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UNLEASH! Equipment Lease Case Study

Executive Summary

The focus of this case study is R&R’s analysis of the required credit enhancement amount for UNLEASH, an equipment lessor that caters to small and medium-sized lease dealers, to raise funds in securitization.   The analysis shows how data-sensitive modeling enables UNLEASH to argue for a substantial reduction of credit enhancement (>5% of initial principal) without sacrificing investment quality.

The key innovation in this case is the mining of depreciation and recovery curves to support the cash flow analysis. A secondary innovation is the use of off-the-shelf equipment lease credit scores to modulate the expected loss performance based on the collateral characteristics.  

 

Introduction

In the mid-2000s, a new leasing company, UNLEASH, enters the market. UNLEASH competes with large funding vehicles like those of CIT and HP Credit. It has a proprietary, state-of-the-art consumer performance and demand tracking system, and it subscribes to a vended small ticket lease scoring system. Its clients are diversified across products and markets; the focus is small dealers passed over by large organizations.

The UNLEASH marketing strategy is to make approvals as fast and convenient as credit card approvals—targeting a 70% approval rate without sacrifice to underwriting. UNLEASH enjoys direct relationships with dealers, growing sales through agents with dealer relationships and signing contracts to receive more allotments of volume when UNLEASH offers better terms or faster response times than their peers.     To meet future needs for expanded working capital, UNLEASH plans to access the capital markets within the next 18 months using securitization.

 

Analysis

Since company has no prior securitization deals, the benchmark for its transaction will be deals issued by its closest competitor, M&N Leasing.

 

Collateral

UNLEASH leases office equipment in the following five business lines:

  • Office products
  • IT equipment
  • Telecommunications
  • Healthcare
  • Commercial & industrial

Ticket size ranges between $20K and $250K, with outliers as small as $2K and as large as $1MM. It finances soft costs for approximately 10% of the total contract amount. This percentage varies due to local variables like taxes. These are usually 4-5% of the total ticket size and upfront fees are another 4-5%. Contract tenor is 24, 36, 48, 60-and-63 (3 months grace period), 66, 72 or 84 months, with longer tenor items for items with long useful lives such as leased dental chairs.

Structuring and Valuation

We briefly review some of the main steps related to the credit structuring of the UNLEASH transaction:

(1)     Collateral analysis was based on a sample of 1,000 loans randomly picked from the firm’s collateral archive on a certain date.

(2)     The sample consists of 24 months of archived performance data of several small ticket leasing originations derived from the Credit Scoring Company data repository and judged by R&R to be a representative sample.

(3)     The Credit Score used was given as default probability and modulated internally to be compatible with the delinquency transition matrix and the assumed logistic shape of the loss curve.

(4)     Delinquencies were simulated using a Markov delinquency transition matrix that R&R reverse-engineered from a sample of issuers within the leasing industry.

(5)     UNLEASH supplied depreciation data that R&R used to build curves specific to each of its five lines of business, Office, IT, Healthcare, Industrial, Telecom, to calculate recoveries on defaulted assets.

(6)     We assumed a 7% cumulative gross expected loss over the life of a single pool as a proxy measure for the analysis-higher than the loss rate quoted by UNLEASH management.

(7)     Multiple exposures for the same customer were assumed to be 100% correlated in terms of their default characteristics, so that if a customer defaulted, all its associated exposures simultaneously defaulted.

 

Markov Delinquency Transition Matrix

R&R’s Precision Metrics© tools start by synthesizing the target issuer’s delinquency transition matrix from actual delinquency experience on peer deals. That is because, due to data limitations, R&R could not use information specific to the issuer.

This is the final result of the reverse engineering the transition matrix:

UNLEASH Delinquency Transition Matrix

B0

B1

B2

B3

B4

B5

PP

D

B0

98.62

1.38

-

-

-

-

-

-

B1

42.31

31.72

25.97

-

-

-

-

-

B2

3.45

20.39

45.71

30.46

-

-

-

-

B3

-

11.39

15.57

24.00

49.05

-

-

-

B4

-

6.79

7.74

9.33

25.52

50.62

-

-

B5

-

-

-

5.59

8.39

13.10

-

72.91

PP

-

-

-

-

-

-

100

-

D

-

-

-

-

-

-

-

100

  • B means bucket, a group of accounts with delinquencies within a given range, where Bucket zero normally represents current accounts, Bucket 1 refers to accounts between 4 to 30 days past due, etc.
  • PP means prepayment. Prepayments were not allowed within the UNLEASH implementation.     This is consistent with empirical evidence and with UNLEASH representations.
  • D means a contractual default. We do not allow accounts to default from lower designation buckets, i.e. all accounts need to migrate down the matrix to status code “Def” in order to be declared in default. This can of course be changed in a trivial way if necessary.


