Structured Finance. Criteria for Rating U.S. Auto Lease ABS. Asset-Backed Securities / U.S.A. Sector-Specific Criteria. Key Rating Drivers

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1 Criteria for Rating U.S. Auto Lease ABS Sector-Specific Criteria Asset-Backed Securities / U.S.A. Key Rating Drivers Inside This Report Page Key Rating Drivers 1 Data Adequacy and Compliance 2 Collateral Analysis 2 Loss Analysis 6 Residual Value Risk 8 Structural Analysis and Cash Flow Modeling 15 Rating Sensitivity Analysis 19 Legal Analysis 20 Counterparty Risk 21 Performance Analytics 24 Criteria Scope and Limitations 26 Appendix 1 Hypothetical XYZ Trust An Illustrative Example 26 Appendix 2 U.S. Auto Lease ABS Request List 30 This report replaces Criteria for Rating U.S. Auto Lease ABS, dated May 24, This updated criteria report is substantially unchanged from the prior report. Related Research Fitch Auto ABS Dashboard April 2012, April 30, 2012 In the Auto ABS Driver s Seat, May 10, 2012 Lease-End Residual Risk: Fitch s analysis of auto lease securitizations places particular focus on residual value risk. Fitch s analysis of residual value risk in any given lease securitization is largely driven by the issuer s historical residual value loss rates and the potential volatility of the future used vehicle market. Historical worst case, month observations are typically set at the BBsf rating level, with increased residual realization stresses associated with the investment-grade rating categories, as described more fully in the report. Lessee Credit Risk: Fitch analyzes static pool data, including lease delinquencies, defaults, net losses, recoveries, the associated timing of these defaults and losses, and prepayments. Both industry and originator data are assessed, with greater weight afforded to originatorspecific data, which are often more detailed and viewed as a more accurate representation of risk in the subject portfolio. Base case losses are stressed increasingly for various rating scenarios, according to the multiples described in the report. The credit risk analysis of auto leases is substantially the same as the approach employed for auto loan ABS. Concentration Risks: Auto lease pools and notably, residual loss performance can be notably impacted by concentrations in the underlying leases or vehicles. Concentrations in vehicle model or segment can expose the trust to idiosyncratic risks affecting specific vehicle types. Additionally, material concentrations in the timing of lease maturities can expose the ABS performance disproportionately to periods of elevated residual losses. Fitch s quantitative analysis explicitly accounts for concentration risks as described in this report. Counterparty Risk: This portion of the analysis is largely qualitative and includes a review of seller/servicer operations. Certain findings of the originator, seller, and servicer reviews may result in quantitative adjustments to the assumptions used to generate base case and stressed credit and residual value losses. Fitch s assessment of other counterparty-related risks, such as commingling of lease payment collections and segregation of bank accounts, are addressed in Fitch Research on Counterparty Criteria for Structured Finance Transactions, dated March 12, 2012 (Counterparty Criteria) and further described in this report. Macroeconomic Risks: The economic environment can have a material impact on U.S. auto lease ABS ratings. As such, Fitch takes into consideration the strength of the economy, as well as future expectations, by assessing key macroeconomic indicators. Analysts Bradley Sohl bradley.sohl@fitchratings.com Margaret Myers margaret.myers@fitchratings.com Peter Chung peter.chung@fitchratings.com John H. Bella, Jr John.bella@fitchratings.com

2 Key Changes to This Criteria Report The updated criteria for rating U.S. auto lease ABS are effective for new and existing ratings as of May 11, All criteria discussed herein are substantively the same as the prior criteria and will apply to the existing portfolio of auto lease ABS ratings. No rating changes are expected to result from the incorporation of these criteria. Data Adequacy and Compliance Fitch s auto lease ABS rating methodology relies on historical performance data as a key input in forming an expectation of future pool performance. Fitch expects to receive at least five years of historical static net loss performance data to support its analysis of credit losses. Additionally, Fitch expects to receive several years of residual loss performance data of the manufacturer and models to be included in the pool. The number of years of residual data provided may vary by issuer. However, to apply the criteria described in this report, Fitch must be comfortable that the residual data provided captures the periods of greatest residual losses on record. For most originators and the industry as a whole, this period will include Fitch may utilize available market-level data or proxy data from various other issuers in situations where issuer-specific data are deemed insufficient. Historical data analysis may also be deemed inadequate by Fitch due to (but not limited to): limited data availability; or a lack of granularity within the underlying pool. In such cases, Fitch will determine the applicability of these criteria versus alternative ratings approaches. Where these criteria are deemed not to be applicable, the criteria applied by Fitch will be highlighted in Fitch s transaction rating reports. If data provided are inadequate or insufficient, Fitch may decline to rate or implement a rating cap on a transaction. Related Criteria Rating Criteria for U.S. Auto Loan ABS, April 16, 2012 Global Structured Finance Rating Criteria, Aug. 4, 2011 Counterparty Criteria for Structured Finance Transactions, March 12, 2012 Criteria for Interest Rate Stresses in Structured Finance Transactions, March 20, 2012 Criteria for Servicing Continuity Risk in Structured Finance, Aug. 12, 2011 Criteria for Special-Purpose Vehicles in Structured Finance Transactions, June 13, 2011 Criteria for Rating Caps in Global Structured Finance Transactions, Aug. 9, 2011 Global Rating Criteria for Structured Finance Servicers, Aug. 13, 2010 In forming residual value loss expectations and analyzing historical vehicle value volatility, Fitch relies on