Less known is Palantir Technologies. It describes itself as \u201cbringing the right data to the people who need it, allowing them to make data-driven decisions.\u201d Palantir clients include some of the most secretive US intelligence agencies. They do a lot with data, and beyond that, I am unable to articulate without revealing my lack of understanding.<\/p>\n
So with equal parts excitement and foreboding, this is what I see Palantir bringing to the mortgage<\/a> fraud fight.<\/p>\n The right data<\/strong><\/p>\n Palantir brings clients the \u201cRight Data.\u201d So what is that? Simply put, the \u201cRight Data\u201d for Palantir is everything. Everything means all the granular mortgage loan data, from a borrower\u2019s private data to the very public property data. Then there\u2019s macro industry data, from origination through to securitization. Anything short of that will hobble their ability to spot or prevent fraud.<\/p>\n Right data \u2013 Occupancy misrepresentation:<\/strong><\/p>\n Let\u2019s apply Palantir\u2019s Right Data to the problem of mortgage fraud. The lion\u2019s share of fraud that Palantir and Pulte find will be occupancy fraud, so let\u2019s look at what the Right Data means in this context.\u00a0<\/p>\n Occupancy fraud is simple and pervasive. Borrowers falsely claim they will live in the home as a primary residence in order to qualify for lower interest rates and down payments.<\/p>\n Palantir will scrape public and private data sources for the myriad of clues left when someone lies about occupancy. For example, they will check rental sites like Airbnb to see if the property is listed there. <\/p>\n Did the borrower register a car, boat, or even a plane at a different address? Palantir will find the addresses for professional licenses, and voter registrations. It will scrub social media to find where our borrower eats, banks, gets dry-cleaning picked up. Which ATMs does the borrower frequent? Palantir will see if the borrower owns other properties and will check their value. It will compare square footage and then search for rental ads for any of the borrower\u2019s investment properties. Ideally, Palantir will find and report on electricity usage, trash pick-up, plus the distance to golf courses or beaches. It should run a report on the commute distance between the borrower and the employer.\u00a0<\/p>\n Right now, Fannie\u2019s fraud investigators are doing most of this by hand. It\u2019s not that Palantir will be any smarter, but it will be more thorough and quite a bit faster. The CEO of Fannie Mae, Priscilla Almodovar, was quoted in HousingWire on May 28, saying that Palantir found fraud in \u201c10 seconds\u201d (possible) but \u201cit took our really talented investigators 60 days\u201d (no). Her statement is forgivable car-salesman puffery, but her point is taken: Palantir will be fast.<\/p>\n Right data \u2013 Asset misrepresentation:<\/strong><\/p>\n Money launderers use real estate to clean dirty money. Therefore, the quality of asset documentation should be a primary concern of Palantir. There are commercially available tools now to verify the legitimacy of assets.<\/p>\n But Palantir\u2019s data should do much more than just verify that a document is valid. It should analyze account balances against borrower profiles, check seasoning of funds and geographical red flags, verify instantly that grantors of gifts are related to the borrower (as required by gift letters), and bump the names of grantors up against the SDN list.\u00a0<\/p>\n