Depreciation and Recovery Curves

Figure 1 below shows the UNLEASH-derived depreciation curves by platform for its five main platforms.

The R&R Precision Metric© model fit a decreasing exponential curve to the above 5 years of data and used the modeled depreciation curves instead of the actual data points, so that depreciated values beyond the given data with R-square values in the neighborhood of 95% for all points between zero and 60 months could be forecast. Figure 2 shows the recovery percentage for a typical lease contract underwritten on office equipment.

Yield-Spread Curves

Total yields are rates of return for wholesale credit grades, presented in Figure 3 below.

Model

Using information from the models above as an input for non-linear valuation loop we can rate the hypothetical UNLEASH transaction. The main structural highlights of this transaction are as follows:

Feature

Value

Number of Debt Classes (tranches)

3

Annual Servicing Fee Rate

1.    50%

Interest Type (all three tranches)

Fixed Rate

Aggregate Advance Rate

100%

Class A Percentage

80%

Class B Percentage

15%

Class C Percentage

5%

Reserve Account Deposit

0.    75%

Target Reserve Percentage

1%

Reserve Account Type

Non-Declining

Trigger Type

Cum.     Gross Loss

Post-Triggering Incremental Reserve

3% (of original)

Trigger Level Months [0-12]

2.    5%

Trigger Level Months [13-24]

4.    5%

Trigger Level Months [>24]

5.    5%

Principal Allocation Method

Pro Rata

Non-Linear Convergence History

The following table shows the non-linear convergence history for this transaction. By any measure it was fairly well-behaved, which speaks volume for the stability of this collateral pool and issuer risk metrics:

Non-Linear Convergence History [UNLEASH]

Iterate

Class A

Class B

Class C

0

5.    00%

5.    50%

6.    25%

1

5.    19%

6.    16%

7.    15%

2

5.    34%

6.    24%

7.    39%

3

5.    26%

6.    36%

7.    53%

4

5.    32%

6.    28%

7.    63%

5

5.    38%

6.    36%

7.    60%

6

5.    37%

6.    45%

7.    71%

Converged Transaction Structure

Consistent with the above final results, the following table is a summary of the UNLEASH fully-converged structure for this hypothetical portfolio of 1,000 loan contracts as of February 3rd, 2005. Note that the Moody’s reduction of yield method, the basis of its structured finance ratings through 1999, is used. The credit ratings are given both as reductions of yield and as their Moody’s letter-grade equivalents.    Within the range of dollar amounts we are considering, the absolute value of the pool balance would be largely irrelevant to the individual values of tranche credit ratings. The average life is expressed in months and the yield reductions are in basis points.

Initial Pool Balance:     $26,575,438

Issued Amount:     $26,575,000

Target Reserve Amount:    1% of Initial Pool Balance (non-declining)

Servicing Fees:     1.    5% APR (50 bps higher than anticipated)

 

Conclusion

A summary of our findings is as follows:

  1. The UNLEASH commercial lease transaction structure references the M&N transaction in all respects, except the OC amount, including the sizes and payment priorities of the senior Class A and subordinated Classes B and C, which Moody’s rated Aa2, Baa2 and Ba2, respectively.
  1. The overcollateralization amount was reduced from 5.75% to 0%, so that the entire principal balance of the UNLEASH leases was able to be monetized.

Class ID

Initial Balance

Coupon

Ratings

Avg. Life

Avg. -IRR

A

$21,260,000

5.37%

Aa2

26.9

0.7

B

$3,986,250

6.45%

Baa2

27.0

20.1

C

$1,328,750

7.71%

Ba2

27.6

74.4

The data-sensitive framework reflects positively on the credit quality of UNLEASH lease contracts and shows that UNLEASH could lower cost of funding by reducing the cash over-collateralization of its lease portfolio securitization relative to peers—by as much as 5.75% of the initial principal contract balance.

 

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