Contributed by

Credit Scoring Model

A credit scoring model is a tool by which financial organizations determine the creditworthiness of individuals or small businesses. Credit scoring is a standardized risk management process used to make credit decisions across loans, mortgages, credit cards, student loans, and other lending opportunities.

A credit score prediction model assigns a numerical value to a potential borrower’s risk, ranked from high to low. Higher scores indicate less risk, making it more likely that the lender will offer more favorable terms, higher loan amounts, and better interest rates.

(Note the difference between credit scoring and credit ratings. Credit ratings apply to corporate organizations, government entities, and asset-backed securities. Credit scoring is reserved for individuals and smaller, owner-operated businesses.)

Types of Credit Scoring Models

FICO and VantageScore are the two most popular credit scoring models.

FICO (Fair Isaac Corporation) is used by the majority of financial institutions while VantageScore was developed by three of the top credit reporting agencies (Equifax, Experian, and TransUnion).

Both models rank a person’s credit-worthiness on a numerical scale between 300 to 850, with higher scores indicating better credit-worthiness. In general, scores under 600 are considered “poor” and scores at 740 and above are considered “good.”

Note that there are multiple versions of FICO scores that may be sent to lenders, depending on the company initiating the request. A person’s FICO score for a bank may be slightly different than a FICO score for a car dealership, for example.

Additionally, the factors that determine these scores vary based on whether a person or small business entity is being assessed.

Personal Credit Risk Model

A personal FICO score is determined by assessing five pieces of data in your credit report:

  • Payment history (35%)
  • Amounts owed (30%)
  • Length of credit history (15%)
  • New credit (10%)
  • Credit mix (10%)

Small Business Credit Risk Model

An owner-operated small business’s credit score is based on different criteria and is scored differently. A credit score prediction model for small businesses ranges from zero to 300 based on these criteria:

  • Company information (number of employees, sales, ownership, subsidiaries, etc.)
  • Historical business data
  • Business registration information
  • Government activity summary
  • Business operational data
  • Industry classification and data
  • Public filings (liens, judgments, and Uniform Commercial Code [UCC] filings)
  • Past payment history and collections
  • Number of accounts reporting and details

The Value of Credit Scoring for Risk Managers

A credit scoring model helps lending organizations minimize risk by using hard data to determine the likelihood that a person or business will repay their debts. Given how much value can be at stake in mortgage or business loan, effective credit risk predictive modeling is a top priority for lenders.

Broadly, credit scores are a measure of financial stability and reliability. Lenders need historical data to enter into their models to determine how to structure loan criteria. As such, both individuals and businesses should prioritize establishing records of on-time payments and commitment to past financial obligations.

Risk managers at lending institutions will also assess criteria including the length of open credit accounts, credit utilization rates, and new credit accounts as part of the FICO score. It’s crucial for all individuals and business entities to understand how these factors affect their credit rating and what steps they can take to support a strong credit score over time.

Those that are familiar with the workforce management space need no introduction to Monday.com and its powerful work OS tool. Monday.com recently moved to an automated accounts receivable (A/R) collection system, powered by Gaviti, to replace its outdated annual reporting methodology.

From Monday.com’s accounts receivables department:

With our business and sales growing exponentially, Gaviti has been a key tool in ensuring our DSO has not only stopped increasing but also shown improvements over a relatively short period of time. The ease of use combined with a highly responsive and helpful team… We have been able to quickly implement a comprehensive and versatile collections process.

When you stop to consider the broader, organizational benefits of automated A/R solutions, it’s easy to understand why Monday.com was so successful. The right A/R collection software can improve cash flow as well as the performance of key metrics – such as days sales outstanding (DSO) – within your organization.

Improve DSO Collection Processes

At its core, DSO collection is a cash flow problem. According to a U.S. Bank study, 82% of businesses fail due to poor cash flow management.

Part of this issue is attributable to the time-consuming processes inherent in manual collections. DSO collections and cash flow already vary from month to month. When you add the time spent managing spreadsheets across late payments, grace periods, and lines of credit, you have an untenable system where staff spends more time corralling reports than processing payments. And while you may not enjoy managing the nitty-gritty details of your business’s finances, your financial processes are ripe for optimization. Consider just a few ways that accounts receivable collection software can streamline your enterprise DSO:

  • Collect on accounts when they’re due with automated customer reminders
  • Create a single source of truth with a centralized A/R database that eliminates the need for tracking/compiling across different spreadsheets
  • Faster invoicing through the elimination of unnecessary payment delays
  • Standardize your process for consistent, repeatable collections every time
  • Streamline payment collection for clients, decreasing the odds of entry errors and making it more likely you’ll get paid on time

When you work to improve your accounts receivable collection, you’re working toward a healthy financial process where DSO stays low. But that’s not the only benefit of an A/R collection solution.

Stay Informed

5 Benefits of Automated Accounts Receivable Collection

In any discussion about the benefits of accounts receivable automation, it’s important to cover the broader benefits it provides:

  1. Better staff efficiency by reducing the manual hours required to perform collections tasks – all those hours you spend chasing invoices, calling clients, or writing follow-up emails add up.

  2. Ensure your data’s accuracy – real-time accurate data will prevent your company from making errors.

     

The benefits of the accounts receivable collection software are clear, and once you’ve deployed
automation,
you’ll have a hard time going back.

A/R Collections Best Practices

Although automated accounts receivable software brings a new dimension to your financial processes, the fundamentals of accounts receivable best practices remain the same. It’s a straightforward process that nevertheless tends to get bogged down by inefficiency. This is where automation software pays off.

Consider how you can leverage financial technology like this throughout your organization to improve key financial metrics. Technology is one option. Outsourcing accounts receivable collections to a service provider that can handle all the details for you is another. You have plenty of options, and now it’s just a matter of selecting which improvements will yield the best results for your enterprise.

Related Terms

Capitalization Ratio

Cash Conversion Cycle

Cash Flow Statement

Top Articles:
Contact Us