The current global geopolitical crisis is amplifying existing risks around conducting business internationally, including the risk of counterparty default and bad debts. This is making it increasingly important for organisations to avoid compromising bank finance or leaving cash flows exposed.
Having 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 analysing the risk of non-payment buyer-by-buyer across an entire portfolio and it can still prove challenging to determine aggregate potential losses.
For many businesses, their trade credit risk exposure is managed by the finance department rather than by risk managers. This may create something of 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.
Harnessing data could drive fresh approaches to this important risk area. A risk and analytics model might be used to analyse an organisation’s trade receivables to create actuarial forecasting on the probability and loss default for their portfolio.
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 be able to 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 be able to offer a breakdown of risk exposures by sector and geography, as well as return on investment calculations examining the cost of premiums against potential sales growth and projected losses.
Real-time modelling of credit risk within receivables portfolios, meanwhile, could help enrich boardroom discussions around ways of 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 modelling approaches can empower risk professionals to put their organisations in greater control of credit risk and make them more resilient against ongoing global turbulence.
Get in touch with myself if you’d like to understand how you can more easily quantify your organisation’s trade credit risk, or to book a demonstration of Trade Credit Quantified at Airmic Conference 2022.
