The COVID-19 Foreclosure Prevention & Tax Revenue Protection Model: A Primer for Local Governments
By: Kevin Ra, Chairman and Founder at Parcel Revenue Corporation
In recent weeks, we at Parcel Revenue Corporation have been busy designing, patenting, and refining the COVID-19 Foreclosure Prevention & Income Tax Revenue Model, or COV-MOD®. We are humbled by the interest that so many local government entities have shown. From day one, we promised to create free content explaining how our system works.
The purpose of this post is to explain Cov-Mod® in greater detail. If you have not read my previous post, “Virtual Land Bank Platform 101: A Five Minute Crash Course”, you will want to read that first.
Now that we have the formalities nixed, let’s dive right into the lesson.
COV-MOD® is a Hyper Focused Real Estate Model designed on the Virtual Land Bank Platform, or VLBP.
VLBP analyzes thousands of scenarios, saving time and money.
In virtual land banking, you may imagine perfect real estate scenarios from the “sell trigger” to the moment a property is transferred to the next owner.
However, the scenario often ends up being far less than perfect.
That time frame can range anywhere from a day or two for a house-flipper to 100 years for an investment property. This could be due to the property having certain mineral rights or land that can be used to harvest timber.
The VLBP analyzes thousands of scenarios based on data entered from traditional real estate transactions. Artificial Intelligence (A.I.) is used to find patterns in the data. Those patterns are then calculated into probabilities which give us a numerical and scientific way to determine the best method to set up a transaction in the beginning to ensure success at the end.
That best method is known as a Hyper Focused Real Estate Model.
The Hyper Focused Real Estate Model can be applied to a plethora of purposes in the real world. Perhaps its consulting a hedge fund to maximize its ROI from real estate investments; or consulting a bank on which homeowners they should target preemptively to deploy programs designed to help struggling homeowners modify their loans.
In this case, our model will predict steep slides at the top of the post-COVID real estate market that can cause a perpetual slide in all markets.
A proactive model for pandemic times
COV-MOD® was created at a tumultuous time in all economic markets – the midst of the COVID-19 pandemic. Fortunately, the VLBP was built to be deployed into the poorest of communities. In my hometown of Cleveland, OH, there is always a pandemic of some sort. Poverty has been an ongoing pandemic, with no sustainable cure.
If there was one thing I learned from the 2008 housing crisis, it was that the first thing you have to find is a constant. This should be done before you deploy any capital while seeking a return on investment.
In Cov-Mod®, the constant is that the communities with the best public and private schools (Green Markets) are going to have the most stable real estate markets. This constant is fueled by the inevitable desire of high-income families with young, school-aged children to be close to great schools and their willingness to pay to accomplish that goal. As any good real estate agent will tell you, this phenomena has stood the test of time.
Now that COV-MOD® has a constant to use as a proverbial pillar, we can build a model on the other known factors that also find their footing on that same constant:
Green Markets historically are composed of a mix of three types of home-owning families:
- Families that are just starting out who moved to connect their children to the education and safe neighborhoods these markets offer
- Families with heads of households that are between the ages of 40 and 55 that are heavily leveraged with credit
- Older families who have lived in the community for decades and are within 3 to 7 years of voluntarily selling their home and who owe far less on their homes than the fair market value – even if the value declines due to an economic downturn;
Families with young children who can afford to live in Green Markets will do so regardless of the state of the economy.
After an economic downturn, it is inevitable that financially injured homeowners will eventually see homebuyers that were not injured by that downturn living in their homes. This will happen either because those homeowners sold their homes or because they lost them to foreclosure.
What does this all mean?
In Hyper Focused Real Estate Models, we are looking at every detail of a real estate transaction at the granular level:
Why is the seller selling? → Why is the buyer buying? → How does the buyer establish the correct amount of money to offer the seller? → How does the seller determine if the buyer’s offer is fair? → What is the buyer’s intended use for the property? → Who will the buyer eventually sell it to? → Repeat.
Why a repeat at the end?
When it comes to homes near great schools, no matter the circumstance, buyers are still constant. Our model can now analyze the best use for a property, as well as other key metrics, for the next decade. In this case, 5 to 10 years from now is the time frame that encompasses when most families buy and resell their homes.
In COV-MOD®, the Green Markets’ assumptions are that these communities are suburban, “bedroom” communities with school systems ranked in the higher percentiles within their respective states. Extracting the most solid data from all the information cited above in this post yielded the following hypothetical, best-use model:
The seller is selling because they are:
- Older and have decided to sell their home and move
- They are facing financial problems
The buyer is buying to be near great schools.
Using 2008 to 2012 home prices as our guide, we built in the assumption that, at worse, prices will fall back to their 2008 levels and buyers and sellers will exchange properties at 2008 values
The buyer will live in the property → The buyer will eventually sell it to a homebuyer who also sees the value of the local schools.
COV-MOD® is a 24/7/365 monitor of data that mitigates the risk of a housing crisis.
COV-MOD® monitors the real estate within your community 24/7/365 by monitoring public records:
- Loan modifications
- Other significant filings
Digital profiles of homeowners are built by analyzing the collected data. This information is used to predict, based on life events, if and when the beginning of the real estate transaction cycle will most likely lead to a foreclosure.
Head foreclosures off at the pass 1 to 5 years in advance.
Typically 1 to 5 years before a foreclosure is filed, social service campaigns are triggered by automation. These campaigns are designed to both educate and assist homeowners by matching them to existing assistance programs
This trigger can automatically set certain tasks in motion, such as mailing the homeowner a series of letters and postcards. Another example could be assigning a home visit from a local official or task force, via an email or text message.
This scenario highlights the unlimited applications available to local governments via Virtual Land Banking. Unlike traditional land banks that only cover a certain geographic area, a virtual land bank can link distressed properties by millions of connected data points regardless of where they are located.
Real world example
We can find all homeowners with a mortgage to a local bank who are over 65 and have recently been sued for unpaid medical bills, and already received a loan modification within the last five years. This indicates a sign that they have previously had trouble making their mortgage payments at a time in life where their income is not likely to increase.
Assuming there was an assistance program at a local bank that could help homeowners, we can now launch a social services campaign to offer assistance to the homeowners who fall within that subset.
You can stop a crisis before it starts.
Local government entities who want to do their part to effectively provide desperately needed assistance to their constituents, may obtain a free intellectual property license and access to all free content required to implement COV-MOV® at http://www.preventforeclosures.org.