What impact has COVID-19 had on the banking sector? A question that has been explored from every angle over the past fifteen months, since the first global confinement led to a financial crisis.
There are so many facets about COVID-19 and banking, some of which have been quite surprising. It has sparked the acceleration of digitization to keep employees and customers safe at a distance. It has changed the way banks analyze risk-sensitive investments, especially when it comes to commercial real estate.
The market for almost every sector of commercial real estate experienced an immediate downturn at the very onset of the pandemic, as the global lockdown resulted in more than half of the workforce working from home and the shutdown of all stores except the most essential. Recreation facilities have been closed, travel has stopped.
Asset managers found themselves forced to renegotiate contracts (or worse) due to an influx of vacant real estate. This, in turn, had an impact on lenders, with a default rate of nearly 8% recorded in July 2020. What was supposed to be a short foreclosure turned into an extended period and businesses flirting with a hybrid work office model and retailers are focusing more on e-commerce.
Even the banks that were well established before the pandemic were not prepared for this shock. When people have to close their businesses, income is lost. No income equals depleted balance sheets, forcing organizations to need loans to stay afloat or pay rent. In their defense, it was a difficult situation for the banks. How do you calculate the unknown risk of a situation never seen before? Volatile commercial property loans are now valued using higher risk exposure calculations, putting a lot of pressure on lenders to restore balance. All of this is going to have lasting effects on commercial real estate. It is impossible to separate the banking industry from the events around it, to quote a well-known consulting firm, “business problems are banking problems”.
Nothing lasts forever, at least we are told, and recreation and tourism are expected to eventually return to pre-COVID-19 levels. However, that may not be until the end of 2022. What the world will look like then is also up for debate, as the future of the real estate finance industry commercial remains to be determined.
To use the hackneyed adage, “the new normal” for most businesses may well be a hybrid model that supports flexible working and shared offices. The idea is that the rise of remote working will lead to a reduction in the need for office space as well. That said, not all industries can function optimally as remote-based agencies forever, and that, coupled with humanity’s need for contact, can be a silver lining for the market. Overall, analysts say it is still too early to predict how office vacancy levels will evolve in the coming months. The only sure thing is that change will be necessary, and innovation will also be needed in the ERC market. Changing what the office means to people and looking at technology to help transform areas that once housed offices is the only way to meet the changing needs of a now more digitally-centric workforce.
Understanding what will happen to store closings, declining office demand, and loan abstentions requires hindsight and foresight, both of which can be gleaned from data. Over the past decade, the way we handle data has changed almost immeasurably. Machine learning and artificial intelligence have made it possible to manage vast amounts of information and discern patterns from previously invisible data. While it is too early to accurately predict the outcome of the pandemic, patterns are starting to emerge and AI allows us to look ahead and adjust our business strategies accordingly.
One of the most important characteristics of AI is its ability to consume and process a large amount of data. AI can be programmed to process data from multiple sources and calculate an unfathomable amount of permutations. For real estate clients, this could include tenant data such as news mentions, financial data including loans, and employee data; market data such as industry indices, data on local employment and availability of remote work; and rental data such as security deposits, lease size and building use.
Artificial intelligence reduces the time it takes to examine this data manually and quickly uncovers patterns of behavior, financial information and business results. The benefit for an asset manager is the ability to better understand the tenant risk factor. Thanks to AI’s ability to draw conclusions from multiple sources, brokers and owners can now establish the risks associated with small businesses or creditors (think startups), with little or no data available about them. This helps them help banks, asset managers and lenders make better decisions about who to finance.
During the pandemic, those who used data to make these decisions, especially in the banking industry, are in a much better commercial position than those who did not. When the commercial real estate industry has a better understanding of data, the information between them and the banks becomes transparent. Achieving a more accurate level of risk assessment allows homeowners to adjust their prices as well as banks to adjust the amount of capital required. Since the most important factor affecting banks during a crisis is risk management, the ability to understand the micro factors involved in risk is essential to the continued health of the banking industry. It can be done by combining data and AI.
The commercial real estate industry needs to exercise caution and patience while exploring how it can innovate and reinvent itself. The same goes for those who hold the purse strings, the banking industry. The takeaway for the real estate and banking sectors is that understanding the patterns, even when they are still emerging, is the key to navigating our bumpy recovery. As Mckinsey suggests, it’s not enough to be reactive, with portfolio managers and lenders thinking beyond COVID-19 survival, those who succeed must be proactive. It is impossible to fully predict what the future holds, just as it is impossible to fully predict rental risk. But they can both be improved by using a simple strategy: start using more data.