Credit data is the traditional lifeblood that lenders use when marketing consumer loans, particularly when it comes to prospecting. According to research by Comperemedia, over 70% of all consumer lending direct mail offers were prescreened using credit bureau data. Top fintech lenders used prescreen offers in over 95% of their direct mail offers, while banking providers used prescreen offers in just over half.
Obviously, credit data is where lenders should start, but they should not overlook other, non-credit data, which is more flexible. And if you know what types of alternate data sources to tap, you’ll find it can be used for broader marketing applications and drive significantly improved marketing ROI.
When talking about “credit data,” we’re referring to the conventional consumer borrowing and payment activities derived from credit reports provided by the three major credit bureaus. The use of credit data in marketing is regulated in part by the Fair Credit Reporting Act (FCRA). FCRA imposes significant — and necessary — restrictions that make it impossible to use credit data for all marketing applications.
Any other data used for marketing that is not covered by FCRA is referred to as “non-credit” or “non-FCRA” data. Typical non-credit data sources include demographics, life events, summarized credit statistics, and lifestyle data, to name a few. Non-credit data is expanding, with more sources that provide an improved understanding of the consumer — without the use of credit data.
Non-credit data might involve credit card usage models, or mobile device app data, or device location information that allows you to understand how mobile wallets are used and where. These sources can provide a unique, robust view of how consumers manage their financial needs, giving lenders the deeper level of insight needed to tailor messaging effectively.
Non-credit data has strong applications in marketing for consumer lending, either by itself or in conjunction with credit data. Here are some of the main areas where non-credit data can be used to improve marketing performance.
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1. Audience Expansion
Many databases with non-credit data sourced from multiple points can have individual coverage rates close to 99% (meaning that the database includes nearly everyone). However, traditional credit data has much lower coverage, due primarily to prescreen opt-outs. The exact coverage rate is not publicly available, but it’s estimated that conventional credit data will exclude between 15% and 20% of a lender’s potential audience, depending on their target market.
So if you are appending credit data to your customer base or using it for sourcing prospects, you are likely missing a significant part of your audience. For lenders with aggressive growth goals, this is a substantial universe to exclude, and these prospects may include a lender’s best responders.
In the early stages, you should identify more conventional prescreened audiences first, then use non-credit data to find additional audiences after suppressing your prescreened segments to remove duplicated.
2. Targeting Improvement
Non-credit data adds new dimensions (e.g., life events, psychographics, wealth, etc.) beyond typical credit-based attributes (e.g., debt utilization, inquiries, level and type of debt, etc.).
In most cases, the size of the audience supported by non-credit data will require building a new response model to figure out what data works best and in which ways.
Ultimately, depending on the product being marketed, targeting models built with non-credit data are almost as efficient as models built with credit data. But any response models for lending products built using both credit- and non-credit data are typically more efficient than those built using just one source or the other.
3. Remarketing and Lead Nurturing
When credit data is used for generating prospects and leads, remarketing and lead nurturing programs can benefit from the addition of non-credit data. Once the consumer has engaged with your brand, the continued use of credit data is either very costly or not feasible, especially when considering digital channels where complying with FCRA has not been fully resolved. For these lower funnel programs, non-credit data can inform customer experience and lead prioritization.
Segmentation is a widely accepted tool to improve marketing performance. Credit data is often used in segmentation for specific prescreen marketing programs to give lenders insight into the consumer’s potential uses of credit, such as refinance or debt consolidation.
However, for broader segmentation applications, the use of credit data is typically not permissible and lacks dimensions to inform motivations, attitudes, and life stage. As lenders mature and grow their product portfolios, there will be a greater need for segmentation tools to support enterprise segmentation, brand positioning, and deepening customer relationships.
5. Expanding to Omni-Channel Marketing
According to data from Comperemedia, prescreen offers accounted for over 70% of direct mail marketing in 2017, prescreen offers comprised only 10% of email media. There is no data to calculate these figures for online display advertising or paid social, but they are certainly going to be far lower than email. And the reason for this? It’s clearly compliance with FCRA.
While the industry has developed solutions to use prescreen data in display ads and paid social, these solutions lack the flexibility to integrate with other media channels for a given audience. It’s tricky though.
Non-credit data sources should be the foundation of your omni-channel integrated marketing plan. With increasing addressability of all media, communications can be managed across media and the customer journey at the individual level. It is critical to have a comprehensive communication plan at each of those touchpoints. From this foundation, credit data can be incorporated to refine targeting for the media where it is permissible and cost effective.