Mastering Modern Banking Analytics using Data Science Approach

The BFS industry is undergoing a profound transformation driven by digital technologies, data proliferation, and the rapid adoption of AI. Financial institutions generate vast volumes of structured and unstructured data from customer transactions, digital banking platforms, payment systems, social media, and regulatory reporting. Converting this data into actionable business intelligence has become essential for sustaining competitiveness, enhancing customer experience, managing risks, and ensuring regulatory compliance.

This three-day MDP is designed to equip banking and financial services executives with a comprehensive understanding of advanced analytics, ML, and AI technologies from a business perspective. By integrating analytical thinking with strategic decision-making, the programme prepares executives to identify high-impact AI opportunities, evaluate technology investments, and lead data-driven innovation initiatives.

Content

  • Session 1 – Fundamentals of BFS and Data Science: Overview of BFS, supervised, unsupervised, semi-supervised, and reinforcement learning.
  • Session 2 – Data Ecosystem in Banking and ML Lifecycle: Data quality, data preparation, feature engineering, model selection, training, validation, deployment, monitoring, and continuous improvement.
  • Session 3 – Fundamentals and Hands-on applications of EDA in BFS: Banking KPI visualization, risk data compression and interpretation.
  • Session 4 – Fundamentals and Hands-on applications of Supervised MLs for BFS: RF, SVM, NB, and ANN for loan default prediction, AML alerts, and fake review detection.
  • Session 5 – Fundamentals and Hands-on applications of Unsupervised MLs for BFS: K-Means, K-Modes, Hierarchical, and DBSCAN for customer segmentation and wealth management.
  • Session 6 – Fundamentals and Hands-on applications of Deep Learning for BFS: RNN and Bi-LSTM for predicting insurance cross-selling, fraud sequence, AML monitoring, and compliance analytics.
  • Session 7 – Fundamentals and Hands-on applications of recommendation systems for BFS: Content-based Filtering and Collaborative Filtering for personalized banking offers and investment recommendations.

Objectives

On completion of the programme, participants will be able to:

  • Develop a strong foundation in advanced analytics and ML and understand their applications across the BFS sector.
  • Understand the end-to-end analytics lifecycle.
  • Apply data-driven decision-making techniques for fraud detection, customer segmentation, and portfolio optimization.
  • Analyse financial risks using advanced analytical techniques.
  • Develop hands-on proficiency with modern analytics tools and platforms commonly used in the BFS industry.

Who should attend?

The programme is designed for organizations that are adopting AI to strengthen strategic planning, improve decision-making, enhance operational efficiency, and achieve sustainable competitive advantage. Potential client organizations include:

  • Public Sector Banks
  • Private Sector Banks
  • Small Finance Banks and Payments Banks
  • Insurance Companies
  • Non-Banking Financial Companies
  • FinTech and Digital Financial Services Companies
  • Asset Management Companies (AMCs) and Investment Firms
  • Credit Rating and Financial Information Agencies
  • Stock Exchanges and Financial Market Institutions
  • Consulting and Technology Service Providers

Target Audience

  • Senior Executives and Functional Heads
  • Chief Digital Officers and Chief Data Officers
  • Risk Management Professionals
  • Credit and Lending Officers
  • Fraud Risk and AML Professionals
  • Compliance and Regulatory Officers
  • Data Analytics and Business Intelligence Managers
  • IT and AI Strategy Managers
  • FinTech Executives and Innovation Leaders
  • Consultants working in BFSI digital transformation

Venue & Duration

The programme is scheduled during December 04-06, 2026 on a residential basis at MDI Campus, Mehrauli Road, Sukhrali, Gurugram. Accommodation for participants would be available at MDI Campus from the noon of December 03, 2026 to the forenoon of December 07, 2026.

Fees

Participants should be nominated by their organizations. The enclosed nomination form should be completed and returned with all the details. The fee of the program which includes a professional fee and all charges for boarding, lodging and supply of course materials during the programme. GST as applicable will be charged extra in addition to the programme fee. Payment should be made by Cheque/NEFT/RTGS.

S.noParticularPer participants Program Fees (exclusive of GST)
1Single RoomRs. 45000/-
2Double Sharing RoomRs. 42000/-
3Non residentialRs. 40500/-

Discount Policy

With a view to our long-term relationship with your esteemed organization, we are pleased to introduce the discount policy in this programme. The discount will be observed in the following conditions: (discount is applicable in NEPAL also)

  • 10% Discount against 3-5 nominations
  • 20% Discount against more than 5 nominations

Important Dates

The last date for receipt of nominations is November 20, 2026. The last date for withdrawal of nominations is November 21, 2026. Any withdrawal received after this date will be subject to deduction as per the Institute's rules. However, substitution may be permitted.

Nominating organizations are advised to await confirmation of acceptance of nominations(s) before sending the participants to the programme venue.