One of the most frequently asked questions when implementing a vehicle subscription program is identifying a proper risk model for underwriting subscription customers. This typically corresponds to two areas that need to be addressed before allowing customers into a subscription membership — driving history and creditworthiness. In this article, we will focus on credit underwriting.
Subscription programs typically advertise convenience and simplicity for customers in accessing a selection of vehicles. These programs are attractive to customers precisely because of the ease of getting into a reliable car. On the flip side, operators need to consider the risks associated with allowing customers to drive their vehicles and create an appropriate qualification process to mitigate this risk.
As we work with operators implementing vehicle subscription services, credit qualification is top of mind for many operators. In general, operators can consider three approaches when thinking about driver qualification for subscription programs.
The first is following the standard creditworthiness checks that are implemented in qualifying auto loans and leases. This is perhaps the most straightforward approach given the broad support for tools and processes to facilitate credit checks. Also, the existence of well-established credit underwriting models makes it simple for operators to be confident about the risks they are taking when allowing subscription customers onto their platform.
On the other hand, as we discussed in our previous article, there are different target segments for subscriptions, and this approach might create barriers for some target customers. Based on the goals and customer audiences for the subscription program, an operator needs to carefully consider if a traditional underwriting model is a fit for its target customers — especially young drivers who might be attracted to the subscription program.
The second approach is the rental car model, which relies on the existence of a major credit card to qualify customers. This is probably the most relaxed approach for qualifying car subscription customers. This is also the most preferred method for mainstream customers as it avoids a credit bureau inquiry, and generally simplifies the process of getting a car. The rental car industry has long utilized this method to underwrite customers successfully.
Some challenges with this approach include cards that are issued with low limits, or even backed by a bank balance (referred to as ‘secured’ credit cards). These cards are typically viewed as major credit cards by the payment processing network but represent limited creditworthiness that might expose operators to more risk than intended.
The third approach is using the requirement of a deposit to qualify customers. Often, the deposit is some multiple of the monthly payment for the subscription plan. This deposit can be applied towards the subscription payment, or be eventually refunded to the customer. Depending on the arrangement, such a deposit can be used to qualify customers and enforce a minimum subscription period. In general, this approach is less popular with customers because it is viewed equivalent to the down payment needed on a loan or a lease, which subscription programs often promise to remove.
In summary, customer qualification is one of the most crucial elements for a successful car subscription program. Operators should carefully consider the target audience for their program, and establish an appropriate customer qualification process for their membership. There are several approaches to qualify customers, and often, some combination of the three strategies discussed above offers a successful underwriting model.
Azarias Reda, Ph.D. is the CEO of Carma Car. Carma is a technology company that offers a complete technology platform to power vehicle subscription program for auto finance organizations, OEMs, and dealerships. Carma Car is part of Techstars Mobility, the premier global network for mobility technology companies. You may reach Azarias at email@example.com.