Executive Education
AI for Banking & Corporate Finance 2.0
Building an AI-First Financial Enterprise through Generative AI & Agentic AI
Go beyond buzzwords. Master AI, Blockchain, and next-gen automation as boardroom strategies. Through expert-led sessions and case studies, learn how to drive smarter decisions, sharpen risk management, and smooth customer experiences. Discover ways to make technology work for your organisation, identify high-impact opportunities, and lead intelligent transformation.
Programme Overview
Banks and financial institutions face evolving customer expectations, regulatory pressure, and digital disruption. This programme focuses on high-impact use cases where AI delivers measurable value — improving efficiency, compliance, fraud detection, and customer experience. This programme equips leaders to move from concept to proof of concept while managing risk, security, and organisational change.
Programme Framework & Curriculum
TECHNOLOGY The ai landscape
Focus: What are these technologies, and how do they work?
Content: Foundational understanding of core technologies driving the next generation of financial innovation.
Modules
- Artificial Intelligence (AI) & Machine Learning (ML) Fundamentals
- Generative AI, Large Language Models (LLMs) & Foundation Models
- Agentic AI & Multi-Agent Systems in Finance
- Enterprise Financial AI Platforms & Architecture
CAPABILITIES The Enablement Framework
Focus: What new capabilities can AI create across Banking, Financial Services & Insurance
Content: Deep-dive into how AI augments human expertise, operational performance, and strategic execution.
Modules
- Enhancing Financial Decision-Making & Strategic Planning
- Improving Forecasting Accuracy & Accelerating Financial Analysis
- Automating Compliance Processes & Supporting Risk Management
- Transforming Customer Engagement & Intelligent Treasury Operations
APPLICATIONS The Use Cases
Focus: How is this applied specifically in BFSI?
Content: Deep-dive into domain-specific applications across major verticals of BFSI and corporate finance.
Modules
- AI in Retail & Corporate Banking
- AI in Investment Banking, Wealth Management & Asset Management
- AI in Insurance (Underwriting & Claims) & FinTech
- AI in FP&A, Risk, Compliance & Capital Markets
TRANSFORMATION sCALING & ENTERPRISE implementation
Focus: How can AI be successfully scaled across the enterprise?
Content: Strategic roadmap for moving beyond pilot projects to enterprise-wide integration, governance, and value realisation.
Modules
- AI Governance, Ethics & Enterprise Risk Management
- Regulatory Compliance in Automated Environments
- Adoption, Change Management & Implementation Strategy
- Value Realisation, Scaling Methodologies & ROI Measurement
Programme Curriculum — Day-wise
Day 1 - Full Day
The New Foundations — Technology & Capabilities
Focus: Redesigning financial operating models, decision systems, and workflows using systems-level AI principles.
Banking, Financial Services & Insurance organisations are entering a new era where Artificial Intelligence is reshaping how institutions assess risk, manage capital, optimise operations, ensure compliance, and make strategic decisions. However, AI cannot simply be layered onto existing processes. Organisations must rethink how financial workflows, operating models, and decision systems are designed. Day 1 introduces participants to the principles of AI-first transformation and provides a structured framework for understanding financial institutions as interconnected ecosystems. Participants explore how financial enterprises evolve from traditional operating models to intelligent, AI-enabled organisations and learn how Ecosystem Thinking, Workflow Thinking, and Systems Thinking can be used to redesign financial processes and operating models.
| Module 1 | The Future of Banking, Corporate Finance & the AI-First Financial Enterprise Examine the evolving financial landscape shaped by Artificial Intelligence, Generative AI, and intelligent systems. Explore the institutional transition from legacy models to AI-first architectures, identifying strategic opportunities to augment financial decision-making, customer engagement, risk, compliance, treasury, and enterprise performance. |
| Module 2 | Financial Workflow Design & Systems Thinking Apply Ecosystem Thinking, Workflow Thinking, and Systems Thinking to redesign financial operations using AI-first principles. Teams engage in practical mapping exercises to develop AI-enabled workflow blueprints that enhance operational productivity, decision quality, risk controls, and customer experience. |
| Hands-on Workshop | Map an existing financial workflow and redesign it using AI-first architectural principles. |
Day 2 - Full Day
Building the AI-First Financial Operating System
Focus: Deploying Generative AI, RAG architectures, and agentic workflows across core financial operations.
