Customer Engagement

Third Quarter 2017: Reflection and Projection

5 mins read
October 2, 2017
By
Total Expert

The mortgage and real estate industries are reflecting and looking forward as we near the end of the third quarter. In our latest podcast, “Third Quarter is Almost Over,” Joe Welu discussed market conditions and attitudes across the country and revealed a generally positive outlook. Reports from top companies and producers so far this year include:

  • Bets they made last fall on recruiting, technology investments and other big initiatives for their businesses are paying off heading into the final quarter of the year.
  • Honest reviews of strengths and weaknesses and the search for leakage in their business and processes are ongoing; repairs and revisions are constant.
  • Course corrections to remain aligned with goals and business plans are taking place at regular intervals rather than waiting for year-end.

On the sales front, supply has certainly affected volume this year as low inventory has become the “new normal” in the housing market, and even consumers realize that finding the right home will take far longer than in the past. Other market conditions that emerged so far this year:

  • Median home sales in January, February and March outpaced June, July and August by a half million homes, according to the National Association of Realtors (NAR) Existing Home Sales Indices 2017.
  • 20% of Millennial homeowners are carrying average student loan debt loads of $41,200 compared to their average incomes of $38,800, according to the NAR/American Student Assistance Survey, April 2017
  • The number of homeowners who are “underwater” has decreased to 5.4% from a crisis-high of 26%; there are still 2.8 million U.S. homes in negative equity position, according to CoreLogic Quarterly Home Equity Analysis Q217.

In addition to low inventory, variations in the sales cycle must be considered in order to grow and succeed. On one hand, the sales cycle is longer and mortgage loan officers (MLOs) and Realtors must stay in front of their prospects and continue to add value over a longer period of time – from the initial home search to closing on a property. In other instances, we see a condensed sales cycle in which consumers decline to engage professionals until they’ve identified a property they want. Both scenarios require good systems in place to not only capture and convert prospects, but uncover the type and timeframe of a lead. Companies that are succeeding this year are using the SWOT matrix to evaluate what they’re doing now – and what they can improve upon:

The SWOT (Strenghts, Weaknesses, Opportunities and Threats) Model

  • Strengths: What are you doing well as a company, team leader or producer? How can you expand on this?
  • Weaknesses: Where’s the leakage in your processes and performance? Are your leads and databases organized and are you consistently in touch with relevant, compelling content? Where do you see waste of time or effort?
  • Opportunities: Are you maximizing all of the opportunities within your market, database of past clients and sphere of influence? Are you developing multiple channels of business and deploying your efforts via email, print, social and other media?
  • Threats: Who’s beating you – and why? What does your competition have or use that you don’t? Have you failed to adjust to changing market factors, consumer preferences and advances in industry technology?

There’s consensus that 2018 will present a similar business climate, and companies are budgeting with that expectation – which underscores the importance of evaluation and course correction today using methods like SWOT. Cost savings and waste elimination resulting from finding and fixing business leaks can create a positive impact of 10-20% instantly, but now is the time of year to look beyond inefficiencies and create a better foundation for increased growth.

Choose adaptation over stagnation

If you or your company have been slow to get on board with the latest technology and adjust to the new demands in the consumer experience, there’s still good news: The early adopters weathered a lot of the pain, and onboarding and adaptation gets easier all the time. However, don’t use that as an excuse for further delay.

Better results and increased success in the coming year depends on setting up your organization, planning for and capitalizing on new initiatives, and committing to change. Failure to adapt will be evident in production and profit numbers, which could result in being swallowed by bigger, more innovative companies – or driven out of business altogether.

Next year holds tremendous opportunity as the biggest segment of home buyers to hit the market in U.S. history continues to mature, increase their income and require professional mortgage and real estate guidance.

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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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