Business Credit Rating Data

What is business credit rating data?

Business credit rating data is a part of business information and company data and offers an assessment of a company’s financial solvency and creditworthiness. It provides a score ranging from 0 to 100, and a higher score indicates a better credit rating.

This data helps companies evaluate potential B2B customers (such as small business owners)and business partners based on credit information. 

Where does business credit rating data come from?

A business credit rating data is a business's credit score derived from several factors such as current outstanding debts, payment history, credit history, and loan payment delinquency. It can also include other relevant information that contributes to assessing the creditworthiness and whether a company is low or high risk to do business with. 

A select group of analysts issues credit ratings for most companies. They include Experian, Equifax, Dun & Bradstreet, and FICO, among others. Experian provides business credit scores, while Equifax publishes business credit reports.

Dun & Bradstreet provides credit scores for businesses and PAYDEX credit scores. The PAYDEX score is calculated from the company’s payments to suppliers and vendors over the past year.

The FICO LiquidCredit Small Business Scoring Service delivers an average score based on the information issued by Experian, Equifax, and Dun & Bradstreet. The FICO LiquidCredit is useful to assess risk (risk score) in extending credit to small businesses, and the Small Business Administration uses this score to decide on d small business loans.

What types of attributes should I expect when working with business credit rating data?

Business credit rating is modeled on a combination of structured and unstructured data.

  • The structured data attributes include firmographics, payment history, late payments, trade history, and public records such as bankruptcy filing and liens. Some of this information can be historic.
  • The unstructured data attributes include news, news reports, published company reports, meeting transcripts, and information shared on social media. Using Natural Language Processing (NLP) helps process the unstructured data accurately and efficiently.

Some vendors may include additional attributes, and you can check if they match your requirements. 

How should I test the quality of business credit rating data?

The most critical test for business credit rating data is how it measures against the S&P Global Ratings Standalone Credit Profile. Depending on your business objectives of using this data, you can also run additional tests.

Company credit data comes from reputed analysts, and their models are proven. The data gets completely tested and back-tested against the previous year’s pre-scored database. As the market, industry, or specific companies change, the models may or may not get re-calibrated. You need to ensure that the updates in the scoring models get reflected in the vendor data.

Your business credit rating model must be accurate to ensure that the outcome is as complete as possible to fulfill your requirements.  For example, consider a new company that does not have sufficient payment or credit history, making it difficult to establish financial stability. The model needs to take into account the personal credit history of the business owner to arrive at an appropriate outcome.

To test the quality of the business credit rating data:

  • Ensure that the data is complete and up-to-date.
  • Verify that the business credit rating model is frequently updated. 
  • Confirm that the data matches your business objectives. 

You can also compare the range and attributes different vendors provide. Asking for a small sample of data is a practical approach to assess if it matches your requirements.

Who uses the data?

Businesses make decisions about investments, loans, extending credit, and risk management, based on the business credit rating data. The financial future of the company depends on its credit rating data.

Using machine learning models, investors, lenders, and others evaluate the creditworthiness of a company. When the creditworthiness is high, companies can easily secure loans because they are indicated to be low risk. While a less than desirable credit score makes companies less attractive for loans or partnerships, it can also help them strategize to become more valuable to investors.

You can use business credit rating data to augment business registry data for assessing credit risk. 

What are the common challenges when buying this type of data?

Business credit rating data indicates the creditworthiness of companies and is derived from reputed analyst reports. If this data is not current, your analysis results can be unreliable. Timeliness is a common challenge for this data, considering that the financial status of companies can change relatively quickly. 

  • Source credibility: Verify with your vendors that their data is high-quality, consistent, and can drive trusted analytics.
  • Data timeliness: The business credit rating data from your vendor must incorporate the most recent information issued by top rating agencies. 
  • Compliance: Financial data needs to meet stringent compliance requirements. These requirements may vary by region, and you need to ensure that the business credit rating data is compliant in every region you operate in.

Before finalizing your vendor, you can test multiple vendors with small samples for the reliability and consistency of their data. 

What are similar data types?

You can use this type of data with funding information and industry NAICS classifier data to assess the financial health of companies.

You can find a variety of examples of B2B and company data in the Explorium Data Gallery

Sign-up for Explorium’s 14 day free-trial to access the data available on the platform.

What are the most common use cases?

This type of data is commonly used for assessing the financial stability of a company, and to derive a business failure score. The typical use cases include due diligence, KYC, B2B credit risk assessment, and regulatory compliance. 

Use Cases:

  • Due Diligence: Before entering into any business transactions, businesses routinely carry out reviews or investigations of financial records of the potential business partner companies. Due diligence uses several types of data to arrive at a composite financial status of the potential partners. Business credit rating data is one of the measures of the financial health of the company.
  • KYC: The Know Your Customer (KYC) process verifies the identity of the potential customers. Businesses and financial services institutions use business credit rating data for a deeper understanding of the financial health of their customers. B2B credit risk analysis assesses the risk in establishing a business relationship with potential partner companies. Fraud risk in B2B transactions is becoming more common, with devastating consequences. Companies use business credit rating data to power ML-driven pattern detection for the early identification of credit risk and fraud. 
  • Mergers and Acquisitions: Investors leverage business credit rating data to investigate potential acquisition opportunities. This data helps them produce company valuation and prepare for negotiations.
  • Supplier Risk: The creditworthiness of suppliers is critical for ensuring uninterrupted supply chain operations, particularly when orchestrated on a global scale. Businesses regularly use business credit rating data to identify and mitigate supplier risk.
  • Financial Robo-advisor: Developments in AI have resulted in processing vast amounts of information to arrive at mathematically backed accurate models for investment predictions. These financial Robo-advisors deliver personalized wealth management services with minimal human intervention across a range of instruments. They provide investment advice in a variety of industry verticals to individuals and small to medium-sized businesses. Robo-advisors use business credit rating data to generate actionable insights on investment opportunities. 
  • Regulatory Compliance: Financial services is a highly regulated industry. Banks, insurance companies, credit card companies, credit unions, stock broker firms, and investment funds need to report their activities to government regulatory agencies. The regulatory compliance criteria is strict and timely reporting is essential. Business credit rating data contributes to the financial data that is periodically updated, processed, and reported to the regulatory authorities.

You can also use business credit rating data to enrich other company data and power data-driven strategic decisions.

Which industries commonly use this type of data?

Various industries use these data points to assess the creditworthiness of companies. Some industries using this data are retail, eCommerce, consumer goods or CPG, banks and financial services, insurance, manufacturing, and hi-tech.                 

How can you judge the quality of data vendors?

You can evaluate the quality of your vendor with:

  • Trial run or demo: Several vendors offer a sample run or a demo to demonstrate the quality of their data. You can use the demo to assess the accuracy of data and if it matches your requirements.
  • Customer reviews and testimonials: Most vendor websites include a customer testimonials section sharing detailed reviews from their valued customers. You can compare their feedback with your specific requirements, such as accessibility, integration, consistency, and quality.
  • Case studies: Many vendor websites provide case studies with their data, sharing information about the work, success, challenges, and the level of customer engagement. These success stories can help you determine if you can build a long-term relationship with the vendor for a wide range of data types.

Additional Resources:

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