Artificial Intelligence in Finance - Fundamentals

Finance is digital and the Financial Services Industry acknowledges the need for a thorough digital transformation as the only means to thrive in the future. Technological capabilities are essential for a future in an industry that is digital in its very essence, the times of managing physical money and bonds being long gone.

Mastering the development and realisation of innovative financial products and services through digital technology is key. Financial systems thus become more reliable and transparent, and user interactions smoother. In terms of user-friendliness and adding value to said interactions, cybersecurity, authentication, (mobile) payments, robo-advisors, etc. all require adequate integration and packaging. 

This course will guide you through the core concepts, techniques, and algorithms that are reshaping financial services. Participants will explore how AI can optimise operations, enhance decision-making, and transform customer interactions. With a focus on practical applications, the training will cover predictive analytics, machine learning models, and neural networks, equipping you with the knowledge to implement AI solutions effectively within your financial organisation.

At the end of this training, participants will be able to: 

• Understand AI fundamentals and their relevance to the finance sector

• Explore AI techniques such as machine learning, deep learning, and neural networks

• Learn to apply AI for predictive analytics in credit scoring and market trends

• Master AI tools and platforms commonly used in financial applications

• Develop skills to implement AI-driven risk management and fraud detection systems

• Discover how AI can enhance algorithmic trading and investment strategies

• Study the impact of AI on customer service automation and personalisation

• Examine ethical considerations and regulatory challenges of using AI in finance

• Gain practical exposure through extended hands-on labs and case simulations.

• Understand future trends in AI adoption within the finance sector, including explainable AI and generative AI applications.

Introduction to AI in Finance

• AI Basics and Financial Implications

  • Overview of AI and its transformative potential in finance

  • Discussion on how AI is reshaping various aspects of the financial industry

• Emerging AI Trends in Finance

  • Exploration of explainable AI, generative AI, and their role in financial innovation

  • Regulatory outlook and evolving compliance standards

Key AI Techniques and Algorithms

• Introduction to machine learning, deep learning, and neural networks

• Overview of algorithms commonly used in financial applications

• Hands-on mini-lab: experimenting with simple ML models for financial datasets

AI Applications in Finance

• Predictive Analytics and Credit Scoring

  • How AI models predict financial behaviours and creditworthiness

  • Techniques for building and refining predictive models

• AI in Risk Management and Fraud Detection

  • Leveraging AI to identify risks and detect fraudulent activities

  • Case studies on successful AI implementations in risk and fraud management

Hands-On AI Tool Development

• Developing AI Tools for Algorithmic Trading

  • Hands-on session on designing and programming AI algorithms for trading

  • Simulation and back-testing of AI models with real market data

• AI-Driven Customer Interaction Solutions

  • Building AI tools for enhancing customer service and personalisation

  • Workshop on creating chatbots and AI interfaces for customer interactions in banking

Capstone Case Study & Ethical Considerations

• Group project: applying AI methods to solve a realistic finance scenario (e.g., portfolio optimisation, fraud case analysis, or credit risk evaluation).

• Discussion of ethical AI, data privacy, bias, and sustainability in financial applications

• Final reflections: how to strategically adopt AI in your organisation

This course is suitable for:

• Finance data managers and analysts seeking to integrate AI into decision-making processes

• Banking and financial services officers aiming to understand AI applications for credit, risk, and fraud management

• Insurance professionals interested in leveraging AI for claims assessment, fraud detection, and customer personalisation

• Investment and asset management practitioners exploring AI-driven trading and portfolio optimisation

• Technology and innovation teams in financial institutions who want to build practical AI solutions

• Individuals aspiring to specialise in financial AI and gain a strong foundation in its tools, techniques, and ethical implications.