Customer Engagement

Avoiding Pitfalls When Advertising on Third-Party Websites and Buying Leads

5 mins read
October 19, 2017
By
Total Expert

Advertising on third-party websites and buying leads are both common practices for top producers, but it seems the lines of right and wrong have started to blur. As Mitch Kider, Managing Partner at Weiner, Brodsky, Kider PC says, don’t get lazy about it – do it right and stay compliant.  

The Skinny on Third-Party Website Advertising

Third-party websites and portals are trying to meet the industry’s evolving needs, including: buying and selling leads, marketing, co-marketing, single- and multi-property websites, and CRM systems. The biggest challenge with these types of sites is use of the site in combination with another settlement service provider, especially one who is a referral source. Kider says there is nothing wrong with co-marketing, as long as you do it right.  

So, how can loan officers (LOs) co-market on third-party websites and portals?  

  • The challenge with third-party websites is if they aren’t open to everyone, someone is acting as a gatekeeper. For example, on certain such websites, the only way a Realtor can gain access to the particular site is via invitation from an LO. In this scenario, the LO has given the Realtor something of value and if this is pursuant to an agreement that the Realtor will refer business back to the LO, you now have a RESPA Section 8 violation. In these types of situations, the LO is likely going to invite Realtors who have partnered with them or done something for them. Kider believes these third-party sites should open their doors and allow access to anyone to eliminate the risk of these types of violations. Until that happens, lenders should approach these types of websites and relationships with caution.
  • The Consumer Financial Protection Bureau (CFPB) is concerned with advertising that the consumer will potentially view as a referral. For example, if a lender advertises on a Realtor website, the advertisement must clearly be marked as an advertisement. Paid advertisements can’t say “preferred lender” or anything similar. If an advertisement were to say “Use my preferred lender,” now the lender is paying for the endorsement, not just the advertisement.
  • The best way to determine fair market value for advertising is a combination of impressions and pro-rata share. Ask yourself: How many people are going to see this ad? In addition, if you’re co-marketing, the Realtor and LO should pay for their pro-rata share of the advertisement and cannot defray the other party’s costs. Both parties should pay their reasonable fair market share of the ad based on impressions, size of the ad and their pro-rata share of the total ad costs, among other potential factors.

Lead Buying vs. Referrals

It is important to first define lead buying: When you purchase a lead, it is not a referral, you are buying basic information about a lead who may be interested in purchasing a product you are selling. Purchasing leads is fine.  

However, and this is where the line is getting blurred a bit – you cannot pay for a lead if the party that is selling you the lead also tells the lead that you are a great lender and they should use your services. Then youare not purchasing a lead, you are purchasing a referral.  

To avoid this blurred line, lenders and LOs should not mix lead-sale agreements with marketing, desk rentals or anything else along these lines. Keep the line clear and easy to explain to a regulator.  

Purchasing leads has been very effective and will continue to be very effective, but do not get lazy about it – if you buy a lead, it is the LO’s job to go out and win the business themselves, not to pay someone to recommend them.

The Lesson: Do Not Get Lazy

Advertising on third-party websites and lead buying are perfectly fine in the mortgage industry. The key is to not get lazy about it – do it right and do not let the lines get blurred.

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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

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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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