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@article{180240,
        author = {Nihar Malali},
        title = {AI-AUGMENTED ACTUARIAL MODELLING IN ERP-INTEGRATED INVESTMENT SYSTEMS: A RISK-AWARE ENTERPRISE ARCHITECTURE APPROACH},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {9167-9182},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180240},
        abstract = {This study investigates the integration of artificial intelligence (AI) into actuarial science to enhance how insurance firms manage investment risk, solvency assessment, and reserve forecasting within enterprise resource planning (ERP) systems. It introduces an actuarial engineering framework embedded within systems such as SAP and Oracle Financials, guided by enterprise architecture principles. The model incorporates advanced machine learning techniques, including gradient boosting and deep learning, to create a modular, real-time structure for dynamic risk evaluation, reserve management, and investment portfolio performance tracking.
By embedding actuarial logic into key ERP modules, the framework enables predictive accuracy, operational scalability, and centralized decision-making. The proposed system facilitates intelligent dashboards and enterprise models that support improved financial governance, automated regulatory compliance, and strategic investment planning in volatile market conditions. The findings demonstrate how AI-driven actuarial reasoning within ERP infrastructure can significantly strengthen risk control and performance monitoring, while enhancing the adaptability of financial organizations to shifting regulatory and economic environments.
This research offers a novel contribution to the intersection of actuarial science, enterprise systems, and artificial intelligence, establishing a scalable, intelligent framework that aligns regulatory, financial, and operational objectives in a unified digital ecosystem.},
        keywords = {AI in Actuarial Modelling, ERP-Integrated Financial Systems, Enterprise Architecture for Risk Management, Machine Learning in Investment Forecasting, Real-Time Financial Risk Dashboard.},
        month = {June},
        }