Modernizing Solvency Regulation in Algeria: A Comparative Study of Static and Stochastic Approaches

Abstract

Abstract

Purpose: This study examines whether Algeria could transition from its current prudential solvency framework, largely based on the outdated Solvency I directive, to a more dynamic solvency assessment approach grounded in stochastic differential equations (SDEs). Methodology: Using an analytical and comparative methodology, the paper contrasts the Algerian Solvency I–based framework with a stochastic solvency model proposed by Wang and Zhu (2021), highlighting their conceptual foundations, regulatory implications, and risk management capabilities. Findings: Solvency I framework relies on static capital requirements that insufficiently capture market volatility, evolving insurance risks, and extreme events. In contrast, the stochastic model incorporates randomness, dynamically manages capital flows between different financial states, and adjusts solvency levels in real time in response to market and claims fluctuations. This results in a more accurate and forward-looking assessment of insurers’ financial resilience. Practical Implications: Adopting a stochastic solvency framework could enhance the stability and risk management capacity of Algerian insurance companies. However, such a transition would require gradual regulatory reforms, institutional capacity building, and close coordination between insurers and supervisory authorities. Originality/Value: This paper contributes to the literature by providing the first structured comparison, in the Algerian context, between the Solvency I framework and a stochastic differential equation–based solvency model, thereby enriching the ongoing debate on the modernization of insurance prudential regulation in emerging markets.