Gaining Trust with Accurate Real Estate Financial Models
Real estate developers and investors constantly compete for attention with other professionals in the business, like brokers, other investors, lenders and more. Oftentimes, though, the real estate financial models they use are inflexible and become an obstacle in their efforts. Beginning as single purpose models which are then applied and reapplied over the years to divergent projects with varying needs, these cumbersome models contain no dynamic components, are difficult to use, and frequently have many suspect calculations.
When lenders in particular evaluate prospective development projects, they prefer models that maximize accuracy, speed, and flexibility. Developers and investors gain a competitive advantage in the battle for capital by leveraging models that allow them — and their lenders — to rapidly reassess any scenario.
Eliminating the ‘Hunt and Peck’ Approach
The inability to run quick updates is one of the major downsides to these inefficient financial models. When the need arises to use monthly calculations, for example, users are typically forced to manually enter everything into the spreadsheet — one column per month, with specific dollar amounts for each entry. Updating only a few values can require tedious edits to dozens of related values in a time-consuming attempt to bring the model up to date. This leaves no way to automatically update and refresh the model.
Worse, this manual process increases the risk of errors. That’s important, because accuracy is a major concern among lenders who want to be able to open a workbook and quickly grasp how the budget relates to lease-up and eventual stabilization. The data also should be integrated: A proliferation of disconnected side calculations unnecessarily complicates analysis. It should be easy to extract the information they need from the model.
Getting Away from ‘Frankenstein’s Models’
Analysts have a term for models that have been patched together from a variety of sources, pursuits and projects: “Frankenmodels.”
In the worst cases, the original template may be 10 or 15 years old and it has slowly accrued a mish-mash of disconnected formulas and tabs, awkwardly patched together as a standalone file that is simply copied from the most recent project. Typically, there’s a Dr. Frankenstein at the company — an analyst who works in the model frequently and feels like they have a handle on the monstrosity. Lenders, and anyone else for that matter, struggle to locate information in such models or make changes as part of a sensitivity analysis. That can stall the momentum and encourage the lender to work with someone else whose underwriting is easier to digest. Once a lender has lost confidence in the numbers, that trust is often hard to regain.
It is also common for legacy models to give short shrift to one of the most integral parts of any private equity real estate deal: the investor waterfall analysis.
Real estate investor waterfall structures can take endlessly different shapes and forms. And yet all too often the models in use today do not empower General Partners (GPs) and developers to run scenarios quickly and easily. Typically analysts build waterfalls deal-by-deal, rather than employing a highly customizable template that saves time and can be reused and adapted. This is because the programming is extremely complicated to build a model that handles every possible scenario, so analysts end up taking shortcuts that meet the needs of the current deal.
The GP needs to be able to sit in a coffee shop with potential investors and pitch their partnership in real time, not show up with a printout and pledge to come back with answers weeks later.
Advanced real estate financial modeling tools (like The CRE Suite by CREModels) incorporate waterfall structures where virtually any scenario can be created by clicking a few dropdown menus. Users can show multiple options in minutes instead of spending days or weeks trying to build different calculations.
The commercial and multifamily industries still lag when it comes to adoption of best-in-class modeling tools and approaches. Lenders and developers alike should insist on models that maximize speed, flexibility, and accuracy. Advanced platforms are more expensive, but they can make a massive difference when courting lenders for capital to get a deal across the finish line.
‘Small’ Modeling Error Translates into Big Headache for Real Estate Co.
When one real estate giant hired CREModels to standardize its real estate financial models, the engagement revealed a catastrophic error that powerfully illustrates the importance of honing these tools until they are bulletproof.
As part of the process, the client ran deals through both its own internal models as well as the ones we provided. Shortly after this comparative analysis, we got a phone call: “Something is wrong,” the client said. “The projected returns don’t match up.”
Turns out the company had been mistakenly double-counting growth rates for quite some time. These faulty projections actually combined growth for year one and year two — and on and on, ad infinitum — instead of treating these as discrete data points. This had the effect of drastically overstating the expected cash flow, which in turn also caused the company to overestimate the reversion prices, leading to substantially inflated returns.
They had acquired billions of dollars worth of assets based on these massively incorrect numbers, and no lender or investor had ever caught the mistake.