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Data Challenges in the Mortgage Industry

June 11, 2014

For years, the mortgage industry has battled for market share and short-term profits. This has led most technology spending into systems for quick processing, securitizing loans, and loan servicing. As a result, data management has often been overlooked and controls on data integrity have not acquired an appropriate share of IT budgets. Hence, many firms have wonderful systems that are populated with poor data, which results in misevaluated risks, poor collection strategies, ineffective marketing, extensive litigation and damages, and heavy regulatory scrutiny and fines.

Although some aspects of the mortgage crisis of 2008-09 as well as other more recent losses can be traced directly to bad data quality, the industry still lacks data standardization. Even within firms, data definitions and formats are inconsistent mainly due to legacy systems, lack of uniform enterprise-wide data standards, failure to keep up with changing concepts and regulatory definitions, etc. With the introduction of Legal Entity Identifier (LEI), it is very clear that government-sponsored enterprises, investors, and regulators are demanding increased data integrity.

The mortgage industry generates customer data throughout the loan lifecycle including loan applications, underwriting, funding, securitization and loan servicing. At each stage it generates a set of vital data that can be transformed into a wealth of information. By having defined processes and a set framework in place, mortgage companies can create a data road-map with regards to what data should be collected at each step, and how data will be shared across the enterprise in a way that ensures data integrity is achieved and maintained. This results in quality data that can support business decisions and aid compliance, especially with the new Consumer Financial Protection Bureau (CFPB) mortgage servicing rules.

Standardized data can be used for predictive models to

  • design new products
  • improve underwriting standards
  • evaluate pricing strategies
  • manage regulatory compliance
  • develop marketing strategies
  • execute collection campaigns
  • handle loss mitigation and other risk management strategies
  • set bond levels
  • Perform surveillance

To achieve this daunting data integrity and quality program, mortgage firms need to closely align business and IT systems to develop an automated workflow system that can capture, compare, validate and route data, and track documents to minimize loan processing time, improve portfolio value and reduce lender exposure. Standardized workflows and reporting functions further streamline processes and help facilitate potential audits.

As data has taken the center stage in the mortgage industry, market participants can no longer ignore the data integrity and quality problem. Lenders that break their legacy barriers and move their operations towards a quality-centric data driven model are well positioned to lead the market.

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