I am a real estate investment company looking to market to property owners that borrowed money from sub-prime banks during 2004-2008. These borrowers are people we want to market to and buy their property. Currently, in order to find these loans, we have to go through thousands of properties to find these borrowers. We do this manually. I wanted to use AI to expedite the process. Here are the characteristics of the loans we are looking for.
1. Loans Originated between 2004 - 2008
2. Loans Originated by Sub-Prime Lender (we will provide list)
3. Loans where Lis Pendens or Notice of Default was filed between 2008 & 2012
4. No Satisfaction of Mortgage recorded after 2008
5. Multiple Index Numbers or Court Case Numbers
6. Court cases where Plaintiff motions have been denied in court with no defendant attorney
I have access to pull all of this data using different sources (mostly public) but the process is literally me dumping a list and manually checking the list I dumped against another list o using another system.
I am not a super technical person but I am able to quickly point out characteristics of the type of properties that have the type of mortgages we are looking for. I wanted to know if someone can help me piece something like this together or least point me in the right direction.
I am open to having a conversation to further explain what we are looking to accomplish. Ultimately, I presume this will be some form of segmentation where we can classify which transactions or mortgages meet this criteria. I want to take a large data set feed it through a machine learning vehicle and tell it what we are looking for. Hopefully we feed it enough information that allows the machine to scan and recognize these types of files and we can market to these owners.
About the recuiterMember since Aug 24, 2017 Dan G.
from California, United States