. Lenders are now competing with digital startups that didn’t exist a decade ago. And 54 percent of customers have stopped doing business with a company because of bad customer experience.

That’s the bad news for banks and mortgage lenders looking to grow revenue: New customers are five times more expensive than repeat customers.

The good news is that you can keep up with customer expectations. And doing so yields massive returns: Boosting customer retention by just five percent can increase profits by up to 95 percent – and that’s not including new customers your top-notch experience will help you win.

Here are four strategies to stay ahead of expectations and win customers for life in this real-time, mobile-first era.

Tip 1: Close The Advice-vs.-Transaction Gap

Seventy-eight percent of customers want advice from their banks and mortgage lenders, but only about 28 percent actually get that advice. That’s a major opportunity to differentiate yourself.

Forty-one percent of people want quick tips to help improve their financial situation, 33 percent want advice to help keep track of spending and household budgets, and 29 percent want advice for saving for a large purchase.

Instead of simply asking questions to drive toward a single transaction, make sure your sales teams truly understand and listen to customers’ needs. That practice not only leads to better service and smarter advice, it can also lead to more transactions.

Tip 2: Master Hyper-Relevance

Accenture calls the practice of delivering the right message to the right person at the right time “hyper-relevance.” Mastering hyper-relevance means automating useful connections with your customers and prospects, which takes the heavy lifting out of building real trust over time.

As for blending timeliness and relevance, consider this opportunity: Despite 78 percent of customers wanting financial advice from banks and lenders (as noted above), only 29 percent of customers can recall recently receiving any type of financial advice.

Also, 58 percent of those who received face-to-face advice feel it completely met their needs, which isn’t bad, but that number drops to 45 percent for people who got advice from a website or app, and to 33 percent for people who got advice via email.

Retail bankers and lenders are strong face to face, so if they keep getting better at translating this high-touch experience to websites, email and other digital channels, it becomes very hard for online-only competitors to match.

Tip 3: Understand Customer Expectations For Local AND Digital

This means bankers and lenders must master both digital tools and human engagement.

Fannie Mae data shows that while 72 percent of people want a digital loan application process, 65 percent want a human to explain loan terms and options.

Again, retail lenders and bankers are leaders in serving the 65 percent who want human help, so now is the time to focus on how that advice can be more easily and clearly deployed via digital means.

Today’s customers expect way more than drip email campaigns for birthdays and life events. Next up is using digital tools to help you stay in front of customers with advice specific to their profile at the precise times they need the advice and / or would be most receptive to it.

Tip 4: Get Alignment at the Executive Level

For all of the above efforts to work, your organization must have an executive team who gets that serving customers with hyper-personalization and immediate advice across digital and local channels isn’t just a tech wish list. It’s an absolute (and ever-increasing) customer expectation. And if customers don’t get it from your org, they will seek it out elsewhere.

According to Google, in the past two years, searches for “best [provider]” have increased 80 percent and searches for “[provider] near me now” have increased 150 percent.

Customers will remain loyal if you can meet their real-time expectations, but if you don’t, they can find other options faster than ever.  

Great leaders and companies who understand this new reality can break down silos between sales and marketing (in data, strategy and elsewhere). Without integration of the sales and marketing teams, it’s almost impossible to create a highly personalized, highly relevant customer experience at scale.

Even with executive alignment, banks and lenders must keep all priorities focused on easy data capture for salespeople, data sharing among teams and technology that takes you beyond simple drip emails and social posts.

Personalized Data Yields Personalized Advice

The reason most of us love Uber, Amazon and Netflix is because they leverage the data they have from past engagements to serve us better every time we engage. The banking and lending industry is on the cusp of learning how to do this just as effectively. As long as we remain focused on customers’ expectations for this type of engagement, we will usher in a new era of personalized finance.

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[Daily Mortgage News Podcast] Joe Welu Talks Agentic AI in the Mortgage Industry

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Total Expert Founder & CEO Joe Welu recently joined Robbie Chrisman for an episode of the Daily Mortgage News podcast where they discussed the current (and future) state of the mortgage industry, challenges facing lenders and loan officers, and the solutions that AI-enabled tools can provide in difficult markets.

Agentic AI is reshaping loan officer productivity and customer engagement. With Total Expert’s new AI Sales Assistant, lenders can automate lead incubation and qualification—achieving human-like conversion rates in weeks, not months. Joe also highlights the power of voice AI to revive aged leads, trigger refinance opportunities, and prevent deals from falling through the cracks, all without the need for massive call centers and without removing loan officers’ ability to build authentic human connections with borrowers and homeowners.

