FinCEN Revises Focus at Dubious Real Estate Transactions – NMP Skip to main content

FinCEN Revises Focus at Dubious Real Estate Transactions

Nov 20, 2018
A pair of new reports are offering distinctive views of the housing market’s horizon


The Financial Crimes Enforcement Network (FinCEN) has revised its Geographic Targeting Orders (GTOs) that require title insurance companies to identify the individuals who use shell companies in all-cash purchases of residential real estate.
 
FinCEN has set its purchase amount threshold at $300,000 for all markets, a switch from an early policy that varied the threshold by location. And in a nod to the growing popularity of cryptocurrency, the agency is also requiring that covered purchases using virtual currencies be reported.
 
FincCEN’s GTOs cover certain counties Boston, Chicago, Dallas-Fort Worth, Honolulu, Las Vegas, Los Angeles, Miami, New York City, San Antonio, San Diego, San Francisco and Seattle.

 
About the author
Published
Nov 20, 2018
Servicers Begin Testing Systems Ahead of VA Partial Claim Deadline

VA lenders and servicers have until Nov. 28 to implement the new loss mitigation waterfall and Partial Claim Program

ROAD Act’s Housing Incentive May Be Too Small To Move Supply

Realtor.com finds the median city risks losing only about $84,000, although the policy could carry more weight in supply-starved Northeast and Midwest markets

CRA Proposal Could Reshape Bank Lending And Affordable Housing Investment

The OCC and FDIC would put more weight on lending while easing community development requirements for hundreds of banks

Fannie Mae AI Governance Deadline Arrives Aug. 6

Seller/servicers using artificial intelligence in origination or servicing must have formal policies, oversight, and vendor controls in place

Condo Review Deadline Puts Lenders On The Clock

Fannie Mae and Freddie Mac will eliminate abbreviated project reviews for condo applications dated on or after Aug. 3

TRUE Releases AI Governance Guide Ahead Of Fannie Mae Deadline

Guide focuses on tracing mortgage data from borrower documents through AI validation, human review, and final LOS entry