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<\/figure>\n\n\n\nWhy is the US Failure Score being updated?<\/h2>\n\n\n\n
The business environment is constantly changing. New data sources become available, while payment behaviour and risk profiles also change over time. To continue providing reliable risk assessments, Dun & Bradstreet has further enhanced the US Failure Score.<\/p>\n\n\n\n
Failure Score v8 uses more and more extensive data. This includes detailed UCC data, information from business registrations, merchant transactions and changes in companies\u2019 risk profiles.<\/p>\n\n\n\n
The model also uses Gradient Boosting, a machine learning technique that helps identify patterns and relationships in large amounts of data more effectively.<\/p>\n\n\n\n
What does the US Failure Score do?<\/h2>\n\n\n\n
The US Failure Score predicts the likelihood that a company will seek legal protection from creditors or cease operations without fully paying all creditors within the next twelve months.<\/p>\n\n\n\n
The score helps organisations identify higher-risk US companies earlier and better assess risks across customer and supplier portfolios.<\/p>\n\n\n\n
A separate model has also been developed for institutions insured by the Federal Deposit Insurance Corporation (FDIC). This model considers factors including liquidity, profitability, solvency and capital ratios.<\/p>\n\n\n\n
What is new in the US Failure Score?<\/h2>\n\n\n\nThe latest version of the US Failure Score builds on more extensive data sources and machine learning. The key improvements include:
<\/pre>\n\n\n\n
\n- more and more extensive data sources;<\/li>\n\n\n\n
- the use of Gradient Boosting for stronger predictive power;<\/li>\n\n\n\n
- greater focus on changes in companies\u2019 risk profiles over time;<\/li>\n\n\n\n
- a separate model for FDIC-insured institutions.<\/li>\n<\/ul>\n\n\n\n
US Failure Score v8 predicts an average of 30% more failures than the current Failure Score v7.1. Among the 10% of companies with the lowest scores, the model identifies 72% of failures and 48% of bankruptcies.<\/p>\n\n\n\n
What does this mean for your company?<\/h2>\n\n\n\n
If you use US business information or monitor US customers, suppliers or business partners, the transition to Failure Score v8 may affect existing risk assessments.<\/p>\n\n\n\n
Due to the new analytical techniques and data sources, we expect a high number of monitoring alerts and changes within portfolios. As a result, companies may receive a different score than before.<\/p>\n\n\n\n
Several Enterprise Analytics solutions that use the Failure Score will also be affected by this change. These include Overall Business Risk (OBR), Supplier Evaluation Risk (SER), Supplier Stability Indicator (SSI), Global Business Ranking (GBR), Maximum Credit Recommendation (MCR) and the Standard D&B Rating.<\/p>\n\n\n\n
It is therefore important to carefully review monitoring alerts, portfolio changes and any decision rules within your organisation after the release.<\/p>\n\n\n\n
<\/pre>\n\n\n\n
US Failure Score v8 predicts an average of 30% more failures than the current Failure Score v7.1. Among the 10% of companies with the lowest scores, the model identifies 72% of failures and 48% of bankruptcies.<\/p>\n\n\n\n
What does this mean for your company?<\/h2>\n\n\n\n
If you use US business information or monitor US customers, suppliers or business partners, the transition to Failure Score v8 may affect existing risk assessments.<\/p>\n\n\n\n
Due to the new analytical techniques and data sources, we expect a high number of monitoring alerts and changes within portfolios. As a result, companies may receive a different score than before.<\/p>\n\n\n\n
Several Enterprise Analytics solutions that use the Failure Score will also be affected by this change. These include Overall Business Risk (OBR), Supplier Evaluation Risk (SER), Supplier Stability Indicator (SSI), Global Business Ranking (GBR), Maximum Credit Recommendation (MCR) and the Standard D&B Rating.<\/p>\n\n\n\n
It is therefore important to carefully review monitoring alerts, portfolio changes and any decision rules within your organisation after the release.<\/p>\n\n\n\n