BRE Properties President Connie Moore had a pretty good idea of what she was looking for when the San Francisco-based REIT joined several other prominent multifamily companies (including Post Properties and Equity Residential) in mid-2006 to pump $3.5 million into Atlanta-based RentBureau, a consumer reporting agency providing data for resident screening that has sought to create a nationwide database of rental payment histories as well as leverage non-traditional payment data in the approval of lease applicants.

“When you think about the millions of renters that we have in this country and, as a landlord, our inability to consistently track how they performed before they came to us, the concept of amassing national rental payment histories seemed ripe to me,” says Moore, who serves on RentBureau’s board of directors. “And as we continue to try to make it easier for our on-site leasing associates to think about the person walking through the door and make a quicker decision, a more reliable ‘yes’ or ‘no,' then accessing past rental performance makes a lot of sense.”

RentBureau president and CEO Eric Hartz characterizes the effort to amass a national database as an exercise in gleaning “positive payment data.” For too long, apartment companies have run traditional screens that tend to key on the negative aspects of applicant backgrounds: criminality and poor credit. While RentBureau does incorporate those traditional screens, it also seeks to include the good stories behind would be renters. “The use of positive data has been the big leap for us,” Hartz says. “A lot of credit- or criminal-related data is really negative. Collections and eviction judgments are obviously important data but overlook the positive data in rental payment history that really no one has been highlighting.”

With 6 million rental records and counting, RentBureau feels it has reached a critical mass in rental payment histories that even the big credit agencies such as Equifax and TransUnion have thus far been unable to crack. TransUnion, in fact, announced earlier this month that the credit agency would begin to include RentBureau data as part of its overall rental screening platform. “By adding RentBureau rental history data into our platform, we can now offer our customers more complete information to identify, attract, and select the right residents,” says TransUnion rental screening group vice president Mike Britti. “We know that a good predictor of a resident’s likelihood to pay rent is their rental payment history. Now we can identify those who lack traditional credit, but have been good renters, in a quick and easy way.”

RentBureau is also incorporating other alternative payment data to come up with a “Rent Predict” score for lease applicants that can mitigate either a lack of credit for Gen Y types or poor credit for the foreclosure set. While Hartz declines to identify the specific data sets that RentBureau is using, he cites examples such as utility and gym club membership fee payment histories. According to Hartz, RentBureau has narrowed some 26 different alternative payment data sets down to five that can accurately predict an applicant’s risk level.

“We all try to keep our delinquencies low, but maybe there are some people that we are turning away that in reality would not be problematic tenants,” Moore explains. “Think about the people whose credit has been completely destroyed over the past couple of years, and the extent to which we can pick up data about how they performed when they were not completely crushed, or how they were performing beyond the foreclosure activity. There are other ways to do it beyond a FICO score, and analyzing alternative payments and prior history on rent is a key barometer in that regard.”

While revenue uplift attributable to RentBureau depends on market variables, Hartz says users typically experience a 0.5 percent to 2 percent NOI increase. “That’s attributable to two sources: cost avoidance of risky applicants and retention of otherwise good renters being sent away because of traditional screening methods. When you begin to incorporate positive data, you’re going to get more auto-accepts, and more accepts with minimal verification. I argue that it increases occupancy and increases performance, too.”