Building a Parametric Insurance Ecosystem in Indonesia: A Narrative Literature Review of Global Practices and Strategic Recommendations

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Authors: Pristiwanto Bani
Cited by: 0

Abstract

Parametric insurance is an innovation in disaster risk management that provides fast, transparent, and data-driven solutions, with claims payments triggered by measurable parameters, such as extreme rainfall or earthquake magnitude. These schemes serve as an essential alternative to risk financing, especially in developing countries such as Indonesia, which face significant challenges in accelerating post-disaster recovery. This article aims to review global practices in parametric insurance and to formulate a context-specific implementation strategy for Indonesia, based on a review of the narrative literature. The study identifies four key pillars for developing a strong parametric insurance ecosystem: strengthening data and technology infrastructure, creating an adaptive regulatory framework, increasing the capacity of the insurance industry, and fostering multi-stakeholder collaboration through pilot projects. The findings suggest that the use of satellite data, IoT-based monitoring systems, and the integration of national hazard data sources can reduce baseline risks. In addition, a transparent and collaborative regulatory framework is essential to ensure transparency and consumer protection. The involvement of local insurtechs also catalyzes the digitization of inclusive parametric products, particularly for MSMEs and the agricultural sector. Through a phased approach based on sectoral pilot projects and government fiscal support, Indonesia has significant potential to become a pioneer in the application of parametric insurance in Southeast Asia. This study contributes both conceptually and practically to strengthening a resilient and sustainable national disaster risk financing system.

Fields of Study & Subjects

Disaster Management and Resilience Agricultural risk and resilience Insurance and Financial Risk Management

Publication details

Journal / source
International Journal of Economic Finance and Business Statistics
Volume
3
Issue
6
Pages
349–362
Publication date
5 January 2026