When a financial institution’s pre-screened customer analysis left too small a pool, a new approach generated more customer prospects and greater account opening results.

A $4.3 billion Mid-Atlantic financial institution wanted to increase equity loans. It started a Home Equity Acquisition program focused on customers who had no equity loans with the institution. But pre-screened data analysis left only 6,800 customer households, which was too few to meet their aggressive equity acquisition goals.


WordCom used aggregated credit data and risk proxy scores to find additional customers who were likely to qualify for an equity loan. The analysis included demographic information to pinpoint customers who had equity in their homes.

The result was a customer list 2.5 times greater than the pre-screened list.
• Tier 1 – 6,800 pre-screen customers
• Tier 2 – 17,000 customers who were sent an invitation to apply (ITA)


As expected, the response rate of the ITA customers was slightly lower than the Tier 1 pre-screened customers. However, the Tier 2 customers accounted for:
• 36 additional equity loans with total balances over $2.9 million
• 27 additional loans and mortgages with balances over $7 million
• An estimated additional $216,000 in first-year revenue

These “bonus” results came without typical red tape from dealing with credit bureaus and avoided the added expense of pre-screened data. Since there was no firm offer of credit to the Tier 2 group, there was no additional risk for the institution.

If customers who responded didn’t qualify for an equity loan, there was the chance to make them another loan product offer or help them in some other way.