Automate the Boring Parts of Your Real Estate Note Business — With AI | Dominic McFadin
Summary
This episode of the Real Estate Note Show features Dave Putz, Nathan Turner, and guest Dominic discussing the integration of AI and automation in the note investing business. They cover how AI can streamline due diligence, improve note creation, enhance portfolio analysis, and assist with communication. Dominic shares his family's long history in the note business and his journey into leveraging AI, emphasizing that it can simplify complex tasks for both new and experienced investors, making processes more efficient and insightful. The conversation also touches on the importance of context and proper prompting when using AI tools.
Key Insights
AI can significantly simplify and enhance the due diligence process for note investors by structuring incoming deal information.
AI tools can process emails and documents related to potential notes, automatically organizing information into a consistent format like bullet points or spreadsheets. This allows investors to quickly identify missing data and make informed decisions about which deals to pursue, saving considerable manual effort and time.
AI excels at data analysis and visualization, enabling note investors to gain deeper insights into their portfolios.
By feeding loan statements, payment histories, and communication logs into AI, investors can uncover correlations and patterns. This includes identifying high-default counties, understanding borrower payment behaviors (like consistent late payments), and even suggesting proactive strategies like payment modifications based on borrower paydays. AI can also create visual dashboards to represent this data, making it easier to understand portfolio performance.
For note creators, AI can assist in understanding fundamental concepts like note valuation and amortization, and even review collateral files.
AI can demystify why notes trade at a discount, generate amortization schedules, and provide general feedback on collateral files to ensure they are sellable. While legal advice still requires an attorney, AI can provide a strong foundational understanding and help structure notes for better marketability and value.
Sections
Introduction and Personal Updates
Hosts Dave Putz and Nathan Turner welcome listeners to the Real Estate Note Show.
Dave Putz and Nathan Turner introduce themselves as hosts and express that things are currently 'crazy' but they are back to sharing insights.
Nathan Turner shares his recent family trip to Korea and the benefits of note investing for securing such travel.
Nathan describes a fantastic two-week family trip to Korea, highlighting how passive income from note investments allows for such travel without constant business interruptions. He emphasizes his 'lazy investor' approach, preferring consistent paper flow over chasing deals.
Dave discusses recent deals going 'sideways' and highlights the need for creative finance professionals and new note investors to connect with them.
Dave mentions experiencing some failed deal closings and emphasizes the importance of outreach from both seasoned creative finance professionals and new note investors. He stresses their long-standing expertise in creating and investing in notes and their willingness to answer questions from all levels.
The Value of Collaboration and Long-Term Thinking in Creative Finance
Creative finance investors are encouraged to engage with note investors for a broader perspective on deal structuring and long-term value.
Nathan urges creative finance practitioners to invite note investors into their conversations. He believes that by approaching deals from different perspectives, they can discover strategies that yield benefits for years to come, promoting a more long-term, big-picture strategy.
Properly originating a note, including necessary security measures, is crucial to avoid costly long-term issues.
The hosts highlight that upfront costs, such as $1,200 for proper origination, are essential. Skipping these steps and simply connecting a borrower to a property can lead to much larger financial liabilities and headaches down the line, especially when dealing with non-performing notes.
Future episodes will cover potential exit strategies for notes, and current discussions touch on automation and AI.
A future show will explore different exit strategies for note investments. The hosts also mention a discussion from a recent event, DME, about VA (Virtual Assistants) vs. AI (Artificial Intelligence) and the importance of starting with simple automation steps rather than getting overwhelmed.
Introducing Dominic and His Background in Note Investing and Automation
Dominic joins the show, bringing extensive family experience in note investing and a strong background in automation and AI.
Dominic is introduced as someone who does AI and automation, possibly more than the hosts themselves. His family has a long history in the note business, dating back to post-WWII with his grandfather, who transitioned from poker winnings to real estate-backed loans.
Dominic's family business evolved through generations, from apartment buildings and home building to specializing in Texas seller finance debt.
Dominic's grandfather started in apartment buildings, his father was a home builder in San Antonio, and his uncle worked in the buy-here-pay-here car loan business. The business eventually specialized in purchasing Texas seller finance debt. Currently, Dominic and his sister run Note Buyers of America and recently acquired a servicing company.
Dominic's early exposure to technology and problem-solving fueled his interest in automation and efficiency.
From a young age, Dominic was technically inclined, disassembling computers and learning to build them. His father's work as a home builder instilled a drive to understand and figure things out. This led him to explore automation in banking and later in private mortgage companies, seeing how it reduced friction and improved processes.