aggregated residual value and wholesale vehicle market data provided by issuers, historical experience on hundreds of prior auto loan and lease securitizations, and data provided by third-party sources. Third-party data sources include vehicle auction houses, such as Black Book USA, Manheim Consulting, ADESA, NADA, Automotive lease guide (ALG), and other vehicle valuation data providers. All of this data combined provide Fitch with nearly 20 years of vehicle wholesale value volatility data, which reflect trends observed across the tens of millions of used vehicle dispositions that occur annually in the U.S. Much of the residual loss and auction performance data provided are stratified to the vehicle segment, model, and unit level, enabling Fitch to evaluate trends within specific collateral types. Analytical Approach The two primary risks in auto lease ABS are lessee credit risk and residual value risk. Fitch s analysis of auto lease securitizations focuses on: An analysis of the collateral pool to determine factors that influence the securitization s credit and residual value risk. Developing base and stress case credit and residual loss assumptions for each rating category. Collateral Analysis Certain characteristics of auto lease collateral pools can have a significant impact on the amount of credit and residual risk present in the ABS transaction. While some characteristics, Criteria for Rating U.S. Auto Lease ABS 2

3 such as credit scores, have a direct impact on credit losses, others, like lease term, could impact both credit and residual loss performance. Fitch assesses the characteristics of the lease contracts and vehicles securing the auto lease transaction to determine the risks presented by that specific pool. This review focuses on the following collateral characteristics: Obligor credit quality. Residual value composition. Lease term and rate. Residual value maturity distribution. Vehicle make, model, and segment concentrations. Vehicle condition (new/used). Geographic distribution. Additionally, Fitch compares the collateral attributes of a proposed ABS transaction to those of previously securitized pools to determine whether loss expectations based on collateral characteristics are consistent with the performance experienced in prior securitizations. Obligor Credit Quality and Scoring Credit default frequency in auto lease securitizations is highly correlated to the overall financial health of lessees. Originators often rely on proprietary scoring models that rank obligors by expected default probability. Many of these models incorporate Fair Isaac Corp. (FICO) scores as an input but augment them with other predictive variables, such as personal leverage ratios. Fitch may utilize the originator s internally derived scores during the credit analysis of a pool of leases in combination with analysis on FICO and other credit-related stratifications. Specifically, Fitch may utilize static pool default data segmented by originator credit score in its derivation of base case credit loss assumptions (see Credit Analysis/Static Pool Analysis section, page 6). However, to do so, Fitch will assess the predictive capacity of the credit scores relative to other predictive variables and review any material changes made to scoring methodology over time that could impact the predictability of the scores. Fitch examines static pool data segmented by FICO score and internal credit tier or score classifications to gauge borrower strength, default performance, and the predictability of scoring models. The combined loss expectation for a securitized pool reflects Fitch s expectation for each tier and its weight within the pool. Residual Value Composition A key variable between securitization pools and individual leases is the relative size of the lease-end residual. Auto lease contractual payments are typically more reliable in that they are only exposed to lessee default risk. Meanwhile, losses on the residual component of a lease have historically been more volatile. The larger the residual component of a lease or securitization pool, the more secondary vehicle market risk the pool is exposed to. Therefore, all things being equal, a pool in which expected residual proceeds represent 80% of securitization cash flows would have a higher loss expectation, and thus expected loss protection, than one in which residual proceeds represent only 60%. The residual value composition of a portfolio is explicitly incorporated into Fitch s cash flow modeling for auto lease ABS. Lease Term Fitch has observed that default frequency and severity generally increase for leases with longer original terms. Such leases also exhibit more volatile recovery and residual value realization Criteria for Rating U.S. Auto Lease ABS 3

4 rates, as the originator must attempt to predict residual values further in the future. An adequate dispersion of original lease terms mitigates the risks associated with such leases. The higher default frequency for longer-term leases is often attributable to credit underwriting, which often relies on payment-to-income ratios (PTI), among other factors. For certain lessees to qualify for lease financing, the monthly payment may need to be lowered to bring the PTI to an acceptable level. This is typically achieved by lengthening the contract term. Another risk associated with a longer-term lease is that the contract balance amortizes more slowly, increasing loss severity in the event of lessee default. Lease terms are explicitly considered in Fitch s analysis of both credit and residual losses, as derived loss expectations incorporate a review of historical default and residual loss data stratified by the original lease term. Residual Value Maturity Distribution Fitch specifically incorporates the contract maturity distribution in its derivation of base and stress case credit losses, as described later in this report. In many transactions, the remaining term distribution can be more meaningful than the original term distribution. If a large portion of the ABS pool s lease contracts mature within a short period, the potential for residual losses to affect bond cash flows negatively is heightened. First, if the concentrated period coincides with a weak wholesale vehicle market, the pool will have significant exposure to that single market cycle. Additionally, if