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@article{199221,
        author = {Shaikh Asad Ibrahim and Siddique Shayan and Shelia Muaviyah Javed and Saad Ansari and Dr. Ashfaq Shaikh},
        title = {TaxBae - Your Personalized C.A},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {3},
        pages = {1105-1112},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=199221},
        abstract = {The increasing complexity of personal finance in India, coupled with widespread low financial literacy (estimated at only 27%) and the growing necessity for continuous support among middle-class taxpayers and gig workers, presents a significant market gap. 1 Traditional advisory service, typically provided by Chartered Accountants (CAs), are often unaffordable or inaccessible to this demographic, leaving them reliant on fragmented, annual tax tools. 1 This paper introduces TaxBae, an integrated personal finance application designed to serve as a holistic, year-round companion. TaxBae utilizes a modular architecture blending four core AI components: a predictive Deduction Engine for tax optimization, an Expense Tracker for daily monitoring, an NLP-driven Investment Planner, and a Conversational Chatbot enhanced by Retrieval-Augmented Generation (RAG). 1 The modular system architecture is essential for scalability and managing the high operational risk associated with regulated FinTech environments. 2 The methodology validates the use of advanced Machine Learning (ML) for superior tax optimization, showing that ensemble models can improve prediction accuracy by up to 15% compared to baseline rule-based systems. 4 Furthermore, the RAG implementation is crucial for mitigating the critical risk of hallucination inherent in Large Language Models (LLMs) used for financial advice, ensuring grounded, verifiable, and transparent regulatory guidance.},
        keywords = {Tax planning, personal finance, expense tracking, AI chatbot, investment recommender, gamification, financial literacy, Retrieval-Augmented Generation (RAG), Ensemble Learning},
        month = {August},
        }