Mortgage fraud is difficult to track and takes many forms â for example, fraudsters cheating borrowers out of their properties with false promises of foreclosure avoidance or using the identity of a real person (often without his or her knowledge) to fraudulently purchase one or more properties. TowerGroup has developed a graphic that helps categorize the different motives and methods of mortgage fraud, as shown here:
âMuch of the growth in mortgage fraud has been due to the ever-increasing sophistication of fraudstersâ schemes to fabricate the values of mortgaged property,â said David Hamermesh, senior analyst in the Consumer Lending research service at TowerGroup. âFraud prevention is best done proactively, before the loan closes. Lenders must invest in analytical tools to identify loans at a high risk for fraud, while technology vendors must do more to improve the predictive power of the analytical tools they provide.â
Highlights of the research include:
⢠The growth rate in filings of Suspicious Activity Reports (SARs) related to mortgage fraud rose to 56 percent annually between 2002 and 2007 from its previous average of 26 percent annually from 1996 to 2002.
⢠Lenders, investors, and other mortgage industry participants will come to recognize the value of pooling their data to support more accurate predictive modeling as well as to facilitate their analystsâ ability to find and react to innovative fraud schemes.
⢠To combat growing losses from all types of mortgage fraud, technology companies should develop a âone-stop shopâ that provides lenders with a truly integrated solution. Such a comprehensive tool would provide increased predictive power, better system performance, and holistic risk assessment that cannot be matched by a lender trying to cobble together individual tools from multiple sources.
âTechnology companies that offer fraud detection solutions will need to develop professional services capabilities to provide lenders with file reviewers who are trained in assessing possible fraud. This service can supplement a lenderâs own underwriters and be an efficient way to evaluate those loans flagged as most risky by automated scoring tools,â added Hamermesh.
The new research, titled âUS Mortgage Fraud: Types, Trends, and Detection Tools,â examines the different types of fraud, characterizes the tools available to combat fraud schemes, and assesses likely future directions of mortgage fraud prevention services and products.