Uncovering The Hidden Truths In Mortgage Portfolios

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REQUIRED READING: Uncertainty continues in the mortgage industry, and servicers are not only dealing with the fallout from nonperforming loan losses, but also the challenges coming from ongoing consolidation through mergers and acquisitions. At the same time, the current situation also presents significant opportunities to purchase portfolios and servicing rights at below-market rates.

As a result, servicer concerns over hidden risks that may be lurking in portfolios are as high as they have ever been. Loans are moving very quickly from owner to owner and servicer to servicer, and while some are held in electronic files, many others still exist only on paper. Performing loan- or property-level due diligence is, therefore, extraordinarily complex, making it difficult for organizations to measure risk and maximize value.

Loan-by-loan clarity
Whether companies purchase mortgage loan portfolios or are in the process of merging with another entity, it is essential to get a reliable analysis of the portfolios being acquired so that institutions are alerted to areas of potential risk. By using analytical tools that leverage a variety of data and public record sources, servicers can generate a snapshot of the risk profile of a particular portfolio on a loan-by-loan basis.
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Of course, one of the first areas an institution should explore when considering a portfolio acquisition relates to foreclosure activities. The value of the portfolio is tied to the performance of its individual loans, and it is important to know both the volume and type of loans that are already in foreclosure, have received a notice of default or are rolling into delinquency status. This type of analysis requires access to information that may be readily available from the acquired company or prior portfolio holder, but gathering supplementary data to get a full picture is often required.
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For example, to analyze portfolios for risk, the visibility of liens is extremely important. If the organization is buying a first-mortgage portfolio, it's essential to know how many second liens exist within that package of loans and how changing home values impact their equity position. Second-lien servicers also need to know whether any properties are listed on the Multiple Listing Service and are up for short sales in order to maximize any potential equity or to begin foreclosure proceedings to maintain their position.Â
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Organizations that are purchasing a portfolio must identify borrowers in the portfolio who are entering, or have already entered into, bankruptcy and determine whether or not the owner is still listed as the lienholder. Within some second-lien portfolios, it is possible to see that the first lien has actually been sold, whether in a short sale or deed-in-lieu, and the collateral no longer exists for the second lien.
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The servicer should also check to see how many second mortgages exist and how recently any second liens may have been added against collateral properties. Borrowers who run into financial difficulties sometimes obtain second mortgages or lines of credit and use those funds to make payments against the first lien.

By examining the portfolio on a loan-by-loan basis, these trouble spots become clear and can be tracked for proactive action. In addition, tax delinquencies are often an early indicator of an at-risk loan. If a borrower is a year – or multiple years – in arrears on property taxes, the portfolio owner could be at further risk of losing the property to a tax sale.

A wider portfolio view

It is also important to use available tools and data to examine portfolios in general and compare portfolios against one another. By comparing key factors, such as delinquency deterioration and recently added second liens – especially against a currently owned portfolio – a financial institution contemplating the purchase of a new portfolio gains a much clearer picture of how the acquisition is going to change the overall complexion of its holdings when the two are combined.
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Another area to look at in a broader analysis is how many upcoming loan resets may exist within a given portfolio. If an organization is purchasing a first-lien portfolio with a large number of adjustable-rate mortgage loans, it should know the mix of change dates, interest-rate increases and the level of change such resets represent for the portfolio as a whole. In this way, the financial institution gains insight into the potential for delinquency, default and eventual foreclosure in the future, and in what time frames.
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These tools also allow the organization to track portfolios from status standpoints, using property value indexes to track historical changes in the portfolio via automated valuation models (AVMs). It then becomes possible to see the portfolio's total value at specific points in time and trend those values, and to determine how they compare with the industry as a whole or with the servicer's existing portfolio.
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Certainly, if a servicer is considering an acquisition of loans and can compare the outstanding balances of individual loans as compared to estimated market values through an AVM, it will gain a valuable indicator as to the risk of potential foreclosures on upside-down loans. Using these summary analytic tools and public record data, servicers gain a view into problem areas, allowing organizations to more accurately target their resources to proactive manage and mitigate risk. They can also give acquiring entities a before-the-fact idea of what loans it may want to exclude from an acquisition.
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Once an organization begins the process of portfolio analysis, it becomes possible to continue to track portfolios forward to understand how acquisitions have performed over time, using historical analysis to refine and better implement future analysis. By benchmarking the risks in a given portfolio based on the types of automated searches and summaries and seeing how the portfolio performs over time, a lender can identify those areas to which it will want devote more attention in future acquisitions.
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These findings can also be evaluated for process improvements and more accurate risk modeling, allowing the organization to improve its acquisition process over time. This process can help servicers better understand the characteristics of loans that eventually require intervention and help them better understand the markers of high-quality loans. Additionally, the information gathered can help refine the mitigation strategies lenders and servicers deploy to proactively manage risk.
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For example, if the data shows significant value changes within a particular ZIP code, the organization may determine it needs to devote more resources to that area (e.g., stepping up efforts for loan modifications, re-staffing for additional foreclosure activity, etc.). Beyond such operational adjustments, the data can also indicate what types of loan programs the lender should be targeting to improve results.
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There are up to a dozen distinct data elements that can be tracked and trended so as to more accurately determine whether the portfolio is improving or deteriorating from a loan performance perspective and in what specific areas the deterioration is taking place. With that sort of clarity, it becomes much easier for the organization to shift resources and plan accordingly to address issues that may arise.
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Ongoing surveillance is also invaluable for proactive risk analysis on a day-to-day operational level. By monitoring loans at regular intervals and trending performance, specific workflow actions can be triggered automatically. As particular events occur, transactions can be flagged and put into work queues integrated into the servicing platform itself, becoming part of the overall workflow automation.
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Whether used as a one-off review of particular loans or as a bulk portfolio analysis tool, this capability is crucial for lenders in this time of industry consolidation. With so many scratch-and-dent portfolios changing hands, it is vitally important for organizations to have the ability to understand where their portfolios are heading.

Ray Ferrarin is managing director of LPS Applied Analytics. He can be contacted at exec.author@lpsvcs.com.

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