How a Transformative CRE Market Is Changing Risk Assessment

The commercial real estate industry is experiencing a transformative phase of disruptive market conditions. Last year, multifamily and commercial real estate loan originations topped even pre-Covid-19 numbers, leading to increased competition within the lending community. This was only heightened by new opportunities to expand lending portfolios in proliferating asset classes, such as single-family rentals, data centers and life sciences.

As the market adjusts to this new paradigm of rapid growth, intense competition and significant demand shifts, lenders are expanding their portfolio of property types and lending in unfamiliar areas. They must be able to analyze requests, identify compelling opportunities, and make funding decisions quickly and accurately to thrive in this new environment. However, many lenders still struggle with narrow datasets, disparate systems, cumbersome reporting and clunky manual processes.

“One of the shocking things about CRE lending is how quickly terms are agreed upon and how incomplete the data is supporting the decision,” said David Mitchell, director of product management at Moody’s Analytics CRE. “However, with technology advancements, there is an automated way to retrieve the depth of analysis that used to take weeks. This is particularly important for lenders that must respond quickly to loan requests but need a more holistic risk picture before agreeing to terms.”

The latest market conditions have made access to a comprehensive risk assessment as early as possible critical to strategic decision making. Ensuring they have complete information early in the process helps lenders determine which deals are worth pursuing and which aren’t.

This robust information can also inform optimal deal structures. For instance, if a borrower is seeking a loan for a property with substantial climate risk, an underwriter will be able to offer terms more in line with that risk, or insert mitigants such as enhanced insurance coverage. If a sponsorship search reveals a recent bankruptcy or a troubling pattern of litigation, then lenders can narrow their pipeline and focus on more attractive opportunities. Having a holistic picture before offering terms also eliminates the need to re-trade the deal terms by attempting to renegotiate, which carries the risk of reputational damage. Modern technology allows for complete discovery at the earliest stages of a deal.

Another way in which technology can benefit deal structuring is via fully integrated Probability of Default and Loss Given Default (PD and LGD) models. These models are typically driven by attributes that are readily available, but not stored in a central repository. With a centralized origination system, however, it’s possible to calculate PD and LGD for a given opportunity without transferring data to another disparate system. This presents the ability to price deals according to the credit risk.

“A recurring advantage I’ve seen is where adding one to three years of interest-only to the structure has either no impact or a favorable impact on the expected loss of the loan. This allows for competitive positioning while introducing no additional credit risk to the transaction,” Mitchell said.

Further, this allows for complete transparency with credit risk, when the PD and LGD model used to help inform the deal structure is the same model used by independent credit-risk groups.

As lenders adopt technology-supported processes, they can also change the frequency of their research from periodic, occurring on a regularly planned basis such as quarterly or annually, to triggered, in which technology and automation allow for analysis to occur the instant new information is available.

By keeping these processes on a regular, periodic basis, it’s possible to miss a key window to intervene and mitigate risk or loss. A lender examining a borrower’s financials annually could, for example, fail to learn about a tripped covenant, and could miss months of proactive borrower engagement, or a cash flow sweep if the loan documents allow. Triggered processes, on the other hand, utilize the latest technology to keep the lender informed about financials and market data in real time.

The success of data-driven risk assessment hinges on receiving regularly updated, valid data from a reputable source.

“Any analysis is only as good as the data it is built on,” said Jocelyn Steelman, Managing Director of CRE Products at Moody’s Analytics. “A comprehensive assessment of risk is made up of many interconnected factors — climate change risk, reputational risks, traditional market risks — and these can all impact cash flow and the ultimate valuation of a property or loan. Ensuring your data source can bring together and surface all these dimensions is critical.”

While the value of this approach is clear, without the right technology this kind of comprehensive process isn’t feasible. Lenders are quickly learning that relying on Google searches such as “borrower’s name + fraud/litigation/bankruptcy,” and data systems burdened with redundancies and noise requiring a borrower’s name to be entered up to five times, is not efficient, and is prone to error or omission.

“At Moody’s Analytics, we are developing intelligent solutions to help customers adopt a technology-enabled approach to risk assessment, Steelman said. “For example, our new integrated lending solution, CreditLens CRE, embeds market data along with cash flow and credit risk-rating activities, allowing for more effective collaboration and providing enhanced insights when making lending decisions.”

Lenders will undoubtedly continue to adapt to the dramatic shifts in the CRE market by leveraging technology to optimize and streamline the risk assessment process. Those choosing to pull in multiple dimensions of risk early in the loan process are rising above the pack by quickly narrowing their pipeline to focus on the most compelling deals, and utilizing analyses to make strategic decisions on how to structure a deal through integrated, streamlined workflows.

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