REBA Blog - Rental Housing & Multifamily Data Analytics Insights

NY headlines say “pricing algorithms banned,” but the law itself tells a different story.

Written by Donald Davidoff | 10/22/25 10:43 AM

Coming quickly on the heels of Governor Newsom signing a California law governing the use of pricing algorithms in rental housing, Governor Kathy Hochul of New York signed the latest law restricting certain types of algorithms for pricing multifamily housing.

Once again, the headlines scream “pricing algorithms banned,” yet the actual provisions of the law paint a more detailed and measured picture.

And by now, there’s a pattern to these laws, the natural result of cities and states drafting off each other and from the coordinated advocacy of organizations such as the American Economic Liberties Project. The New York law is a close cousin to the Seattle ordinance passed just a few weeks ago which, by banning even the use of publicly available competitor data, makes it one of the more onerous laws passed. One should also note that, while the language was different, the recent California law also bans the use of even publicly available competitor data.

While it’s natural to decry ill-conceived government intervention into robust business markets, we at REBA resist this in favor of looking at the positive side of this legislative onslaught. While seemingly onerous, these laws actually now provide clear and direct clarity on what is permissible and what is not.

As the famous quote attributed to Jimmy Dean says, “You can’t control the wind, but you can adjust your sails!” So, let’s take a good look at the New York law and understand its implications.

The key element in the law prohibits the use of pricing algorithms that perform a coordinating function. It then defines a coordinating function as one performing all of the following sub-functions

(I) COLLECTING HISTORICAL OR CONTEMPORANEOUS PRICES, SUPPLY LEVELS, OR LEASE OR RENTAL CONTRACT TERMINATION AND RENEWAL DATES OF RESIDENTIAL DWELLING UNITS FROM TWO OR MORE RESIDENTIAL RENTAL PROPERTY OWNERS OR MANAGERS, PROVIDED THAT AT LEAST TWO SUCH RESIDENTIAL RENTAL PROPERTY OWNERS OR MANAGERS ARE NOT WHOLLY-OWNED SUBSIDIARIES OF THE SAME PARENT ENTITY OR OTHERWISE OWNED OR MANAGED BY THE SAME RESIDENTIAL RENTAL PROPERTY OWNER OR MANAGER;

(II) ANALYZING OR PROCESSING THE INFORMATION DESCRIBED IN SUBPARAGRAPH (I) OF THIS PARAGRAPH USING A SYSTEM, SOFTWARE, OR PROCESS THAT USES COMPUTATION, INCLUDING BY USING THAT INFORMATION TO TRAIN AN ALGORITHM; AND

(III) RECOMMENDING RENTAL PRICES, LEASE RENEWAL TERMS, IDEAL OCCUPANCY LEVELS, OR OTHER LEASE TERMS AND CONDITIONS TO A RESIDENTIAL RENTAL PROPERTY OWNER OR MANAGER.

Being virtually identical in language to the Seattle ordinance, the key is to parse through the prepositional phrase in (II), “the information described in subparagraph (I) of this paragraph.” Simply replace that phrase with its antecedent and you get (yellow highlights are mine for emphasis):

(II) ANALYZING OR PROCESSING HISTORICAL OR CONTEMPORANEOUS PRICES, SUPPLY LEVELS, OR LEASE OR RENTAL CONTRACT TERMINATION AND RENEWAL DATES OF RESIDENTIAL DWELLING UNITS FROM TWO OR MORE RESIDENTIAL RENTAL PROPERTY OWNERS OR MANAGERS USING A SYSTEM, SOFTWARE, OR PROCESS THAT USES COMPUTATION, INCLUDING BY USING THAT INFORMATION TO TRAIN AN ALGORITHM; AND ...

The implications are clear

  • We cannot process data from two or more owners or managers to create pricing recommendations
  • We cannot use publicly available competitor information (as with Seattle, and unlike all the other state and local laws to date, this text does not qualify the prohibited data as “non-public…”)

All other actions, INCLUDING ALGORITHMS THAT PROCESS ONLY ONE OWNER OR MANAGER’S DATA, are clearly legal.

I would argue that this is, perhaps unintentionally, a good thing. As we’ve argued before in our point of view paper, the industry over-relies on competitor data to each company’s own detriment.

The future is clear: PRM software must stick to using only individual owner or manager data. No inter-mixing of data, no training AI algorithms on industry-wide data, and at least in Seattle, California and now New York, no use of any competitor data. Note that those three jurisdictions represent 1.8%, 7.8% and 14% of US GDP respectively, a total of almost a quarter of overall US GDP!

This is a serious, dare I say existential, issue for all the prior and new software that relies on competitor data as a key input. However, it is decidedly not the death knell for automated pricing software. It simply means that operators and owners need to turn to well-designed software that is compliant in this new world.

The future of pricing and revenue management in multifamily is now clear. Come join us on this journey!