an excessive number of leases supported by similar vehicles are due to mature in the same period, the supply shift could have a negative impact on sales proceeds. A pool with well distributed contract maturities mitigates such risks. Vehicle Make, Model, and Segment Significant exposures to specific vehicle makes, models, and segments may expose an ABS pool to additional counterparty or event risks. The primary risk of manufacturer and model concentrations lies in the potential for a negative event, such as a manufacturer bankruptcy, to affect the depreciation, brand value, and demand for those vehicles, thus reducing recovery and residual value realization rates. Fitch has observed that concentration by vehicle segment (sport-utility vehicle [SUV], crossover utility vehicle [CUV], luxury sedan, sports vehicle, minivan, and light van or truck, among others) can also affect residual value performance in auto lease securitizations. A significant concentration in a particular vehicle segment increases the potential for event and market risk to affect the securitization negatively. Event risk results from the potential for a specific external event, such as increasing fuel prices, tougher emissions standards, or increased safety requirements, to reduce the demand for a vehicle segment. Similarly, market risk arises due to falling consumer demand for a particular vehicle type that is unrelated to any external event, as illustrated by the migration from minivans to SUVs and CUVs. Pools with significant model concentrations are subject not only to the above risks associated with vehicle segments, but also to potential problems related to the specific model, such as recalls. Fitch specifically accounts for vehicle manufacturer bankruptcy risk, brand eliminations, and make, model, and segment concentrations in its residual value analysis of auto lease ABS pools. As described later in this report, Fitch s residual loss expectation is derived on a vehicle model level basis. Additionally make, model, and segment concentrations are specific inputs in the derivation of the ultimate haircut to be utilized for each stressed rating category. This will result in higher residual realization haircuts to account for the heightened risk of event risk in cases where material concentrations are present. Criteria for Rating U.S. Auto Lease ABS 4

5 Lease Rate Fitch not only considers the weighted average lease rate, but also the distribution of these rates when analyzing auto lease ABS. Lease rates are primarily a function of the lessor s tiered pricing strategy, with higher lease rates assessed to lessees with a higher risk profile. Lease rates are also a function of the market environment at the time of origination. Therefore, two otherwise identical pools originated by the same issuer may have different weighted average lease rates. Another key driver of lease rates is lease rate subvention programs. Lease rate incentives or subvention provides for lease rates that are below market levels as a result of financial support, provided by either the vehicle manufacturer or a finance company. These programs are typically offered by the captive finance companies to strong borrowers who demonstrate excellent credit characteristics. These better quality obligors would typically perform better than those not eligible for a lease rate subvention program. The poorer relative credit quality of high-rate leases will generally be captured in Fitch s derivation of base case loss assumptions based on obligor credit quality. However, Fitch may employ cash flow stresses, as described later in this report, to simulate excess spread compression that may result from higher default experience on higher yielding leases. Vehicle Condition (New/Used) To date, most auto lease ABS pools have primarily consisted of new vehicle contracts. Used vehicles tend to present a number of significant challenges. Importantly, forecasting residual values at lease inception can be more challenging considering the expected age of the vehicle at ultimate disposition. Additionally, Fitch has observed the credit quality of used vehicle lessees to be historically worse than that of new vehicle lessees, as payments on used vehicle leases can be significantly lower. For transactions that include a significant amount of used vehicle leases, Fitch expects to receive static pool credit loss performance and historical residual value loss data for used vehicle leases. This segmented data will be utilized in Fitch s credit and residual loss derivation. As a result, lease pools with significant used vehicle lease concentrations will often carry higher base case residual loss assumptions (See Residual Value Loss Rate section, page 9). Geographic Distribution A pool of auto lease receivables that exhibits geographic diversification minimizes potential exposure to regional economic downturns. Fitch closely examines the measures a lender employs to minimize portfolio exposure to local economic events. For material concentrations, Fitch analyzes available performance data by geographic region to determine how the concentrated regions perform. Fitch may apply adjustments to the base case credit loss proxy of a pool if significant state or regional concentrations are present. Such adjustments are described in more detail in Fitch Research on Rating Criteria for U.S. Auto Loan ABS, dated April 16, 2012, available on Fitch s Web site at Most servicers utilize sophisticated models and a national footprint of auto auctions to determine how to maximize net sales proceeds. This often involves transporting vehicles to regions other than where they were returned. This practice helps mitigate residual risks associated with specific regions. However, there will typically be increased costs of disposition for transportation and storage in these cases, decreasing the net proceeds available to the Criteria for Rating U.S. Auto Lease ABS 5

