How Artificial Intelligence is Revolutionizing Resident Screening

Artificial intelligence (AI) is one of those terms used so liberally that you’re never sure whether you’re being snowed by marketers. But in the context of RealPage’s new AI-based resident screening solution, the payoff is so obvious and easily documented that there’s no question it’s bringing about a revolution. The ROI is proving to be absolutely remarkable: millions saved and billions added to asset values, based on an average of $31 in per-unit savings over the course of a year without negatively affecting occupancy or revenue. All other screening solutions available for multifamily continue to rely on older methodologies for sizing up the likelihood of applicants paying their rent. They’re based on statistical and FICO scoring models, which are relatively imprecise in determining likelihood of rent payment. And the records are actually becoming thinner due to reduced credit card debt. Knowing this, and under pressure to keep occupancy numbers up, leasing agents are turning more often to intuition and overrides, opening up properties to more risk and even Fair Housing or HUD violations. Without the most accurate screening, you’re always in danger of either turning away potentially good renters or moving in bad ones. And what happens if there’s a downturn or spike in the market? The old scoring models simply can’t keep up with a rapidly changing rental environment where criteria need adjustment to reflect new local economic realities. A second leap for resident screening RealPage’s first major contribution to improving screening accuracy, one that still hasn’t been matched, was the addition of over 31 million records from actual rent payment histories to the mix of screening criteria. This was driven by the fact that the #1 indicator of whether someone will pay their rent is whether they’ve paid it in the past. Some people have a history of consistently paying rent even when falling beh...