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Date
August 03, 2026
Program Duration
3 days
Language
English
Fees
24,863
In Class Training
London
About Program
This program serves as a strategic gateway to mastering the application of data analytics and Artificial Intelligence in shaping the future of banking and asset management, blending core concepts with high-value practical use cases. It aims to empower participants to anticipate opportunities within advanced algorithms while providing a comprehensive view of AI-related risk management and compliance with evolving regulatory perspectives. Through an interactive, learner-centric approach, the program seeks to instill a data-driven corporate culture, ensuring the transformation of raw data into smart investment decisions and proactive banking services that enhance operational efficiency and competitive advantage in the digital age.
Program Goals
Identify high-value AI and data analytics applications across banking and asset management.
Interpret, analyse, and communicate data insights to support informed decision-making.
Apply foundational AI, modelling, and portfolio simulation techniques in practical scenarios.
Evaluate AI-related risks, ethical considerations, and regulatory requirements in financial services.
Join us for an unforgettable journey of exceptional learning
Program Structure
Overview of AI and data analytics in financial servicesKey drivers shaping digital transformation in banking Case studies: AI transforming banking operations Simulation: Deploying AI in a bank
Day 1
Importance of data literacy in modern bankingFoundations of interpreting and Analyzing financial data Case studies: Data literacy in action Hands-on: Interpreting datasets Data storytelling techniques -Simulation: Data-driven decision-makingAddressing challenges in data literacyWrap-up and assessmen
Day 2
Role of AI in portfolio managementHow AI enhances asset allocation and risk analysis -Case studies: AI success stories in investments Hands-on: Portfolio optimization with AI Simulation: Predictive modelling of market trends Using alternative data (ESG, sentiment, etc.) in investment decisions Ethical and regulatory considerations in AI-driven asset management Wrap-up and assessment
Day 3
Program Agenda
In Class Training
Overview of AI and data analytics in financial services
Key drivers shaping digital transformation in banking
In Class Training
Case studies: AI transforming banking operations
Simulation: Deploying AI in a bank
In Class Training
In Class Training
Foundations of interpreting and Analyzing financial data
Importance of data literacy in modern banking
In Class Training
Case studies: Data literacy in action
Hands-on: Interpreting datasets
Data storytelling techniques
In Class Training
Simulation: Data-driven decision-making
Addressing challenges in data literacy
Wrap-up and assessment
In Class Training
Role of AI in portfolio management
How AI enhances asset alloca
In Class Training
Case studies: AI success stories in investments
Hands-on: Portfolio optimization with AI
Simulation: Predictive modelling of market trends
In Class Training
Using alternative data (ESG, sentiment, etc.) in investment decisions
Ethical and regulatory considerations in AIdriven asset management
Wrap-up and assessment
Trainers
Venture into a whole new realm of knowledge
Application Process: Your Journey Starts Here
The admissions team will carefully review all elements of your application. The selection process will take up to eight weeks from the date of submission of a completed application.
Step 1
Online application and video interview
Step 2
Pre-selection and decision
Step 3
Interview with acceptance
Step 4
Admission Committee
Step 5
Final decision
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