Point of View: The System Is the Solution

Mr. Showalter is senior vice president of product and analytics for First American Second Lien Outsourcing. Mr. Benson is vice president and managing director for FASLO Capital Markets Group.

Economic conditions of the last few years have brought about an environment of low interest rates and extremely high home price appreciation in many areas of the mortgage market. The result of this phenomenon was higher origination volumes, particularly subprime mortgages, along with relatively low-loss expectations. The popular assumption that housing prices would forever continue their steep ascent further inflated the issue. Resulting loss levels of 2006 during what seemed to many like a utopian environment in the mortgage industry were approximately $10 billion - typical of the prior few years although volumes had increased significantly.

It was, however, this virtual utopia that contributed to the forthcoming perfect storm within the industry. The subsequent implosion of the mortgage industry led to losses in 2007 of approximately $100 billion - nearly tenfold that of the prior year - and some predict total losses related to subprime mortgage debt in the neighborhood of $450 billion.

The consequent increase in the number and volume of distressed assets poses problems for traditional servicers. The volume and complexity of the distressed asset problem created a paradigm shift for servicers. As recently as 12 months ago, servicers were largely coupon processors. Now they are asset managers, one of the few remaining ways of mitigating a tidal wave of loan losses.

In the past, servicers have relied heavily on the expertise of their people in servicing mortgage loans. This expertise was embedded in an age-old process where the expert made critical decisions regarding which path to follow to ensure maximum economic value.

Referred to here as the "expert-is-the-solution" model, servicers historically have viewed each loan as having a unique problem that required expert opinion for resolution. The primary faults of this model are that it is neither scalable nor consistent. Expert opinion differs many times and thus produces inconsistent results. Further, it is extremely difficult to find, hire and train legions of new experts especially at the rate the distressed space has grown recently.

Resolving distressed loans is now more complex than ever. The complexity of loan resolution has quickly evolved beyond the comprehension and infrastructure of the typical mortgage servicer. The multi-dimensionality created by combining the assessment of the current economic environment with the consideration of the borrower, property, product and treatment among other variables attached to servicing a pool of distressed assets is far too tall an order for a process-driven model based primarily on expert opinion.

It is becoming patently obvious that a revolutionary, not an evolutionary solution is required. Just tinkering with the existing process is not sufficient. Something new and revolutionary is required. Moreover, simply repurposing a performing asset data and analytics (e.g., a FICO score) is not enough. In fact, it is not even relevant.

The servicer needs a distressed asset-specific solution that leverages data, analytics and technology in a systematic, scalable fashion. In this approach, the data, analytics and technology are used to evaluate the distressed loan and decide on optimal processing, replacing or augmenting the expert in the former approach. The resulting business model is called the "system-is-the-solution" as opposed to the traditional "expert-is-the-solution" model currently in used.

In the system-is-the-solution model, each distressed loan is viewed as a member of a "class" of problems, each of which has a well-researched class-specific solution. The business model uses robust data and analytics to classify a loan into the most appropriate class. Once the loan is correctly classified, an optimal treatment can be applied.

Classifying a loan and assigning the optimal treatment has become a task that absorbs copious amounts of data, a huge portfolio of analytics and sophisticated optimization algorithms. In effect, it has become an analytics and information-processing problem, not a people problem.

The output of this process is an immensely complex decision tree, which is used to classify and treat the loan to produce a cash-maximizing outcome. Decision trees of over one million branches are common. This means that the system must select which one in a million branches are most suitable for this loan and guide it down this path to ensure maximum outcome. In effect, the system replaces the expert in much of the decision-making role, ensuring both consistency and scalability.

To solve the loan resolution problem and ensure maximum economic benefit requires that the expertise needed to classify and treat a loan is institutionalized in computer systems and applied via computer-driven processes, preferably those with a capability to trade off potential economic gain with risk.

The need for sophisticated, computer-based solutions is similar to what occurred in the aerospace and microcomputer industries. In both industries, task complexities evolved to the point where they exceeded human capability and forced firms (Boeing, Intex) to become extremely reliant upon institutionalized expertise computer-aided design systems. In these industries, engineers exercise the CAD system to develop ultra complex and functional designs, relying on the CAD system to apply design rules necessary to ensure a sound design. This is the perfect marriage of human insight and intuition (talented engineers) and institutionalized expertise. What only a few realize is that without a computerized source of institutionalized expertise similar to CAD, the mortgage industry cannot manage its distressed assets. The problem has become that big.

Along with the complexity of assigning a loan to the most appropriate class and determining the most appropriate treatment (e.g., loan modification) and agent (e.g., servicer), execution is another key solution dimension. A well-developed execution system is a decision distribution system that delivers robust treatment recommendations to the most appropriate agent in a timely manner. Execution also includes the ability to capture treatment, agent and performance effects to ensure that the proper treatment was offered and results are retained to eventually include in future decisioning efforts.

We believe that two dimensions will separate the winners from the losers in the distressed asset space: decisioning and execution capabilities. Decisioning capability is the ability to make a huge number of extremely complex, timely and high-quality decisions in an environment of rapid and profound change. Robust decisioning results in the accurate classification of a loan or security and the application of the most appropriate, class-specific solution. Those who can do this will have determined how to maximize the cash from fragile, rapidly changing distressed assets and will gain an advantage in the distressed asset space.

Execution capability is the ability to execute cash-flow-maximizing decisions in volume. In loan level operations, this means executing the right treatment with the right agent across thousands of decisions and agents. (c) 2008 Mortgage Servicing News and SourceMedia, Inc. All Rights Reserved. http://www.mortgageservicingnews.com/ http://www.sourcemedia.com/

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