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About the Course

The AI Strategy Implementation for Banking Program is a three-day, in-person course designed to help financial services professionals move from AI ambition to practical implementation. The program focuses on identifying valuable AI use cases, building the right governance and risk frameworks, and developing a clear implementation roadmap aligned with the realities of the banking and financial services sector.

Who Should Attend?

The program is designed for mid to senior-level professionals across the financial services sector, particularly those involved in strategy, digital transformation, innovation, technology, risk, compliance, operations, and business functions exploring the adoption and implementation of AI.

Modules

  • Session 1: Overview of AI and its Role in Fintech

    • Definition of AI, machine learning, and generative AI

    • AI applications in financial services: payments, lending, insurance, wealth management

    • The transformative potential of AI in fintech

    • Case studies of AI in finance

     

    Session 2: Fundamentals of AI: Key Concepts

    • Introduction to data-driven decision-making

    • Key AI technologies: machine learning, natural language processing, and computer vision

    • Overview of AI lifecycle: data collection, model building, and deployment

  • Session 3: Machine Learning Fundamentals for Fintech

    • Supervised vs. unsupervised learning

    • Application of machine learning models in financial forecasting and risk assessment

    • Understanding credit scoring models and fraud detection

     

    Session 4: Hands-On Introduction to Machine Learning

    • Basic hands-on exercises in data analysis and model training (simplified using no-code/low-code tools)

    • Demo of a machine learning tool in the financial context

  • Session 5: Introduction to Generative AI

    • What is generative AI and its core components

    • Use cases of generative AI in fintech: personalized financial services,= chatbot development, and automated content generation

     

    Session 6: Generative AI and Chatbots in Financial Services

    • Exploring AI chatbots for customer service and financial advice

    • Case studies of chatbot deployment in fintech companies

  • Session 7: The Role of Data in AI and Fintech

    • Importance of data quality and data governance in AI applications

    • Introduction to data analytics tools in fintech

    • Compliance and privacy concerns related to financial data

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    Session 8: Data-Driven Insights for Financial Decision-Making

    • Practical example: building basic financial dashboards using data analytics tools

    • Real-world case study: leveraging AI for personalized financial product recommendations

  • Session 9: AI for Fraud Detection in Fintech

    • Machine learning algorithms for detecting fraudulent transactions

    • AI-driven risk-scoring models

    • Case study: AI tools used by banks and payment processors

     

    Session 10: Implementing AI for Risk Management

    • Identifying risks using predictive modeling

    • AI applications for credit risk, operational risk, and liquidity risk management

    • Demo: Basic predictive risk model using AI tools

  • Session 11: AI in Payments

    • How AI optimizes payment processing systems

    • Use cases: AI-driven payment gateways and fraud prevention

    • Case studies: PayPal, Stripe, and AI-driven payment solutions

     

    Session 12: AI for Lending and Credit Scoring

    • AI’s impact on peer-to-peer lending and microfinance

    • Credit scoring models powered by AI

    • Case studies on AI in digital lending platforms

  • Session 13: Regulatory Landscape for AI in Finance

    • Overview of financial regulations impacting AI adoption

    • Compliance with data protection laws (e.g., GDPR, PSD2)

    • Addressing algorithmic bias and fairness in AI models

     

    Session 14: Ethical AI and Responsible Innovation in Fintech

    • Importance of transparency, fairness, and accountability in AI models

    • Ethical considerations in customer data usage

    • Best practices for deploying ethical AI in fintech

  • Session 15: Future Trends in AI for Fintech

    • Trends shaping the future of AI in finance: decentralized finance (DeFi), blockchain, AI-driven asset management

    • How AI and fintech will evolve in the coming years

     

    Session 16: Capstone Project Presentation and Course Wrap-Up

    • Team-based or individual capstone projects

    • Presentations and feedback ○ Course review and next steps

AI Strategy Implementation for Banking

In-Person

|

BHD 800 | SAR 8,000 *excl. VAT

A powerful, multi-institutional program that equips leaders with the strategic direction needed to drive digital transformation, while maintaining strong governance and identifying the right tools to support the journey with confidence and impact.

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Duration

3 Days

Dates

27 - 29 Sep, 2026

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Location

Innovate for Bahrain, Riyadat Mall

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Earn a Certificate of Completion

What to Expect

  • Understand how AI can create value across financial institutions, assess potential use cases, and prioritize opportunities based on business impact, feasibility, and strategic objectives.

  • Explore the governance, regulatory, data, risk, and responsible AI considerations required when introducing AI within a financial institution, including considerations relevant to Bahrain's regulatory environment.

  • Turn AI opportunities into an actionable implementation plan, covering stakeholder alignment, operating requirements, execution priorities, and the development of a practical AI roadmap.

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