Data Quality Key to Mortgage Risk Analysis
The more regulators look into borrower complaints as an indicator of servicing quality, the more servicers are bound to expand borrower-related datasets and behavioral analytics to minimize loan default risk.
Mortgage servicing quality today equals borrower satisfaction, says Ghazale Johnston, senior executive, Accenture Credit Services, a global management consulting, technology services and outsourcing company.
It means mortgage banks, especially mortgage servicers, have to create practices that use high-quality borrower communication and loan data analytics.
If going forward the housing market will continue to switch from a buyers’ to sellers’ marketplace, at least for the foreseeable future it will be primarily borrower oriented.
Like many others in the mortgage servicing space in the past few years Accenture has been working with various middle-size lenders and servicers to develop risk evaluation tools that ensure system users get a better transparency into their loan servicing portfolio.
“Everyone’s focus has been on improving the infrastructure, the quality of the data, access to information and then using analytics to find the risk areas and to determine what technology need be used,” Johnston told this publication. “Securing better data transparency is key.”
Even though compliance remains the No. 1 mortgage banking challenge, she argues, despite improvements, “It’s all about the quality of the data, because for the longest time information was coming from different sources and had to be refreshed at different points in time.”
Lenders and servicers cannot implement change and adequately assess servicing risk unless they have data.
“There’s recognition in the industry that there’s so much analytics you can really implement, if you’re not really doing it right. The challenge continues to be getting the right data,” Johnston says. Service providers already have developed a large number of data tools that have helped improve mortgage servicing data quality.
The servicers who made early efforts to centralize datasets and add new technology designed to clean up loan data are better equipped to compete in the marketplace, she says. Banks with large delinquent loan portfolios and unresolved foreclosure backlogs, on the other hand, started joining the quest for up-to-date technology later in the recent past when overall housing market improvements are allowing them to invest more resources into improving their servicing systems.
According to Johnston, solving loan compliance data problems “is a real issue,” driven by two primary factors.
New data reporting requirements are the most challenging as the number of regulators and stakeholders that require information is as different as the datasets they expect from mortgage servicers. Demand from investors, federal and state regulators, customer advocacy groups, to mention a few, altogether put a strain on servicers.
“They need to have the right data governance in place—gather information, synthesize it and convey it in a way that keeps them away from the hot list, or headline risk,” she says. “It takes capacity and consumes resources.”
Also, building the right data model can be a challenge because in many cases “it’s a pretty intricate infrastructure,” sometimes servicers “do not necessarily have the information reports they are asked to provide.”
The volume of judicial requirements constantly grows. Mortgage banks recognize the need to route resources away from other initiatives to make sure they are complying with regulation.
“You cannot be in the game unless you can meet compliance requirements at least at a bare minimum. That is a big cultural shift that is evident, in terms of where they’re spending their dollars,” she adds.
Another shift, the executive says, is in determining what kind of action to take when improving end-to-end processes: focus on the short term, or be strategic and look at new market demands as an opportunity to restructure everything from the long-term perspective.
Despite the size of their shop servicers are interested in investing in technology solutions that provide deeper data drills, she says.
Longevity of systems and processes used is another concern.
Over the past few years mortgage servicers have come to recognize the challenge with mortgage servicing risk management “is not about just throwing bodies at a problem.” It is about solving issues in a methodical way, picking the right skills, quantitatively and analytically, and looking at the tools needed to preserve process efficiency and quality borrower experience.