KBRA Assigns Ratings to FREMF 2025-K759 and Freddie Mac Structured Pass-Through Certificate Series K-759

KBRA is pleased to announce the assignment of ratings to four classes of FREMF Series 2025-K759 mortgage pass-through certificates and three classes of Freddie-Mac structured pass-through certificates (SPCs), Series K-759. FREMF 2025-K759 is an $857.5 million CMBS multi-borrower transaction. Freddie Mac will guarantee six classes of certificates issued in the underlying Series 2025-K759 securitization and will deposit the guaranteed underlying certificates into a separate trust that will issue the SPCs.

The underlying transaction is collateralized by 24 fixed-rate multifamily mortgage loans. The loans have principal balances that range from $7.8 million to $79.3 million. The largest loan in the pool, Canfield Park At Fairfield Metro (9.2%), has an in-trust principal balance of $79.3 million and is secured by a Class-A, mid-rise multifamily complex located in Bridgeport, Connecticut. The five largest loans represent 39.1% of the cut-off date balance and also include The Haven Of Ann Arbor (8.9%), Newark Urby (7.4%), Carrara At Cole (6.9%), and Kensington Park (6.6%). The assets are located in 15 states, with the three largest concentrations in Texas (17.5%), Connecticut (14.8%), and Michigan (11.1%).

KBRA’s analysis of the underlying transaction incorporated our CMBS Multi-Borrower rating process that begins with our analysts’ evaluation of the underlying collateral properties’ financial and operating performance, which is used to determine KBRA’s estimate of sustainable net cash flow (KNCF) and KBRA value using our North American CMBS Property Evaluation Methodology. KBRA’s weighted average KNCF for the portfolio is 6.1% less than the issuer’s NCF. KBRA capitalization rates were applied to each asset’s KNCF to derive individual property values that, on an aggregate basis, were 38.0% less than third-party appraisal values. The weighted average KBRA capitalization rate for the transaction is 8.58%. The KBRA credit model deploys rent and occupancy stresses, probability of default regressions, and loss-given default calculations to determine losses for each collateral loan, which are then used to assign our credit ratings.

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Methodologies