6 trust. In cases where material single state or regional concentrations are present, Fitch may employ higher residual realization haircuts to account for the potential increased cost of disposition, as described later in this report. Loss Analysis Lessee Credit Risk Credit-related losses in auto lease securitizations are realized when a lessee defaults and proceeds from the sale of the repossessed vehicle, insurance claims, and judgments collected from the lessee are insufficient to cover the remaining securitization value (SV) of the lease. Static Pool Analysis Fitch s determination of expected credit defaults and net losses is substantially the same for auto loan and auto lease securitizations. As in auto loan securitizations, Fitch s basis for the analysis of lessee default behavior in lease securitizations is static pool loss data. Static pool data are useful in determining both the historical magnitude and timing of losses and provide one of the best indications of how the underlying collateral will perform in stress scenarios. Static pool analysis relies on the isolation of static subsets of originated leases (vintages) and detailed tracking of the performance of the vintage over time. Fitch analyzes static pool data, including lease delinquencies, defaults, net losses, recoveries, the associated timing of these defaults and losses, and prepayments. Static pool data may also be derived specifically from securitization pools. While data from existing securitizations are useful, data derived from the originator s total managed portfolio are often more detailed. Fitch seeks the highest level of detail possible in static pool data, capturing portfolio performance by numerous factors, including new and used vehicles, lease terms, and credit scores as well as multivariate combinations of these factors. This level of granularity is critical in helping Fitch understand the unique credit loss drivers associated with each issuer s portfolio. Static pools capture performance over a specific period, and, thus, their performance is influenced by prevailing macroeconomic conditions at the time. Consequently, Fitch evaluates the economic conditions present for the period captured with each static pool and may adjust loss expectations to reflect economic expectations during the term of the transaction. Changes in underwriting guidelines may also result in future pool performance that is inconsistent with historical performance. Therefore, Fitch reviews changes made to a lessor s underwriting guidelines over time and may adjust current loss expectations as appropriate. For a full description of how Fitch utilizes static pool default and loss data to forecast expected credit loss performance, see Fitch s auto loan ABS criteria report titled U.S. Auto Loan ABS Rating Criteria, dated April 16, 2012 and available on Fitch s Web site Conversion of Credit Losses to Securitization Value The majority of static pools are derived based on defaults and losses incurred against the contractual book value (BV) of the leases. In contrast, the majority of securitized lease assets are discounted at an interest rate higher than the asset yield and may be securitized utilizing a residual value other than the contractual value. This is often referred to as the lease s securitization value (SV). Both of these factors contribute to creating a mismatch under which Criteria for Rating U.S. Auto Lease ABS 6

7 base case cumulative net loss (CNL) assumptions derived using BV may not be directly applicable to the securitized assets and require a conversion. The table to the right highlights how net losses on a single defaulted vehicle may differ when calculated using BV versus SV. In the provided example, the BV of a defaulted lease contract was $20,000 while the SV of the same lease would have been $18,500. The servicer was able to recover $12,000 after the vehicle securing the defaulted lease contract was repossessed and sold through a wholesale auction. The recovered $12,000 translates into net losses of $8,000 ($20,000 minus $12,000), or 40% ($8,000/$20,000) of the BV of the lease. The same $12,000 recovery generates a loss of $6,500 ($18,500 minus $12,000), or 35% ($6,500/$18,500) of the SV of the lease. As demonstrated in the example, the lower SV results in lower credit losses generated because the recovered amount is applied to the lower balance. As a result, when applicable and where sufficient data are available, Fitch adjusts the base case CNL derived off the BV to reflect the lower SV of the securitized lease assets. For example (see the bottom table at right), a lease pool with a BV of $1 billion has an SV of $800 million, an unadjusted CNL of 1.0%, and a 50.0% recovery rate, Book Value vs. Securitization Value CNL (Single Vehicle) Book Value (BV) ($) 20,000 Securitization Value (SV) ($) 18,500 BV Default ($) 20,000 Recovery ($) 12,000 BV CNL ($) 8,000 BV Recovery (%) 60 BV CNL (%) 40 SV Default ($) 18,500 Recovery ($) 12,000 SV CNL ($) 6,500 SV Recovery (%) a 65 SV CNL (%) 35 a Calculated as recoveries divided by securitized value ($12,000/$18,500). Book Value vs. Securitization Value CNL (Securitized Pool) Book Value (BV) ($) 1,000,000,000 Securitization Value (SV) ($) 800,000,000 BV Default ($) 20,000,000 Recovery ($) 10,000,000 BV CNL ($) 10,000,000 BV Assumed Recovery (%) 50.0 BV CNL (%) 1.0 SV Default ($) 16,000,000 Recovery ($) 10,000,000 SV CNL ($) 6,000,000 SV Recovery (%) a SV CNL (%) 0.75 a Calculated as recoveries divided by securitized value. resulting in an implied gross default rate of 2.0%. The above assumptions translate into $20 million of defaults with $10 million of both recoveries and losses. Fitch adjusts the gross default levels of $20 million proportionally to account for the difference between BV and SV. In this example, the adjustment results in assumed SV defaults of $16 million (2% of $800 million). Applying the same $10 million in recoveries, net losses are only $6 million, or 0.75%, compared with the BV-based estimate of 1.00%. Fitch s methodology for adjusting base case CNL to the SV is highly sensitive to recovery assumptions. As such, Fitch places an emphasis on receiving reliable historical recovery data from the issuers. If such data are not available, Fitch will not make the described adjustment and will utilize a CNL proxy derived off the BV static loss curves. The magnitude of the adjustment (if any) will be disclosed in the deal-specific reports. Criteria for Rating U.S. Auto Lease ABS 7

