INTELLIGENT AUTOMATION IN BANKING OPERATIONS: IMPACT ANALYSIS ON RENEWABLE ENERGY INVESTMENT ASSESSMENT

Abstract

The integration of Artificial Intelligence in investment banking's middle office operations marks a transformative shift in how financial institutions evaluate, manage, and facilitate green energy investments. This article examines the technological infrastructure enabling AI-driven decision-making in renewable energy project assessment, carbon market operations, and energy transition strategies. This article analyzes the convergence of machine learning, natural language processing, and robotic process automation within traditional middle office functions, highlighting their collective impact on operational efficiency and risk management. This article demonstrates how AI-enabled systems are reshaping feasibility assessments for renewable projects, automating carbon credit verification, and enhancing market intelligence for energy transition investments. This article reveals significant improvements in processing speed, accuracy, and scalability of middle office operations while identifying key technical challenges in system integration, data security, and regulatory compliance. This article contributes to the growing body of knowledge on financial technology's role in accelerating sustainable energy adoption and provides insights into the future architecture of AI-powered investment banking operations.