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IL House Passes ‘Junk Fee’ Bill The Illinois House passed a bill ( HB 228 ) that would amend the state’s Consumer Fraud and Deceptive Business Practices Act to prohibit businesses from...
Anthropic Not Releasing New AI Model to Public The artificial intelligence company Anthropic—recently in the headlines for demanding that the Pentagon agree to certain limitations on the use of...
CT Lawmakers Target AI in Employment A bill (SB 435) before Connecticut’s legislature would require employers to disclose to job applicants when they are communicating with artificial intelligence...
On March 11, Washington Gov. Bob Ferguson (D) signed HB 2303 . The law, which takes effect June 11, bars employers from requesting, requiring or coercing workers or job applicants to accept a subcutaneous...
ND Regulators Approve Bank-to-Bank Stablecoin Use North Dakota’s Industrial Commission approved the use of the state bank’s planned stablecoin, the Roughrider Coin, for bank-to-bank transactions...
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Just as state legislatures vary in their bill passage rates, some state agencies adopt far more of the rules they propose than others. The reasons for that disparity are even more difficult to discern than with the legislative process, but understanding how they shape adoption rate patterns is no less critical for organizations seeking to comply with the regulations or engage in the rulemaking process of any state. That knowledge is the foundation of the analytics tools developed by LexisNexis® State Net® to support legislative and now regulatory forecasting.
Pioneering research by State Net® beginning in the 1980s revealed that in spite of their diversity, legislative passage rates “remain highly consistent from session to session,” varying less than 2% over multiple bienniums. Rigorous tracking of regulatory actions from proposal to adoption over the past four decades has now made it possible for State Net® to document similar historical rule adoption patterns. “Just as we were surprised by the unyielding consistency in legislative passage rates, our analysis of regulatory adoption reveals an equally rigid pattern across agencies and states,” said Crain. “This stability, despite the processes’ diversity, provides a strong foundation for determining the timing and likelihood of rule adoption.
State Net has now built predictive models for every state agency that proposes regulations—8,992 forecasts in all—drawing on key indicator analytics derived from decades of regulatory activity and employing advanced machine learning. The graphic visualizations of these predictive models, along with other indicators, can provide important insights about pending rules, such as their likelihood of adoption or whether consideration is moving faster or slower than usual. By simply using these tools—and the State Net platform’s powerful searching and tracking capabilities across state, federal and local agencies—users gain access to extensive knowledge of regulatory processes, helping them make more informed data-supported decisions.
Download the latest State Net Capitol Journal thought leadership article to learn more.