8 Stressing Credit Losses Fitch Auto Lease Credit Loss Rating Multiples (x) Rating Prime Rating Nonprime Rating Category Multiples Multiples AAA AA A BBB BB B Note: These represent typical Fitch rating multiples for the prime and nonprime auto lease segments. After deriving the base case credit loss assumption for an auto lease pool, Fitch employs stress multiples commensurate with each rating category. Fitch s credit loss multiples for auto lease ABS are consistent with those utilized for auto loan ABS and are displayed at left for prime and nonprime securitizations, respectively. Most prime transactions will utilize multiples of 5.0x for AAA, 4.0x for AA, 3.0x for A, and 2.0x for BBB. However, the multiple will be determined by Fitch on a transaction-specific basis, in conjunction with the base case assumption, and can vary due to certain factors identified in the Qualitative Considerations section on page 13. Residual Value Risk The residual value is the expected sale price of the vehicle at the end of the lease term. Upon lease maturity, the lessee can either purchase the vehicle for the contracted residual value or return the vehicle to the lessor, who subsequently sells it either to an affiliated dealer or in the used vehicle market. If the lessor is unable to sell the vehicle in the open market for at least the contracted residual value, a residual loss will be realized. In an auto lease securitization, the risk that a vehicle s fair market value will be less than its stated residual value at lease end is passed through to investors since the securitized value of the lease typically includes the residual value of the leased vehicle. Since residual values typically represent a large portion of a securitization s initial balance (50%80% on average), realization of residual values emerges as the primary risk in an auto lease securitization. As such, Fitch s analysis of auto lease securitizations places particular focus on residual value risk. Fitch s analysis of residual value risk in any given lease securitization is largely driven by the issuer s historical residual value loss rates, characteristics of the ABS pool, and Fitch s expectations for the state of the used vehicle market. Turn-in Rates The proportion of lessees who do not purchase their vehicle at the end of the lease contract or return the vehicle during the term of the contract is measured by the turn-in rate. Turn-in rates measure the portion of the lessor s portfolio that is eventually sold in the open market and, hence, exposed to residual value risk. Turn-in rates are affected by a number of factors, including the condition of the new and used vehicle markets, financial conditions of borrowers, and the structure of lease terms. Turn-in rates can also vary significantly depending on the manufacturer and even popularity of the individual model. While turn-in rates vary by issuer, Fitch assumes that 100% of vehicles not assumed to default will be turned in for all stressed rating categories. While this is a conservative assumption, Fitch views it as appropriate to assume that an auto lease ABS will be exposed to all potential residual risk in the pool in stressed scenarios. In addition, Fitch reviews historical turn-in rate data to determine the volatility of historical turn-in rates. This review helps Fitch determine whether or not a specific issuer s historical residual loss data reflect periods of high turn-in rate experience. If an issuer has not been exposed to high turn-in rates in the past, Fitch may utilize a larger residual value haircut to account for the fact that the lessor s historical residual realizations may not reflect the potential effects of oversupply resulting from elevated lease turn-in rates. The derivation of the residual realization haircut and the importance of historical turn-in rates are discussed specifically in the Residual Value Haircut section (see page 12). Criteria for Rating U.S. Auto Lease ABS 8

9 Residual Value Loss Rate To determine base- and stress-case residual losses, Fitch relies primarily on a combination of the historical residual value realization experience of an issuer and deterministic haircuts to account for the relative uncertainty of future wholesale used vehicle market conditions. Fitch reviews the historical differentials between the expected residual value realization levels forecast by the issuer or third parties, where applicable (such as those produced by ALG), versus the actual residual value realization data for each issuer. Due to varying manufacturer popularity and residual-setting policies, static residual value realization experience may vary significantly by vehicle manufacturer. Moreover, residual realizations for the same manufacturer often vary significantly by model, vehicle segment, and lease term. Fitch requests historical residual realization data stratified by various combinations of the above characteristics (i.e. model by term). Deriving the Base ( Bsf ) Case To determine a base case assumption, Fitch reviews historical residual loss experience specific to the majority of the vehicle models present in the pool stratified by term. Fitch focuses on the total historical average in the derivation of the base case. The derived model and term-specific average historical loss assumptions are then weighted according to the composition of the ABS portfolio to derive a pool-specific base case residual loss assumption. Where performance is expected to be stable and consistent with historical experience, Fitch views this base case derived level as the equivalent of a Bsf rating scenario. Where transaction performance is expected to depart from historical averages (e.g. entering an economic downturn), upward adjustments may be applied based on an assessment of the expected impact of macroeconomic and automotive market conditions on residual values, when deriving the base case. Fitch s Bsf ratings indicate that material default risk is present, but a limited margin of safety remains. Financial commitments are currently being met; however, capacity for continued payment is vulnerable to deterioration in the business and economic environment. Covering for only the average historical residual losses would subject a class to potential default in the event of macroeconomic deterioration. Deriving the BBsf Case In auto lease ABS, Fitch utilizes the BBsf rating stressed assumptions as the anchor of all investment-grade rating scenarios ( BBB sf and above). To derive residual loss assumptions for the BBsf rating category, Fitch focuses its analysis on periods that have exhibited the greatest residual