Background on Discriminatory Restrictive Covenants
There are historical covenants in land records that in the past prohibited the sale or lease of property based on race, ethnicity, or religion. While not legally enforceable today, these covenants are remnants of a period in American history that have caused significant pain and harm for many Americans. In 1917, when the U.S. Supreme Court deemed city segregation ordinances illegal, discriminatory covenants began appearing in property records. Even though the Fair Housing Act made these covenants explicitly illegal in 1968, title professionals continue to discover discriminatory language when conducting title searches – a required step before a homebuyer can close on a home.
Amidst practical hurdles and varying state guidelines, there remains no one-size-fits-all solution to addressing the continued existence of these covenants. More recently, state lawmakers have proposed various approaches to further address the existence of these covenants. Some county offices provide notices on their websites and at record access points indicating the potential existence of discriminatory covenants. Others support a declaration in the land records repudiating discriminatory language or adding a new, superseding document. Redaction is also an option being considered among legislatures – completely removing all discriminatory language from existing land records, while maintaining copies to further research and quantify the harm they have caused. With each of these solutions, steps must be taken to ensure modification or removal of property record information does not inadvertently jeopardize homeowners’ property rights.
To comprehensively address discriminatory covenants in land records, they must be identified and quantified.
In 2021 Sen. Tina Smith, D-Minn., introduced the Mapping Housing Discrimination Act, which would provide funding to research and document discriminatory covenants. Passing this bill is a critical first step to understanding the far-reaching negative impacts of these covenants and building an effective legislative approach to removing these reminders of the Jim Crow Era.
At Extract it has never been our stance to tell organizations what they should or shouldn’t redact, but rather teach them what is possible with technology. As leading organization in the redaction industry, We are committed to proactively working towards solutions that address these covenants for the counties and states that so choose and whether it be discriminatory restrictive covenants in land records, marijuana-related charges in court records, or HIV status or drug use in medical records, Extract can automate that redaction process for you.
Extract’s Discriminatory Restrictive Covenants Solutions
Combining Flex Index, Google Cloud Vision (GCV), and ID Shield for an all in one solution
FLEX Index uses OCR and a combination of machine learning/natural language processing to capture the required information on each of your most recorded documents. We focus the initial rules on the document types that represent the top 80-90% of your recording volume because that is where we will have the biggest and most immediate impact on reducing manual data entry. Extract creates the preliminary rules configuration at our facility by analyzing a sample set of documents and index data from your system.
We use either a standard data entry panel for all document types or several unique data entry panels for various document types. There are significant benefits associated with using our data entry panel(s). First, we have several swiping, rubber band, and text capture tools that allow users to highlight data and pass data to the data entry panel without manually keying the information. The second major benefit is it allows us to capture changes as users edit the software proposed index data. The system will analyze the keywords around the new information and train the system over time to capture information more effectively when it sees repeat patterns. Lastly, using our data entry panel allows us to provide detailed accuracy and user metric analytics dashboards.
Preview our solution in this virtual webinar
Some counties have poorer quality documents or contain handwriting (or both)- in that case we leverage Google Cloud Vision (GCV) to identify the keywords. GCV is not perfect but we have run many of our customers documents through GCV and seen great accuracy rates, but it is not perfect, and requires verification. If any vendor gives you an indication that handwritten or cursive text can be read perfectly is simply untrue, but as stated above, GCV can read it very well.
For DRC Extract leverages our automated redaction software ID Shield to meet the requirements for all of our DRC clients. The rules are configured to monitor a list of county-specific terms. Changes to the database can be managed on a county level without requiring a rule modification from Extract.
When a document is flagged as containing one or more of the keywords, it will go into a queue for the RR/CC staff to review. By default, the rules flag only the keywords, but can also be configured to redact the entire sentence.