Customer Engagement

Tight Inventory: Combat Cash with Customer Care

5 mins read
August 21, 2017
By
Total Expert

It stands to reason that fewer home sales would mean fewer loan originations, but low inventory is hitting mortgage companies and MLOs even harder in the pocketbook: The number of cash sales have increased in today’s competitive buying environment to almost double the norm. According to Freddie Mac’s Monthly Outlook for August, cash sales were nearly 18 percent in June compared to its average of 10 percent.  

Freddie Mac’s Chief Economist, Sean Becketti puts the numbers into an ominous, tangible perspective, saying, “If cash sales remain around 20 percent, that would translate to $172 billion less in mortgage originations than would occur if the cash share returned to its historical norm.” It’s tempting to take a pessimistic view and fear you’ll have to work harder to simply maintain market share, but keep the following in mind:  

Don’t default to refis. Data from Ellie Mae’s July Origination Insight Report shows refi business up three points to 35 percent of all closed loans after dropping two consecutive months, likely due to the lowest interest rates since January. Even though more consumers are raising their hands to refinance recently, the increase in share is based on volume overall. Refis consisted of 48 percent  of all originations in 2016, but Freddie Mac projects that will fall to 33% for this year and 25 percent  in 2018.   

Strength in purchase numbers. The August 2017 forecast from Freddie Mac’s Economic Housing & Research Group shows 6.01 million new and existing homes were sold in 2016. The group projects there will be 6.2 million in 2017 and 6.3 million in 2018. In spite of inventory challenges, home sales will happen.

 Helping Homebuyers Combat “Cash is King” Mentality

It’s hard to deny the premise that “cash is king,” when it comes to a multiple offer situation in a competitive market. And trying to convince people who have the ability to make cash purchases to get financing in this still favorable interest rate climate may be difficult or completely unrealistic. What MLOs can do is ramp up their efforts and help the more typical potential home buyers combat cash:

Pre-approval: Realtors and MLOs understand the importance of pre-approval, but consumers don’t. Many still don’t know the difference between getting pre-qualified and pre-approved. Most important is to educate the public that getting pre-approved for a mortgage is helpful even if someone doesn’t think they’re ready to buy. Marketing and conversations need to convey the value of learning what it will take for someone to get pre-approved and that there’s no obligation.  

Pre-purchase planning: Potential buyers who know they could face cash competition are more likely to face challenges – like paying an extra month’s rent to accept a quick closing date –  
head-on. Work with your Realtor partners to prepare and position people to be able to act quickly.  

Pitch:  Encourage potential buyers to write a letter to homeowners to be included with any offer they make to purchase. A brief but personable letter (with a live signature) that introduces the buyers, describes the efforts they’ve made to prepare to purchase and what homeownership means to them is a great touch.  

Implement an Education-Based Marketing Strategy  

There’s a lot MLOs can do to help homebuyers compete in today’s market, but first, consumers have to get in the game. Do you have piles of leads from multiple sources littering your desk, computer or brain? Those leads aren’t necessarily cold or dead, they’re probably just discouraged.  

Headlines like, “Inventory Shrinkage Jacked Up July’s Home Prices” sound even scarier to the public when they make their way from trade magazines to local and national news. Offer another perspective to consumers (who may have done a little casual online home browsing) through consistent, education-based marketing that addresses their fears and provides useful information that can help them move forward to becoming a homeowner today or sometime in the future.  

Despite today’s challenges, homes are going to sell. Be part of helping people achieve something they think is difficult or out of reach by educating them and showing what’s possible.  

Listen to our podcast for more on pursuing purchase business, Expert Strategies: Pivot to Purchase.

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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.

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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