Day 2 focuses on translating enterprise strategy into practical operating models. Participants explore how Generative AI, Foundation Models, Retrieval-Augmented Generation (RAG), and Agentic AI work together to create intelligent financial systems. The day emphasises AI Thinking as a foundational framework for integrating emerging technologies into operational workflows and institutional decision-making. Participants gain hands-on exposure to specialised financial AI architectures, institutional knowledge systems, and multi-agent workflow orchestration.
| Module 3 | AI Thinking, Financial AI Architecture & Knowledge Systems Explore core architectural foundations, including Large Language Models (LLMs), Foundation Models, embeddings, and vector databases. Evaluate production use cases across financial analysis, management reporting, investment research, regulatory intelligence, customer advisory, and treasury decision support. |
| Module 4 | From Financial AI Transformation to Agentic Financial Workflows Examine the implementation of Retrieval-Augmented Generation (RAG) and autonomous Agentic AI to power explainable, interconnected systems. In a structured design lab, participants orchestrate multi-agent workflows across credit underwriting, treasury management, compliance monitoring, FP&A, reporting, and fraud detection. |
Day 3 - Half Day
Designing the AI-First Financial Enterprise
Focus: Establishing enterprise governance, risk controls, adoption frameworks, and execution roadmaps.
The final day focuses on turning concepts and prototypes into a scalable, sustainable transformation strategy. Participants learn how to govern, operationalise, and scale AI initiatives across complex financial environments. The curriculum addresses responsible AI, model risk management, regulatory alignment, change management, and value realisation metrics to ensure enduring institutional impact.
| Module 5 | AI Governance, Adoption & Value Realisation Establish rigorous governance and operating frameworks for responsible AI adoption, model risk management, and regulatory compliance. Learn structured methodologies to evaluate AI capital investments, lead organisational change management, and measure quantifiable value realisation aligned with strategic business objectives. |
| Capstone | Banking & Corporate Finance AI Transformation Blueprint Lab Consolidate all programme learnings into a boardroom-ready enterprise blueprint. The deliverable integrates opportunity identification, workflow redesign priorities, knowledge architectures, generative and agentic use cases, governance mechanisms, and phased implementation roadmaps. |
Faculty
The programme is led by faculty and practitioners with experience in AI/GenAI strategy, financial risk management, Blockchain implementation, and regulatory compliance within the BFSI sector.
Dr. Shailesh Kumar
AI leader and Chief Data Scientist at Reliance Jio. Driving Deep Learning, Computer Vision, and NLP. Named a top 10 data scientist in India; former AI researcher at Google.
Dr. Binay Bhushan Chakrabarti
Esteemed finance academic and former Director of IIM Ranchi; Professor at IIM Calcutta. Gold medallist (IIM-C, Jadavpur); former corporate President (24+ years) and consultant to the UN and major banks.
Dr. Goutam Das
Founder and Principal Data Scientist at insAnalytics with over 30 years' experience in data science, ML, and analytics strategy. Former Chief Data Scientist at the Ministry of Power, Global Head of Analytics Consulting at TCS, and Senior Data Scientist at IBM; IIT Kharagpur and IIFT alumnus.
Experience
The fully-residential programme will be held at Jio Institute’s campus in Ulwe, Navi Mumbai. Participants will be housed in comfortable residential facilities with access to the high-performance gymnasium, recreational centre, library and athletic track.
- Meals and materials included
- Certificate on successful completion
- Access to campus amenities during programme days
Fees
The programme fee covers tuition, materials, and on-campus meals. Accommodation details are provided upon admission.
- Programme Fee: ₹40,000 (plus applicable taxes)
For questions about eligibility, sponsorships, or group nominations, contact us at:
- Toll-Free: 1800 889 1100
- Mobile: 90821 20978
- Email: admissions@jioinstitute.edu.in
You can also request a call back to discuss fit and objectives.