Utilizing Fraud Prevention & Detection Tools

Transcription

1 Utilizing Fraud Prevention & Detection Tools SourceMedia Presentation Presented by Jay Meadows President/CEO Rapid Reporting

2 Mortgage Fraud Defined Fraud for Property: Mortgage fraud on a loan for a borrower who intends to repay, but would (may) not otherwise qualify for the loan requested The primary motivation is home ownership. Either as a primary residence or investment Typically involves borrower as perpetrator on a single loan An industry professional is often involved The borrower makes misrepresentations (usually regarding income, personal debt, and property value) 20% of reported fraud Fraud for Profit: Mortgage fraud where interested parties are trying to obtain illicit profit at the lender s expense Borrower never had intent to repay, or borrower was materially misled by and industry insider* into purchasing the property Multiple loans frequently involved Multiple misrepresentations frequently involved (e.g. fictitious properties, straw borrowers, inflated property values) 80% of reported fraud

3 Impact of Mortgage Fraud Per FBI, lenders reported mortgage fraud losses of $1 billion in FY 2005 up from $429 million in FY 2004 Rising real estate values in virtually all U.S. markets in recent years have undoubtedly masked a significant amount of mortgage fraud loss. Industry experts agree that declining real estate market will produce more mortgage fraud loss. According to the FBI, Identity Theft is the fastest growing white collar crime in America today. 80% of all reported mortgage fraud losses involve collaboration or collusion by industry insiders. 64% of all mortgage fraud involves income or identity misrepresentation by the borrower. FinCEN (Financial Crimes Enforcement Network) Nov. 2006: SARs pertaining to mortgage loan fraud increased by 1,411 % between 1997 and This report filing trend continues apace in 2006, with 7,093 reports filed on suspected mortgage loan fraud during the first quarter, an increase of 35% over the SAR filings in the first quarter of 2005.

4 Mortgage Loan Fraud Reporting Trend 35,000 30,000 25,000 20,000 15,000 10,000 5, ,279 25,989 18,391 9,539 3,515 4,696 5,387 1,318 1,720 2,269 2,934 7, Actual Projected FinCEN (Financial Crimes Enforcement Network) November 2006

5 Number of Mortgage-Related Fraud SARs Filed, Fiscal Years (10/01/98 09/30/05, Nationwide) Num ber of SARs Received $25,000 $20,000 $15,000 $10,000 $5,000 $0 $21,994 $17,127 $11,611 $4,210 $5,623 $6,936 $6,784 $2,973 $2,122 $3,085 $4,569 $3,088 $3,711 $3,245 $1,374 $1,850 $2,126 $979 $1,293 $1,764 $1,724 Mortgage Fraud Commercial Loan Fraud False Statement Fiscal Year 1999 Fiscal Year 2000 Fiscal Year 2001 Fiscal Year 2002 Fiscal Year 2003 Fiscal Year 2004 Fiscal Year 2005 Sources: Department of Justice, Federal Bureau of Investigation

6 Dollar Losses of Mortgage-Related Fraud SARs Filed, Fiscal Years (10/01/98 09/30/05, Nationwide) Dollar Losses Rep orted ( $m illio n s) $1,200 $1,000 $800 $600 $400 $200 $0 $1,014 $581 $429 $264 $293 $225 $156 $1,163 $1,060 $1,010 $998 $728 $711 $665 $659 $679 $502 $502 $469 $458 $388 Fiscal Year 1999 Fiscal Year 2000 Fiscal Year 2001 Fiscal Year 2002 Fiscal Year 2003 Fiscal Year 2004 Fiscal Year 2005 Mortgage Fraud Commercial Loan Fraud False Statement Sources: Department of Justice, Federal Bureau of Investigation

7 Most Common Areas of Fraud in the Marketplace LOANS IDENTITY EMPLOYMENT COLATERAL INCOME

8 Protection using Internal & External Tools Independence is key when not originating documents Multiple sources defeats insider fraud Checks and balances defeats insider fraud Maintain human logic Tools should be definitive Streamline and enhance processes with results (i.e. income match, minimal income review at underwriting) Customize for your risk tolerances, products and measure results for accuracy Provide resources to integrate with your LOS Short term pain and long term gain Collect the appropriate and accurate data (seller, realtor, loan officer) Leverage and Learn from other industries (i.e. insurance, banking)

