The PGDM Retail Management Department and PGDM International Business Department at Jagan Institute of Management Studies (JIMS), Rohini organised an insightful academic Open Elective titled “AI in Finance: Transforming Financial Decision-Making Through Artificial Intelligence” exclusively for the Finance students of Batch 2025–27. The three-session elective was conducted on 23rd July, 23rd August, and 12th September 2026 and was led by Mr. Ashish Bansal, Chief Operating Officer & Finance Director, Aqualite Industries Pvt. Ltd., who brought valuable industry-oriented perspectives and practical insights into the application of Artificial Intelligence in finance.
The sessions provided students with an understanding of Artificial Intelligence, Machine Learning, Deep Learning, and Generative AI, with a specific focus on their applications in financial services. Students explored practical applications including AI-based credit scoring, fraud detection, transaction monitoring, algorithmic trading, robo-advisory, predictive analytics, financial forecasting, sentiment analysis, and AI-assisted investment research. The discussions helped students understand how AI is increasingly being integrated into financial analysis, risk assessment, investment decisions, and banking operations.
A major focus of the Open Elective was on hands-on application of AI tools in financial analysis. Students worked with ChatGPT and Excel to analyse annual reports, identify revenue and profit trends, assess business risks, and evaluate future outlooks. They also worked on historical stock market data, identifying trends and developing forecasts using Excel, followed by a comparison with AI-generated forecasts. Through financial news sentiment analysis, students classified market news as positive, negative, or neutral and examined its potential implications for investor behaviour and market movements.
The elective further explored the growing role of Generative AI and AI Agents in Finance. Students were introduced to applications such as financial reporting, investment research, financial planning, budgeting, regulatory compliance, autonomous financial assistants, and agentic workflows. The sessions also highlighted how AI-enabled systems can support finance professionals by automating repetitive tasks, assisting with financial analysis, and improving the speed and accessibility of financial information.
A dedicated component of the programme focused on AI risks, governance, and responsible adoption in financial services. Students discussed issues including model bias, data privacy, cybersecurity, AI governance principles, responsible AI, explainable AI, financial regulations, and compliance. The discussions also covered the sustainability implications of AI and the potential role of technology in supporting ESG considerations and ethical investing, enabling students to understand the importance of balancing technological innovation with responsible financial practices.
The final session, conducted on 12th September 2026, included a capstone practical workshop and final assessment. As part of the practical exercise, students worked on an AI-Powered Credit Approval Model from a managerial perspective. They analysed a sample loan dataset, identified key variables influencing credit decisions, used AI tools to support approval or rejection recommendations, and evaluated the fairness and risk implications of AI-assisted credit decisions. The exercise provided students with practical exposure to how AI can be applied to real-world financial decision-making while highlighting the importance of human oversight and responsible use of technology.
Overall, the three-session Open Elective successfully connected financial concepts with practical applications of Artificial Intelligence, providing Finance students with hands-on exposure to emerging AI tools and financial technologies. The programme enabled students to develop practical skills in financial analysis, forecasting, investment research, credit assessment, sentiment analysis, and AI-enabled decision-making, while also building awareness of the governance, ethical, regulatory, and risk considerations associated with the adoption of AI in the financial sector.
Key Takeaways
- Understanding the practical applications of AI and Machine Learning across banking, investment, credit, risk management, and financial services.
- Using ChatGPT and Excel for annual report analysis, financial forecasting, market research, and financial decision-making.
- Applying AI to stock market trend analysis, financial news sentiment analysis, and investment research.
- Understanding the role of Generative AI and AI Agents in financial reporting, investment research, financial planning, budgeting, compliance, and automated workflows.
- Exploring AI-powered credit scoring and credit approval through a practical loan dataset exercise.
- Evaluating model bias, fairness, data privacy, cybersecurity, and risk in AI-driven financial decisions.
- Understanding AI governance, responsible AI, explainable AI, financial regulations, and compliance in the financial sector.
- Exploring the potential of AI in supporting ESG considerations and ethical investing.
- Gaining industry-oriented insights from Mr. Ashish Bansal, Chief Operating Officer & Finance Director, Aqualite Industries Pvt. Ltd.