The problems of inconsistent data names, definitions, structure, cleanliness, usability, transfer and governance are well known in the mortgage industry. In his May 2007 Mortgage Banking column entitled "Data Quality: Crucial for Every Organization," Gabe Minton discussed the benefits of good data quality -- first by defining it, then by describing progress made defining data field names, definitions and structure using MISMO guidelines. This article examines the costs and other consequences of dirty data in secondary marketing and securitization, as well as the contribution of dirty data to the current mortgage liquidity crisis. Data quality can vary dramatically, depending on the mortgage investor and lender. Lenders should improve quality-control procedures not only to ensure accurate loan documents and salable loans, but also to correct inaccurate data in core lending systems.
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