Conceptual Design of Ethical Investment Assessment Models Using AI-Enhanced Financial Decision Tools
DOI:
https://doi.org/10.32628/IJSRST24115123Keywords:
Ethical Investment, AI-Enhanced Decision Tools, Fintech, ESG, Machine Learning, Explainable AI, Financial Modeling, Responsible Investing, Sustainability, Algorithmic Fairness, Ethical Finance, Natural Language Processing, Impact Metrics, Risk-Adjusted Returns, Portfolio OptimizationAbstract
This paper presents a forward-looking conceptual framework for developing ethical investment assessment models using AI-enhanced financial decision tools. As financial markets experience increasing pressure to align with Environmental, Social, and Governance (ESG) standards, there is a growing demand for systems that can evaluate investment opportunities through both ethical and performance-based lenses. By combining principles from finance, ethics, and artificial intelligence, this study outlines a novel approach that enables responsible capital allocation while ensuring robust financial returns. The proposed model integrates advanced machine learning algorithms with ethical scoring mechanisms derived from ESG data, corporate social responsibility disclosures, and impact metrics. Natural language processing (NLP) is used to evaluate unstructured data sources such as news articles, corporate communications, and regulatory filings to detect signals of ethical compliance or violations. These AI-enhanced tools are embedded into financial modeling environments to simulate risk-adjusted returns while filtering out investments that conflict with defined ethical thresholds. The architecture prioritizes transparency and interpretability, incorporating explainable AI (XAI) techniques to justify recommendations and enable stakeholder accountability. The framework also addresses potential algorithmic biases by embedding fairness constraints and continuously retraining models with diverse datasets. By integrating ethics into the decision-making layer of investment models, the approach mitigates reputational risks and aligns portfolio performance with long-term sustainability goals. This conceptual design not only supports institutional investors, asset managers, and financial analysts in meeting fiduciary and ethical obligations but also responds to regulatory shifts and investor expectations for sustainable finance. The paper positions ethical AI integration as a competitive differentiator in the evolving FinTech landscape. This framework ultimately charts a course toward a future where ethical imperatives are not an afterthought, but a core dimension of investment analysis, enabling financial systems to generate value while upholding societal good in an AI-driven economy.
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