Dominic found significant opportunities for automation in his family's long-standing business, which was largely paper-based.
Upon joining his family's business, Dominic discovered they were still using paper for quoting and had minimal online presence (Gmail for emails). This presented a vast opportunity to implement and test automation solutions, leading him to learn what works and what doesn't, saving significant time and money.
Leveraging AI and Automation for Note Investors: Initial Steps
Due diligence is the most critical step in note investing, and AI can significantly expedite and improve this process.
The accuracy of due diligence is paramount, as errors can lead to significant financial losses. AI can help by structuring the data received from various sources, ensuring all necessary information is presented consistently, which is crucial for making sound investment decisions.
AI can automate the initial processing of incoming loan tapes and deal information.
Investors often receive deal information in various formats via email. AI can be instructed to extract specific data points from these emails and present them in a standardized format, such as bullet points or an Excel sheet. This significantly speeds up the initial review process and helps identify missing information quickly.
AI can help investors identify missing information in deal packages with greater efficiency.
A common challenge is that deal packages lack consistent information. By using AI, investors can automate the process of identifying missing elements like next due dates or servicing data, allowing them to send targeted requests back to the seller or broker.
Advanced AI Applications for Note Portfolio Management
AI excels at analyzing large datasets to uncover correlations and insights within a note portfolio.
AI, particularly 'agentic AI', thrives on data. By feeding it portfolio data (like lender statements and payment histories), AI can identify patterns, such as correlations between loan performance and geographical factors, or common borrower late payment cycles. This allows for more informed portfolio management and strategic decisions.
AI can visualize complex portfolio data into easy-to-understand dashboards.
Investors can use AI to transform unstructured data from spreadsheets and PDFs into structured visual representations, such as dashboards. This makes it easier to track portfolio performance, identify trends, and communicate insights, even without complex technical skills.
AI should be used to complement human efforts, not replace them entirely, ensuring safety and accuracy.
The goal of AI in note investing is to augment existing processes, making them more efficient and insightful. This approach ensures that human oversight remains, maintaining accuracy and safety while leveraging AI's analytical power. Dashboards created by AI can be updated by simply re-uploading new data, simplifying the tracking process.
AI can proactively flag loans needing attention, such as those significantly past due or showing consistent late payments.
AI can automate notifications for loans that are 90 days delinquent, require demand letters, or exhibit patterns of late payments. It can also highlight well-performing loans, suggesting opportunities for partials or other strategies. This turns data analysis from a reactive task into a proactive management tool.
AI for Note Creators and Understanding Note Valuation
Note creators can use AI to understand the financial aspects of notes and improve their deal structuring.
AI can help note creators generate amortization schedules, set realistic pricing expectations, and understand why notes are sold at a discount. This knowledge empowers them to create more valuable and sellable paper from the outset.
AI can educate note sellers about market dynamics, leading to more productive conversations with note buyers.
Potential note sellers can use AI tools like ChatGPT to learn why notes trade at a discount. This educates them on market realities, preventing unrealistic expectations and leading to smoother negotiations with buyers who are already familiar with these concepts.
For legal advice regarding note creation, consulting an attorney remains essential, even with AI assistance.
While AI can assist with financial calculations and market understanding, it is not a substitute for legal counsel. Complex legal matters related to note creation and collateral should always be reviewed by a qualified attorney to ensure compliance and mitigate risk.
Strategic Application of AI in Note Investing: Proactive vs. Reactive Use
Effective AI use requires providing context about your business, transforming it from a reactive tool into a proactive assistant.
Simply asking AI questions reactively yields limited results. The key is to provide AI with context about your business, company policies, and operational data. This allows AI to act as an informed assistant, offering relevant insights and solutions, much like a human employee would require context to perform their job effectively.
AI can analyze existing business processes and suggest areas for improvement or automation.
By feeding AI details about daily tasks, workflows, and company documents, investors can receive suggestions on what can be improved or automated. This prompts AI to identify 'low-hanging fruit' opportunities that can yield significant benefits with minimal initial investment.
Using AI requires an exploratory mindset, treating it as a tool for gaining new knowledge and insights.
The core of using AI effectively involves continuous exploration. Investors should treat it as a mission to discover new information or perspectives. Simple prompts like listing daily activities and asking how AI can assist transform the interaction into a discovery process.
Beware of expensive AI 'expert' courses; much of the information is publicly available and can be learned through experimentation.
The hosts caution against overpriced masterminds and courses claiming to be AI experts. They suggest that the necessary knowledge can often be acquired through self-study and practical application, emphasizing that the AI itself can even generate course-like content if prompted correctly.
