black book white paper...black book white paper: innovation driving profitable portfolio growth the...

Innovation Driving Profitable Portfolio Growth

Black Book White Paper

2 Black Book Lender Solutions

Notes

Black Book White Paper:Innovation Driving Profitable Portfolio Growth

The auto lending landscape remains a highly competitive business based on continued pent-up demand for the replacement of vehicles. The average age of vehicles on the road today is estimated to be a record 11.4 years of age according to a report in CNNMoney.com1. While this indicates Americans are holding onto their vehicles longer it also points to the largest reason why they’re ready to shop for replacements.

Given this scenario, auto lenders have an opportunity to continue with the portfolio growth they’ve experienced over the last few years. With this growth, especially in sub prime, lenders need to find the right opportunities for expansion in order to realize higher profit margins.

Lenders can realize more profitable portfolio expansion if they take into account historical depreciation curves in combination with future projections based on accurate data. Knowing how a certain car has performed historically can have significant impact on what it will do in the future, and this information can be leveraged to mitigate risk or capitalize on a more aggressive lending strategy. What’s more, residuals should no longer be thought of as a lease-only resource, and lenders realize that residual forecasting can deliver great insight for financed vehicles in a given portfolio.

Above and beyond this more complete picture based on accurate insight, new innovations in technology are impacting profitable lending even further. An auto lender must make portfolio decisions that match the speed of today’s automotive business environment, which has evolved past spreadsheets and manual portfolio calculations. As such, it’s important for lenders to rely on the latest technology innovations that allow them to make portfolio adjustments more efficiently, and with higher profit potential in mind.

Identification Of Collateral Risk

Collateral data is important because it can help guide lenders into understanding the historical performance of a specific vehicle or segment. As an example, in order for lenders to determine how a residual projection will measure against their portfolio, they need to understand how a certain vehicle has performed during the uptick of the last few years. This collateral data can provide depreciation curves that mitigate risk by showing which vehicles will fall back the farthest, and which ones that are projected to have stronger retention in the coming years.

Collateral is also becoming a more important ingredient to lenders as they look to expand portfolios in a sub-prime-intensive market. Some lenders are paying closer attention to the age of the vehicle, and how many miles it has registered. As one lender stated in a recent edition of Automotive News2, “We’re seeing terms of 60 to 72 months on cars in excess of 100,000 miles,” said Jonathon Levin, CEO of Turner Acceptance Corp., Skokie, Ill., a regional lender primarily for independent, used-car dealerships. Having the right insight into historical collateral trends can often provide the right amount of visibility into risk management.


Collateral risk is also critical in determining how aggressive lenders can be when setting their terms. If a bank has on average a high repossession rate at eighteen months on the collateral in its portfolio, it is important to understand how certain vehicles or segments have historically performed so that lender will have a better idea what that collateral will be worth in eighteen to twenty-four months down the road. Being able to leverage this historical data for collateral risk provides lenders with the confidence to grow in a certain segment, and it also provides the insight to be more conservative in other segments.

Historical collateral values can help lenders make the right residual decisions because they can show patterns of how vehicles have performed in the past. In Example 1, vehicle “A” model year 2006 shows a retention rate of 62% after the first twelve months, while vehicle “B” shows 53%. However, vehicle “A” model year 2010 has a retention rate of 60% while vehicle “B” shows 69% after twelve months. Knowing the differences can help lenders determine which vehicles have performed historically, and can drive better decision making on future forecasts.

Example

Source: Black Book Collateral Insight Engine


Loss Forecasting

Auto loans have grown longer in recent history, with lenders offering terms that are noticeably longer than just a few short years ago. The average auto loan issued in the second quarter 2013 was for sixty-five months, up from sixty-four months in the same quarter 2012, according to Experian Automotive and reported in Automotive News3.

While length of term does not affect the value of a vehicle, it can affect how a lender mitigates portfolio risk. As the term continues to grow, lenders will have less opportunity for equity based on what the cars will actually be worth, a critical component in the ability to forecast losses.