losses on a historical basis. For many issuers, this period will include 2008, a year when extreme residual value volatility tied to increased fuel prices, manufacturer uncertainty, and general macroeconomic weakness was experienced. Specifically, for pools with diversified contract maturity profiles, Fitch derives its BBsf rating case as the worst month average historical loss level, weighted by model, term, or segment composition of the proposed ABS portfolio. The specific time period utilized for this average (within 1218 months) may vary by transaction based on multiple factors, including the relative RV maturity concentrations, Fitch s current outlook on the near-term wholesale used vehicle market, and historical RV loss volatility. If sufficient data are available, Fitch will also review vehicle auction proceeds during these periods. Fitch may adjust the BBsf loss levels to account for significant fluctuations in the residual-setting policies of the issuer or third-party forecasts. For example, if third-party residual Criteria for Rating U.S. Auto Lease ABS 9

10 forecasts for a similar model/lease term were to increase well outside historical norms without sufficient justification as to the rationale for such increase (i.e. constrained future supply), Fitch may assume larger BBsf residual losses than would be suggested by historical data. Any such adjustment will be detailed in the applicable transaction rating report. Sample BBsf Residual Loss Derivation XYZ Trust A simplified illustration of a BBsf residual value loss analysis is provided below. The data provided show quarterly residual losses against the relevant benchmark used in determining the securitized residual value. This can be the contractual residual value at lease inception, a third-party forecast at lease inception, or other potential benchmarks. In this case, losses are presented relative to a thirdparty forecast at lease inception, as the transaction s securitization value is based on the same forecasts. In essence, the BBsf case can be considered a stress to the accuracy of historical residual setting policies. However, as the focus is on the period of greatest inaccuracy, Fitch views this stress as greater than a base case scenario. The percentages in the top portion of the table represent the difference between the actual sales proceeds and the initially forecast sales proceeds for those vehicles at lease termination. Negative numbers represent residual losses. XYZ Trust Historical Residual (Loss)/Gain (%) Pool Weight 4Q10 3Q10 2Q10 1Q10 4Q09 3Q09 2Q09 1Q09 4Q08 3Q08 2Q08 1Q08 4Q07 3Q07 Model (0.0) (1.1) (2.0) (2.1) (3.3) (7.5) (7.8) (9.0) (4.0) (2.6) (2.2) (1.0) 1.5 Model (0.1) (1.4) (2.1) (2.2) (3.7) (7.0) (10.9) (12.2) (8.2) (3.0) (2.8) (1.5) 2.2 Model (0.6) (1.5) (3.1) (4.2) (4.9) (8.1) (10.9) (13.6) (12.4) (7.4) (4.0) (3.4) (2.7) (2.4) Model (0.7) (2.9) (4.1) (4.5) (4.8) (8.6) (11.5) (12.9) (13.4) (2.9) (2.6) (0.6) (0.4) Periodic WA Residual (Loss)/Gain (0.5) (2.0) (2.9) (3.2) (4.9) (8.3) (11.3) (12.0) (8.4) (3.2) (2.9) (1.6) 0.6 XYZ Pool Weighted RV Losses Maximum Loss 4Q10 3Q10 2Q10 1Q10 4Q09 3Q09 2Q09 1Q09 4Q08 3Q08 2Q08 1Q08 4Q07 3Q07 Three-Month Average (12.0) 0.1 (0.5) (2.0) (2.9) (3.2) (4.9) (8.3) (11.3) (12.0) (8.4) (3.2) (2.9) (1.6) 0.6 Six-Month Average (11.7) (0.2) (1.3) (2.5) (3.1) (4.1) (6.6) (9.8) (11.7) (10.2) (5.8) (3.0) (2.2) (0.5) 12-Month Average (10.0) (1.4) (2.2) (3.3) (4.8) (6.9) (9.1) (10.0) (8.7) (6.6) (4.0) (1.8) 15-Month Average (9.0) (1.7) (2.7) (4.3) (6.1) (7.9) (9.0) (8.6) (7.6) (5.6) (3.1) 18-Month Average (8.0) (2.3) (3.6) (5.4) (7.1) (8.0) (8.0) (7.7) (6.6) (4.6) XYZ Trust Residual Loss Analysis BBsf Derivation (Pool-Weighted Residual Losses/Gains) 0 (2) (4) (6) (8) (10) (12) (%) 12-Month Average 15-Month Average 18-Month Average 4Q10 3Q10 2Q10 1Q10 4Q09 3Q09 2Q09 1Q09 4Q08 3Q08 2Q08 In this case there are four vehicle models that comprise the entire portfolio. Residual value losses are first weighted based on the model composition in XYZ trust to derive the poolspecific quarterly weighted average residual loss experience. This experience is then Criteria for Rating U.S. Auto Lease ABS 10

11 aggregated into multiple time spans. As discussed above, Fitch s BBsf case considers the peak historical 1218 month residual loss experience. In the example below this ranges from 8.00% for 18 months to 10.00% for 12 months. Utilizing months of data provides some benefit for the maturity diversification of the portfolio, as residual values have historically evidenced cyclicality and rarely remained at severely depressed levels for more than six months. However, pools with material residual maturity compositions during a short period present more residual value risk, as they may be exposed to more severe residual losses tied to specific market down cycles. As a result, Fitch utilizes the following parameters to stress for this risk in its derivation of the BBsf case residual value loss assumption: For pools with 60% or more of residual values due in any six months, Fitch utilizes the largest six consecutive month average historical residual loss levels. For pools with 50% or more of residual values due in any three months, Fitch utilizes the largest three consecutive month average historical residual loss levels. For example, in the case of XYZ Trust (see table on the previous page), the worst 12 months of historical experience evidence residual losses of approximately 10%, while the worst six and three months produce 11.67% and 12% loss estimates, respectively. Mark-to-Market Reports Fitch is typically provided projected residual values both at the time of inception of an individual lease and when a seasoned pool of leases is being analyzed for securitization (a mark-tomarket study). The mark to market is useful in analyzing how current production levels and incentives, as well as expected economic conditions, may impact residual realizations relative to the historical experience provided. Fitch s BBsf case residual loss level will be the greater of: The number derived as described above. The sum of the estimated mark-to-market gain or loss, plus the average historical loss on residual values as derived in the Bsf case above. For example, consider a pool with an average base residual loss level relative to the contract residual value over the worst 12-month