TRADE CREDIT DATA TAKING NO CREDIT The value of trade credit data in <strong>2023</strong> and the increased use of Artificial Intelligence (AI). AUTHOR – Craig Evans THERE are currently 2,552,674 companies that have an account period end date in 2022, and 1,055,190 companies have an account period end date in 2021. So it’s no wonder why the value of trade credit data is currently being questioned. Combining the statistics, with the fact that the latter is really showing the financial position of a company during the COVID years, then it’s value could well be argued against…or is it? Trade credit data plays a crucial role in assessing the risk associated with a particular business or entity. When evaluating the creditworthiness and risk profile of a company, financial accounts data still provides highly valuable insights into the trend and previous performance regarding financial stability and in terms of its weighting on most credit information providers score cards, remains the highest weighted value. Historical financial information provides insights into how a company has performed in the past and is used to predict future performance or risk. Risk assessment requires a forwardlooking perspective to anticipate potential challenges and opportunities that may impact a company's financial stability and credit worthiness. So what are risk assessment teams doing today to understand the current financial position of a company in order to underwrite credit lines? Future modelling In my experience, many teams have now made the leap toward forecasting/ modelling, by using more current data obtained directly from the client, in order to forecast/model the latest financials against. Scoring models and their methodology should be robust enough to accurately predict risks regardless of the ingestion of data. The currency of the data just means that the outcomes are much more enhanced and predictive, due to the advanced age of the data being input. While current and historic financial information is important for analysing risk, there are several issues and limitations associated with relying solely on financial data. The business environment is dynamic, The future of AI in financial risk assessment holds immense potential for transforming the way organisations identify, analyse, and mitigate risks. and industry conditions, regulations, and market trends can significantly affect a company's risk profile. Historical data alone may not capture the impact of these external factors or the ability of the company to adapt to changing circumstances. Financial statements, while essential, do not provide a comprehensive view of a company's risk. Other non-financial factors, such as market reputation, management quality, competitive landscape, and legal or regulatory issues, also contribute to overall risk but may not be fully reflected in historic financial data. Also, financial statements can be subject to manipulation or misrepresentation, intentionally or unintentionally. Accounting practices, reporting standards, and auditing procedures may vary across companies and jurisdictions, leading to inconsistencies or inaccuracies in the financial data. Relying solely on historical financial information may not uncover such discrepancies, potentially leading to an inaccurate risk assessment. Historical financial data may not adequately account for extraordinary events or black swan events that can significantly impact a company's risk profile. Examples include natural disasters, economic crises, or global pandemics, which can have severe consequences on financial stability and disrupt traditional risk assessment models. However, it’s not all about just the financials. The latest accounts form a basis for risk assessment, but other indicators and factors also play a part. Further indicators Payment information includes information about a company's payment history with its suppliers and trade partners. It tracks how promptly the company pays its bills and whether there have been any instances of late payments or defaults. A consistent pattern of timely payments suggests financial stability and lower risk, while frequent late payments or defaults raise concerns about the company's financial health. <strong>Credit</strong> utilisation is also a useful tool as it reveals the extent to which a company utilises its available credit. High credit utilisation may indicate a heavy reliance Brave | Curious | Resilient / www.cicm.com / <strong>September</strong> <strong>2023</strong> / PAGE 16
This augmentation of human decision making with AI technologies enhances the accuracy and efficiency of risk assessment processes. Brave | Curious | Resilient / www.cicm.com / <strong>September</strong> <strong>2023</strong> / PAGE 17 continues on page 18 >
Change language