ABSTRACT
This Article addresses a fundamental challenge in liability insurance law: distinguishing between injurers who deliberately engage in risky behavior and those who, despite their best efforts, fail to meet the standard of care due to human limitations. The ‘expected or intended harm clause’, a standard provision in commercial general liability policies that excludes coverage for harm the insured expected or intended, serves as the primary mechanism for making this distinction. Yet courts have struggled to interpret this clause consistently, employing divergent approaches that lead to both over-inclusive and under-inclusive coverage determinations.
The Article develops a novel taxonomy of non-compliance, categorizing negligent behavior into three distinct types: (1) intentional infliction of harm, where the injurer deliberately seeks to cause damage; (2) intentional negligent risk-taking, where the injurer knowingly engages in risky behavior without intending specific harm; and (3) unintentional non-compliance, which encompasses lapses in attention, inability to meet objective standards, and other involuntary failures that constitute ‘bad moral luck’. While insurance coverage appropriately excludes the first category and should exclude the second to prevent moral hazard, the third category – representing ordinary human fallibility – deserves protection.
Current judicial approaches fail to reliably distinguish these categories. The broad Carter Lake test, which applies an objective ‘should have known’ standard combined with a substantial probability inquiry, often excludes coverage for unintentional non-compliance. Conversely, the narrow Johnstown test, requiring purely subjective intent, may inadvertently provide coverage for calculated risk-taking when subjective awareness proves difficult to establish.
This Article proposes a ‘best efforts’ defense that shifts the analysis from knowledge-based to behavior-based assessment. Under this approach, once an insurer establishes that harm was expected or intended, the policyholder can defend by demonstrating that their conduct reflected their best efforts to comply with the standard of care, measured against their own ordinary behavior and capabilities. This personalized standard leverages advances in InsurTech – including big data analytics, continuous monitoring, and AI-driven underwriting – to create more accurate risk assessments and enable courts to distinguish genuine lapses from deliberate risk-taking. The Article demonstrates how this framework achieves more efficient outcomes by properly aligning coverage with the fundamental purposes of liability insurance while maintaining appropriate incentives for precautionary behavior.
Shiman, Yehonatan, Expected Bad Moral Luck (September 1, 2017), 25 Connecticut Insurance Law Journal 112 (2018).
Leave a Reply