Recall a recent commercial loan you structured. What would have enabled you to structure a better deal for your financial institution, and for your client? The decision to issue a loan to a prospective borrower is not solely based on the stand-alone risk of the customer or the specific transaction. Understanding the current risk, borrowing limits, exposure and collateral values for each counter party within the customer’s borrowing group, and across your portfolio, empowers deal makers.
These data points coupled with deal specific covenant terms, allocation of collateral, guarantees, and the structure of the loan terms are all critical to a financial institution’s profits. But most important is the transparency of these metrics at origination and on a real-time monitoring basis to deal stakeholders. Borrowing group dynamics and centralization and intuitive aggregation of risk metrics, in a single system, are two important areas lenders should think about when underwriting their next commercial loan.
Borrowing Group Dynamics
A primary trouble spot for lenders these days is the ability to compile critical data points related to their portfolio of clients in time for making commercial loan decisions. The complete counterparty view is just as much about availability and accessibility of quality data as it is about putting that data to use. When evaluating the risk of a single obligor, lenders typically understand the legal hierarchy of a customer. But it is imperative to understand the credit hierarchy of the customers borrowing group before making that origination decision. The credit hierarchy includes direct and indirect ownership relationships (counterparties) where collateral and other credit risk mitigants must be properly valued. An example of an important entity in a customer’s credit hierarchy can be a third-party guarantor. Another important credit hierarchy borrowing group member are key tenants (e.g., anchor tenant) in an income producing commercial real estate property. This type of relationship information often exists at financial institutions but can only be found deep inside different information systems (often only in spreadsheets), often across different geographic locations. Tracking down this information equates to unnecessary expenses to the business, and is sometimes ignored or just not timely understood which prevents structuring the best deal possible.
Centralization And Aggregation Of Risk Metrics
In addition to understanding the structure of a borrowing group, lenders should understand the risk of all entities in the credit hierarchy to structure the best deal. This is particularly important for related party influencers (e.g., guarantor) within a group. If a guarantor’s internal credit rating changes, this must be understood and transparent across the stakeholders (e.g., relationship managers, portfolio managers) of a borrowing group’s credit hierarchy. This rating change can have a ripple effect on covenant breaches and more importantly credit risk.
Several financial institutions I am working with are centralizing the risk view of their counterparties. This is helping with the optimization of structuring commercial deals. (By the way it also helps tremendously with regulator queries regarding obligor and portfolio risk management.) This optimization includes the ability to structure different types of deals through performance of multiple “what-if” probability of default (PD) and loss given default (LGD) risk analyses. The centralization of data further includes the aggregation of different kinds of lending limits set by the financial institution whether at the industry, geography, business unit, borrowing group or facility level. These defined limits are then compared against current loan accounting system based balance data on a daily or real-time basis. Also, covenants and collateral valuation play an important role to mitigate risks of commercial loan transactions. These deal conditions are defined and tracked alongside the existing and proposed loan terms and risk metrics of borrowing groups.
In conclusion, current risk data transparent to deal structuring stakeholders enables better lending decisions. Historically this type of information was time consuming to gather resulting in unnecessary deal closing delays, poor lending decisions, and lost customer opportunities. Leading institutions are seeing the value of centralizing and consolidating commercial loan origination systems and business processes. And these analyses of commercial loan deals are happening in a single system across multiple business units and geographies.
John Baer is a senior director for Moody’s Analytics
