February, 2008

To current & prospective clients:

The US housing and mortgage industries are presently experiencing their second collapse in less than two decades. And, based on results, the legacy systems of risk management have failed to protect mortgage investors and home-owners, alike.

One recent report estimates that two to three million residential properties across the US will go through foreclosure. Exclusive of the trauma to the families involved, the impact on the banking system, tax base, real estate and construction businesses will be significant. However, with an expected drop of 20% to 30% in values in many cities, some ten million properties will have debt that exceeds their market value. This leaves little incentive for those borrowers to do anything but hand the house keys to their mortgage lender should a change of residence be forced by job, health or family needs.

The securitization process, which has provided the on-going source of funds to re-invest in the housing market, saw a complete abrogation of underwriting standards along the production chain from loan originators through to the rating agencies. Further, the appraisal process has proven itself essentially ineffective as long standing appraiser-client conflicts of interest remain unresolved and valuation methodologies in increasingly complex markets approach obsolescence.

The current system effectively passes risk along to the next player in line with investors far removed from the production process left holding residential mortgage backed securities (RMBS) of questionable or declining value. Unfortunately, regulatory changes are unlikely to significantly reduce the problems as it is difficult to legislate and enforce morality in a profit driven environment.

The critical issue for RMBS investors is what happens if a borrower stops paying the mortgage. Can the market absorb the house or condo at a price sufficient to cover underlying debt and closing costs or will the mortgagee end up with the property?

Risk Management Alternatives: Barring catastrophic events, it is possible to accurately forecast, several years in advance, market-based risk for property and mortgage investors.

Using proprietary, patented algorithms, a Market Strength Index or Collateral Risk Score can be produced to accurately measure investor risk posed by the housing market. This work can be conducted immediately on a consulting basis and can potentially be made available on-line if demand from the investment and/or regulatory community so dictates. It is possible to avoid market melt-downs.

Although legacy business interests inherently resist change, it is clear they no longer serve the best interests of the housing and mortgage economy in the United States. As such, it would be prudent to ask how many more housing-related traumas mortgage banking and real estate can sustain before a broader based economic collapse results.

With more effective collateral risk management it is possible to minimize the re-occurrence of a market collapse. Application of the patented Market Strength Index and Collateral Risk Score algorithms can be a viable complement or possible alternative to legacy risk management processes. It is a responsible approach to protecting the interests of investors.

Three market studies are cited below that demonstrate the effectiveness of the patented risk management algorithms. They reflect large data samples examined over seven years in two housing markets with a combined population base of some seven million people. The studies present substantive proof that it is possible to accurately identify, years ahead of the event, which properties are most likely to be a source of loss for mortgage investors or the greatest source of appreciation for property investors.

This risk management work can be conducted immediately and in a cost-effective manner via consulting on a market by market basis. There is also the potential of creating an on-line Collateral Risk Score enterprise, similar to channels for credit risk scoring.

I invite you to contact me at the number below to discuss this work. Your questions and comments are welcomed.

Sincerely,

Robert E. Rothstein
206-525-7267

Study #1 was undertaken in 2005. This involved a sample of 108,000 sales of single family residences located in King and Snohomish Counties (Seattle & Everett) Washington that closed between January of 2002 and March of 2005. New construction, manufactured homes, houseboats and most townhouses were excluded from the study.

From this large sample of 108,000 sales, over 2,400 properties were identified where the property was held for a period of at least one year then re-sold between 1/03 and 3/05. Using the patented algorithms, a Market Strength Index (MSI) was allocated to each of the re-sold properties based upon their respective sub-markets.

A sub-market can be a property type, neighborhood, vintage or size of a home, or other type of criteria buyers might use to filter properties during a home search.

These 2,400+ re-sales were sorted by both the rate and amount of price gain over the period they were held. This group was then divided into quintiles.

Quintile #1 showed the highest average gain and the highest average MSI. Quintile #5 showed the lowest average gain and the lowest average MSI. The three middle quintiles lined up in appropriate order, as well.

A crucial item to note is that the MSI samples were generated in mid-2000, proving that the patented algorithms can accurately forecast which properties would under-perform or out-perform the overall market in terms of appreciation, three to five years ahead of the event. Note that the under-performers pose significantly higher risk of loss to lenders, borrowers, or both.

Quintile #1, the highest MSI group, outperformed the middle of the market (Quintile #3) by 31% and the lowest Quintile #5, by 62%.

Study #2 Application of the patented MSI methodology was initiated in mid-2006 and covered a data sample of nearly 54,000 sales in 70 sub-markets from the Phoenix metropolitan housing market.

During the period between May of 2006 and May 2007, the supply of available single family houses (i.e. MLS listings) in the Greater Phoenix area more than doubled, the sold volume dropped by 67% and marketing times increased about 66%. Phoenix is reportedly among the hardest hit markets from the sub-prime mortgage collapse. These changes clearly reflect a serious contraction for the Phoenix housing market.

As of May 2007, the average price for a single family residence in the Greater Phoenix market was $360,200, an increase of less than 2/10ths of a percent over May of 2006.

The 2007 update showed that the five highest indexed sub-markets from the 2006 MSI analysis experienced price increases averaging 9% with two of the ’06 performers showing price gains as high as 10% and 13%. Again, this compares to the overall 2/10ths of a percent appreciation for the market as a whole.

Thus, as demonstrated by the data from the Phoenix market, by using the patented algorithms, even during an economic contraction it is possible to accurately forecast which properties present lower risk to mortgage and real estate investors.

The table that follows details statistics from the actual MSI research. Note that, even though the index rating dropped significantly between 2006 and 2007 in each of these five sub-markets, in May of 2006, these represented some of the strongest components of the Phoenix housing market and still significantly outperformed the overall market.

Study #3: was undertaken in the summer of 2000. Some 2,000 sale transactions of single family houses and condominium units located in the King County (Seattle) area were examined where the mortgage was funded by either Citigroup or Wells Fargo Bank.

From these 2,000 transactions, 184 were identified using the patented MSI algorithms as posing high risk of loss to the lender, the borrower, or both.

It generally takes about 5% of the transaction price to close a transaction from the purchaser’s side and 10% from the seller’s side. Thus, exclusive of funds invested for property improvements or funds extracted from a refinance, any subsequent re-sales that occurred from the 2000 study were considered to be “losers” if they sold for 115% or less of the previous price.

A 2003 follow up study showed that 20% of those initially identified as high risk in 2000 came to the market in the three-year hold period. 95% of those high-risk re-sales sold for 115% or less of the previous price. Were we to be able to gather figures for cash extracted via refinance or funds spent on remodels, the 95% accuracy rate might be higher.

Please note that these algorithms have been granted two US patents with other domestic and foreign patents pending. The methodology has also been validated by an independent consulting actuary and used successfully in court and mediation venues for over a decade.

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