That’s because AI-enabled tools are designed to reduce the administrative and repetitive tasks that take you away from what you do best: advising customers and guiding them toward the best possible financial outcomes. Joe also shares insights on selecting AI partners wisely, managing data responsibly, and capitalizing on both front- and back-office efficiencies. As the AI arms race heats up, Total Expert aims to empower originators—not replace them.

Joe and Robbie's discussion begins at the 4:55 mark.

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Delivering AI Solutions that Drive Real Value in Financial Services

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By Pete Karns, Chief Product Officer, Total Expert

AI is no longer a future state—it’s already here, embedded in everything from ride-sharing apps and food service to factories and farms. In the world of financial services, though, this ubiquity comes with pressure to integrate AI fast, appear innovative, and keep up with competitors—all while being mindful of evolving federal and state compliance requirements. Moving fast without a plan or awareness of up and downstream implications often leads to AI-enabled solutions that either underdeliver or don’t deliver at all.

At Total Expert, we’ve taken a different path: thoughtful integration over flashy announcements. As more financial institutions wrestle with what “real AI adoption” should look like, here’s what we’ve learned and what lenders need to consider to get it right.

Where enterprise AI goes wrong

Too many financial services leaders have experienced what I call “AI failure to launch (and scale).” They’ve rushed to try unintegrated AI-enable offerings and bolt on AI tools—often generalist chatbots, white-labeled versions of generative tools, and/or hooking up to MCP servers—without a clear sense of how these tools will solve their business problems or add potential risk. The result? The occasional value-add result. However, what we see more is poor user adoption, wasted spend, and limited impact.

This is the same trap we saw with “digital transformation” a decade ago, or the original horizontal SaaS applications that evolved or were replaced by vertical-specific solutions. AI-enabled solutions offer tremendous, generational promise but they risk becoming vanity-first, value-later tools. We are focused on the former.

AI that thinks and adapts: Welcome to agentic AI

Let’s make one thing clear: not all AI is created equal.  

Chatbots have been commonplace in financial services for a decade now, but remain rigid, rule-based tools that handle repetitive tasks.  I’ve worked with “AI” services for more than 15 years and each had their own place and potential when used properly. Herein lies the opportunity. Modern lenders that are focused on retaining and growing their customers in an ultra-competitive market need something more dynamic. Enter AI agents that can understand context, adapt on the fly, and speak in a human-like way. These agents are coachable, brand-aware, and learn from every interaction. They don’t follow scripts—they think in real time. And when built correctly, they become a seamless part of your customer experience.

This is the evolution from AI as a support function to AI as a trusted team member.

Total Expert recently launched an AI Sales Assistant that puts this principle into action. It functions as a scalable, intelligent teammate—able to engage leads, deliver personalized conversations, and identify high-potential opportunities—all while staying aligned with your brand voice and compliance requirements. It’s not a chatbot bolted onto a CRM—it’s a fully integrated AI-enabled solution, utilizing data, embedding within workflow orchestration, and playing nice with application logic because it has the necessary context to work within your lending ecosystem.

The real “why” behind AI adoption

Before choosing any AI solution, or any technology solution, financial services firms must ask themselves: What business problem are we solving?

For example, when mortgage rates dropped for a few weeks in September 2024, our customer intelligence capabilities identified nearly $2 billion in immediate refinance opportunities. But no team of loan officers could scale quickly enough to reach every qualified lead. That’s where AI tools prove invaluable—automating first-touch outreach at scale, surfacing the best opportunities, and empowering human teams to scale up execution to drive retention and growth.

Why embedded beats bolted-on

The types of AI-enabled solutions we are talking about can’t function effectively in isolation. Without access to timely and accurate customer data, and invoked within a specific workflow process, it can’t personalize interactions, anticipate needs, or drive conversions at the right time.

Picture an AI assistant offering a refinance to a customer, only to stall when asked for more details. If it doesn’t know the customer’s current rate or financial profile, the experience feels hollow. That’s not just ineffective—it damages trust.

By contrast, when AI-enabled solutions are embedded within a unified customer experience platform like Total Expert, it draws on a 360-degree view of the customer. It knows the data, understands the history, and delivers contextually rich conversations that convert.

This is why we’re designing our AI capabilities with a focus on the unique needs of financial services organizations. The same purpose-built approach has earned the Total Expert platform its unmatched reputation for usability and time to value.

Generalist AI offerings can be a gamble that increase costs—and time to value

Implementing AI that’s not purpose-built for financial services introduces two major risks:

1. Usability failure: Your team must spend months customizing and configuring a generalist AI tool to make it work for your specific needs—if it will ever work at all. For example, imagine you’re a loan officer and one of your referral partners introduces you to a borrower. Now, you have to choose the best way to approach the first conversation with this borrower. There are countless permutations of questions and answers which all require deep personalization, compliance awareness, and consistent representation of the sales processes and brand tone of the lender. Generalist AIs will quickly reach their limitations in these complex use cases.

