The Theory of Credit Scoring Every Mid-sized Business Should Know!

In the current economy, cash is the oxygen for a business, which is why mid-sized businesses must have a steady cash flow to meet their daily business expenses. But there’s no bigger truth than this - not all customers would pay on time, customers will default. And the money you are owed would seem like disappearing in the black hole of uncertainty. While it’s not possible to be sure about a customer defaulting on a payment, businesses could and should have a robust credit management process to mitigate risk and make lending more cost-efficient.

This blog aims to highlight some of the key pointers every mid-sized business needs to keep in their playbook when assigning the credit score to their customers. But before that, let’s understand what makes credit scoring such a vital necessity in the business world.

The Golden Circle of Credit Scoring

Why is Credit scoring so important?

During uncertain economic times, credit analysis and scoring play an important role in evaluating the credibility and financial performance of a business to determine if the customer will be able to generate enough cash to pay for their orders. Moreover, the COVID crisis has left most credit analysts scratching their heads to entertain customer requests for flexible credit terms and payment plans to accommodate the global crisis and unstable cash flow.

Without an infrastructure to assess credit worthiness of the customer portfolio, businesses could incur significant losses if they extend flexible or lenient credit terms to their customers.
In order to stimulate business growth and encourage sales, credit professionals need to have a comprehensive understanding of credit data to get a 360-degree view of associated risks and business opportunities.

What makes credit scoring vulnerable?

Most mid-sized businesses do not realize the importance of having a strong credit policy until they have taken quite a few blows of revenue loss due to poor evaluation of the financial capabilities of their customers. Not that anyone is to be blamed, but lack of proper infrastructure and poor credit management system often has a detrimental impact on the cash flow.

Companies often rely on either subjective credit assessment, or a primitive credit policy to extend credit to their customers. Typical credit policies with standard credit limits and payment terms might make customer onboarding simple but could also expose you to the risk of losing money if a customer’s business takes a sudden nose dive or in cases of financial uncertainty. For instance, in the COVID economy, where the customers are negotiating for flexibility – lack of credit assessment process makes the decision of ‘who to extend credit’ and’ how much ‘, difficult and time-consuming.

How is Credit Scoring Done?

Credit scoring is done based on the credit data of a customer, such as repayment history, delinquency history, length of credit history, and total debt. For a new customer, all of these credit data are aggregated from credit agencies and credit groups. Applying this credit data into a scoring model allows businesses to get the respective credit score, risk class, and credit limit of a customer.
What’s important to note here is the authenticity of the credit information that businesses collect. The sources need to be credible to help businesses make decisions backed by reliable data and intelligent insights. Some sources to trust include:

• Credit Bureaus like D&B, Experian
• Credit Groups like NACM
• Public Financials (Purchase and assumptions(P&A), Balance Sheet, etc.)
• Alternative sources like Personal guarantee

Shine the spotlight on the 7 must-have credit scoring factors

A healthy credit scoring model consists of three key components: Accurate information, sound financial management, and regular monitoring. To effectively manage credit, businesses need to be aware of the 7 must-have parameters for effective risk management and making better financial decisions.

• Delinquency Score (D&B): This score provides insight into the likelihood of a business paying late or having future payment problems. On a scale of 1-5, a delinquency score of:
  • 1 suggests a low chance for delinquency
  • 5 suggests a high chance of delinquency
• Paydex Score (D&B): This score is assigned by Dun & Bradstreet, based on the past payment performance of a company, and puts the company into a risk group based on a score ranging from 1 to 100. The risk categories are as follows:
  • 0-49: High risk of late payment
  • 50-79: Moderate risk of late payment
  • 80-100: Low risk of late payment
• Average Days Beyond Term(DBT)(D&B): This is an important credit term that describes the average number of days it takes a business to pay its bills past the due date. If payment is made beyond terms, for example, let’s say based on open invoices,
  • customer A had to pay $1000 by April 30
  • $1000 is paid on May 2
  • Days in arrears = 2
  • DBT = [sum (payment amounts x days in arrears)] / [sum (payment amounts)]
  • DBT = (1000 x 2) / 1000 = 2
• Predictive Scoring (NACM): This score takes into account 12 months of historical trade data to predict severe delinquency looking forward 6 months. Based on a score between 450 to 850, the risk categories are as follows:
  • Very low risk – Score Range 751 – 850
  • Low risk – Score Range 671 – 750
  • Low to moderate risk– Score Range 621 – 670
  • High risk – Score Range 571 – 620
  • Very high risk – Score Range 511 – 570
  • Extreme risk – Score Range 450 – 510
• Total Employees (D&B): This data reflects company size based on net worth or equity as computed by D&B. This is assigned to businesses that do not have a financial statement. Based on the employee size and analysis by D&B of public filings, trade payments, business age, and other important factors, a business is assigned a score between 2-4, where:
  • 2- Good
  • 3- Fair
  • 4- Limited
• Failure Score (D&B)
  Previously known as Financial Stress Score is a dynamic risk indicator predicting the probability of a business going bankrupt in the next 12 months. On a scale of 1 to 100, higher scores indicate a lower probability of failure.
• Years in Business (D&B): A company’s ability to pay on time can be partly determined by its size and number of years in business. This is one of the many firmographic information taken into account to determine the creditworthiness of a customer. More the number of years, the more trustworthy the business is.

