B.Com. (Financial Markets) Artificial Intelligence in Financial Markets Syllabus - Mumbai University
This is the TY BFM syllabus under NEP 2020, in force from the academic year 2026-27. The University still sets the earlier Choice Based papers alongside it for ATKT candidates, so check which scheme your exam form names before you revise.
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Syllabus for Artificial Intelligence in Financial Markets
Module I: Artificial Intelligence and Financial Markets (Theory)
- Introduction to Artificial Intelligence
- Meaning and evolution of AI
- AI, Machine Learning and Deep Learning – overview
- Scope and importance of AI in financial markets
- AI Applications in Financial Markets
- AI in stock market analysis and price prediction
- Algorithmic trading – conceptual understanding
- AI in portfolio management and robo-advisory services
- AI in Banking and Financial Services
- Credit scoring and loan decision-making using AI
- Fraud detection and risk management
- Customer analytics and personalized financial services
- Ethical and Regulatory Aspects
- Ethical issues: bias, transparency, explainability
- Risks and limitations of AI in finance Overview of AI regulation in Indian financial markets
Module II: Practical Applications of AI in Financial Markets
- Introduction to AI-enabled financial tools and platforms
- AI-assisted stock trend analysis
- Financial ratio interpretation using AI tools
- AI-based comparison of investment alternatives
- Portfolio construction using AI or robo-advisory tools
- Case study analysis of AI usage in fintech companies
- Ethical bias analysis through real-life financial cases
- Mini project: AI-assisted financial decision or strategy
Reference Books
- CFA Institute – AI in Investment Management Reports
- RBI & SEBI publications on FinTech and AI
- NSE Academy, Investopedia
- AI-enabled financial analysis platforms
- Artificial Intelligence in Finance (Springer) – comprehensive book on AI techniques and real financial applications.
- Machine Learning and AI in Finance (Routledge) – theory and applied perspectives on AI models for financial problems.
- Foundations of Artificial Intelligence in Finance: Insights for Practitioners – covers predictive analytics, NLP, case studies, and ethical/regulatory topics.
- Machine Learning and Data Sciences for Financial Markets (Cambridge) – modern practices in data science and machine learning applied to trading and asset decisions.
- AI in Asset Management: Tools, Applications & Frontiers – CFA Institute publication focusing on AI for portfolio design and risk oversight.
Reproduced from the University of Mumbai syllabus for B.Com. (Financial Markets) under NEP 2020, in force from the academic year 2026-27. Wording is as printed in that syllabus. Module numbering is as printed there too.
The complete syllabus
This subject is cut from the University circular for its year. Open a document here if you want the whole thing rather than a single subject.