Thanks to powerful information-processing technology, businesses have dramatically changed the way they market to their customers.
Rather than blindly sending messages to countless prospects – and hoping for a 2% response rate (at best) — messages can now be targeted to (and customized for) each individual candidate. While this shift has spelled imminent doom for the U.S. Postal Service, it’s been a boon to marketers.
Understanding which products a prospective customer is likely to buy, and offering them incentives to do so, has become commonplace, greatly increasing response rates to promotion offers. Rewards cards are just one example of a customer’s agreement to share buying habits in exchange for specific coupons or discounts on the products they buy most often. (We see you bought diapers today, here are some coupons for baby food).
Unfortunately, for loan officers, finance managers and others looking to extend credit, these targeted marketing programs fall short — they may tell what a customer is likely to buy, but do little to reveal whether a prospect can actually afford it.
This limitation is especially acute with online commerce. Identity thieves, fraudsters, and the merely ineligible can hide behind the anonymity of the Web, appearing exactly the same as a company’s best prospects.
Immediate access to information can improve a credit manager’s ability to pre-screen, pre-qualify and ultimately qualify prospective borrowers. Further, the ability to identify each customer’s fiscal eligibility (or lack thereof) can ensure from the onset a mutually rewarding transaction. Neither the customer nor prospective lender waste time or good will considering inappropriate offers. Products and services can be offered exclusively to those customers best qualified to accept, with each offer (a credit limit for instance) customized for each prospect.
Those charged with extending credit have long filtered their prospects with the use of prescreening. Prescreening works in one of two ways: first, a creditor may establish certain criteria, such as a minimum credit score, and then ask a consumer reporting company for a list of those in its database who meet that criteria; or a creditor might provide a list of its potential customers to a data reporting company and ask them to identify those on the list who meet the selected criteria.
Making risk assessments based on prequalifying prospects differs in subtle ways from pre-screening. Pre-screening prospects allows a credit manager or lender to offer a specific pre-approved product; (e.g. “you are eligible to lease this new car at the following terms….”) whereas prequalification more directly involves the customer in the process.
Prospective customers can be invited to inquire which offer best suits their particular financial situation. This allows the lending manager to ask, “Would you like to see the types of financing that you might qualify for?” If the answer is yes, one or more credit options can then be offered.
Once presented with options, consumers can then decide whether or not to proceed with a more formal credit application. This allows a business to suggest various products or services that best match each customer’s specific needs (and ability to afford). Consumers benefit by being in the driver’s seat – they opt in to the 0requalification—and can review their loan options before deciding whether or not to proceed to application.
Because prequalification in itself is not an actual application for credit, it has no effect on the customer’s credit score. (Prequalification is viewed as a “soft” credit inquiry, as opposed to actual credit applications, which are “hard” inquiries that may impact a credit score). Therefore, it’s in both the vendor and customer’s best interest to reserve a formal application for credit to those prospects most likely to ultimately consummate the transaction.
Prequalify on Demand
When used online as a filtering tool, prequalification allows credit managers to work in real-time to consider lending requests. This gives businesses (particularly Web-based businesses) the opportunity to offer their prospective customers a variety of credit options that prospects may qualify for based on their credit report and/or credit score.
When available on demand, the process of qualifying prospective customers becomes seamless by providing immediate access to transaction information. This can greatly increase response rates to offers by performing the filtering process in seconds, as opposed to days. Lending decisions can be made that lead to additional business opportunities. For example, offers such for credit or additional value-added products can be presented while a prospect is still on the phone with an agent, or online at a Website.
Regrettably, most businesses have had neither the time nor budget to access consumer financial data quickly enough to make customer prequalification practical as a real-time application. However these robust “decisioning” tools are increasingly being delivered via a decisioning-as–a-Service (hosted) environment.
Rather than investing their own capital toward data-analysis systems, credit managers are able to access credit screening tools on demand. Hosting allows prospective lenders to instantly filter each potential transaction and make lending decisions in real time.
Using sophisticated scoring techniques, multiple data sources and automated business rules within a hosted environment can also help lenders make more appropriate, cost-effective lending decisions. Decisions can be made as to which applicants to prequalify or decline, tailoring the terms and offers to the applicants according to their profiles.
This can also place more control in the customer-facing agent’s hands while ensuring that decision processes remain consistent across the business. Additionally, it can open a number of cross-sell opportunities for current customers while filtering out the occasional bad apple.
Roger Ahern is Senior Director of Experian’s Decisioning as a Servicecapabilities.