By Joanne W. Rose, executive managing director, structured finance ratings, Standard & Poor's
The evolution of risk analysis in the structured finance market
The domestic growth in homeownership in the 1970s in the U.S. fuelled the expansion of residential mortgage-backed securities. The rating of these mortgage-backed securities involved the risk analysis of large diversified pools of mortgage loans. Other large homogeneous portfolios of consumer debt, such as credit cards, home equity loans, and auto loans, soon followed. New asset classes then emerged; these included commercial real estate loans, loans to small and medium-sized enterprises and larger corporate institutions, corporate bonds, and so on.
Over the past decade, the boundaries of the structured finance market have widened considerably to encompass not only deals for traditional funding considerations and balance sheet management but also deals done for risk management and risk transfer in the broadest sense. There has also been significant convergence between different markets. For example, the synthetic CDO market now routinely makes use of both the financial contracts (credit default swaps) and the quantitative models developed for the burgeoning credit derivatives market.
Automated origination systems and credit risk and cash flow models have shaped every component of the residential mortgage market from origination to acquisition, securitization, servicing, and secondary market trading. Advanced uses of mortgage technology have also contributed to greater efficiencies, additional diversified product offerings, and more refined risk-based pricing techniques.
All major mortgage underwriters in the U.S. now incorporate some form of credit scoring and/or mortgage scoring algorithms for qualifying borrowers and identifying the appropriate mortgage products by borrower characteristics and credit experience. This global trend appears to support similar developments by local financial institutions and non-U.S.-based companies.
Many large financial institutions across Europe and the U.K., Australia, and Canada have developed proprietary scoring systems that are being used as part of the growing trend toward risk-based pricing in the mortgage origination process. Standard & Poor's is asked with increasing frequency to use these scores in its credit analysis and to provide analytical models, similar to those in the U.S., that incorporate its ratings criteria into the marketplace's processes.
As the level of available data has increased, Standard & Poor's ability to analyze and bucket risk globally using loan-level models has expanded. In addition, the ability to mine loan-level data has become more commonplace, and the ability to create and refine models that integrate the specific nuances of each jurisdiction, such as consumer protection laws, privacy and disclosure rights, and borrower credit behavior, has grown.
Isolating credit risk through structuring
Structured finance transactions isolate the credit risk of portfolios of assets from the originator of the assets, leading to securities (liabilities) whose risk characteristics and pricing are driven primarily by the credit risk and cash flow mechanics of the asset portfolio and, to a lesser extent, by the evolution of market factors, such as interest rates, prepayments, and exchange rates. This means that risk management and pricing models must be capable of quantifying the following aspects of each transaction:
* Default and loss-given-default of each asset in the portfolio;
* The joint default and loss behavior of the portfolio as a whole;
* The impact of portfolio default and loss on the payments to liabilities; and
* The impact of market factors on the behavior of both assets and liabilities.
The quantitative models used globally by Standard & Poor's to quantify portfolio credit risk depend to a large extent on the nature of the assets. For example, large diversified consumer asset portfolios can be assessed using actuarial methods, while residential mortgage portfolios are amenable to credit-scoring techniques. On the other hand, less diversified corporate bond and loan portfolios require models based on Monte Carlo simulation. These credit risk models are then integrated with cash flow models that replicate the detailed payment priorities of each security, allowing investigation of the sensitivity of the performance of each security to both credit and market risk.
Investors demand alternative risk measures
Structured finance credit ratings are opinions on the creditworthiness of a security. However, there are many other risk measures that investors demand when forming an opinion of the relative value of a structured finance investment. These include recovery prospects, implied ratings and price volatility, and sensitivity to changes in modeling assumptions. All of these considerations could affect the risk premium an investor demands for taking a leveraged exposure to portfolio credit and market risk.
Behavior beyond the credit rating
If investors are to continue to invest in the wide array of structured securities, thus fostering the growth of this market, they must be able to manage increasingly larger portfolios. To do so, they begin with a credit rating; but they need additional information to understand behavior, not just default risk.
As always, Standard & Poor's encourages your thoughts and comments. You can e-mail us at: SF_Perspective@standardandpoors.com
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