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The credit risk of a Commercial Real Estate (CRE) deal is associated with a highly complex and non-linear deal structure. Historically the approach to assessing the risk has therefore been to try and reduce the complexity to a linear weighting of key factors or ratios, e.g., into a scorecard. The weights assigned to each factor may be determined either through expert judgment, or if sufficient data is available, through a regression analysis. A scorecard has the advantage of being easy to explain and simple to understand. A very simple example of such a model would be to have a look-up table using Debt Service Coverage (DSC or DSCR) and Loan-to-Value (LTV) to assess the risk of a CRE deal.

In this paper we will demonstrate that taking such a simplified approach does not capture the essential risk of a CRE deal over time. Two deals with the same DSC and LTV may have significantly different risk profiles when looked at in their entirety. In fact, for the example provided in this paper, the risk (and therefore the economic capital and price) can differ by more than a factor of ten. This has significant implications for institutions that are subject to regulatory capital that is mainly dependent upon only DSC and LTV.

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