Lending

Prioritizing Lifetime Loyalty: Thinking Beyond the Next Quarter

5 mins read
November 11, 2024
By
Mike Waterston

Leaders of banks, credit unions, and other financial services organizations have been on a roller coaster since 2018. Trying to keep up with the predictions and the conversations about what will happen with rates could leave you with whiplash. And yet, according to Deloitte, the top challenge for financial institutions in 2025 will be adapting to what it calls a “low-growth, low-rate” environment, where a mix of slower consumer spending, higher unemployment, and lingering geopolitical and regulatory uncertainties keep us teetering on the edge of a recession that’s been threatening the last three years.

But leaders need to resist rash reactions to these anxieties because, as we’ve said before, financial institutions can’t cut their way to growth. Those that pull back too strongly on investing in innovation will quickly damage customer experience and hurt long-term loyalty—and won’t be ready to capture opportunities when conditions do begin to turn around.

Success in 2025 depends on thinking beyond the next quarter. Financial institutions need to build enterprise-level strategies that position their businesses for long-term success.

So, what does that long-term, enterprise-level strategy look like?

How we got here: Boom times shifted the focus from relationships to transactions

Think back to the five years leading up to the start of the pandemic: Things were good. Many financial institutions saw such high business volume that they were just trying to get the transactions done. Strategies became ad hoc and short-term—making quick hires to throw people at the problem and/or piling on point-solution products that promise to solve specific issues.

We can look past the pandemic period of 2020-2021 as a (hopefully) once-in-a-century anomaly. But when rates started increasing in 2022 and the economy slowed down, the transactional focus of many financial institutions led to some knee-jerk reactions: cutting costs, cutting staff, and cutting vendor expenses.

The economy proved surprisingly resilient, holding off the recession that was forecast in 2022 and 2023. Some financial institutions saw volume bounce back—forcing them to quickly add staff and develop ad hoc strategies to keep up.

Today, we’re back to worrying about a slowdown. We’re seeing major banks worldwide announce significant job cuts, with Citigroup, Wells Fargo, and Goldman Sachs all making huge layoffs.

What smart financial institutions do differently: invest in a long-term growth strategy

The most successful financial institutions over the last several years (and, more broadly, the most successful businesses across all sectors) share a common strategy: They didn’t enact massive cuts. In fact, many invested more, doubling down on building the best tech stack and developing extremely efficient processes.

There are two outcomes of this double-down strategy:

    1. Leading financial institutions remain leaders in delivering best-in-class customer experience. After all, with revenue already down, no business wants to lose customers. And with FinTech disruptors constantly innovating, if you’re not keeping up, you’re falling behind.
    2. Leading financial institutions are able to build the scalable infrastructure they need to capture opportunities at speed. So, when the economy turns back around, they’ll be instantly ready to handle the increased volume—without having to add incremental costs by throwing staff at the problem.

Case study: Lake Michigan Credit Union maintains mortgage purchase volume through high-rate years

A great example of this is Lake Michigan Credit Union: As rates rose over the last two and a half years, this credit union’s mortgage volumes stayed far higher than most.

Why? Because when the refi boom occurred back in 2020-2021, Lake Michigan CU stayed the course on its overall strategy of balancing purchase and refi business. They didn’t over-index on refi, so they were able to stay consistent through the down economy.

Moreover, they continued to evolve and advance their tech stack. Bet on them to be at the front of the line to capture volume when it returns.

Learn more in our case study with Lake Michigan Credit Union >

Three pillars of a long-term strategy

How can financial institution leaders take a long view on positioning themselves for success when the economy turns around? Here are three key pillars of a long-term strategy:

1. Building an enterprise-wide data strategy

Financial institutions generally have three main pools of data: accounting, marketing, and IT. These data pools are typically not well integrated—and short-term strategies tend to only reinforce those data silos.

To effectively leverage data to interact and prospect, financial institutions need to develop an enterprise-wide data strategy that integrates all their data to unlock new insights and drive better outcomes. The benefits of consolidated data management will almost inevitably come in the form of better marketing ROI, improved customer interactions, and even increased profitability.

