Credit Risk Scorecards – Automating Credit Decisions

The traditional process of extending credit, heavily relies on the analytical skills of credit professionals and how they interpret the data to arrive at a logical decision. While this method is certainly not obsolete, but surely time-consuming, considering the manager has to go through various spreadsheets & credit reports, confirm with trade references and perform thorough customer due diligence before onboarding a customer – a time which could have rather been spent on higher exposure accounts and strategic brainstorming projects. In addition, all these decisions have to be made in a critical time while putting guard against bad debt, bankruptcy, and fraud.

Considering the cut-throat competition where you can neither afford to lose a customer nor enter into a bad deal, credit scorecards are an effective solution. Credit scorecards provide a quick way to effectively identify customers who might pay late or pose other threats to the business. These formula oriented cards offer a consistent and accurate alternative to manual credit decisions.

What exactly are Credit Risk Scorecards 

Credit risk scorecards are mathematical models which attempt to provide a quantitative estimate of the probability that a customer will display a defined behavior with respect to the current or proposed position with the lender. It aims to categorize borrowers according to their creditworthiness. In other words, it is a mathematical formula that uses data elements & variables to determine the acceptable level of risk. The goal of a credit scorecard is to easily distinguish between customers who repay their loans and customers who will not – at a glance!

What goes inside a credit scorecard? 

Credit scorecards represent different characteristics of a customer such as age, residential status, time at current address, time at current job, and so on. Each characteristic is assigned a point and the variables are added together to determine a credit decision of “yes”, “no” or “maybe”. Here are some of the variables that go into the making of a credit risk scorecard.

  • Credit Score: The major contributor to the scorecard includes third party commercial credit report & credit score calculated by credit bureaus such as CRIF along with other historical data and statistics. Also, since third-party providers have access to abundant reliable data, they can provide a more complete picture than internal data or self-supplied references from the customer.
  • A/R & A/P details: Accounts receivable and payables provide an accurate picture of how a company is handling its financial obligations
  • Public Records: Lawsuits, Liens, Judgements, bankruptcies can all indicate a company’s ability to survive.
  • Financial Information: This information includes overall cash flow, current liabilities, assets, working capital, and net worth.
  • Other details: This includes the non-financial details such as industry type, size, geography, business history, years of operation, etc.

Benefits of automating the Scorecard calculation process 

While credit scorecard calculation can be accomplished at a better speed using formulas in spreadsheets, it still takes a considerable amount of time to input the necessary information. Complete automation for new credit requests allows credit teams to scale and eliminate any inefficiencies in the workflow and presales process. The benefits include:

  • Drastic reduction in bad debts: Automation can decrease the occurrence of bad debt and lower DSO/DBT by immediately flagging high-risk accounts.
  • Improves Speed & Efficiency: A formula oriented approach and a predefined algorithm saves a lot of time spent in performing typical tasks, giving the credit manager time to focus on unique decisions and important accounts. What used to take hours can be accomplished with just a few clicks. This can also make way for less experienced staff to work without extensive training.
  • Maintains consistency & quality: Routine credit decisions done with the same formula ensures consistency and removes any subjective bias, leading to fewer customer disputes as well.
  • Increase Sales: Automation speeds up the process and saves a lot of time which means new customers can be onboarded quickly with minimal risk and more time can be invested in creating strategies to improve existing processes and attract new customers.

If you want to capitalize on the immense benefits of credit scorecard for making new customers, improving credit decisions and gain competitive advantage, contact CRIF – one of the leading credit information companies in India. CRIF provides a full portfolio of credit risk analytics & modeling tools, empowering business analysts, from beginners to advanced modelers, to develop, build, test, deploy and manage predictive models. This is especially important for those having large volume accounts and huge competition.