Do you know what the worst problem for any business is – one that can severely impact cash flow? It’s when customers stop paying altogether, leading to aging invoices, higher days sales outstanding, cash flow issues, and increased bad debts. These problems often arise from ineffective credit policies and poor credit risk management.
So, how can you prevent these issues?
The key is to gain a thorough understanding of your customer’s creditworthiness and assess your existing credit policies. This is where credit risk analysis becomes essential.
Want to learn how it can streamline accounts receivable and improve cash flow? Let’s get to it.
Credit risk analysis refers to evaluating a customer’s creditworthiness and determining their ability to settle overdue invoices. The process involves examining a customer’s financial history, credit score, income statements, cash flow status, and other relevant factors to determine the level of risk associated with offering credit.
The purpose of credit analysis goes beyond credit evaluation. It is a process that helps you weigh the costs and benefits of taking on credit risk and measure, analyze, and manage risks your business should accept. However, creditworthiness is not the only risk a business faces in credit sales. You may also face potential losses from missed payments and chances of bad debts that need to be weighed against benefits like risk-adjusted return on capital (RAROC).
Credit risk assessment helps you explore the acceptable amount of credit risk and streamline accounts receivable risk management. To find out the cost of risk, the AR team gathers and applies countless information from customers, external parties, or dedicated credit agencies. These measures include credit risk scores, credit risk assessment models, etc. They are further used to find out the expected loss (EL), probability of default (PD), exposure at default (EAD), and loss-given fault (LGD).
Here are the main reasons why credit analysis is vital for accounts receivable risk management.
A robust credit risk assessment enables you to evaluate the likelihood of default and detect potential losses and chances of non-payments early on by devising tools like credit risk scores and risk models. This will also help set appropriate credit limits and minimize the chances of bad debts and late payments, thereby adopting a proactive approach. You will be able to adjust credit terms to reduce the impact on cash flows or request collateral for high-risk customers, adjusting financial losses.
Credit analysis is not merely evaluating default payments. It also considers a customer’s overall financial health, including liquidity, solvency, and profitability, and gives a comprehensive view to assist AR teams in making informed decisions. It may include whether or not to extend credit to newer or high-risk businesses, potentially leading to business growth and expanded market presence.
Credit risk assessment also allows you to weigh the benefits of additional credit risk, such as interest revenue and portfolio growth, against the potential costs. By optimizing credit policies and managing risks effectively, you can achieve a favorable Risk-Adjusted Return On Capital and foster a strong, long-term customer relationship.
An effective credit risk analysis is critical to maintaining stable cash flows in the business. Poor credit analysis can lead to higher bad debts, inadequate liquidity, making it difficult to meet operational expenses, and insufficient working capital, which stands in the way of expansion.
Invoices might become bad debts if adequate measures are not taken to collect the payments. Credit risk assessment enables you to extend credit to reliable customers who are more likely to repay on time, helping you avoid the risk of bad debt.
Whenever your business has a trend of increasing DSO (day sales outstanding), you must take additional steps, including spending more resources and time collecting the payments. Credit risk analysis helps reduce the hidden operational costs of late payments by lowering the DSO. It also contributes to maintaining positive working capital to fund the company’s current operations and future growth initiatives.
Credit analysis provides greater visibility into accounts receivable forecasting. It helps your business identify high-risk customer accounts and plan strategically to tackle them. Reducing default risks can improve the financial health of your business.
Customer satisfaction is vital for a company’s long-term growth. Credit analysis enables you to onboard low-risk customers quickly and improve their overall experience. Loyal customers who pay on time also help you utilize your resources to expand your services.
Choose the right credit management vendor with our credit management vendor evaluation scorecard.
Conducting a comprehensive credit risk analysis can enhance cash flow and mitigate the impact of bad debt. For optimal outcomes, prioritize periodic assessments over annual ones.
Moreover, you can elevate your credit processes through the prowess of automation. By implementing Credit Risk Management Software to automate the process, you can consistently monitor the health of your receivables and achieve unprecedented reduction in bad debts.
You can calculate credit value at risk in three phases:
List all collections of assets or debts first. The value of each asset or credit must then be evaluated in context of the open market. Then, find out the probability of each customer breaking the terms of their credit terms during the contract.
