REO By The Numbers: Upgrading Disposition Strategies

REQUIRED READING: For close to a year now, real estate owned (REO) departments have been focused on preparing for the arrival of a rush of properties backlogged within predecessor departments. As a result, REO leaders have had an opportunity to focus on fine-tuning and perfecting their marketing and disposition strategies in anticipation of this spike in inventory.

However, continued foreclosure challenges and regulatory scrutiny have pushed out the arrival of much of this inventory, further delaying the pricing correction that the housing market needs. This is subsequently creating a stale, low-value market in which servicers are forced to liquidate their properties – a less-than-favorable situation.

To effectively handle current REO inventory and prepare for the potentially daunting number of properties anticipated to arrive over the next few years, servicers need to devise a methodical approach to how they develop the infrastructure that is required to analyze, process and liquidate their inventory. The following three key competencies should be present in REO operations in order to improve asset recoveries:

  • targeted data capture and data analysis to formulate property-value estimates and insights,
  • strong risk management practices and controls over key processes, and
  • decisioning tools that serve to identify the disposition channel and strategy with the highest return.

Finding the appropriate liquidation strategy for a property begins well before a property arrives in REO. Key data elements – both internal and external – need to be gathered and available to properly diagnose each situation and determine the appropriate outcome.

For servicers to be successful, they need to dig deeper into the background of
each property in order to identify which costs can be controlled versus those that cannot. For example, although there are limited actions servicers can take to mitigate the cost of health and safety repairs, servicers have more control over the amount offered to an occupant for access to the property (i.e., cash for keys) or the amount spent on discretionary property repairs.

Servicers also need to determine the liquidation levers that they can use to improve recoveries while mitigating key risks (i.e., operational, regulatory and reputational risks). Costs and expenses are critical to decisions regarding disposition strategies and channels. The ability to forecast and model REO costs and expenses at the property level allows servicers to complete cost-benefit and net-present-value (NPV) analyses that ultimately drive educated decisions.

For example, if a property is anticipated to spend several months in the eviction stage, it may make sense to significantly increase a cash-for-keys offering to further incentivize the occupant(s). When compared to the projected aggregation of carrying, eviction and potential rehab costs over those several months during eviction, the increase in cash offered is often much less.

In order to support detailed analyses, REO servicers should have decision models that can facilitate best-execution practices – essentially applying a capital-markets mind-set to REO properties. These models require robust systems that can capture key data elements, which, in turn, can be leveraged in forecasting and estimating hold times and expenses.

When successfully developed and implemented, these models or tools allow servicers to focus on improving net realizable value (net liquidation proceeds less all holding and servicing expenses) via NPV decision analysis that takes into account acquisition costs, as well as estimated holding times and expenses, at a daily interval. Introducing the concept of a "daily burn rate" allows for improved channel selection, which can lead to increased recoveries on the asset.

In order to properly structure the exercise of calculating the cost to liquidate a property through REO disposition (including multiple disposition scenarios), REO servicers need to partner with their upstream default counterparts to agree upon calculation methods, assumptions, data refresh, back testing and data ownership.

These groups can then have a unified method for determining what the potential disposition value is for a given property. Any properties that could potentially create extended liquidation times or costs in excess of liquidation value should be analyzed by an upstream default group and potentially selected as a candidate for alternative or early disposition.

Once a detailed understanding of all the incurred and potential costs/expenses associated with each of the disposition channels is calculated, choosing the appropriate path becomes an exercise in identifying the largest potential recovery. For instance, although one sales offer may present a lower net proceeds figure, it may carry a much lower probability of falling out (i.e., it could be a cash or non-Federal Housing Administration financing purchase) and, therefore, be a much better option than other offers presented.

The cost of having an offer fall out (additional marketing and carrying time) can quickly absorb the price difference between those offers. As in any modeling situation, however, the output is only as good as the quality of the inputs and assumptions. As such, data integrity is critical.

Translating data into results

Once the REO asset management team has determined the estimated net proceeds/REO liquidation value for a property, the focus then shifts to analyzing the different disposition methods available. Although the large majority of properties that are sold by REO servicers are done so through the traditional "listing with an agent" method, there are several different options that should be considered for disposition.

Properties that servicers may not have the appetite to repair or that are located in areas of high REO concentration typically present good opportunities for sale through an auction or bulk sale. These options provide the servicer with an easy-to-assemble housing package (for bulk sales) and/or a property that has the potential to attract interest from a party that has the ability to rehab and return a profit.

In all portfolios, there are properties that are easy to identify early on – long before REO – that will provide very little, if any, net proceeds through REO liquidation. These may include properties located in low-value areas, as well as properties where only extensive investments in health and safety repairs will bring the property up to the condition of being eligible for traditional liquidation methods. In these cases, servicers can work proactively with city, community and non-for-profit groups to reduce low-value inventory and provide a benefit to the community through alternative disposition methods (e.g., donations).

