While the application of AI in leasing took time for multifamily operators to adopt, AI leasing tools are now widely embraced. These front end solutions, like AI chatbots or AI leasing assistants, improve prospective resident engagement, reduce workload for property teams, and accelerate lease conversion. What about the application of AI on the back end, beyond leasing?
As operators look for opportunities to drive property performance, increase NOI, and gain a competitive advantage, savvy management companies are deploying AI-based solutions to optimize back end operations like revenue management, risk mitigation, and bad debt recovery. Oftentimes, the same proptech solutions designed for unrelated objectives wind up having a positive impact on leasing.
But the multifamily industry still has a long way to go, as it has only begun to tap the potential of AI tech beyond leasing. To illustrate the pressing need for operators to implement AI across the lease life cycle, LeaseLock Chief Technology Officer, Sudip Shekhawat outlines the impact of applying AI to loss management with data-driven lease insurance.
Whether applying AI to leasing or operations, AI technology is only as powerful as its data pipeline. At the same token, while data is king, data is meaningless without AI analytics.
When it comes to loss management, proptech must have both rich data as well as smart technology. Combined, data and AI make powerful solutions that empower operators to make better business decisions and future-proof their assets.
Just as revenue management tech has unlocked droves of data to predictively set optimal rent pricing, loss management software needs to do the same in order to predict risk and optimize protection against loss. In addition to robust data, AI technologies need strong integration capabilities. This allows AI to leverage the full potential of data.
Lease insurance, for instance, is fully integrated into the native PMS workflow, allowing AI risk technology to access ledger data. That ledger data has a rich risk profile with a built in record of historical account balances, as well as the amounts owed, recovered, and written off as bad debt. Through data-driven loss prediction models, the software forecasts the likelihood of residents owing high balances or leaving excessive damage after move-out, then it employs AI to optimize loss protection at the property level. The result is customized coverage that eliminates traditional security deposits (which carry loads of risk for residents and operators alike).
In removing security deposits—a common leasing obstacle—operators improve back office operations like claims processing and revenue capture at move-out. On the front end, property teams see improvement in leasing metrics like move-in times and occupancy, as well as reductions in administrative burdens and regulatory risk in the leasing office.
Integrated AI technologies coupled with data have strong predictive potential, enabling operators to make informed, data-backed decisions. Now, it’s time operators embrace new data strategies and develop an AI technology roadmap.
For more insights from the multifamily technology leader and visionary, read the full article here.