Lending

Attract New Customers or Members but Keep the Old with Proven Strategies from Data and Behavioral Science Experts

5 mins read
September 5, 2019
By
Total Expert

Banking used to be a primarily relationship-based model. Consumers would stay with the same bank for the duration of their lives and may have even worked with the same branch that their parents used. Why? Because it was familiar to them, it met their needs (both convenience and otherwise) and they had a trusted relationship with the bank.

Today, financial brands are walking a fine line to attract new customers or members – all while remaining true to their brand. Marketing to up-and-coming generations adds an additional dimension to this challenge given certain personas may not be fully fleshed out yet.

Hear from Total Expert Product Marketing Manager Matt Noyes and Data Propria President Matt Oczkowski as they discuss the best ways for you to attract new audiences and showcase what your financial brand has to offer.

Matt Noyes: So, Matt, when we were at the Financial Brand Forum earlier in the year, we spoke with a lot of marketers, branch managers, all sorts of folks from various financial services orgs. A lot of them shared their goals for the business and the challenges they were trying to solve.

Matt Noyes: One example that came to my mind was a conversation I had with a couple of marketers who made up their bank’s entire marketing team, a regional bank here in the Midwest. They talked to me about how branch traffic was declining and that their customer base in this mostly rural community was aging and that they knew that they needed to attract some new customers, because they knew if they didn’t start attracting new customers from outside of their general branch traffic that they weren’t going to have customers for that much longer.

Matt Noyes: The problem for them was that they just didn’t know where to start. They didn’t know these potential new customers because they didn’t see them in the branch. They didn’t know how to get in front of them because they didn’t know where they might be coming from or where they “spent their time”, digitally or otherwise, and they didn’t know what they wanted from the bank.

Matt Noyes: They didn’t know where customers were going for their current needs and why they weren’t coming into the branch. As we think about this, to really help our listeners better build their audience and address their customer’s needs, I think it’s worthwhile for us to run through a few of these bigger challenges facing financial services orgs because these challenges pose a significant barrier to taking this meaningful action we’re talking about.

Matt Noyes: Let’s maybe talk through what you and your team at Data Propria are seeing out there regarding the challenges facing these financial brands. Let’s just talk through a couple of these: aging demographics, catering to those changing demographics as well, whether that’s growing younger in the customer base or otherwise. Let’s talk through a few of these and get your thoughts on what you guys are seeing.

Matt Oczkowski: I mentioned the term self-fulfilling prophecy before, and I think that’s something that’s very prudent in understanding changing and aging demographics. If you’re only using knowledgeinside of your institution and only relying on data of what your current customers look like, you’re going to be building models and forecasts on audiences about where you are today in that aging demographic but not necessarily where you’re going tomorrow, and I think to focus on the future of the financial customer.

Matt Oczkowski: There are some ways you can do this in a very lean, cost-effective way that doesn’t necessarily have to be a massive market research program or something like that. It’s the idea of getting outside of your comfort zone and starting to understand different data resources, but also authenticity. Where authenticity meets new data is really the focus when you’re talking about aging demographics. I see far too many financial customers say, oh, young people are using things like Venmo and the Cash App, so I have to mimic that approach.

Matt Oczkowski: No, don’t do that, because that’s not authentic to who you are as a brand and what you’re trying to do. Be real to your customer. Certainly, embrace new technologies, but yes, what are the underlying elements in why people like those organizations? Is it convenience? Is it user experience? Is it functionality? Is it customer service? Whatever it may be, learn from those elements and use those authentically to who you are and what you do, but then again you also have to understand who that audience is.

Matt Oczkowski: I think there’s far too much of an inclination to read a publication on Adweek and say, oh, young people are using Snapchat, so I’ve got to be on Snapchat. Well maybe, but how do you know that? Is Snapchat the right vehicle, is that the right media preference for the customer that you’re trying to go to? Could you be doing better just with customer segments between 35 and 50 rather than trying to go down to 18 to 25? Is that efficient? Is that effective? How do you test that? Being able to find other data resources outside your organization, maybe leveraging some commercial data sets that exist in the marketplace.

Matt Oczkowski: But maybe conducting some market research to your existing customers, asking them what they like and don’t like about your brand, going out and doing some small testing. There’s a lot of online survey tools today within tools like Google and Facebook that you could use that are still very helpful directionally that might not be the end all be all of a large scale quantitative research experiment, but that could help you learn about the customer base and what they want. Once you start to build that information it’s going to help point you in the right direction, not only of persona and audience development but also productization and how do you point your organization in the right direction.

Listen to the full webinar to drive relationships and revenue in your organization.

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