Although liquidation is typically the most common strategy for REO servicers, the prolonged housing-price-index woes present the need for alternatives to the traditional REO model of liquidating inventory sooner rather than later. Included in the liquidation analysis should be a rental-income assumption. Many properties in areas of high REO concentration may sit on the market and present challenges for servicers in terms of vandalism risk, unauthorized occupants seeking cash for keys, and the upkeep costs of a vacant property (not to mention the stigma accompanying the property, which can bring down value).

In addition, the introduction and implementation of new legislation at the local level (city ordinances) is compounding the costs and complexity for servicers with inventory footprints in those respective areas.

To help mitigate these risks, servicers may consider renting properties not only to hedge their cash outflow with income, but, more importantly, to keep families in homes and prevent neighborhoods from becoming blighted. Taking it a step further, servicers may also consider developing rent-to-own strategies for their properties. The rent-to-own option provides an exit strategy for servicers in terms of the property. It also provides the occupant(s) an interest in the property, hedging a liability risk for the servicer, while allowing some time for market recovery.

However, prior to the implementation of these programs or others like them, servicers need to evaluate whether they have proper controls and risk management in place. Extended occupancy periods expose servicers to additional risks, such as potential liability suits, additional maintenance responsibilities, property neglect (if the occupant does not provide upkeep) and additional reputational risks that must be evaluated prior to undertaking these strategies.

Recent industry pressures and crisis events have exposed weaknesses in the risk and quality programs of many servicers. Over the years, quality and risk frameworks have lost some of their strategic alignment and have become very reactive in nature.

As a result of the soaring cost of risk events, coupled with increased regulatory oversight, risk and quality have jumped to the forefront. REO servicing should be no different than other parts of the servicing operations in this regard. Sound risk management and quality practices are a necessary requirement, and those shops that do it well will likely enjoy a competitive advantage over industry peers.

Similar to the discussion around liquidation strategies, robust analytics have a strong role to play in effective risk management. Detailed analytics that harness operational and financial data can help facilitate proper oversight of key processes and confirm that controls are operating as intended. Historically, REO servicers have measured their performance based on limited and post-transaction data points, such as reconciled value (combination of an appraisal, broker price opinion and automated value points), days on market, and net proceeds.

However, servicers should be expanding their use of available data from servicing systems, workflow tools and vendors to gain insight into the key components that formulate the aforementioned key indicators. For example, if a servicer is obtaining poor-quality valuation data points (i.e., values that are significantly below market) in their property-value reconciliation calculation and their net proceeds are matching reconciled value, that servicer may believe that it is performing very well, when, in fact, significant opportunities are being left on the table. A likely outcome here could be that the servicer's properties are being resold shortly after the servicer liquidates and that another party is realizing large gains through a subsequent disposition.

Managing the risks associated with REO properties requires a quality-assurance program that monitors controls of key business processes and provides decision-making oversight. REO areas such as the management of listing agents, list price adjustments and approval authorities governing offer acceptance all require the proper controls and oversight to drive best execution. Utilizing available data can help servicers develop a strong quality-assurance program, integrate key controls into their business process and ensure operational excellence.

In addition, quality control should not always be conducted post-transaction. There are areas in the REO process, such as valuations, where quality control can be done "in flight" to identify any issues and allow for remediation prior to completing the transaction.

Although risk management programs and controls are critical to success, so is having adequate staffing in order to effectively manage and execute on the inventory. Excess REO inventory levels and roll-rate fluctuations can make it difficult to plan for adequate staffing capacity. The risks and costs associated with poor capacity planning will increase significantly in a bubble environment.
Today's capacity models typically project future REO volume based on historical patterns that quickly become irrelevant in a period of rapidly increasing volumes. For more effective capacity planning, models should be enhanced to factor in historical data as well as internal and external leading indicators. An example of an internal indicator is increased volume in the foreclosure or short sale departments, which signals more volume on the way in the form of REOs.

Additionally, external factors – including the recent foreclosure moratoria that temporarily halted foreclosures but resulted in a larger buildup of properties set to emerge as REOs – should be considered. Robust models should also be able to account for protracted foreclosure timelines, potential legislative and macroeconomic impacts, existing portfolio behaviors, migration patterns and timelines, and internal-versus-external resourcing.

To further refine capacity modeling, servicers should also consider factoring in the resource needs at various stages of the REO life cycle. For example, occupied REOs will require resources to handle evictions and the potential legal issues that could arise. Forecasting the volume of work at each of the major stages of the REO process can serve to refine capacity planning, enabling a servicer to better manage large volumes.

Today's market poses several challenges for REO servicers, but it is also an opportune time to either start or continue planning for what lies ahead. Effective decision tools with quality inputs and assumptions, along with robust capacity-planning capabilities, are cornerstones for success.

In addition, risk and quality management must be paramount in all parts of the operations and culture to successfully navigate the new market environment. Opportunities exist to take a much more proactive view of REO inventory and begin to develop disposition strategies well before properties hit REO, including deed-away programs, more deeply discounted short sales or other nontraditional strategies that make economic sense. Focusing on these items can provide a competitive advantage and help to optimize recoveries.

Carlos Brunet is a senior manager, and John Beyer is a manager, respectively, in PricewaterhouseCoopers' Consumer Finance Group. Brunet can be contacted at, and Beyer can be reached at


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