9 Fraud Prevention Tools

10 The Problem of Identity Misrepresentation Industry Statistics In 2002, approximately 680,000 people became victims of identity theft. The equals 1,863 per day, 77 per hour, and 1.29 per minute. Gartner Inc. study, released September 2003 In 2003, approximately 7 million people became victims of identity theft. That equals 19,178 per day, 799 per hour, and 13.3 per minute. Gartner Inc. study, released September 2003 The incidence of victimization increased 15.5% between and 80% between Harris Interactive study, released September % of all reported mortgage fraud losses involve collaboration or collusion by industry insiders. Federal Bureau of Investigation May 2005 Financial Crimes Report to the Public

11 DirectChek Statistics Orders 105, , ,083 SSA Verifications 59, , ,536 SSA No Matches 4,811 12,370 18,590 Death Master Hits 283 1,184 1,608 OFAC Hits 131 2,182 4,656 % Negative Hit Ratio 8.62% 7.41% 6.38% Savings (Hard Costs- $30K to $50K)* $144M-$240M $371M-$618M $557M-$929M Savings (30% to 40% of Loan Amt)* $216M-$288M $556M-$742M $836M-$1.11B *Rapid Reporting has saved somewhere between $1.78B to $2.14B for the mortgage industry.

12 How do you verify Identity? 1. SSN Validation (real-time results) Merely validates that a number sequence COULD have been issued 2. Credit repository and/or public database searches (real-time results) 3. SSN Authentication (results posted daily) Definitively matches the borrower s name, SSN and date of birth against the SSA database in Baltimore, MD

13 Definitive Answer Identity Verification: The Social Security Administration

14 Income 4506-T IRS Tools

15 Pre-Funding Income Verification Program Return-On-Investment Prior to 1996, NAMC losses totaled approximately $6M annually From 1998 to 2001, NAMC avoided an estimated $21M in potential losses by processing 4506 s (average fraud loss was $25,000) Since 1998, NAMC fraud losses were less than $1M annually From 1998 to 2001, NAMC s Fraud Prevention Program reduced the fraud detection rate from 4% to 1.6% NAMC s fraud repurchase incident rate dropped from 21 Basis Points of originations to less than 1 Basis Point *Statistics were provided by Jim Griswold of North American Mortgage Company in a report to Rapid Reporting citing the effectiveness of it s IncomeChek product.

16 New IRS IVES Program Electronic Return Data As program progresses speed increases Is not inconceivable for same day turn around Summary report capabilities Lists computer results W2s & 1099s soon to be included

17 Stated Doc/Income Program Allows lenders to verify filing of tax returns without providing specific income figures Confirms filing of a Schedule C and/or E Stated Income also includes verification of a lender-determined, minimum AGI Replaces the CPA letter Opportunity to rework the deal

18 Employment Verification Tools Public record databases (fee-based) TALX and others Yellow pages White Pages Reverse directory State and local business licensing directories Small business administration Credit report employment found

19 Collateral Important to compare apples to apples Identify the AVM with best confidence score Identify the AVM with the best accuracy Identify the AVM with the best hit rate The cascade should be dynamic You control the view and confidence score based on your lending criteria or area (can be customized by you in hot spots) All of these lead too Greater AVM accuracy High national hit rate coverage Enables you to identify overvalued appraisals Mitigate default risk Minimize lost opportunities associated with undervaluation error

20 LoanSentry Report Benefits: Clear fraud warning indicators associated Potential flipping Unusual price appreciation Extensive property and neighborhood data that gives you insight into potential fraud including Detailed deed transfer history Relevant comps along with other neighborhood sales Key statistics relating to the neighborhood relevant to the subject property

21 Why Don t We Use Fraud Tools? I don t want to know If I use them, they will go to my competitor who doesn t They take too long and are too much work My company does not have fraud They cost too much

22 Happy Holidays Ya ll