The Fundamentals of Credit Risk Management and How to Mitigate Credit Risk

“We are experiencing a fundamental shift in the global economy, from a world of relative predictability … to a world with more fragility — greater uncertainty, higher economic volatility, geopolitical confrontations, and more frequent and devastating natural disasters,” said Kristalina Georgieva, Managing Director of the International Monetary Fund in a speech at Georgetown University in Washington, DC in October 2022.

Her words pretty much sum up the VUCA world as it exists today, VUCA meaning Volatility, Uncertainty, Complexity, and Ambiguity. This environment has made the job of the risk manager harder than ever before. In a VUCA world risks are higher, but more importantly, they are unpredictable, making it much harder to take prudent business decisions. Credit risk becomes tricky to manage in such an environment; hence, it is imperative to be cautious while granting credit to counterparties.

What is Credit Risk?

Credit risk is the possibility that a lender might lose money if a borrower fails to repay a loan or adhere to contractual obligations. In trade, credit risk refers to the odds that customers purchasing goods, products, or services on credit may not pay their invoices. Credit risks are calculated based on a borrower’s ability to repay the amount lent to them or a buyer’s ability to pay for the goods and services purchased.

What is Credit Risk Management?

Credit risk management is the process of assessing and evaluating credit risk using the 5Cs—credit history, capacity to pay, capital, conditions of the loan/transaction, and collateral offered. Determining the creditworthiness of new and returning customers helps a firm extend the appropriate amount of credit to them and reduces the risk of late payments or defaults.

The following are the key components of credit risk management.

• KYC/KYB and Streamlined Customer Onboarding Process: Know Your Customer (KYC)/Know your Business (KYB) is a step in due diligence and risk mitigation that helps identify and verify the legitimacy of counterparties to help build trust and avert identity frauds, money laundering, tax frauds, and other financial crimes. A proper KYC/ KYB is possible only if accurate and current information is gathered and verified during the onboarding process. The data points can include details about business registration, tax ID, ownership structure, related parties, and management. The submitted data and documents need to be validated through various government databases. If a customer has a Legal Entity Identifier (LEI) code issued by the Global Legal Entity Identifier Foundation (GLEIF) and LEIL, its Local Operating Unit in India, the registration and ownership of the company can be validated easily. The identity risk pertaining to a counterparty can be mitigated by insisting that it obtains a LEI before a transaction can take place.
• Designing and Deploying a Robust Credit Scoring Model: Traditionally, sales executives have exerted a major influence on credit limits and customer onboarding decisions, depending on their own impression of the client. It can often result in having high-risk customers who enjoy higher-than-prudent credit lines. In fact, data-driven assessment of customers’ creditworthiness should be the basis of credit decisions. Companies need to design and deploy Credit Risk Models that predict the probability of default of their customers. These credit risk models arrive at Risk Scores for each customer based on the transaction history, financial statements, statutory compliance, litigation data, social media profile of promoters and management, ownership pattern, trade references, related parties, and customer and employee feedback. Automated Risk Management and Monitoring platforms offered by specialized companies can be used for this purpose.
• Credit Limit Setting Model: Companies also deploy credit limit setting models to set credit limits systematically and prudently. These models recommend actionable credit limits for customers, distributors, and dealers by calibrating their Risk Scores with the companies’ credit risk appetite.
• Credit Monitoring and Periodic Review: In the present volatile environment, a one-time risk assessment is not adequate; the risk of counterparties requires continuous monitoring, as risk profiles can change rapidly. A low-credit-risk entity two years ago may carry one of the highest credit risks today. A large customer from a year ago could be on the verge of bankruptcy. There needs to be an Early Warning System (EWS) that can collate key risk indicators on a near real-time basis from various data sources, including statutory compliance and financial filings, news, and media, to provide a dynamic view of a company’s risk profile. A clear understanding of the sector in which the counterparty operates is also essential. In particular, the potential short-term challenges need to be identified, as these could impact the counterparty’s performance and its ability to meet its financial obligations.
• A Proper Credit Workflow and Credit Limit Approval Protocol: Now, more than ever before, credit decisions have to be made faster, as customers are demanding shorter processing times. However, the number of checks required to be undertaken on a business has only grown. In the absence of standardized workflows, there could be miscommunication or misinterpretation of risk data, resulting in flawed credit decisions. Therefore, credit risk management requires an effective technology-enabled mechanism to facilitate swift and correct decision-making. Automation can help speed up the process and improve the accuracy of credit decisioning.
• An Effective Collection Mechanism: It is easy to sell on credit but difficult to collect on time. Collecting timely payments from debtors is critical to ensuring optimal cash flows. A robust debt recovery mechanism sends a clear message to counterparties about the importance of prompt payment. It also enhances a company’s brand and reputation for conducting prudent business. Modern debt collection solutions leverage data, analytics, and technology to help predict, segment, and prioritize collections, thus helping in the reduction of the company’s overall Days Sales Outstanding (DSO).

Best Practices in Credit Risk Management

• Continuous evaluation of your data sources: Ensure that your model uses the best available and latest data from the most credible sources.
• Protect yourself against financial fraud using the latest risk management platforms.
• Maintain a proactive risk monitoring program
• Ensure that your credit risk scoring model is up-to-date to keep up with the changes in the market.
• Automate the process: Automation reduces the time spent on peripheral tasks and helps your Credit Risk team to focus on the areas that matter the most.

John Shedd evocatively wrote, “A ship in harbour is safe, but that’s not what ships are built for.” Similarly, it is impossible to grow a business without taking credit risks, but it is important to do so prudently in today’s stormy and volatile global business environment.

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