Vehicle supplies may have a more material impact on losses, though, since additional inventory can impact the value of the vehicle over a given period of time. Also reported in Automotive News4, a Morgan Stanley study said carmakers will look to add 3.5 million units of North American capacity between 2011 and 2015, a 25% increase. This increase in vehicle inventory may have a significant impact on vehicle values, further muddying the waters for loss forecasting.

This influx of supply may be staggering and prompt a shifting of collateral values downward. As this happens, it may be more difficult for lenders to arrive at an equity position on a vehicle with sixty-six month loan terms. Particularly with interest rates rising, during the amortization of the loan a lender may have more finance charges to the early part of the loan, which would provide more exposure for a loss. This loss severity could become exposed for banks that do not have a strong portfolio


Loss Forecasting Calculation

The standard calculation of expected loss is:

Expected Loss = Probability of Default x Exposure at Default x Loss Given Default

• Probability of Default: Probability of default by a borrower (typically estimated from a credit score).

• Exposure at Default: Amount to which the lender is exposed to the borrower at the time of default, measured in dollars.

• Loss Given Default: The magnitude of likely loss on the exposure, expressed as a percentage of the exposure.

Sources for estimating LGD:• Historical depreciation curve of the vehicle.

As an example, consider a vehicle for which the average historical depreciation curve of the vehicle shows that the vehicle value is 61% of the Equipped Retail Value in the first year. For this vehicle, the LGD is (1-61%) for the origination amount or (1-61%)/95% for the principal balance at time of default i.e., after a year, assuming 5% is paid down.

• Projected retention/residual value of the

vehicle. In many cases, the historical average depreciation curve may not reflect the forward-looking retention value of a vehicle for several reasons: lack of historical data for a new vehicle model; changes in model; market changes; etc. Forward retention values can also be used to estimate an LGD, and in many cases may be a better estimate than historical depreciation.

• Range of Historical depreciation curve of the vehicle. It is also advisable to estimate a “downturn LGD” and a “best-case LGD”. A historical range would provide best data in terms of the variation in values. For instance, our vehicle may have a historical range of 58% to 65% in terms of 1-year value. From the average of 61%, this provides 3% point increase for calculating a downturn LGD and a 4% point drop in calculating a best-case LGD.

Source: Black Book

Finding Opportunities

Lenders are going to rely more on residual forecasting for vehicles beyond leases because they want to know what prices will look like in the future for their entire portfolio. In this sense, collateral data and residual forecasting will team together to help lenders find the right opportunities for portfolio expansion.

Feeding off the continued growth in auto sales, on pace for 2013 sales of 15.2 million units according to Reuters5, banks are continually looking to expand their automotive portfolios. According to the Memphis Business Journal6, auto lending at one southeast bank currently represents 3.4% of the bank’s total loans. The bank’s auto portfolio has actually doubled over the past eight quarters and is worth billions. This bank’s auto portfolio made $2.6 billion during the second quarter of 2013, up 34% from the same time previous year and 73% higher compared with its 2011 portfolio. This activity mirrors the national trend for auto portfolios, which has grown $27 billion nationally (8.8%) and trails only commercial and industrial lending by percentage of growth. The National Credit Union Administration says auto loans are growing even faster at its institutions at 9.8% year-over-year.

With light-vehicle sales projected at 16.1 million units in 2014 according to Black Book, auto portfolios will only continue to grow at banks across the country.

Example 2 shows how two vehicles with projected values differ over time. Vehicle “A” model year 2006 has a projected retention value of 62% while vehicle “B” has a projected value of 53%. While this represents a nine-point spread in favor of vehicle “A”, a different snapshot is revealed for the same two vehicles from model year 2010, which shows a nine-point spread in favor of vehicle “B”. Depending on which model year a lender is looking to add to their portfolio, they can see which vehicle offers them the chance to be more aggressive on their loan terms.



