Amerirad, B.; Cattaneo, M.; Kenett, R.S.; Luciano, E. Adversarial Artificial Intelligence in Insurance: From an Example to Some Potential Remedies. Risks2023, 11, 20.
Amerirad, B.; Cattaneo, M.; Kenett, R.S.; Luciano, E. Adversarial Artificial Intelligence in Insurance: From an Example to Some Potential Remedies. Risks 2023, 11, 20.
Amerirad, B.; Cattaneo, M.; Kenett, R.S.; Luciano, E. Adversarial Artificial Intelligence in Insurance: From an Example to Some Potential Remedies. Risks2023, 11, 20.
Amerirad, B.; Cattaneo, M.; Kenett, R.S.; Luciano, E. Adversarial Artificial Intelligence in Insurance: From an Example to Some Potential Remedies. Risks 2023, 11, 20.
Abstract
Artificial intelligence (AI) is a tool that financial intermediaries and insurance companies use in most cases or are willing to use it in almost all their activities. AI can have a positive impact on almost all aspects of the insurance value chain.: pricing, underwriting, marketing, claims management, after-sales services. While it is very important and useful, AI is not free of risks, including its robustness against cyber-attacks and so-called adversarial attacks. Adversarial attacks are conducted by external entities to misguide and defraud the AI algorithms. The paper is designed to provide a review of adversarial AI and discuss its implications for the insurance sector. The study starts with a taxonomy of adversarial attacks and presents a fully-fledged example of claims falsification in health insurance. Some remedies, consistent with the current regulatory framework, are presented.
Keywords
AI; insurance; adversarial attacks
Subject
Business, Economics and Management, Finance
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
