PAYCE<sup class='tm'>TM</sup> Score

Harnessing deep neural network technology to bring you a highly accurate score for private company bankruptcy risk assessment.

The PAYCETM score provides a highly accurate measure of financial stress when no financial statements are available for private companies. It utilizes payment and U.S. federal tax lien data from CreditRiskMonitor’s extensive database, analyzed with sophisticated deep neural network modeling technology, a type of artificial intelligence, to deliver a 70% accurate score on approximately 80,000 private companies.

Payment Data

The first of the fundamental components to the PAYCETM score is payment data obtained through CreditRiskMonitor’s Trade Contributor Program. Our network of trade contributors provides more than $130 billion in trade data on their counterparties every month, giving them visibility into their biggest dollar risks. 

As our Trade Contributor Program grows, so will the number of PAYCETM scored businesses in our database.

U.S. Federal Tax Liens

The second of the fundamental components which make up the score is based on U.S. federal tax lien data. The Internal Revenue Service goes to great lengths to negotiate terms with a company that has defaulted on its tax debt. When a federal tax lien is filed, this is often a signal there’s a serious issue with the company’s ability to pay its federal taxes.

PAYCE™ score

We stay at the front of cutting edge technology.

CreditRiskMonitor strives to bring you the most accurate financial risk assessment tools and solutions available today. We utilize innovative technologies such as crowdsourcing, a component of our 96% accurate FRISK® score, used with public company risk analysis. As mentioned above, our deep neural network technology, a type of artificial intelligence, is used to formulate our new private company PAYCETM score. 

Public companies behave differently than private ones and our scores accurately reflect the differences to help you make the best informed decisions.

kill-padding-bottom