I recently had the pleasure to serve as moderator of a panel presentation titled “Actuarial Insights into Today’s F&I Products” at the P&A Leadership Summit. The panel was made up of three independent actuaries: George Belokas of GPW & Associates, Lee Bowron of Kerper Bowron & JH Briscoe, and Michael J. Covert of Perr & Knight. For those of you who were unable to attend this session, here are some interesting vehicle service contract (VSC) highlights discussed at the session.
The panel started at a high level to review methods used to analyze a VSC portfolio. The traditional approach involves loss triangles organized by original purchase date, where loss emergence is tracked over the life of the contracts. The end result is a triangle where the oldest contracts are fully earned and the newest contracts have only a couple of data points. The triangles allow a comparison of one year of experience to another to see how losses are trending. A loss emergence pattern can then be selected for a given block of business and applied to forecast ultimate losses for each policy year. This approach is fairly easy and works well for rate filings and statements of loss reserve opinions, but can be problematic if the underlying business is changing.
For example, consider the changes that were made by many manufacturers back in 2006 and 2007 to increase the term of their underlying warranties. A loss pattern based on 2005 data and used to project 2007 ultimate losses would be inaccurate because the exposure on the 2005 contracts started at an earlier point and generated higher losses during the first two years. One technique to combat this problem is to segregate the triangles by variables such as underlying warranty, starting odometer miles and term, but this can generate a lot of triangles for review. If a program had just five mileage bands, five underlying warranty variations and five terms, there would be 125 different loss triangles to analyze (assuming they were all large enough to be credible).
An alternative approach is to remove the triangle concept and consider the underlying unit of coverage; which is the number of miles driven per VSC outside the manufacturer’s warranty. This method requires an analysis that takes every contract and strips out the manufacturer warranty and reviews driving patterns to calculate a base cost per mile driven. Driving patterns can be developed by analyzing cancel and claim data to see how fast customers are expiring their contracts. This type of modeling is more complicated and not ideal for a rate filing, but it allows for more detailed analysis over a number of variables such as starting mileage, coverage, deductible, class, age of contract, and whether it’s reinsured. This model could even be used to develop an earnings pattern specific to that contract.
Impact of Starting Odometer
The panelists noted that there has been a large increase in the starting odometer on used VSCs. The typical used car mileage bands have been in the 40-60K mileage range, but many providers are allowing higher mileage vehicles into their programs; some even up to 150K miles or more. As one would expect, these older vehicles tend to have more losses, which increases the claim frequency. In addition, the average claim cost is higher because more expensive items are breaking. What the actuaries see from providers is that some of these older vehicles are not priced adequately to reflect the exposure and the segment is typically unprofitable. A mix of business shifting towards a higher mix of these vehicles may be particularly alarming.
New Car Profitability
New car profitability continues to increase year over year. In other words, if all business were combined for a single term/mile segment, a VSC written on a new 2009 model year vehicle is more profitable than a comparable 2006 vehicle. Possible explanations include increased underlying manufacturer warranties and continuing improvements in vehicle quality. Another possible explanation is a migration toward Asian vehicles from domestics. This trend is supported by provider portfolios as well as public data from industry sources such as NADA. Asian vehicles traditionally have had lower loss costs and the shift in business could explain an overall increase in profitability of new cars. The panelists agreed that it is too soon to tell what the impact of more sophisticated technology will be on new car loss experience.
Distribution Channel Impact
The distribution channel impact on profitability is largely a pricing issue. Many providers use the same reserves (i.e. “rate charts”) for a VSC sold by a dealer as they do for a VSC sold to a customer shopping on the internet, despite clear evidence of adverse selection on the latter. From a profitability standpoint, the best time to sell a VSC is at the dealership or financial institution when the car is new and the car’s future performance is unknown. As the car ages, defects become known and the opportunity to shop in anticipation of a claim increases.
Mix of Business
A typical VSC rate chart tends to be priced by component coverage, new/used, term/miles, and initial odometer mileage. The result is that one can end up with very lengthy rating manuals that are difficult to analyze and price. The panel suggested that not enough time is spent pricing each individual segment. For example, as a general rule, most classes are priced incorrectly. Asian vehicles are typically priced too high, domestics are about breakeven and Europeans are generally underpriced. But huge rate charts make it very difficult to discern these differences. If one slices the data by vehicle make, these differences would become obvious since the Asian loss ratio would likely be too low and the European loss ratio too high. The same analysis should be conducted on each rating variable, including term and initial mileage. Shorter terms are easier to analyze since losses emerge quickly, but one must pay close attention with longer term business or there can be an unpleasant surprise several years down the road after it’s too late to turn the ship around. Without digging in at the outset, it’s hard to understand what is happening and why.
Reimbursement vs. Default Coverage
Most VSC business is insured via a reimbursement type insurance policy where claims are paid when the vehicle breaks down. There is a significant amount of historical data to analyze when pricing that coverage, which increases an actuary’s confidence in the rate adequacy. There is a lesser used type of insurance policy that is only triggered when there is a default by the contract obligor. The reason for default is often related to financial, economic, or other market related reasons that are much harder to predict. Thus, the question of profitability under one type of coverage versus the other can be tricky. Default coverage has a very low frequency, especially when the economic environment is good, and thus a lower insurance fee. But if a loss does occur, the severity is significant. By definition, any individual default policy will either be priced too high or too low and one just hopes that in aggregate, an insurer’s premium and surplus is adequate to cover any potential default. There is also the question of when to earn an insurer’s premium with default coverage. Some choose to wait until the contract expires, earning 100% at contract termination.
Why Do Some VSC Providers Lose Money?
Why do some well-intentioned providers lose money on an auto VSC portfolio when there is so much data to analyze? The answer often comes down to poor rate development and inaccurate earning curves. Rate chart development is typically performed by 1.) finding a competitor and copying theirs or 2.) performing an actuarial analysis to determine rates. The risk with copying a competitor is that plans are often lengthy, difficult to understand, and not priced correctly. And over years of rate changes and tweaking, the underlying relativities that once existed among the rating variables (such as class plan, new vs. used, mileage) have become blurred. So if you copy a competitor plan you could very well be replicating their pricing inadequacies. The more appropriate approach is to take an existing rate chart and try to back out a set of base rates with relativity factors. A new rate chart could then be generated by multiplying those out to reestablish those important rating factors among variables. One must also consider a competitor’s underlying forms in conjunction with a rate comparison to make sure that any coverage differences among programs are addressed. For example, the competitor might have different car components covered in their plans that don’t cleanly map to the plan being reviewed.
Incorrect earning patterns also cause some providers to lose money because a flawed earnings pattern can disguise poor loss results. For example, a pro rata earnings curve might be an acceptable curve for used VSC’s initially but over time as historical data is built, customized earnings curves should be created to more accurately predict ultimate loss ratios. A correct earnings pattern captures the emergence of losses so that the loss ratio remains constant over time. Said another way, the loss ratio evaluated at month one should be the same as in month 60. VSC providers can use many different customized earnings curves within their portfolio to capture important differences by segment. Any of the three actuaries in attendance at the P&A Leadership Summit would be happy to assist you with this project.