Multifamily’s Refinancing Crunch Is Raising the Stakes for AI

For many multifamily owners, the next refinancing could come with an unwelcome surprise: a sizable equity contribution just to keep the property.

Apartment borrowers could need $6.8 billion in additional equity to refinance loans maturing through 2028, according to an October analysis by CRED iQ. The study also found a striking difference in property performance. Loans that could meet refinancing requirements had seen median net operating income (NOI) increase 31 percent since underwriting, while those facing a shortfall had seen a 12 percent decline.

Higher borrowing costs are a major factor, but deteriorating property performance can make an already difficult refinancing even harder. Consider an apartment community with a loan maturing in 18 months. Occupancy remains relatively stable, but concessions are becoming more generous. Insurance premiums are climbing. Maintenance expenses are running ahead of budget. Individually, these developments may seem manageable. Together, they could significantly reduce the amount a lender is willing to advance.

Experienced asset managers have always monitored these indicators, reviewing operating statements, tracking budget variances and adjusting financial projections as conditions change. The challenge is doing so frequently and thoroughly across portfolios with hundreds or thousands of units, particularly when the warning signs are subtle.

This is where artificial intelligence can make a meaningful difference. AI can examine large volumes of operating activity, identify emerging patterns, and direct management’s attention to properties showing early signs of financial strain. An increase in concessions across thousands of leases, a gradual deterioration in collections or a sustained rise in certain expenses can be flagged before those trends have a substantial effect on overall NOI.

For an owner with 30 properties, that might mean identifying the handful where operating performance is beginning to diverge from expectations, then determining which warrant immediate attention because of an approaching loan maturity.

The ability to conduct this analysis regularly and at scale can give owners valuable additional time to respond and can create opportunities for more informed financial planning. If a property’s operating results suggest that expense growth will exceed the original business plan, owners can test alternative assumptions to understand how projected NOI and refinancing proceeds might be affected.

What happens if concessions remain elevated for another year? How much would a further increase in operating expenses reduce the property’s borrowing capacity? Would adjusting capital spending or pursuing a different leasing strategy materially improve its position? The resulting decisions remain firmly in human hands. An owner might renegotiate service contracts, revisit leasing incentives, reconsider capital expenditures or begin discussions with lenders and equity partners earlier than planned.

Some problems will be beyond management’s control as AI cannot reverse higher interest rates or eliminate the refinancing challenges facing highly leveraged properties. Even substantial operational improvements may leave owners facing an equity shortfall. But there is a meaningful difference between discovering that shortfall shortly before a loan comes due and recognizing the risk a year or more in advance.

As multifamily owners confront the next wave of loan maturities, the measure of AI’s usefulness will be whether it helps them identify the financial issues that deserve attention and act while meaningful options remain.

Arunabh Dastidar is the co-founder and CEO of real estate AI infrastructure platform Leni.