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For Mortgage Industry, Big Data Signals Opportunity and Risk

August 14, 2014

A preview of 2013 Home Mortgage Disclosure Act data that is expected to be formally released in September indicates that mortgage applications were down 8 percent from the year earlier and loan denials were up a sharp 13 percent.

The preview, based on a survey of 400 mortgage providers conducted by Mortgage Trueview and first reported in National Mortgage News, also found that origination rates dropped from 52 percent to 44 percent, meaning there were now more unfunded applications than funded ones.

In June, Federal Reserve Chair Janet Yellen also remarked on the mortgage industry’s challenges. “It is difficult for any homeowner who doesn’t have pristine credit these days to get a mortgage. I think that is one of the factors that is causing the housing recovery to be slow,” she said.

With tougher underwriting standards and tighter credit making it tougher for mortgage providers to approve applicants, some say that lenders need new tools to support the process of qualifying mortgage applicants, and those tools may come in the form of big data and data analytics.

Lenders have long relied on a wealth of data to find and qualify mortgage applicants, but increasingly data analysis is being leveraged in more predictive ways.

 “While "big data" is truly the purview of giants like Facebook, Google or Twitter, the tools and strategies developed to define, parse, interpret, standardize and, last but not least, monetize data, will evolve mortgage banking,” writes Ruth Lee, executive vice president of Denver-based Titan Lenders Corp. predicted in an article she wrote for MortgageOrb.

Lee predicts that “the technology of analyzing data will redefine how the industry measures risk.” But Lee also noted, given its recent history, the mortgage industry must proceed with caution. “Bad data is worse than no data, and frankly, we as an industry have not done a great job with our data,” Lee wrote.

Lee is not the only one to take a cautious approach. The fear that taking in data from too wide a variety of sources may lead to qualifying candidates based on flawed data models is a real concern for an industry that remains on a long road to recovery from the housing bubble.

More data being pulled from a wider variety of sources will lead to the need for more data control, cautioned Frederic Veron, senior vice president and chief technology officer for Fannie Mae, in an article that ran in the Huffington Post. “At Fannie Mae we are building towards our ultimate goal of qualifying data at the outset,” Veron wrote.

 “This is a monumental challenge that will take time and resources, but the industry is headed in the right direction” Veron concluded. “Shoring up our data at the enterprise level will improve the country’s business performance and help ensure that we learn from important lessons about prioritizing data management and integrity.”

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