The Differences Between Prescreen Credit Data and Invitation to Apply (ITA) / Modeled Data

Since the volume of mortgage, refinance and credit card offers is steadily increasing, and we are all getting calls from banks, mortgage companies and loan officers looking to prospect, I thought it would be a good time for a quick refresher on the differences between prescreen credit data and Invitation to Apply (ITA) using modeled data.

Using prescreened lists is the best option when soliciting loans to customers or prospects. But there is another very good option available to help find more loan prospects: the Invitation to Apply (ITA), using modeled data.

Prescreened lists provide a great way to ensure that marketing targets are credit worthy and conform to specific criteria requirements, such as actual credit score. Typically, these lists provide reduce the number of responders that may not be approved for a loan and therefore generate the best results for loan acquisition.

However, prescreened lists don’t come without their shortcomings. They can often be expensive and require extensive red tape to get a marketer set up to rent lists or to get mail pieces approved. Some companies are just simply not qualified to receive prescreen data. Also, there is required legal language that can eat up valuable real estate on a mail piece and require the marketer to make a firm offer of credit.

For businesses who are not making a firm offer of credit, who are offering the consumer an “Invitation to Apply, we suggest using Invitation to Apply (ITA) or modeled lists. While ITA lists may not perform quite as well as prescreen lists, they are a great second option because:

  • The costs are comparatively less expensive
  • It’s easier to acquire this list of credit worthy people
  • No firm offer of credit is required
  • Ability to overlay demographics, home data

BTW – Even when using a modeled / ITA list, it’s not necessary to completely sacrifice being able to target households by credit worthiness. ITA lists allow you to select modeled credit, which can be modeled at either the household or the zip+4 level. In addition to this, you can use demographics, home data, and other criteria to further qualify the best targets for a loan or credit card offering.

BEST OPTION:

To maximize marketing dollars and get the most response, marketers can use a combination of both prescreen credit data and invitation to apply (ITA) lists. This offers the greatest opportunity for success. By selecting the best targets via prescreening and supplementing that with modeled / ITA records, it allows the audience to be expanded.

CASE STUDY:prescreen data and invitation to apply

A mid-Atlantic institution used this collaborative approach for an Equity program. First, they took their own list of customers and ran them through a prescreening process to qualify them for the particular offer. They ended up with nearly 9,000 customers that met the required credit and other criteria. They then used the same criteria – however taking modeled data – and were able to locate an additional 20,000 households, which expanded their outreach to a new group of prospects.

The prescreen list achieved a response rate of 0.46% as a result of 41 equity openings. This exceeded the 0.31% response rate seen from the ITA list. But, the inclusion of this ITA group enabled the bank to open 61 additional equity accounts. As a result, the bank realized an incremental increase of $30,000 in revenue through these additional accounts.

Bottom line, even thought there are differences between prescreen credit data and invitation to apply data, both can provide a good response. Mortgage companies need to review all the different options that are available to them.

Comment