Description
The current global geopolitical crisis amplifies existing risks around conducting business internationally, including counterparty default and bad debts. This makes it increasingly important for organisations to avoid compromising bank finance or exposing cash flows. A deeper understanding of your trade credit risk can navigate these risks, protect the balance sheet and potentially make it more feasible to expand into new markets.
Typically, achieving a detailed view of total trade credit risk can prove a complex, time-consuming, and potentially costly process. This might call for analyzing the risk of non-payment buyer-by-buyer across an entire portfolio, and it can still prove challenging to determine aggregate potential losses. In addition, for many businesses, their trade credit risk exposure is managed by the finance department rather than risk managers. This may create a false distinction between these credit risks and other types of risks and unintentionally create risk registers that don’t sufficiently cover the full range of exposures facing the business.
Harnessing data could drive fresh approaches to this important risk area. For example, a risk and analytics model might be used to analyze an organization’s trade receivables to create actuarial forecasting on their portfolio’s probability and loss default. By identifying the unique frequency and severity of potential credit risk losses within a firm’s receivables portfolio, data-driven approaches would enable risk managers to structure the most appropriate solutions in light of their specific risks.
A model might cover the rating and spread of risk on an aggregate portfolio, looking at it on a region, sector, or individual buyer basis. It might also offer a breakdown of risk exposures by sector and geography and return on investment calculations examining the cost of premiums against potential sales growth and projected losses.
Meanwhile, real-time modeling of credit risk within receivables portfolios could help enrich boardroom discussions around managing and mitigating risks for this significant asset. These strategies could include carrying a known level of risk or adjusting risk tolerances, halting an insurance purchase, or going to the insurance market to indemnify non-payments of debt for the first time. Regardless of the ultimate strategies, the sophisticated financial health check enabled by modeling approaches can empower risk professionals to put their organizations in greater control of credit risk and make them more resilient against ongoing global turbulence.
