Data Integrity: The Key to Recovery

By Fulmer, Ann | Mortgage Banking, October 2011 | Go to article overview
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Data Integrity: The Key to Recovery


Fulmer, Ann, Mortgage Banking


Trust and reputation are not discretionary. They are as necessary in business as the people in whom they reside.

--TONY ALESSANDRA

The theme of the Mortgage Bankers Association's (MBA's) Annual Convention this year is "Driving Change." There is no question that the landscape in financial services is changing, and rapidly, but one must wonder: Who, or what, is driving the change?

Agents of change in the current environment include demographics, economic cycles, politics, regulation and technology.

The congressional mandate to reshape the financial services industry has pushed regulatory compliance to the forefront as the primary driver of change. From loan officer compensation, licensing and registration to the latest round of Real Estate Settlement Procedures Act (RESPA) reform, and from the Dodd-Frank Wall Street Reform and Consumer Protection Act's underwriting and due-diligence standards to the futures of Fannie Mae, Freddie Mac and the private secondary market, the entire system is in a state of flux. The economic environment makes it more difficult to keep up with what seem to be daily regulatory transformation and uncertainties.

The primary stated motive behind the new regulatory scheme was the prevention of systemic risks to the economy in the future. However, when viewed in their entirety, the tide of laws and regulations sweeping over us reflect a deep mistrust of the financial services industry. It's evident in the imposition of stringent quality and due-diligence standards for loan originations and in the level of loan detail that must now be provided to the regulators and to secondary market participants.

It's the financial services version of "trust but verify," and it's a necessary first step to restoring confidence in the industry.

Although implementation and ongoing compliance will be extremely challenging, the new regulatory scheme may ultimately represent the industry's salvation because it elevates data integrity and transparency to the top of the enterprise risk-management priority list. Prudent lenders would therefore be well served--regardless of the outcome of the Qualified Residential Mortgage (QRM) and Qualified Mortgage (QM) definitions--to focus like a laser on quality-control processes and procedures.

Data integrity

Data integrity is the foundation of successful mortgage lending. It is essential to restoring the trust of consumers, investors and legislators. When loan data is accurate, lenders are able to make fully informed credit decisions and sustainable loans.

Transparency is also critical because it allows market participants to examine and understand the loans they're buying or insuring and it ensures they don't exceed acceptable risk parameters. As they used to say in the early days of computing, "Garbage in, garbage out."

The dangers inherent in making loans based on inaccurate data are coming into sharp focus as a result of repurchase and rescission investigations into defaulted loans. Forensic file examinations are providing proof that fraud was, as the Federal Bureau of Investigation (FBI) warned in 2004, at epidemic levels during the boom. Whether it related to collateral valuations or borrower qualifications, the data used to support millions of loans were intentionally corrupted through affirmative misrepresentations and omissions, and that both sparked and exacerbated the economic crisis.

Nowhere was this problem more severe than in the stated-income and no-documentation loan programs. These programs were designed to facilitate loans to a specific niche market--self-employed borrowers with substantial assets and income. They became malignant products as housing prices rose and they began to be widely available for W-2 employees.

How did a beneficial niche product end up turning into such a defective product? The answer is through faulty data and inadequate underwriting processes and controls.

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