What impact did COVID-19 have on the banking industry? A question that has been probed from every angle over the past fifteen months, ever since the first global lockdown led to a financial crisis.
There are so many facets to the topic of COVID-19 and banking, some of which have been quite surprising. It has sparked the acceleration of digitization to keep both employees and customers safely distanced. It has changed how banks analyze risk-sensitive investments, particularly when it comes to commercial real estate.
The market for almost every sector of commercial real estate experienced an immediate downturn in the very early stages of the pandemic, as global lockdown resulted in over half of the workforce working from home and closures of all but the most essential of stores. Recreation facilities were closed, travel came to a standstill.
Asset managers found themselves having to renegotiate contracts (or worse) due to a surge in vacant real estate. This, in turn, impacted the lenders, with a reported repayment delinquency rate of almost 8 percent experienced by July 2020. What was to be a short lockdown turned into a protracted period and companies flirting with a hybrid work office model and retailers are focusing more on e-commerce.
Even the banks that were sitting pretty before the pandemic, were not prepared for this shock. When people must close their businesses, income gets lost. No income equates to drained balance sheets, leading to organizations needing loans to stay afloat or pay the rent. In their defense, this was a tough situation for banks. How do you calculate the unknown risk of a never seen before situation? Volatile loans on commercial properties are now being evaluated using higher risk exposure calculations, placing a lot of pressure on lenders to redress the balance. All of this is going to have lasting effects on commercial real estate. It is impossible to divorce the banking industry from the events around it, to quote a well-known consultancy firm, “business issues are banking issues.”
Nothing lasts forever, or so we are told, and the expectation is that leisure and tourism will eventually return to pre-COVID-19 levels. However, that may only be by the end of 2022. What the world will look like then is also up for debate as the future of commercial real estate finance sector is still yet to be determined.
To use the over-used adage, “the new normal” for most companies may well be a hybrid model that supports flexible working and hot desks. The thought is that the rise of remote work will see a reduction in the need for office space and. That said, not all industries can work optimally as remote-based agencies forever, and this, coupled with humanity’s need for contact, may be a beacon of hope for the market. Overall, analysts claim that it is still too early to predict how office vacancy levels will change over the coming months. The only sure thing is that change will be necessary—and so will innovation in the CRE market. Changing what the office means to people and looking at technology to help transform areas that once played host to desks is the only way to support the changing needs of a now more digital-centric workforce.
Understanding what will happen from the store closures, shrinking office demand, and loan forbearances requires hindsight and foresight, both of which can be gleaned from data. Over the past decade, the way we process data has changed almost immeasurably. Machine-learning and artificial intelligence has made it possible to handle vast amounts of information and discern patterns from previously invisible data. While it is too early to predict the outcome of the pandemic accurately, patterns are starting to emerge, and AI allows us to look into the future and adjust our business strategies accordingly.
One of the most important features of AI is its ability to consume and process large amount of data. AI can be programmed to process data from multiple sources and compute 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, local employment data, and remote-working availability; and lease data such as security deposits, lease size, and building usage.
Artificial intelligence reduces the time it takes to review this data manually and quickly unearths patterns in behaviors, financial information, and business outcomes. The benefit to an asset manager is the ability to better understand the risk factor of tenants. With AI’s ability to draw inferences from multiple sources, brokers and landlords can now establish risks associated with smaller businesses or creditors (think startups), with little or no data available on them. This helps them assist banks, asset managers, and lenders make better decisions on who to finance.
During the pandemic, those who used data to make these decisions, especially within the banking sector, are in a much better business position than those who didn’t. When the commercial real estate industry has a better grasp of data, the information between them and the banks becomes seamless. Reaching a more accurate level of risk assessment allows landlords to adjust their prices as well as banks to adjust the amount of capital required. Since the most significant factor affecting banks during a crisis is risk management, the ability to understand the micro-factors involved in risk is essential to the ongoing health of the banking industry. This can be done by combining data and AI.
The commercial property industry needs to exercise caution and patience while looking at how they can innovate and reinvent themselves. The same goes for those holding the purse strings, the banking sector. The takeaway for both the property and banking industries is that understanding patterns, even while they are still emerging, is key to navigating our bumpy recovery. As Mckinsey suggests, it is not enough to be reactive, portfolio managers and lenders thinking beyond surviving COVID-19, those who will be successful must be proactive. It is impossible to perfectly predict what the future holds, just like it is impossible to perfectly predict tenant risk. But they can both be done better using one simple strategy: start using more data.