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Data-Quality Matters: Lenders Today Face Growing Pressure to Ensure That the Quality of Their Loan Data is Good. Here are Some Things to Think About to Ensure Better Data Quality (Technology)

eBook details

Title: Data-Quality Matters: Lenders Today Face Growing Pressure to Ensure That the Quality of Their Loan Data is Good. Here are Some Things to Think About to Ensure Better Data Quality (Technology)
Author : Mortgage Banking
Release Date : January 01, 2009
Genre: Industries & Professions,Books,Business & Personal Finance,
Pages : * pages
Size : 90 KB

Description

For as long as mortgage banking has existed, there have been data-quality and integrity issues. As one executive with a megalender once said, "There are only two types of data in the mortgage business: dirty data and very dirty data." The list of where the data problems come from is lengthy, and includes automated and manual processes. * Here in the 2009 mortgage market, data quality is ever more important and under intense scrutiny. As a result of the market downturn, the secondary market has had to ask originators to buy back bad loans based on, among other things, data-quality issues--thus creating a direct business impact on the industry. * This article is based on work by the Mortgage Bankers Association (MBA) to address data quality head-on from a lender and secondary market perspective. Yet it is important to point out that while data-quality problems exist throughout the mortgage universe, we are only choosing to focus on a specific area in need. * Over the years, the mortgage process has become increasingly automated. Manual, paper intensive processes have given way to dynamic and demand-driven workflow automation. Introducing new forms of technology and automation does not always improve data quality and security; in fact, complexities of new systems often do the opposite. * At the same time, regulation and compliance requirements have been rapidly increasing, which has introduced more complexity and additional technology systems to typical operations. An example is the ever-expanding methods by which lenders obtain leads/applications. Twenty years ago, people predominantly went into a bricks-and-mortar establishment and filled out a loan application with a loan counselor (and many still do). Today, you have Internet-direct consumer Web sites, aggregators, call centers, broker networks and many more methods of obtaining the initial loan application data--all of which could introduce data-quality problems into the process. We have moved forward technologically, but backward in terms of increased complexity. The potential for data-quality issues without increased investment in tools and processes to obviate them is tremendous.