Collateral matters in any lending situation, but not all collateral is created equal.
Collateral can vary from cash in your bank to raw land in a far away location. Recovering your principal on this collateral can range from “extremely simple” to “almost impossible,” and the time it takes to recover can vary as well.
The recovery rate – specifically, where you set it - is the main configuration point impacting collateral in PrecisionLender. Recovery Rate is defined as the amount of net-proceeds your bank will see from the liquidation of the subject collateral, considering both the time and the expense to do so. As you will see in this paper, the recovery rate has a large impact on the economic return of the loan that your bank is considering.
Most clients do not think that they have great data on the Recovery Factor across different types of collateral. Recovery Factors should differ greatly across the spectrum, from cash and near-liquid securities to raw land or multi-family real estate. We also find that in current economic conditions many banks haven’t had a lot of recent loss experience that would guide them toward appropriate stressed Recovery Rates. In this paper, we will discuss the impact that the Recovery Factor has on the ROE of a loan, by using two different collateral types in a similar deal structure.
To start, lets look at this simple example. The appraised Value is $1,333,333 and our Loan to Value is 75%. That means that our loan amount is $1,000,000. Based on our experience we would only recover about 50% of the appraised value of the collateral at the time the loan was made if the loan were to default and we needed to rely on the collateral as a source of repayment. At default, we would assume that our economic recovery would be 50% of $1.33MM or $666,667. In this example our aEAD (adjusted exposure at default) would be $1MM-.667MM = $.333MM. The amount of $333,333 would be the figure that we apply to our Loan Loss ratio for expected loss and our Risk Capital ratio for unexpected loss.
Let’s further examine the relationship between Loan to Value and Recovery Value and how they impact the risk adjusted return (ROE) of a loan. This will illustrate the impact of varying recovery rates across different collateral types and how they may impact the calculated return.
Let’s take a $1MM, 5-year term, 20-year amortization loan, with a standard pass 4 risk rating. We will price the loan using the same Loan to Value (LTV) but using two different collateral types. We will use CRE-Office with a 45% recovery factor and CRE Multi-Family with a 65% recovery factor. Note that the Loan Loss Reserve (LLR) and Economic Capital that drive these results will vary by institution. As such we will use estimates and keep these variables constant throughout the analysis to focus on the impact of varying the Net Recovery Rate input assumption.
In this example all else is equal except for the collateral and the underlying recovery factors. We are using an interest rate of 5% with no fees.
Notice in Figure 2 that there is no ROE benefit derived from any improvement on LTV below 85% or about $1.176MM in appraised value when using Multi-Family with a 65% recovery rate.
In Figure 3 using CRE-Office, you need to reduce LTV to around 57% or increase appraised value to about $1.754MM before you max out the benefit of additional collateral, which improves the ROE on the loan. Next page (Figure 4) is the side-by-side comparison of the two deals. $1 is the deal with the CRE-Office Collateral Type and $2 is the Multi-Family deal.
As you can see, the Net Interest Income numbers are exactly the same, as is the non-interest expense representing the average annual servicing cost. But we start to see differences in the Loan Loss Reserves. These are driven by the expected Net Recovery associated with the collateral, which impacts the Loan Loss Reserve required for the loan.
Many banks set up minimum annual loss figures. In this case we have our minimum annual loan loss of 15bps. Banks set up an annual loss percentage based on the risk rating of the loan. This is often duration based, changing for the term of the loan. (See figure 5 below for the assumptions used in this example.)
Since this is an amortizing loan, the annual loss % (LLR) will be interpolated (using the numbers in Figure 5) for each monthly cashflow between the 60-month and 12-month period, based on the aEAD. When the ratio of calculated Annual Loss (aEAD * LRR)/Average Balance falls below 15 BPS, the 15BP minimum reserve will be applied. Notice how the math works in Table 2.
After running through the math exercise here, we determine that the annual average Loan Loss Reserve required on the Multi-Family deal is $1,479, or 16bps of the average outstanding balance, and the LLR on the CRE-Office deal is $3,771, or 41bps.
The second factor that drives the Risk Adjusted Return is the amount of Capital that is applied to each loan which is again, driven by the Exposure at Default. We are assuming no additional guarantee factors in this example.
The next page is a table of how capital would be calculated in month 1.
As you can see, the Multi-Family deal has a Month 1 Economic Capital Calculation of 5.65% that will decrease over time, given the duration weight credit capital assumptions from Figure 5. Because the PrecisionLender solution can be set up to use the higher of calculated economic capital (which includes operational risk capital as well) or a “regulatory minimum” with each monthly cashflow, the actual capital used in the ROE calculation for the Multi-Family deal ends up being 8%.
With the Office deal the average capital used in the ROE calculation is 9.83%. A deeper analysis of the Office deal reveals that at about month 32, the EAD is reduced (through amortization) and the calculated capital rate — which is a function of the EAD times the interpolated required economic capital rate based in Figure 5 — becomes less than the 8% regulatory minimum. As such, the capital percentage bottoms out at 8%.
These two examples demonstrate that the recovery value on the collateral does matter and sometimes has a significant impact on the risk adjusted return on the loan. It is impossible to know what the exact recovery rate will be on each piece of collateral and at the time of default in the future. However, using the best estimate based on past experience, industry knowledge, and collateral preference will drive your bankers toward building that purposeful balance sheet.
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