eMasters in Financial Technology & Management will be offered as a 60-credit program delivered over 12 modules of 5 credits each. The modules are categorised into Compulsory (C) and Projects (P) and participants need to study the compulsory courses and undertake projects, following the 10 C+2 P structure.

The Compulsory Modules include

• Banks and Financial Institutions:
  Through this module, you will get an insight into how the Banking and Financial Institutions operate and their role in enabling global and domestic economies. It provides a broad coverage on the evolution and role of financial institutions and the regulatory system governing them, an overview of fiscal policy, foreign trade and a glimpse of the financial institutions in India.
• Capital Markets and Financial Products:
  The module will provide a complete picture of the capital and financial market structure and various products offered by these markets. Some of the other topics covered in this module include the structure of the equity, debt, forex, commodities, F&O markets, Indian capital markets, mutual funds, insurance, forex and pension funds.
• Financial Big Data Analytics:
  The module puts a spotlight on data analytics. It also covers intricacies of descriptive, predictive and prescriptive analytics in solving business problems. In addition, coverage is also provided on how text analytics and big data analytics are used in solving banking problems.
• Investment Banking:
  Here you will gain a familiarity with how disruptions are taking place in capital markets and investment banking. In particular, it will introduce you to how machine learning can be used in algorithmic trading, how Robo-advisors can help improve portfolio performance, lower costs, and improve reporting and compliance for both retail and institutional investors.
• AI, Machine Learning, and Deep Learning:
  The module lays emphasis on the intricacies of ML and DL models used in solving finance-based problems. You will also get to deepen your understanding of NLP, reinforcement learning concepts through case studies and demonstrations. For instance, chatbot development, cyber fraud detection including phishing/spam/malware detection, credit card fraud detection, financial forecasting using ML, and sentiment analysis.
• Blockchain and Distributed Ledger Technologies:
  Blockchain adoption has paved the way for more transparency, efficiency and resilience to fraud. This module will highlight the mechanisms underlying this transformative technology – their origin, applications and key characteristics to differentiate between ‘public’ and ‘private’ distributed ledger technologies. In addition, the module will focus on the roles and risks associated with cryptocurrencies.
• IT Platforms, Cloud Computing, and loT:
  This is an introductory module that spotlights cloud computing, IoT architectures, virtualization and its role in cloud computing. It also features delivery and deployment models of cloud computing and various private and public cloud platforms. You will explore how to determine the right sensors and communication protocols to use in a particular loT system, understand the data generated from an loT device and migrated to the cloud and the security features required to protect data stored in the cloud.
• Cyber Security:
  Build an adequate understanding of various cyber-attack tactics, techniques, and procedures, along with hands-on training in different cyber security tools. In addition, you will also build capabilities to identify, detect, analyze and prevent popular cyber-attacks in your organization. Topics covered include cryptography, vulnerability analysis, penetration testing, VAPT framework, organizational security, network security tools – Firewalls, VPN, Intrusion detection/prevention, WAF, Packet capturing using Wireshark, NAC, and NBAD.
• Open Banking in a Mobile-First, Cloud-First World:
  This module will introduce you to platforms and tools driving the neo-banking ecosystem alongside the operational aspects of such platforms. Topics covered include Open APIs, mobile banking, and recent AR/VR/MR-based innovations in FinTech.
• Extreme Automation & Programming FinTech Applications:
  The module covers various aspects of RPA / DPA and its use cases, eg customer onboarding, KYC Compliance, Report Generation, AML and doubtful transaction identification etc. Exposure will be given to popular RPA / DPA platform(s) such as UIPath, Pega, Automation Anywhere and Blue Prism. Further, the module will focus on how RPA and DPA assist banks in automating repetitive tasks, leveraging the power of bots and thereby increasing productivity and engaging customers in real-time.

Live interactive sessions will be mostly held during the weekends. The exact schedule for the live interactive sessions for each module will be announced closer to the start of the module.

Bachelor’s degree (3/4 years program) for Financial Analysis, Business Finance, Public Policy, Quantitative Finance and Risk Management, Power Sector and Fintech Program or Bachelor’s degree (4 years program) for all other program or a Master’s degree in appropriate discipline with at least 55% marks or 5.5/10 CPI + 2 years of work experience (an applicant need not be employed to be eligible). Candidates with relevant experience will be preferred.