AI Risk Coverage: Designing New Products to Cover Liability from AI Model Failures or Biased Algorithmic Decisions
DOI:
https://doi.org/10.63282/3050-9416.IJAIBDCMS-V4I1P114Keywords:
Artificial Intelligence, AI Risk, Algorithmic Bias, Model Failures, Liability Insurance, Risk Management, Insurance Product DesignAbstract
Artificial Intelligence (AI) is rapidly finding its application in the industries, with appropriate opportunity and threats. The failures of AI models and the bias on the algorithms are regarded as those issues, which are highly important to the company and can lead to financial losses, fines, and statistical annihilation of the image. This paper is going to explore the development of insurance product and risk management strategies that would mitigate their liabilities in case of AI errors. The article is devoted to the awareness of the nature of the AI risks, the evaluation of the potential financial impact, and the new models of covers related to the AI risks. Systematic methodology where risk assessment frameworks, actuarial models and scenario analysis frameworks are implemented is adopted to measure the potential liabilities. The paper will also review the existing literature alongside a review of some of the literature that has been done on biases detection and insurance mechanisms as well as AI failures. The results also indicate that the AI risk insurance products must involve the dynamic monitoring, periodic model auditing and the adaptive premium structure. Among the regulatory frameworks and the use of AI in an ethical manner and technological protection, as explained in the discussion, the area that has a great impact on the coverage of AI risks. The paper is important to the academic discussions and practical answers to the policies which underwriters employ to reduce the rising perils of AI by presenting ideas on how the policies are to be shaped, how the policies affect the formation and also the extent to which the policies are adopted in the industry
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