Set the stage for credit scoring model

A robust Business Credit Scoring Model with the ability to analyze different customizable parameters from credible sources such as D&B, Experian, and NACM could help credit professionals automatically assign credit scores to customers, ensuring that accounts with the highest risk are identified. Moreover, It could give a credit professional visibility into a customer’s future financial condition and help forecast what the coming years might look like- whether the business will still be running or end up being bankrupt.

Similar to Hawking’s theory of everything, Mid-sized businesses need to have one all-encompassing Credit Scoring Model to counter the misfortune of triggering a credit event such as bankruptcy, obligation default, or failure to pay. A Ready-to-use excel based credit scoring model might come in useful for effectively scoring a customer while ensuring a reduction in bad debt and improvement in cash flow.

Roll out the red carpet for automation

While an excel-based scoring model might give companies an edge and accelerate the credit scoring process, it’s still a dime a dozen. The rise of artificial intelligence and technology has made it easier, faster, and more cost-effective to mine vast quantities of data and make meaningful decisions out of them. While most mid-sized businesses are yet to discover the full potential of automation, credit professionals are betting on technology to find the best customers, partners, and vendors to do business with.

To quote Arthur Schopenhauer, “All truth passes through three stages: First, it is ridiculed. Second, it is violently opposed. Third, it is accepted as self-evident.” sums up the present degree of acceptance of technology in mid-sized businesses.

Well, with time, evolving from traditional and manual processes is a must. Streamline credit management to identify potential opportunities and mitigate risks with faster customer onboarding with HighRadius’ RadiusOne A/R Credit Risk Management App.

With automated credit scoring pre-loaded with models and algorithms- configured based on industry-specific best practices, businesses could easily auto-assign risk score, risk category, and credit limits for customers. The future of automation is here, so leverage automated credit scoring to- decelerate risk and accelerate revenue growth. Get a free demo now!

How HighRadius Credit Risk Software Helps Improve Credit Risk Assessment

HighRadius Credit Management Platform helps mid-market finance teams automate credit decisioning, standardize risk evaluation, and gain real-time visibility into customer exposure without increasing analyst headcount. Built for organizations scaling beyond spreadsheet-driven approvals, the platform combines AI-driven credit scoring, automated workflows, and continuous monitoring to accelerate onboarding, reduce manual reviews, and improve control over credit risk.

With real-time credit risk management tools and AI-powered credit management solutions, finance teams can receive alerts for changes in customer credit profiles and make faster, data-driven decisions using unlimited credit reports. The platform integrates with ERP systems and can begin monitoring customers in as little as 30 days.

• With real-time credit risk analysis software and credit decisioning software, you can receive alerts for any changes in your customers’ credit profile and make data-driven credit decisions from unlimited credit reports. Our software integrates with your ERP system and can start monitoring your customers in just 30 days.
• We offer configurable credit scoring software and approval workflows that can be customized based on geography, customer segments, business units, and other factors. You can fast-track credit approvals through complex corporate hierarchies, making the credit application process more efficient and streamlined.
• Our highly configurable online credit application allows you to onboard customers across the globe with multi-language, customized credit applications embedded on your website. You can automatically capture financials, personal guarantees, and check bank references, reducing the need for manual data entry.
• Our software also automatically extracts credit data from over 40+ global and local agencies, including credit ratings, financials, and credit insurance information. You can configure the auto-extracted data in your preferred currency, making it easier to analyze and interpret.
• With AI-based blocked order management, you can auto-predict blocked orders based on the customers’ credit limit utilization and payment history. You can leverage AI-based release or partial payment recommendations for faster credit decisions, reducing the need for manual intervention.

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