Example 2

Source: Black Book Collateral Insight Evaluator

Innovation Helps Uncover Opportunities

The speed of today’s automotive industry can also dictate how lenders discover opportunities for their portfolios. New technologies available allow lenders to access historical values and residual projections on demand, giving them access whenever they need. They can also review their portfolio through a variety of different vantage points based on a number of vehicle/segment data sets. This means that at the click of a button they can see how adding groups of a certain vehicle would impact their portfolio, based on the updated data they plug into their system. If they have a large population of a certain vehicle model and want to see how that vehicle has performed historically, they can now gain visibility into this insight and make a decision that’s profitable for the growth of their portfolio.

This innovation is important to lenders because of their need to see how today’s changing values will impact their portfolio in real time. This level of innovation is occurring across a number of industries, making it a requirement for lenders to match the speed of today’s business. According to an editorial in The Wall Street Journal7 authored by Dr. Erik Brynjolfsson, a professor of management at the MIT Sloan School of Management: “People don’t talk about running experiments months into the future [as now] they’re into immediacy, because they can see that they can test ideas right away…A provocative hypothesis proposed during a morning meeting might graduate into a full-blown experiment by day’s end.

“Digital technology, as we have seen, allows companies to test new ideas quickly and easily. But the technology also lets companies easily scale those ideas or implement them rapidly and cheaply throughout the whole business.”

New innovations allow lenders to incorporate all the necessary data they use to project residuals in their portfolio by leveraging a desktop environment to give them a look at different value points on a car. This will go beyond a particular model year to also include make, segment and trim level. Lenders can now see how a specific vehicle has depreciated over a given time period, where it stands today and also view where its value is expected to go. More than just one vehicle, though, lenders can compare this data to other vehicle makes, models and model years, allowing them to build their portfolios easier and more accurately, all with the highest of profits in mind. Innovation is also allowing lenders to see which vehicles they can be more aggressive on, where they should be more aggressive, and also where they may not want to lend at all.


Portfolio Balancing & Management

It is important for lenders to measure risk in a portfolio and devise strategies to balance risk to ensure they are taking calculated risks and trending in the desired direction. This desired direction may be to increase risk (i.e., larger risk appetite), decrease risk (i.e., lower risk appetite) or maintain risk (i.e., same risk appetite).

Three main characteristics that measure risk include:

1. LTV (loan to value): The higher the loan amount to the value of the vehicle, the higher is the risk 2. Credit Score: Typically ranging from about 200 to 900, the higher the score, the lower is the risk 3. Term: Typically ranging from 12 months to 72 months, the higher the term, the higher is the risk

A fourth but important characteristic in measuring risk is often ignored.

4. Drop in collateral value over time: The higher the drop in vehicle value, the higher is the expected severity of loss and higher is the risk

Example 3 looks at how different strategies can impact the overall balance of an example lender portfolio, with varying options for portfolio expansion depending on their desired appetite for risk. In this example portfolio, the following five segments make up more than 80% of all vehicles:

• Compact Car – 21% • Full Size Pickup – 18% • Full Size SUV – 15% • Upper Mid-Size Car – 14% • Mid-Size SUV – 12%

It is clear that movements in the top segments and top models are likely to impact portfolio stability and risk forecasts. In the example portfolio, we review historical depreciation and residual forecasts:


Example 3A

Historical Depreciation

Projected Residuals


A quick review shows the average historical depreciation rates for the top segments in the portfolio. This information can be used to evaluate the average loss in vehicle values versus the average expected pay down of the loan balances. In addition, lenders can also compare recent trends. For example, the compact cars performed the best among the five segments recently and are projected to continue to outperform other segments.

It is important for lenders to understand the value dynamics of the top vehicle models in their portfolio. For example, Vehicle “X” shows an improving trend over time.

Example 3B


Vehicle “Y”, on the other hand, shows more volatility in trend. Example 3C

On model analysis of this portfolio, lenders may lead to the conclusion that Vehicle “X” in example 3A may present more opportunity. On the other hand, lenders may choose to be more conservative with Vehicle “Y” shown in example 3C since it has more volatility.


