Marketing professionals in any industry are inundated with segmentation variables and reports that enable them to develop optimized campaigns to drive results. Segmentation is critical for marketers to identify the leads that have the highest propensity to buy and craft offers that are targeted at each segment. However, conventional metrics available in most segmentation providers are not particularly useful: they have little to no correlation with risk-based metrics that would indicate eligibility or openness to an offer, leaving lenders without key information about their leads and stuck with "spray and pray" marketing tactics. Just like you wouldn't use a hammer for a screw, why try and use conventional segmentation for credit? At the end of the day, your prospect's credit assessment will determine whether or not they qualify for your products: by putting this assessment at the top of the funnel, your marketing team can direct your resources at the leads that matter, and avoid potential compliance issues when trying to emulate this. With Lead Decisioning by Credit Bureau +, we help lenders apply a credit risk lens to their marketing efforts, enabling lenders to screen and segment their leads for:
- Optimized customer acquisition costs and efficiency;
- Substantially improved approval rates by connecting underwriting and marketing; and,
- Higher average deal sizes and sustainable portfolio growth.
How It Works
Credit Bureau + is a platform designed to provide FCRA-compliant decisioning from lead to loan. We can help you source a lead pool, or we can support your lead purchasing from third-party sources. Through soft-pull credit reports and alternative data reports, we can score and implement credit-based knockout rules that align marketing with your underwriting strategy. Our platform generates automated buy/pass decisions and suggests possible loan amounts, terms, and rates, and arms your marketing team with a series of leads that are pre-qualified for a specific lending product. We also integrate into your existing workflows and are designed to enhance your existing processes, and will work with you and your marketing mail house, LOS/LMS, other partners for the most seamless experience possible.
Trust Science takes it a step further to develop a propensity score that can predict which of your leads are most likely to accept your loan terms, enabling laser-focused direct marketing strategies that target your best leads to stop wasting valuable resources on unqualified or low-propensity prospects.
Want to see how we helped a leading US Installment Lender with this service? We successfully doubled their originations, boosted their approval rate over 90%, increased their average deal size by 35%, and offered a 2-5X ROI.
Compliance and Steering with Demographic Factors
The most common conventional segmentation variables are demographic factors: things like age, gender, location, family situation, income, and education. They are the easiest to access and generally can be quite effective for standard product marketing. In lending, however, most of these factors are prohibited under the ECOA and similar legislation.
Even in marketing, lenders need to be careful on disparate impact, as this FDIC report illustrates. When lacking compliant credit metrics to support segmentation efforts, marketers may rely on improper, and possibly non-compliant, correlations between demographic information and booked loans, resulting in different demographics receiving different promotional content (or no promotional content altogether). The non-compliant practice of steering is characterized by guiding customers to a sub-optimal loan product relative to what they would qualify for, made especially illegal if done on the basis of these prohibited factors, and this is a key activity that marketers must avoid. Applying a compliant credit-based lens in marketing, like Lead Decisioning by Credit Bureau +, enables lenders to reap the upside that marketers attempt to emulate, without missing Invisible Primes in other demographics and without facing regulatory exposure.
Steering on the basis of explicitly prohibited demographic factors is an obvious use case; where one age group, gender, or similar clearly receives promotions of sub-optimal offer. However, lenders (and more specifically marketers in lending) should watch for factors that correlate with prohibited factors.
For example, consider hypothetical Neighborhoods A and B. Neighborhood A consistently receives promotional offers with lower amounts or higher rates compared to Neighborhood B, to the extent that residents of Neighborhood A are signing up for these offers, even though they would qualify for the offers in Neighborhood B. While this alone may already cause some regulatory trouble, Neighborhood A is also disproportionately comprised of one particular group protected under a prohibited factor (e.g., race, gender, age). Because of this, there is a disparate impact, where there is a demonstrable difference in exposure to certain offers along prohibited factor divisions. Furthermore, even if there is no harm done, in the sense that eligible Neighborhood A residents are able to find the Neighborhood B offer and sign on with that, regulators may still find the existence of a non-compliant steering practice.