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V5I1206 - Financial Intelligence Units (FIUs)
V5I0806 - Money Laundering: The Exception
V5I0406 - Network Monitoring
V5I0106 - Filing Compliance
V4I0405 - Terrorism Financing
V4I0305 - Telephone Toll Analysis
V4I0205 - Wire Transfers for Alien Smuggling
V4I0105 - Bust-out Schemes
V3I1204 - Structuring Financial Transactions
V3I1104 - Finished Intelligence (Proactive Analysis)
V3I1004 - Exposing Mortgage Fraud
V3I0904 - MIND Lab Integrates Course Data
V3I0804 - Suspicious SAR-MSB Filing Data
V3I0704 - Integrating Multiple Data Sources
V3I0604 - Analyzing Airline Profitability
V3I0504 - Corporate Fraud
V3I0404 - Employee Master File Analysis
V3I0304 - Prescription Fraud Patterns
V3I0204 - Social Network Analysis (SNA)
V3I0104 - Fraud Detection System (FDS)
V2I1203 - Integration with our Digital Information Gateway
V2I1103 - Financial Transactions Investigation
V2I1003 - Compliance Analysis
V2I0903 - Medical Insurance Claims Analysis
V2I0803 - Corporate Fraud Investigation
V2I0703 - Possible Domestic Terrorist Shooting
V2I0603 - Suspicious Activity Report (SAR) Filing
V2I0503 - Detecting Financial Crimes
V2I0403 - "Referential" Data Sources
V2I0303 - Proactive Analyses
V2I0203 - Transactional Activities
V2I0103 - Temporal Grid

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Referenced in our Newsletter Volume 3, Issue 10 - October 2004

Exposing Mortgage Fraud

When dealing with millions upon millions of records, VisuaLinks provides a number of unique ways to "slice & dice" the data to support proactive analytics. In the context of financial crimes analysis, there are certain types of situations that will always result in further evaluation. These typically include large numbers of transactions, frequent use of accounts, or connections to multiple ID numbers, addresses, or phone numbers.

The following example is based on SAR (Suspicious Activity Report) data using the Summarize service to expose a SUBJECT using multiple Social Security Numbers (SSNs) operating out of a specific LOCATION. The interesting aspect of this Summarize configuration was that the Count By selection used the SSN/EIN and the Group By was set to the NAME/DOB of the SUBJECT. Additionally, a filter was applied to only acquire records from a certain geographic region (defined by a CITY/STATE). Furthermore, a SUM aggregation was selected for the VIOLATION AMOUNT associated with the transaction.

The result set identified quite a number of potential targets and the query results were sorted by a combination of the number of SSN/EINs and the summed VIOLATION AMOUNT. Immediately, a specific target was identified and is shown below with 11 unique SAR violations.



A quick inspection of the NARRATIVES shows that all of the SARs reflect ongoing mortgage fraud(s). Generally, the banks indicated that there were misrepresentations in employment, overstated income, or falsified assets. With historically low interest rates, rising housing prices, and record new-home construction (9.4% in August 2004), the marketplace has been wrought with various frauds - especially mortgage fraud. The next level of the diagram is shown below indicating that there are at least 1-2 additional SUBJECTs per transaction involving our primary target.



From here, the networks were expanded again to bring in any ACCOUNT information associated with the SUBJECTs. Clearly the diagram indicates these subjects are all working independent of one another because each involves a separate account. The primary subject (in the center) is the controlling entity for all of these mortgage frauds.



Finally, the ADDRESSes for these SUBJECTs are displayed, which confirms they are all based on separate transactions. Notice, for each pairing of SUBJECTs for a SAR, there is a common address shown between them. Supposedly, these addresses would be the properties involved in the mortgage fraud.



Finally, a Temporal Grid was generated using the Day-of-Week (X-axis) and Week-of-Year (Y-axis) settings to show when these SARs took place. As depicted in the diagram below, there is a heavier concentration towards the end of the summer for this activity. Keep in mind that a SAR may contain multiple, independent transactions.

The behavior of our primary subject clearly shows the few transactions conducted earlier in the year tested the waters to determine if the scheme was detected by authorities. The last transaction occurred a week prior to writing this description, which indicates the fraud is presently active and our target is subject to prosecution from law enforcement.



Money laundering takes on many different characteristics. Whether people are structuring transactions to avoid the $10,000 filing limits, kiting checks, performing terrorist financing, or committing mortgage fraud - all of these types of violations are ultimately reviewed by the government agencies (e.g., FBI, IRS, FinCEN, DEA, etc.) chartered with investigating these types of crimes.

For more information on mortgage frauds, see the following CNN news reference:

http://edition.cnn.com/2004/LAW/09/17/mortgage.fraud/


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