Ai-Based Decision Support System for Green Investment Risk Assessment in Emerging Economies

Rahiba Abdulhasanova^1* , Sadagat Ahmadova²

Abstract. Green investment in developing economies is poorly served by conventional risk tools. This paper examines how artificial intelligence methods, from hybrid econometric-machine learning architectures to natural language processing and distributed ledger systems, can be embedded within decision support frameworks for green portfolios. Drawing on a structured narrative synthesis of 61 studies published between 2018 and 2024, it maps AI deployment in sustainable finance across emerging markets including Morocco, Mongolia and Azerbaijan. Bidirectional recurrent networks and hybrid architectures consistently outperform standard approaches under data scarcity and macroeconomic instability, while ownership concentration and governance quality moderate AI-driven environmental performance. The paper concludes with recommendations for regulators and investment professionals in institutionally fragmented markets.

Keywords: green investment, risk assessment, decision support system, machine learning, ESG, blockchain, emerging economies, sustainable finance