To calculate the expected loss, use this formula:
Expected loss = Probability of default x Default probability x Loss given default
Where, default loss = 1 – recovery rate
You can use simulation to find out the loss distribution of the credit terms with the customer. To calculate the same:
Worst credit loss – expected credit loss = credit value at risk
Consider a B2B credit sale where Supplier A extends a $50,000 credit limit to Company B to purchase inventory. However, Company B faces an unexpected downturn due to a market shift, affecting its cash flow. As a result, Company B begins delaying payments and struggling to meet the agreed-upon credit terms.
Supplier A assesses Company B as a high credit risk due to the potential for default. They review Company B’s financial statements and payment history and may consider adjusting credit terms or seeking a payment plan. If Company B cannot resolve its financial issues, Supplier A may have to initiate collection procedures or even write off some of the debt, resulting in potential losses due to credit risk.
The credit risk assessment method involves assessing unpaid invoices, categorizing and grouping customers, calculating DSO, reviewing receivables aging reports, conducting periodic credit reviews of your customers, streamlining deteriorating payment trends, finding AR concentration ratios, and more.
The first step is to review your customers’ past few years’ invoices and understand the reasons for delayed payments. You can use the record of unpaid invoices to determine which customer is more prone to default risks or requires additional payment guarantees. After analyzing the invoices and identifying the default risks, you can categorize the late payment trends and group customers accordingly for dunning purposes.
The more segmented your customer base is, the easier it is to identify and analyze high-risk profiles and focus accordingly. Consider grouping your customers based on factors such as:
For instance, if a few customers exhibit poor payment practices, you can group customers based on their payment trends. You might notice that most defaulters belong to the same industry, and currently, it might be risky to do business with them You can accordingly reduce your exposure to clients from that industry or take additional precautions when dealing with them.
Days sales outstanding measures the average number of days a company takes to collect payment for a sale. You can segregate customers using this metric and analyze which segments make their payments on time and whose DSOs and more prone to risks. To calculate DSO:
DSO = (Accounts Receivable / Total Net Credit Sales) x Number of Days
The accounts receivable aging report lists the unpaid invoices and their outstanding duration. Let’s assume a company has $250,000 in its accounts receivable. $50,000 falls under the 0-30 days aging bucket, $150,000 in the 31-60 days aging bucket, and the remaining $50,000 in the 61-90 days bucket.
An aging report gives you a more detailed breakdown of the open invoices. It reflects how long your invoices remain open and gives an idea of how many customers delay their payments. It also helps determine whether the current credit limits are suitable or not. If your report shows any deviation from the standard payment patterns, there might be a need to investigate the issue.
Periodic credit reviews assist you in evaluating your customers’ credit profiles at regular intervals. They help you review credit risk scores and assess customers’ creditworthiness to determine appropriate credit limits. Additionally, you gain a more nuanced view of your customers’ financial health, especially during volatile market conditions.
Your AR policy should include what actions to initiate against customers who default or pay late, and make sure to communicate your policies clearly to customers. Some of the potential steps you might consider to manage deteriorating payment trends are:
The accounts receivable concentration ratio is a metric to determine the risks associated with your accounts receivable. It helps evaluate:
If the ratio of unpaid receivables to total receivables is high and closer to one, it indicates that even if one customer fails to pay, it will significantly impact your business, and you need to reduce it.
It is necessary to understand your customer’s industry well to ensure consistent credit risk mitigation. Some of the factors that you should consider are:
Based on the insights, you can tailor your services to fit their specific requirements. It also establishes a trustworthy relationship between the customer and the company.
Using predictive analytics tools can help you accurately forecast future events and risks associated with credit sales and better prepare your business to mitigate credit risks. These analytics will allow you to Identify doubtful debts, anticipate bad debts, and help you put in extra payment collection measures when dealing with high-priority customers. To understand your customer’s future financial health, you should also analyze their growth strategies and upcoming projects.
Technology solutions help optimize processes and improve efficiency. An automated credit management software will enable you to streamline the process with the right technology, standardize the process, enable real-time credit data monitoring, and increase the efficiency of detecting potential risks.
Manual credit analysis comes with numerous challenges. First, businesses have a hard time getting complete access to critical data. The information available is either incomplete or inaccurate. Second, there is no interconnectedness regarding credit risk management in a global landscape. Third, the constantly changing financial landscape makes it challenging to keep the process simple and ensure transparency.
