There are five primary sources of information you can use to evaluate Small Business applicants, which are:


1.      External commercial information about the credit applicant’s business compared to their peers.

2.      External consumer data about the payment habits of the principals of the business.

3.      Credit application information.

4.      Up-to-date financial statements and bank references.

5.      Credit references.


All businesses large and small have accounting software where a current Balance Sheet and Operating Statement typically is available by simply a mouse click.  Banks have blank forms whereby a credit applicant can pencil in information and direct it to the creditor.


It is always a good idea to inquire with as many credit grantors as the applicant has had experience with.  Those seeking credit may have a short list of references involving small dollar amounts.  It is not unusual to keep a select group of creditors “current.” Ask for more credit references than the credit applicant is willing to give.


A principal’s credit history is very valuable when dealing with a sole proprietorship or partnership. This can also be a valuable tool if a new corporation was formed from using personal savings or a loan by the principal to the business. Bear in mind that the consumer credit history of the principal of a business will look more risky than a typical consumer.


DEVELOPING SCORE CARDS – Viewing, interpreting and making informed decisions from a number of sources of information could be a daunting task.  Developing statistical models for risk requires expertise in four of the following areas:


1.      Your business – to interpret the statistical results and implied decision rules.

2.      Data collection and sample instruction.

3.      Advanced analytical techniques to accurately transform data elements into meaningful predictors with appropriate weights.

4.      In-depth understanding of commercial and consumer information.


INTERPRETING THE STATISTICAL RESULTS AND APPLYING DECISION RULES – As the credit grantor decision maker, you must decide on what the DSO (Days Sales Outstanding) or DPT (Days Past Terms) should be and then assign a weighted value as to frequency and length outside of Terms. National averages can be found at our statistical model within our web page entitled “When to Place.” A typical Small Business Scorecard defines a “bad account” as a severely delinquent company that fails to repay its financial obligations within 90 Days Past Terms.  Typically, banks do not recognize receivables as having value beyond 30-Days Past Terms. Credit Departments tend to adopt a passive position and wait too long to act rather than be proactive.


DATA COLLECTION AND INTEGRATION – Information on the credit application, trade reports, credit references must be gathered and assigned values.


MODEL ESTIMATION – Modeling begins with a careful determination of the business and the principal owner characteristics associated with poor payment behavior.  These relationships should be converted into statistical probabilities, which rank in order of a small business with respect to potential delinquent behavior.


MODEL PERFORMANCE AND VALIDATION – After the model has been constructed, there should be rigorous statistical testing. The model should reflect that firms with lower scores exhibit poor payment behavior on a wide range of small business transactions.  This is the only way to determine if the scorecard model is effective in assessing and rank order of small business risks. A good scoring model will withstand a downturn in the economy and continue to rank risk order properly.  Credit scoring is a proven, effective technique that helps estimate a company’s future payment performance so you can quickly decide if a company is low, moderate or high risk.  These scoring solutions allow you to automatically accept risks or deny credit.  A scorecard model need not be elaborate but it can be simple provided all the important factors are included and properly weighed.  Any scoring model should include 1) payment history, 2) bank and trade references, 3) credit agency ratings and 4) financial statement ratios.  It is vitally important that financial statements be obtained on a regular basis.  Weights should be assigned to all of the above-described elements. Negative changes should serve as a “red flag,” i.e. a decrease in net worth or the reduction in sales.  Other sources that should figure into a scorecard model would be aging, disputes and trade association history. 


Most companies use a combination of “judgmental” and “rule based” systems whereby certain data gathering is weighed objectively by the evaluator who gathers the information based on a series of questions resulting in a ship/do not ship decision. Rule based scoring is a traditional standard that is weighted, which includes payment history, bank and trade references, credit agency ratings and financial statement ratios. Past credit department experience should be used in determining the weights of all the information sources referenced above.  The amount of credit extended should always relate to the risks associated with the results of the scoring model used by credit departments.  Once the scorecard model is constructed and weights are applied to the varying factors, the credit score should help predict the creditworthiness of a potential or existing customer. In the credit scorecard do not forget to assign a weight to number of years in business, credit reference histories and incidences whereby the debtor fails to address the undisputed portion of an overdue balance.