period of 10% as in the case of XYZ Trust above. At the same time, if the ALG mark-to-market study shows a current expected residual loss of 8%, and long-term average historical residual losses (the Bsf case) were 5%, Fitch would utilize a 13% residual loss level for the BB case (8% mark-to-market loss plus the 5% historical average) instead of 10%. If a mark-to-market study is not provided, Fitch may conduct an alternative analysis to gauge the impact of expected market conditions, which could result in an increase to the derived BBsf case. Any such adjustment would be described in the transaction rating report. Many auto lease transactions take the conservative step of defining the securitized residual component of a lease as the lower of contract residual, third-party forecast at lease inceptions, and the updated mark-to-market residual forecast for each vehicle. Meanwhile, Fitch s BBsf RV loss analysis typically focuses on historical RV losses to forecasts at inception. In scenarios in which the practice of securitizing the lower mark-to-market value results in the securitization of lower residual values than Fitch s analysis contemplates, Fitch may adjust the BBsf RV loss assumption or haircut to account for this reduced residual exposure. Any such cases will be detailed in the transaction rating report. Criteria for Rating U.S. Auto Lease ABS 11

12 Why the BBsf Case? Fitch views this derivation as representative of a BBsf rating scenario. Fitch s BBsf ratings indicate an elevated vulnerability to default risk, particularly in the event of adverse changes in business or economic conditions over time. As residual loss levels in this case are derived from the worst month period observed, they represent a stressed scenario. However, a class that is only able to cover for residual loss levels seen previously, and in many cases seen recently, is exposed to adverse changes in business conditions, consistent with a BBsf scenario. The derived BBsf case residual value loss assumption serves as the starting point for all above-investment-grade rating categories ( BBB sf and higher). The incremental stresses applied to the BBsf case to reach investment-grade ratings are achieved via residual value haircuts as described in the section below. Residual Value Haircut The residual value haircut stresses the residual cash flow available to support a transaction by reducing the projected residual realization rate for investment-grade rating categories. The purpose of this stress is to provide a cushion for unforeseen residual realization volatility that could result from a number of factors, such as: Manufacturer, segment, or model-specific deterioration in used car values resulting from bankruptcy, recalls, or a shift in consumer preferences. Unprecedented shifts in the used vehicle supply and demand balance. Macroeconomic factors, such as rising fuel prices or recessionary conditions. Fitch utilizes specific haircut ranges for each investment-grade rating category. In establishing the haircut ranges for each individual rating category, Fitch reviewed the performance of used vehicle prices within the U.S. wholesale vehicle market over the past two decades. The performance of vehicle prices within this period was considerably volatile, with notable deterioration during the and recessionary periods. As a measure of this volatility, Fitch looked at vehicle price changes from the highest and lowest index values to derive the maximum level of value deterioration observed during these secondary market downturns. Fitch utilized vehicle value indices produced by auto auction providers Manheim Consulting and ADESA, as well as other available sources of residual value volatility data. Over the observed timeframe, all data sources available to Fitch (described in the Data Adequacy and Compliance section, page 2), including the Manheim and ADESA indices, issuer-specific vehicle auction data, and prior auto lease ABS residual loss performance, suggest the worst deterioration on record in 2008 resulted in an overall drop of 15% 20% in used vehicle values. Slightly more deterioration is evident when isolating specific segments or makes. Fitch s residual loss haircut ranges are detailed in the table to the right. Fitch views these ranges as conservative but appropriately so in light of the historical used vehicle market volatility, potential forecasting error, and the future market uncertainty. At the AAAsf level, Fitch s residual loss derivation provides that, at a minimum, a proposed structure is expected to be able to withstand two times the worst historical experience ( BBsf case plus 15% 20% worst value downturn identified above). Midpoints of the haircut ranges have been stepped down from Residual Value Loss Haircut Range Rating Category Positive Neutral Negative AAA AA A BBB Criteria for Rating U.S. Auto Lease ABS 12

13 20% for AAAsf to 0% for BBsf. It should be noted that these specific haircut ranges are representative of the U.S. wholesale vehicle market only. To determine the actual haircut from within the ranges described above, Fitch considers five primary qualitative factors and whether each factor could potentially have a positive, neutral, or negative effect on residual value realization. These factors and the risks they present are described below: Health of the Vehicle Manufacturer Risk: Bankruptcy could result in residual value deterioration. Historical Turn-In Rates Risk: Residual loss data from manufacturers or vehicles that have experienced low historical turn-in rates do not display the potential effect of high turn-ins, creating an oversupply of that vehicle. Segment Diversification Risk: A lack of segment diversity could expose the transaction to more residual value risk associated with certain segments, such as increased fuel prices (SUVs) or a change in consumer preferences (Minivans). Model Diversity Risk: A lack of model diversity could expose the transaction to more risk associated with model-specific residual value stresses, such as vehicle recalls. Remaining Term and Wholesale Market Outlook Risk: Pools with short remaining terms may have more predictable residual realizations. Whereas pools with long remaining terms introduce more uncertainty as to the expected status of the wholesale vehicle market when contracts mature. This factor is considered in