Conventional B2B credit analysis is leaving businesses with blind spots.
Credit managers and financial executives are increasingly recognizing the limitations of conventional business credit evaluations based on consistent creditworthy performance, steady historical payment habits, and no alarming public facing information. Historical payment data alone is no longer enough to evaluate creditworthiness and can leave creditors surprised when a business fails.
If payment data is not enough, where are credit managers turning for deeper insights?
Most companies are privately held and much of their most valuable business information is not disclosed. How do you sort through prospective customers to determine creditworthiness and identify which customers are in financial retreat? Most credit managers are striving to make these tasks easier by:
- Subscribing to several information sources
- Foraging the internet for publicly available information
- Leveraging search applications to streamline information collection Does simply adding more data to your credit analysis process improve your understanding of companies’ financial health? If you are amassing conventionally available business information, the answer is almost certainly no.
AI can help gain efficiencies and identify news that is important and relevant.
Credit managers have always used news to help understand and monitor their customers. But news volume has exploded in recent years, leaving many organizations complaining of information overload. Today, stakeholders can use artificial intelligence (AI) methods to help identify which articles are worth reading and why. This option frees up time for deeper investigations and allows more names to be monitored. Credit Sentiment is a proven risk assessment method when conventional payment and other related data is not readily available. Using a Credit Sentiment Score delivers the following benefits:
- Quickly identify credit-relevant news: If a Credit Sentiment Score is high, then the article contains negative credit sentiment and deserves further investigation. High scores capture negative news such as default, bankruptcy, covenant default, debt restructuring, rating downgrades, lawsuits, downsizing, and fraud events.
- Drive efficiency: Credit managers can significantly reduce time spent on company research and monitoring activities. Our results show that Credit Sentiment Scores help filter out approximately 75–99% of articles from an initial search.
- Early warning of credit events: Credit Sentiment Scores rise before major credit events. Our research indicates that scores are more than three times higher than normal and continue to rise starting five months before such an event.
- Explainable: Credit Sentiment Scores help users assess the negative credit sentiment of news stories. A news story can easily be read to understand its impact on the company in question.
- Comprehensive credit quality view: Using the Credit Sentiment Score alongside other quantitative metrics gives additional context for why changes in credit quality may occur.
Cybersecurity evaluation is a critical indication of credit quality.
One of the primary responsibilities of credit managers is to ensure that their firm does not engage with customers who pose a significant risk of default. Companies that exhibit poor cybersecurity pose a higher risk of delinquency and default on their obligations. Conversely, strong cybersecurity is a positive indication of strong corporate governance and management effectiveness. Trade credit managers must give dedicated attention to managing cyber risks, alongside financial, operational, and compliance risks. And trade credit managers have the following key concerns when it comes to their customers’ cybersecurity:
- Data Breaches: Sensitive and often proprietary data is shared in a breach, including financial and pricing data. A data breach can lead to monetary loss, reputational damage, and potential legal and regulatory consequences.
- Fraudulent Activities: Cybersecurity threats can result in fraudulent activities, such as identity theft, phishing scams, or invoice fraud. Often these events are due to business email compromise. Trade credit managers need to be cautious about the authenticity of the parties they are dealing with and ensure that their customers’ and suppliers’ systems are adequately protected with the right cybersecurity controls to prevent business email compromise and related fraudulent activities. Phishing scams in particular can affect if and when your invoices are paid.
- Business Disruption: Cybersecurity incidents, such as ransomware attacks, can cause significant disruptions to business operations. For trade credit managers, this can result in delays in processing orders, payments, or collections, leading to potential financial losses and damage to customer relationships. Cyberattacks can be an existential threat, especially to small businesses.
Utilizing key indicators can help unveil business fraud.
Fraud presents a huge financial and reputational risk to businesses. Compliance with sanctions rules is also an important consideration, as businesses have a duty to ensure they are not trading with sanctioned individuals or entities. Access to real-time news and information will help reduce the risk of being associated with trading counterparties found to be committing an offense.
Businesses need ways to identify whether companies within their counterparty network are legitimate, including whether there are associated shell companies, which could indicate illicit activity. Moody’s Shell Company Indicator supports transparency, automatically flagging outliers related to companies you may be reviewing or investigating that demonstrate elevated risk. This can aid investigations and form part of your fraud prevention, supplier due diligence, and third-party risk management programs.
B2B transaction data continues to be a crucial element for modern credit analysis.
In recent years, B2B purchasing data has been incorporated into credit analysis as a powerful predictor of a company's financial health. By analyzing customer spending trends in areas like materials, shipping, and operations, you can detect signals of growth, contraction, or financial instability. To leverage this effectively, credit departments need a comprehensive solution that offers a large, categorized dataset of purchasing behavior, intuitive data presentation, detailed company reports, and seamless integration into existing systems. This approach offers a nuanced understanding of a company's financial trajectory, enabling credit professionals to make informed, proactive decisions.
The impact on credit analysis, management, and beyond.
Traditional methods of credit analysis are no longer sufficient in our increasingly complex business environment, and the need for a more comprehensive, nuanced approach is clear. By harnessing nontraditional credit data, businesses can illuminate the blind spots left by conventional methods. The integration of artificial intelligence and the use of Credit Sentiment Scores can streamline the process, helping to filter out irrelevant information and highlight potential risks. Cybersecurity evaluation and fraud detection tools, like Moody's Shell Company Indicator, are essential components in identifying potential risks and protecting reputations. Finally, the use of B2B transaction data has emerged as a key predictor of a company's financial health, providing valuable insights into spending trends and financial stability. By adopting these innovative tools and techniques, credit managers can make more informed decisions, manage risks more efficiently and effectively, and ultimately secure their businesses' financial future.
Moody’s trade credit solution helps trade credit managers obtain an integrated, holistic view of risk, empowering them to protect their businesses in an era of exponential risk.