An industry-focused AI offering will be trained on this specific use case and provided with the context needed to hold a dynamic conversation with the borrower. This type of AI learns and adapts with each interaction, performing the most time-consuming tasks so you don’t have to.    

2. Compliance risk: Without built-in industry guardrails, you’re gambling with regulatory violations and brand safety.  As we know, the compliance landscape for financial services is broad and evolving at the federal and state level.  Look for AI offerings that are regulatory aware and enable you to configure them based on your organization’s risk tolerance and interpretations.

Lenders don’t need more tools—they need the right tools—ones that work out of the box, understand industry nuances, and deliver immediate, compliant value.

Ask these questions before you commit to an AI offering  

To maximize the probability of success, here’s a quick checklist for vetting solutions:

  • Can it solve a real, high-value business problem, and how? Review specific examples and ask to speak with other organizations that have implemented the tool.
  • Does it function as a true AI agent, not a static bot?
  • Can it be deeply integrated into your core system(s), workflow orchestration, and data?
  • Does it include financial industry compliance and brand guardrails?
  • Can it scale without sacrificing quality or regulatory integrity?

Building the future with purpose-built AI

Total Expert has always designed technology with financial services in mind, and our approach to utilizing AI is no different. We’re not chasing hype. We’re solving problems.

Our focus on AI isn’t simply building standalone features—it’s about embedded, intelligent, and deeply integrated AI solutions. It’s helping lenders scale smarter, engage more meaningfully, and turn data into action. Our AI Sales Assistant is just the beginning—an example of how purpose-built, AI-enabled solutions can solve real problems and deliver tangible value. We are already testing and exploring other AI-enabled solutions and I could not be more excited about the current and potential value our clients and our market will achieve.

Because when AI works, it’s not just impressive—it’s indispensable.

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The Loan Officer’s New Co-Worker: Total Expert’s AI

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*This article was reposted from HousingWire.com*

In this exclusive interview, Joe Welu, Founder & CEO of Total Expert, shares the company’s latest advances in AI. He focuses on lessons learned from their pilot program and explores how AI is delivering a measurable lift in operational efficiency and lead conversions across lending teams.

Beyond internal improvements, Joe reveals Total Experts’ focus on the borrower experience and how their technology is designed to supercharge loan officers, not replace them. Joe shares with Allison LaForgia his forward-looking perspective on the innovations expected in the near future that will continue to drive Total Expert’s leadership in mortgage technology.

“We anticipated… it would probably take maybe nine months to a year to be able to get to parity with a human… and we’re blown away. It happened within two weeks,” Welu said. The voice AI agent, designed to qualify leads through inbound and outbound calls, is now handling more than 2 million calls a month, with multiple lenders, in various stages of scaling.

Welu attributes the rapid progress to the unprecedented pace of innovation in AI. “It’s like nothing anyone’s ever seen before… there’s hundreds of billions, if not soon trillions, being invested in infrastructure and large language models… we get the opportunity to build on top of those capabilities and reimagine what we can do in our industry.”

The pilot program, he said, was rooted in an iterative approach with tight feedback loops. “As we learn… it gives us information, and we make adjustments… A key thing we’ve learned with AI projects… get really super clear about what it is in the business that you are improving. Give them that target… so it’s not this ambiguous sort of black box.”

The results have been measurable: “We are seeing, in some cases, 10 to 20% better conversions,” Welu said. AI’s consistency is a major factor. “It always remembers to call people back… never calls in sick… works weekends… It allows you to take your great people and… have them doing the most highly productive work possible.”

Borrower experience is also improving. “One of the pleasant surprises… is the quality of the experience to the end consumer,” he said. Whether or not lenders disclose that a caller is AI, “the quality of the interaction is so high, they continue down the path.” The AI agent maintains “the right tone… the ability to match… the tempo of the conversation” while instantly tapping into contextual customer data.

Welu emphasized that Total Expert’s AI is designed to “supercharge,” not replace, loan officers. “There are still moments where consumers want high quality advice… Our goal is to take a loan officer and put them in a position where they are spending… the majority of their time having the highest quality conversations… and abstracting away things that don’t add value.”

Looking ahead, Total Expert’s roadmap focuses on intentional, scalable AI. “We think about getting super clear on… use cases, and partnering with people that are going to be as obsessive as you are, about making it great,” Welu said. Over the next year, customers can expect new capabilities in customer intelligence, lead management, and additional AI-driven use cases. “Seeing it all come together is what gets me up and excited every day.”

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