Portfolio Balancing Strategy Action

1. LTV alignment Tighten LTV cutoff for higher risk; improve LTV for lower risk

2. Risk-Based Pricing Increase APR for higher risk; lower APR for lower risk

3. Collections acceleration Accelerate collection activity for higher risk

4. Improved loss forecasting Lower loss provision due to more accurate loss forecasting

Source: Black Book

Residual analysis could also point to certain pockets of risk in the portfolio. It is clear that different segments and different models within those segments have varying depreciation curves. Such analysis can determine risks in certain segments or models. For example, the loan volume may be increasing on Full-Size Pickups in the portfolio due to a recent relaxation in LTV or credit criteria. However, a value analysis from historical and projected residual perspectives may lead lenders to tighten credit on that segment to balance portfolio stability.

A combination of portfolio balancing strategies could be implemented based on improved risk assessment of the collateral. Such actions could improve the portfolio P&L by 10-20 basis points. For a $500MM portfolio, the benefits could be in the range of $500,000 to $1MM.

Summary

In order for auto lenders to remain competitive and find areas for growth, they must rely on innovative tools and technologies that give them the ability to analyze their portfolio in an efficient manner. These tools will also allow lenders to study and analyze how different vehicles and segments impact their portfolio at a much quicker pace than with previous portfolio management practices. This portfolio balancing process will become even more crucial in the coming years, as supply increases and places downward pressure on vehicle prices. Lenders can offset this pressure by leveraging accurate residuals, which are now being utilized for financed vehicles as well as leases. What’s more, lenders must leverage historical values in addition to forecasted projections when analyzing collateral. Collateral risk based upon historical and residual values can help lenders make more accurate decisions. Ultimately, lenders that use today’s leading tools, and leverage accurate data that give them a snapshot into past vehicle performance as well as future projections will have better balance in their portfolio and drive higher profits.

Historical values, current values and projected residuals are made possible through access to vehicle insight that is timely, unbiased and accurate. Black Book’s suite of values includes wholesale, trade-in and retail values that are updated on a daily basis. Black Book now offers the industry’s most innovative portfolio management technology, which lets lenders analyze their portfolio via desktop, and evaluate different vehicle options to see how each would impact a portfolio in real time. Black Book’s data can also help with loss forecasting, which include historical trending and depreciation curves to measure the impending risk of downward or upward movement in specific vehicles and vehicle segments. These are all offered with detailed analytics provided in a variety of file, portal, web or mobile platforms. For more information, please visit www.BlackBookAuto.com/lender-solutions or call 855-371-7532.


Appendix

1 “Average U.S. Car Is 11.4 Years Old, A Record High”; CNNMoney.com; August 6, 2013

2 “Subprime: Full Throttle Despite Some Concerns”; Automotive News; October 16, 2013

3 “Longer Loans, Rising Leases May Come At A Price”; Automotive News, October 16, 2013

4 “Longer Loans, Rising Leases May Come At A Price”; Automotive News, October 16, 2013

5 “Ford Up, GM Down In Subdued Month For U.S. Auto Sales”; Reuters; October 1, 2013

6 “Memphis Banks Rev Up Auto Loans”; Memphis Business Journal; September 20, 2013

7 “The New, Faster Face Of Innovation”; The Wall Street Journal; August 17, 2009


Black Book Lender Solutions Support

Contact Information:(855) [email protected]

Lender Solutions Team

Susan HughesLender Solutions ManagerPhone (770) [email protected]

Brian CleggLender Solutions ManagerPhone (770) [email protected]

Kevin CarioLender Solutions ManagerPhone (770) [email protected]

Brett CollettProduct ManagerPhone (770) [email protected]

Jeff BunchVP, Lender SolutionsPhone (770) [email protected]


Huntcrest II1745 N. Brown Rd., Suite 130Lawrenceville, GA 30043Phone (855) 371-7532 www.BlackBookAuto.com/lender-solutions

Black Book® is a registered trademark of Hearst Business Media Corporation. © 2013 Hearst Business Media Corporation. All rights reserved.

black book white paper...black book white paper: innovation driving profitable portfolio growth the...

Documents