Today, we’re seeing more and more financial institutions hiring consultants to help them design this kind of overarching data strategy—delineating how data will be aggregated and integrated. A comprehensive data strategy will also set data governance policies to ensure data is cleaned and protected—and define how compliance teams handle data to ensure sensitive data is locked down properly.

2. Reducing friction points in CX (and EX)

Leading financial institutions are doubling down on tech investments, particularly around reducing friction points in their customer experiences (CX) and employee experiences (EX). Building a tech stack that works seamlessly together often means consolidation. Following an analysis, the financial institution will work to remove duplicative or point products and replace them with widely adopted, comprehensive platforms.

For customers, that means delivering omnichannel, predictive, and hyper-personalized experiences. For employees, it means connecting data silos and making it easy for them to get the information and workflows they need to be productive.

3. Enhancing internal training & onboarding

The short-term, transactional approach treats staff as fungible resources: When volume goes down, financial institutions lay off employees. Because when volume comes back, it seems easy to just hire additional people. This approach overlooks the reality that the value of employees largely depends on their experience.

Moreover, training is the only shortcut to experience. A smart, long-term strategy focuses on maximizing the value of a financial institution’s human resources. Building strong internal processes and training programs will ensure employees are both able to execute well within your environment and enable you to more efficiently and effectively onboard new staff if you need to add people to accommodate volume.

Double down on relationships & build long-term loyalty

Right now, we’re seeing a sharp divide in how financial institutions are reacting to slowing growth amid other persistent economic anxieties and uncertainties.

It feels like half of financial institution leaders are waking up every day scared—and letting those emotions guide an overall strategy toward a much shorter-term focus. Of course, it’s human nature to get concerned when revenues drop. The natural temptation is to slash costs and take a month-to-month or quarter-by-quarter view on survival. But it’s never smart to let emotions guide enterprise strategy.

The other half are doubling down—continuing to focus on improving CX and deepening loyalty. They’re building scalable business models that will let them pounce on opportunities, without the chaos and costs of having to scramble to add people and build ad hoc processes when the moment of opportunity hits.

Total Expert General Manager of Banking James White says, “It isn’t about cutting costs. It’s about giving your organization the ability to generate more revenue for every dollar spent.”

Cutting back and focusing on survival is a risky proposition. By doubling down on what you need to win loyalty today and capture volume in the future, your financial institution will be able to differentiate from transaction-focused financial institutions—and win the long game by earning customers for life.

Building deeper customer relationships starts by truly understanding your customers’ financial needs and goals. Learn how Total Expert Customer Intelligence can give you the insights you need to engage your customers in more meaningful conversations.

Explore Customer Intelligence
Resources

Related posts

AI

[Lykken on Lending podcast] Supercharging Mortgage Lending with AI

mins read
Read more

The mortgage industry is in the midst of a historic transformation—and artificial intelligence is leading the way. Our Founder & CEO, Joe Welu, joined David Lykken for an episode of the Lykken on Lending podcast to discuss how Total Expert’s AI solutions will reshape the customer journey for lenders.

From incubating leads and mining databases to nurturing post-close relationships, Joe shares how voice AI is giving loan officers “superpowers” that help scale productivity, improve retention, and focus on delivering the high-value advice consumers need most. With compliance guardrails built in and multiple AI agents on the horizon, this episode offers an inside look at the future of mortgage lending and why early adopters of AI will hold a major competitive edge.

Joe also explains why the human element remains central to homeownership, and how AI is designed not to replace loan officers, but to free them up for more meaningful conversations that strengthen customer trust and drive long-term loyalty.

Catch the conversation to hear how AI is revolutionizing lending and why Joe believes those who embrace it will be tomorrow’s market leaders.

Supercharging Mortgage Lending with AI
AI

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

mins read
Read more

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.

AI

Delivering AI Solutions that Drive Real Value in Financial Services

mins read
Read more

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.

See Total Expert
in action

Sign up
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
Create sustainable growth and increase loyalty with a customer engagement platform that’s purpose-built for financial institutions.
Schedule a demo