conjunction with the current state of and nearterm expectations for the wholesale market. Other items that may be considered in Fitch s evaluation of the wholesale market include expected incentives, expectations for future macroeconomic conditions, technological risk, and fuel price outlook. Fitch evaluates the pool and individually assigns a qualitative score of Positive, Neutral, or Negative for each of these factors to determine the residual value haircut used to calculate the residual value loss for each rating category. For illustrative purposes, the table at lower right demonstrates a residual haircut derivation example for the AAAsf rating category in which Fitch assigned a factor score of Negative to the health of manufacturer, Positive to the remaining term and seasoning category, and Neutral to all other categories. Each factor was equally weighted and assigned a value from the table at page 12 (15% for Positive, 20% for Neutral, and 25% for Negative). However, in some situations, Fitch may consider certain factors to represent disproportionate risk to future residual realizations. In these cases, Fitch may elect to assign more weight to these factors. For example, consider an OEM of particularly poor credit quality (i.e. distressed level issuer default rating [IDR]). If Fitch believes that OEM bankruptcy is considered a realistic scenario during the term of the securitization, Fitch could potentially assign all weight to the risk categorization for Health of the OEM (Negative). This would result in a 25% Fitch Haircut Derivation Risk Assessment Inputs Risk Factor Positive Neutral Negative Health of the OEM X Historical Turn-In Rate X Segment Diversification X Model Concentration X Pool Remaining Term/Seasoning X Overall Risk Assessment Fitch Haircut Derivation Risk Assessment Results (%) AAA Positive Neutral Negative Health of the OEM 25 Historical Turn-In Rate 20 Segment Diversification 20 Model Concentration 20 Pool Remaining Term/Seasoning 15 Average Haircut 20 x Criteria for Rating U.S. Auto Lease ABS 13

14 haircut, despite the risk assessment of the other four variables. Any such assumptions would be detailed in the related transaction rating report. Fitch completes the risk assessment discussed above for all auto lease ABS. However, there may be risks or mitigating factors that are not considered in this analysis. In these cases, Fitch may elect to adjust the residual haircut. Such circumstances may include: Excessive Geographic Concentrations: While vehicles may be moved across the country to maximize residual realizations, there is a cost that will be incurred in transporting and storing these vehicles. These costs will ultimately reduce the net proceeds available to the trust to service debt. For transactions with material state (greater than 30%) or regional (greater than 50%) concentrations, Fitch may incorporate an additive haircut to account for these increased disposition costs. The haircut will be sized based on Fitch s estimation of the cost and specifically detailed in the related transaction rating report. Loss Data Not Representative of Open Auction Experience: The residual loss data provided to Fitch can vary by servicer. Some issuers may include excess wear and tear collections in their residual performance data. Other issuers disposition experience may include residual loss data from all disposition channels, rather than only open auction. For all transactions Fitch inquires as to the composition of the residual loss data presented. In cases where non-auction channel disposition experience is included (such as dealer sales or upstream dispositions), Fitch evaluates the pricing strategies for such sales. In cases where residual loss data provided is inconsistent with historical auction experience or artificially low (such as cases in which wear and tear collections provide for material additional proceeds), Fitch may incorporate additive haircut stresses. Other Haircut Adjustments: There may be factors aside from those specifically identified above that can have a material impact on residual realizations for an ABS pool. For example, substantial changes to residual setting policies may call into question the relevance of historical loss data utilized in Fitch s analysis. Therefore, substantial increases to forecast residuals may result in increases to Fitch s RV haircut. Conversely, cases in which the securitized residual component is lowered relative to historical standards (such as the case in which the securitized residual is the lower of the initial forecast and mark-to-market) may warrant a decrease to the RV haircut. Any of the above adjustments will be described in the transaction rating report. Total Stressed-Case Residual Loss Calculation XYZ Trust Total RV Loss Calculation (%) a. Base ( BBsf ) Assumed Residual Losses b. Remaining Residual (1-a) c. AAAsf RV Loss Haircut Remaining Residual after AAAsf Haircut d. (b a [1-c]) e. Total AAAsf Residual Losses a (1-d) a As a % of turned-in residual. Once all the qualitative factors are weighted and scored as Positive, Neutral, or Negative, the scores are averaged to produce a haircut for each rating category. The haircuts are applied after the assumed residual losses derived in the determination of the BBsf case. Thus, in the case of XYZ Trust described earlier, the BBsf residual loss assumption of 10% leaves 90% of the residual balance remaining. That 90% is next subjected to the 20% haircut, which results in a residual realization rate for the AAAsf rating case of 72% (90% times [100% minus 20%]). This equates to a residual loss of 28% (100% minus 72%). This means that for a class of notes issued by XYZ Trust to be eligible for a AAAsf rating, the class would have to support stressed credit losses commensurate with AAAsf, as well as 28% losses on all turned-in residuals. Fitch applies this stress to all returned residuals returned over the life of an auto lease securitization, in essence assuming the trust is exposed to a single extended market downcycle. Such a scenario would be inconsistent with the cyclicality historically observed in the U.S. wholesale vehicle market. Fitch believes this assumption is appropriate for stressed rating scenarios, albeit conservative considering most ABS pools residual maturity diversification. Criteria for Rating U.S. Auto Lease ABS 14