Requirements for AI Implementation in Digital Insurance Supervision: A Gap Analysis

The rapid integration of Artificial Intelligence (AI) across the insurance value chain, while boosting efficiency in areas like claims automation and fraud detection, introduces novel and complex risks, including algorithmic bias, model risk, and opaqueness in decision-making. Consequently, the insurance regulatory body must transition from traditional oversight to Digital Supervision (SupTech) to protect policyholders and maintain market stability. This research aims to develop a practical framework detailing the requirements for AI implementation within the insurance regulatory body of Iran, utilizing the Gap Analysis methodology. Five critical dimensions of requirements Regulatory, Ethical, Data, Technical, and Human Capital were systematically extracted from international standards (e.g., IAIS recommendations) and specialized literature to define the Desired State. A subsequent evaluation of the existing domestic infrastructure and regulatory landscape revealed significant discrepancies. The most substantial gaps were identified in Algorithmic Governance (the absence of dedicated regulations mandating AI transparency and fairness), the lack of a unified and Integrated Data Infrastructure for supervisory access, and a critical shortage of Specialized Human Capital within the supervisory body capable of auditing complex AI models. These deficiencies significantly undermine the regulator's capacity to effectively monitor emerging systemic and consumer protection risks. The paper concludes by proposing specific policy interventions, including the immediate establishment of a Regulatory Sandbox and the urgent issuance of comprehensive Algorithmic Governance Regulations, to bridge these essential gaps and facilitate a secure digital transformation.

کلیدواژه ها:

Digital Supervision ، Artificial Intelligence ، Gap Analysis ، Algorithmic Governance ، Regulatory Framework