An automated credit management software monitors external data such as bankruptcy alerts, credit ratings downgrades, and lien notices to alert your credit analysts about “at-risk” accounts, enabling real-time credit data tracking. For instance, D&B will provide the bankruptcy alert indicator in its reports, which gets captured and shown in the worklist. Or, Bloomberg publishes an article about Company X acquiring Company B. This news will get picked up by the monitoring systems to trigger a credit analysis of Company X and Company B, two of your customers.
Credit management software like ours offers out-of-the-box financial statements and data extraction features to public financials from S&P, Edgar, BvD, Moodies, etc. Besides downloading the balance sheet, income, and cash flow PDF statements, granular financial metrics like key ratios are captured to feed into credit scoring algorithms. Additionally, private companies can upload a copy of their financial statements through the online application form that reads using AI-based data capture algorithms.
For instance, if the current ratio is one of the financial indicators of a company’s health, it will be captured from the company’s balance sheet, and the value will be automatically extracted and used in the credit risk score.
A good credit application software offers you out-of-the-box credit agency integration with over 25 agencies like D&B, Experian, Creditsafe, BvD(Moody’s), Equifax, Cortera, Graydon, and others. These integrations not only capture the credit PDF reports but also give granular credit fields for granular credit fields that can be automatically fed into the credit scoring algorithms.
For example, ‘Paydex’ is a score that D&B calculates based on a customer’s historical payment performance. It is very similar to a FICO score used to evaluate customers’ payment behavior. The credit software will automatically capture this value to use in credit scoring algorithms.
With automated credit application software, you can create a daily work list of prioritized customer accounts for analysts to review with automated credit workflows. You can categorize customers in the worklist for reasons like credit limit exceeded, blocked orders, new customer applications, bankruptcy alerts, expiring collaterals, periodic reviews, etc.
For instance, John reviews his customer accounts per the prioritized credit worklist. During the day, the system automatically prioritizes any blocked orders to show as the highest priority in John’s worklist, enabling him to review and determine if the order can be released quickly.
Create or update your credit policies and strategies using our
Customizable Credit Policy Template
If you want to make the best of credit risk analysis, you would need integrations for at least three credit agencies, around 10-20 application forms for different scenarios, and AI modeling to predict. All this build-up will easily cost up to as much as $670K and maintenance costs of $200K if you try to custom-build in your ERP instead of using out-of-the-box functionalities.
To help you avoid these costs and build a firm credit risk assessment in place, HighRadius brings you state-of-the-art, automated credit management software. The solution identifies at-risk accounts and reduces bad debt write-offs by 10-20%. Through the built-in workflows, you can approve, reject, or reassign with a single click, simplifying credit approvals. Additionally, if you are working with multiple agencies at once, HighRadius, using a waterfall model, can aggregate data from one agency at a time and stop once it captures all the necessary data. This way, you can reduce the cost of consuming credit agency reports.
The results? You can increase reviews by 3X while increasing credit analyst productivity by 30%.
Credit exposure is a critical component of credit risk that indicates the maximum loss to a business if a customer defaults on the credit. Other components include the default probability, which refers to estimating the probability a customer will fail to pay his past dues against invoices.
To minimize credit risk, you must carefully evaluate customers’ creditworthiness. After assessing credit risk properly, you can set up credit limits and renegotiate payment terms that benefit both your business and the customer. Additionally, you can offer discounts to encourage early payments.
The primary component of credit risk involves the chance of not repaying and the magnitude of loss if repayment doesn’t occur. Three aspects are crucial in credit risk analysis: evaluating the borrower’s payment history, assessing their financial situation, and gauging the stability of their industry.
Suppose you want to close a deal with a credit sale. But before, you have to evaluate their creditworthiness using a credit risk score. You will assess financial indicators like payment history and debt levels to estimate the likelihood of default. Based on the analysis, you can adjust credit limits.
An accounts receivable risk assessment identifies customers most likely to fail their payments using factors like credit and payment history, financial stability, and account balance. It essentially determines the chances of a business not receiving payment for the services or goods sold on credit.
Credit risk analysis usually involves logistic regression analysis – a statistical method used to model binary outcomes such as customers failing to pay their invoices. Other techniques are linear discriminant analysis, decision tree models, and machine learning models, which are used depending on the complexity level of the analysis.
The 5 Cs of credit risk analysis are Character, Capacity, Capital, Collateral, and Conditions. These components help businesses assess a customer’s creditworthiness by evaluating factors such as the customer’s reputation, ability to repay, financial assets, collateral offered, and the broader economic conditions that may impact payment reliability.
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