Using Automated Decisioning to Get Loan Mods Right
Late last year it was reported that loan modifications done earlier that same year were again in default.
Overture Technologies in Bethesda, Md., has launched a new tool dubbed Mozart for Special Servicing to help servicers use analytics and decisioning to get troubled borrowers into the right loan modification the first time around. Specifically, Mozart for Special Servicing uses automated decisioning technology and rules systems to re-evaluate the loan to get the borrower into the right modification. “There are a couple of things that are unique about this offering,” said Linda Simmons, general manager of Overture Technologies’ Mortgage Finance Solutions.
“For instance, we include a full credit parse instead of just a FICO score. We also include multiple valuations because we don’t think the industry will or should bank on one valuation. When the servicer talks to the borrower we want them to have a good set of information on the borrower before having that talk.” And with Credit Suisse estimating another 8.1 million foreclosures are expected between 2009 and 2012, there will be a lot for borrowers and servicers to talk about. The current rate of defaulting mortgages in the U.S. today far exceeds the manpower capacity for banks or servicers. The Overture solution provides the servicer with several best-fit options to ensure the borrower gets the right modification for their needs.
“We’ve been talking about re-decisioning and using analytics across the mortgage lifecycle for some time,” added Ms. Simmons. “We discovered by talking with clients that the capability to do special servicing already existed in our product. For example, the need to provide integrations to get updated data, the rules engine, the decisioning engine, etc. We wanted to find a way to get the borrower into the right program the first time.
“First, we needed to get the pieces together to make this happen. Second, it has to be defensible because we’re going to have to explain why this was the best fit and why it’ll work. As important as all of this is, it has to align the best interests of the borrower, servicer, investor and other parties from the outset. In saying this, we are not replacing the servicing system. We Velcro on top of the servicing system. In October we started a proof of concept with a customer. I like to tell the story that within 20 minutes of demonstrating the proof of concept the client said let’s do it. So now we’re in development.”
Mozart for Special Servicing enables servicers to reduce recidivism and maximizing home retention using more current, relevant data about the borrower and the asset. It also aligns the interests of borrowers, bankers, secondary markets, investors and other third parties. In addition, the tool maintains consistent, defensible, transparent, processes; levels of discretion and approval practices; calculations and agreed-upon outcomes for every loan, regardless of spikes in volume and industry booms; and provides tailored workout options at the loan level, leveraging existing infrastructure, integrating with legacy systems and other data facilities.
But why should lenders be more confident using technology to do modifications? “We’re not aware of automated decisioning being used in this area,” Ms. Simmons said. “So, the servicer has to remember everything and do calculations with a calculator. The reason why the loan-mod program may not have been right for the borrower was because the decision was being made by a human who can make mistakes.”
In Brookfield, Wis., Fiserv executives are finding that processing capacity and a thorough loan screening process that allows lenders and servicers to evaluate risk in different levels are concerns the industry will continue to face this year when dealing with loan modifications.
Demand for sophisticated tools that facilitate the workout process has generated products like Prism, a home retention analytical program developed by Fiserv.
In general, one of the biggest challenges for servicers is processing capacity, Bill Garland, senior vice president, Fiserv Home Retention Solutions, told MSN. “What we think here at Fiserv, being so tuned in with the Case-Shiller index and the other evaluation products that we offer, there is a lot of dialogue about when will the home values in the single and one-to-four family residence market stop declining and hopefully start rising,” he said.
In reality, historic vintage analysis and the delinquency rates for the 60-day delinquent period, if we roll them out, using analytical models servicers can detect what loans will convert into real estate-owned without some level of intervention.
Through Prism, Fiserv here allows servicers to review a pool of loans and report what loans are about to be priced or could default. It analyzes data provided by the investor and the servicer of the loans based on information sources already available in the Fiserv database, explained Mr. Garland. That market data combined with borrower information obtained from the servicer, Mr. Garland told MSN, allows Prism users to run the analytical model “in a couple of different levels” that generate a lateral risk score, a credit risk score and an overall risk score of default.
The lateral risk score results from data about the marketplace and the perceived trends in values in a particular market. The credit risk score would basically clarify where the borrower stands as it pertains to one’s employment status and type.
The overall risk score is based on weighing together general information and statistics about the particular market where the borrower resides and individual profile evaluations.
“We take a pool of loans and drill down into what we think is the potential for a loan to have a problem in the foreseeable future,” he explained. “We also have a second level where we can go out an obtain more current information, maybe a AVM, or BPO and approximate price for a specific property, along with a FICO risk analysis that would indicate what is the credit profile of the borrower. It enables us to provide a greater transparency into the situation of a particular loan.”