Lending

From Lone Wolves to a Unified Pack: Why Lenders Need a Shared Platform

5 mins read
June 30, 2025
By
Mike Waterston

The mortgage industry has always prized the hustle. The most successful loan officers (LOs) are those with the motivation and self-direction to relentlessly chase leads, manage relationships, and close deals—and the ingenuity to develop their own best practices. Those qualities remain essential. But in today’s market, mortgage lenders can’t afford to treat their LOs as lone-wolf salespeople. That conventional model doesn’t just limit growth—it actively undermines it.

Fragmentation is a real problem for lenders, and the lone wolf model isn’t making it any easier. Individual excellence isn’t enough when data is disconnected, messaging is inconsistent, and decisions get made in silos. Meanwhile, LOs can (understandably) over-rotate toward short-term wins, while the bigger opportunities—building long-term relationships and sustainable growth—get lost in the noise.

What lenders need now is alignment, visibility, and unification. They need a way to turn one-time borrowers into lifelong customers. And that starts by getting everyone on the same page—and the same platform.

Why lone-wolf lending fails

When LOs are left to figure things out on their own, the result is predictable: they optimize for what they can control. They chase leads. They close loans. And they do it all with whatever tools and processes they’re most comfortable with.

This approach is serviceable for the individual LO. But when you scale that to dozens or hundreds of LOs—each working in isolation—issues quickly emerge:

  • No shared customer insight. Everyone’s working from their own spreadsheets, contact lists, or partial CRM views.
  • No coordinated engagement. Borrowers get wildly different experiences depending on which LO they’re working with.
  • No long-term strategy. Because LOs are buried in day-to-day deals, there’s no time—or incentive—to nurture relationships that might pay off months or years down the road.

The result? Short-term gains that cause long-term stagnation. Without a coordinated strategy, you end up with isolated efforts that fail to make a lasting impact. And the moment the market shifts, lenders are left scrambling. Those once-shiny wins quickly become embarrassing monuments to short-sighted tactics.

A seamless platform provides limitless visibility

So, what’s the answer? The most important change is giving your team a common foundation to work from—and that comes down to choosing the right technology. Centralizing customer data and engagement on a single platform can change how your business functions at all levels:

It unifies the customer experience. Everyone’s drawing from the same source of truth, so your borrowers get a consistent message and a more personal, relevant journey—no matter which LO they’re working with.

  • It gives LOs insight they can actually use. A centralized view reveals not just who’s ready to do business today, but who’s showing long-term intent signals—credit checks, property listings, life events—and who’s worth nurturing over time.
  • It boosts efficiency and productivity. Automating outreach, follow-up, and lead prioritization frees LOs to focus on what they do best: building trust, closing deals, and deepening relationships.
  • It creates a real growth engine. With shared data and a scalable engagement strategy, you can stop scrambling and start building a system that can grow predictably and sustainably, even when the market gets choppy.

LO adoption: where most tech implementations go wrong

Of course, tech on its own won’t fix anything. If LOs don’t use the platform, you’re back to square one.  

This is a big hurdle in the lending world, where there’s very real inertia to change. Most LOs aren’t eager to change what’s already working for them. If a new tool or platform just feels like it will add extra work, they’ll ignore it—leaving your new solution to collect dust and your investment or time and money largely wasted.

This is why solving the adoption problem needs to be part of your strategy from the start. And while it’s a serious issue, there are three key steps to mitigate it:

  1. Keep it simple. Give your LOs tools and dashboards that surface what matters most—who to call, when to follow up, what’s driving intent—without forcing them to dig or overwhelming them with features and functions they won’t ever use.
  1. Show, don’t tell. Help them connect the dots between using the platform and hitting their numbers. If it helps them close faster, follow up smarter, or get more repeat business, they’ll at least be willing to try. As the saying goes: “You can lead a horse to water…”
  1. Support them like it matters. Training should be hands-on and tailored, not a one-time webinar. This is just as much your vendor’s responsibility as it is yours. Make sure you vet any vendor’s ability to commit to successful implementation.

The extent to which you follow these three steps will go a long way in determining whether you see ROI on your tech investment.  

You can’t scale in infinite directions

Every lending organization has LOs who go above and beyond; LOs who lag behind, and LOs who simply meet expectations. And lone wolves permeate all three groups; following their own roadmap, chasing any opportunity they find, and hindering the organization’s larger growth strategy. That’s why organizations structured this way find it impossible to scale.  

Now, imagine if you could have tech that elevates every LO to the same high-performing level. By aligning your entire sales organization on a single platform that helps them work more efficiently, your good LOs will continue to produce, but now your struggling and middle-of-the-road LOs can level up—allowing leaders and platform administrators to spend less time reigning in lone wolves and more time supporting the pack.  

Wolves hunt better in packs  

LOs will always be at the front line of your lending operation. But treating them like individual agents instead of coordinated players in a unified strategy is holding your business back.

By moving to a shared platform and getting serious about adoption, you set your organization up for something far more valuable than short-term wins. You build a system that gets smarter over time and nurtures every relationship—not just the ones that close quickly. You also strengthen the resilience of your business, setting it up for growth no matter how the market moves or how your organization evolves.

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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.

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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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