Data Readiness Will Help Your Bank Weather the Next Big Surprise

Most of us are trying to avoid stress in our lives even though it’s inevitable. For banks, it’s unavoidable. The real question is, are they prepared to withstand the stress on their loan portfolio. 

The Federal Deposit Insurance Corp. encourages banks to pursue portfolio level stress testing as part of risk management. But while the agency has outlined principles and examples of stress testing, it stops short of mandating or offering a specific methodology for banks to use. 

Most banks with assets under $100 billion typically perform two of the five recommended tests related to  commercial real estate credit: transactional sensitivity analysis and portfolio-level stress testing. By modeling shifts in interest rates and vacancies, bank executives can calculate how those changes affect the debt service coverage ratios as well as the loan-to-value percentages, revealing how those changes would impact their overall portfolio quality. This has satisfied regulators — for now.  

The FDIC also highlights two more challenging practices on its website: scenario analysis and reverse stress testing. These practices are necessary in response to unusual or unforeseeable events, such as a financial crisis or pandemic, and force significant changes to an institution’s key metrics and loan portfolio performance outcomes, among other things. Few institutions have the necessary data to pursue this type of stress testing. 

Under these conditions, many banking executives have conducted, formally or informally, a type of reverse stress testing to identify causes that affected the loan portfolio’s performance. However, this testing rarely produces concrete and actionable results because the institution didn’t have the necessary data to run the analysis for such a situation.

The issue here isn’t so much an unforeseeable event as it is that the data isn’t there to model them an appropriate response. Because bankers aren’t known to behave like movie scriptwriters or video game developers who imagine a catastrophic scenario and reverse-engineer response scenarios, they need to develop the methodology and focus to build and capture data that will provide the flexibility to adapt to any given situation.  

Part of this exercise will be reviewing past events and noting any gaps between data that was available and data that wasn’t but that the bank needed. For example, the pandemic had everyone scrambling to determine the impact escalating vacancy rates would have on office buildings. Maybe the bank’s data was able to identify office properties taken as collateral but didn’t provide the office space class type or single- versus multi-tenant properties. Identifying these gaps is the first step in building the data infrastructure that will prepare the bank for stress testing. 

Some questions related to fundamental data sets, such as the financials of the bank’s borrowers or guarantors, collateral details of type and value as well as the loans and related deposits of the borrowers, that bank executives ought to ask include: 

• What level of detail in each of these areas has the bank captured?  

• Is the bank capturing data in a consistent manner, or is it up to the individual to determine how the bank captures the data? 

• Where is the bank capturing the data, and how easily can the various data sets be linked? For example, calculate relationship exposure and loan-to-value where a single piece of collateral secures multiple loans (or multiple pieces of collateral secures a single loan). 

Too often, data collection is inconsistent, siloed or incomplete. Without a foundation, even the most sophisticated stress test produces little more than broad hypotheticals to address any unforeseen but looming event.  

For bank executives, the path forward is clear: Build the data infrastructure today that will prepare the bank for any scenario. Stress testing isn’t about predicting the next crisis. It’s about building resilience to geopolitical shocks, policy changes or whatever else comes along by ensuring the bank has the right data to respond when the crisis comes.