Mastering AI Prompts and Choosing the Right Tools
AI can be prompted to interview the user to clarify uncertain needs, leading to more precise solutions.
A powerful prompting technique involves asking the AI to interview the user until it is highly confident it understands the user's true needs, rather than just their stated desires. This ensures the AI's output is aligned with the user's actual goals and addresses underlying issues.
Simplifying technical explanations to a fifth-grade level can improve comprehension and AI interaction.
It is advised to ask AI to explain concepts in simple terms (e.g., 'explain like I'm five') to ensure better understanding. This approach acknowledges that even high-level professionals often benefit from clear, fundamental explanations, making complex AI outputs more accessible.
AI can automate repetitive tasks, such as following up on deals, which is a common time-consuming activity for note investors.
A significant pain point for note investors is managing follow-ups. AI systems can be designed to track tasks, schedule reminders, and even draft follow-up communications, ensuring that no deal or contact is missed, thereby reducing anxiety and improving efficiency.
Agentic AI with file system access and decision-making capabilities is more powerful than simple chatbots for task automation.
While chatbots like ChatGPT are useful, true AI assistants (agentic AI) that can connect to tools, access files, and make decisions are more effective for complex automation. These require proper integration, which might involve APIs or specific local applications, not just web-based interfaces.
Gemini is integrated with Google services, while Claude is a desktop application, each offering different strengths.
Gemini offers seamless integration with the Google ecosystem (Gmail, Calendar), making it reactive within those apps. Claude, as a desktop application, can run proactively in the background and interact more directly from the user's workspace, acting more like a constant digital assistant. The choice often depends on user workflow and preferred ecosystem.
AI models possess different 'personalities' and excel at different tasks, allowing for strategic tool selection.
Different AI models have distinct strengths. Claude is favored for creative tasks and brainstorming, while OpenAI (like Codex) is better for scientific and structured implementation. Gemini integrates well with Google services. Users should select models based on the specific task, whether it's creative ideation, technical execution, or ecosystem integration.
The Current State and Future of AI in Note Investing
Many people are not using AI properly, leading to frustration and a belief that it 'doesn't work'.
A significant portion of the population has not even used AI tools like ChatGPT or Claude, let alone used them effectively. Frustration often stems from incorrect prompting and a lack of understanding of AI's capabilities and limitations, leading to the misconception that AI is ineffective.
Learning to 'talk' to AI requires a different skill set than traditional search engines, involving context and intent.
Unlike simple search queries for factual information (e.g., population of Seoul), interacting with AI involves providing context, history, and desired outcomes. This shift from finding information to co-creating solutions requires a learning curve, but it is achievable for everyone.
Getting started with AI involves simple experimentation and documenting daily activities for AI analysis.
The best way to overcome the learning curve is by starting small. Documenting daily tasks and asking AI how it can assist simplifies the process. AI can then analyze these activities and suggest improvements or automation opportunities, making the AI interaction more relevant and beneficial.
Collaborating with peers and understanding real-world use cases significantly accelerates AI adoption and effectiveness.
Engaging with communities and discussing AI usage with others at similar levels provides valuable insights and practical examples. Sharing experiences, like building a website with AI or refining email strategies, helps individuals overcome initial hurdles and discover new applications, fostering a more rapid and effective adoption.
AI's Impact on the Note Servicing and Collections Landscape
AI is becoming incredibly powerful in mortgage note servicing and collections, analyzing vast datasets for patterns.
In the servicing sector, AI can process years of data to identify correlations and patterns that improve collections. This includes analyzing call data, promises to pay, and borrower payment histories to optimize outreach timing and methods.
Voice AI is advancing rapidly, though its application in sales is limited due to human preference for personal interaction.
While voice AI is improving, its use in direct sales (like talking to a note seller) is not yet viable due to a preference for human interaction. However, in servicing and collections, it can improve efficiency by identifying optimal contact times and understanding borrower challenges.
AI's non-judgmental nature makes it effective for sensitive interactions like loan collections and personal health inquiries.
The non-judgmental aspect of AI platforms like ChatGPT makes borrowers more forthcoming about their financial difficulties. This anonymity can foster honesty, improving the chances of successful collection or problem resolution, similar to how people use AI for personal health questions.
Investors can use AI to review their bid calculators and identify potential missed factors or strategies.
AI can act as a consultant, reviewing an investor's bid calculator for properties or notes. It can suggest potential factors missed, identify risks based on data (e.g., higher foreclosure likelihood in certain counties), and propose adjustments to purchase prices or strategies to increase profitability and reduce risk.
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