AI Governance and Strategic Risk Management in Financial Services Training Course

Artificial Intelligence (AI) is reshaping the financial sector by driving smarter decision-making, strengthening risk management, and enhancing capabilities in fraud detection, regulatory compliance, financial forecasting, and process automation. This course equips finance professionals with the practical expertise needed to understand AI technologies and apply them within banking, insurance, investment management, and broader financial services.

Learning Objectives

Upon completing this course, participants will be equipped to:

• Grasp the core principles of Artificial Intelligence and Machine Learning as they apply to finance.
• Recognise significant AI use cases throughout the financial services ecosystem.
• Leverage AI techniques to enhance risk management, detect fraud, and improve financial forecasting.
• Deploy AI-driven tools to boost operational efficiency and support evidence-based decision-making.
• Navigate the ethical, regulatory, and governance aspects associated with adopting AI.
• Assess the potential opportunities and complexities involved in implementing AI within financial institutions.

This live, instructor-led training in New Zealand, available online or onsite, is designed for intermediate-level financial professionals, risk analysts, and AI engineers who aim to develop and deploy AI-driven solutions for financial automation and fraud detection.

By the end of this programme, participants will be able to:

• Understand the role of AI in financial automation and fraud detection.
• Build AI models for detecting fraudulent transactions.
• Leverage machine learning for real-time risk assessment.
• Deploy AI-powered financial monitoring systems.

AI is transforming how financial institutions assess creditworthiness, price risk, and optimise lending decisions.

This instructor-led, live training (online or onsite) is aimed at intermediate-level finance professionals who wish to apply artificial intelligence to enhance credit scoring models, manage risk more effectively, and improve lending operations.

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

• Understand key AI methods used in credit scoring and risk prediction.
• Build and evaluate credit scoring models using machine learning algorithms.
• Interpret model outputs for regulatory compliance and transparency.
• Apply AI techniques to improve underwriting, loan approval, and portfolio management.

Format of the Course

• Interactive lecture and discussion.
• Plenty of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customisation Options

• To request a customised training for this course, please contact us to arrange.

Artificial Intelligence is a technology that enables the development of digital products with advanced data-driven capabilities and personalised customer experiences.

This instructor-led, live training (online or on-site), combined with asynchronous activities and face-to-face workshops, is designed for intermediate-level banking professionals who wish to design, develop, and deliver AI-powered digital products effectively.

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

• Identify customer needs and define a clear product vision.
• Apply AI technologies to enhance digital banking products.
• Use agile and design thinking methods to create user-centred solutions.
• Measure, iterate, and optimise product performance for sustained value.

Course Format

• 50% synchronous classes (virtual or in-person).
• 25% asynchronous activities (videos, readings, forums).
• 25% in-person practical workshop with case studies.

Course Customisation Options

• To request a customised training session for this course, please contact us to arrange.

AI is transforming how financial institutions detect fraud and combat money laundering through intelligent, real-time analysis of vast transaction datasets.

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to apply machine learning and AI tools to automate and enhance financial crime detection, compliance monitoring, and operational governance.

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

• Understand AI use cases in fraud detection and AML monitoring.
• Design and implement models for anomaly detection and transaction scoring.
• Leverage graph-based AI for network risk detection.
• Ensure ethical, explainable, and regulatory-compliant model deployment.

Course Format

• Interactive lectures and discussions.
• Ample exercises and practical activities.
• Hands-on implementation in a live-lab environment.

Course Customisation Options

• To request a customised training session for this course, please contact us to arrange.

AI in Financial Services is a strategic enabler for risk reduction, customer experience, and operational efficiency.

This instructor-led, live training (online or onsite) is aimed at financial services executives, fintech managers, and compliance officers with limited prior exposure to artificial intelligence who wish to understand how to responsibly and effectively implement AI solutions in their institutions.

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

• Understand the strategic value of AI in financial services.
• Identify and mitigate ethical risks associated with AI models.
• Navigate the regulatory landscape for AI in finance.
• Design responsible AI governance and implementation frameworks.

Course Format

• Interactive lectures and discussions.
• Case study analysis and group exercises.
• Application of ethical frameworks to realistic financial scenarios.

Course Customisation Options

• To request a customised training session for this course, please contact us to arrange.

AI is transforming FinTech by enabling intelligent automation, hyper-personalisation, and secure real-time financial services.

This instructor-led, live training (online or on-site) is aimed at beginner-level to intermediate-level FinTech professionals who wish to explore the convergence of AI, APIs, and Open Banking innovations to design next-generation financial products.

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

• Understand how AI and machine learning are applied across FinTech use cases.
• Leverage Open Banking APIs and data aggregation for product innovation.
• Design AI-driven features for digital wallets, neobanks, and financial assistants.
• Align innovation with regulatory, ethical, and security considerations.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and hands-on practice.
• Practical implementation in a live-lab environment.

Course Customisation Options

• To request a customised training session for this course, please contact us to arrange.

Artificial Intelligence is a powerful set of techniques used to develop intelligent trading systems that analyse market data, make predictions, and execute strategies autonomously.

This instructor-led, live training (online or onsite) is aimed at intermediate-level finance professionals who wish to apply AI techniques in trading and asset management, with a focus on signal generation, portfolio optimisation, and algorithmic strategies.

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

• Understand the role of AI in modern financial markets.
• Use Python to build and backtest algorithmic trading strategies.
• Apply supervised and unsupervised learning models to financial data.
• Optimise portfolios using AI-driven techniques.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practical sessions.
• Hands-on implementation in a live-lab environment.

Course Customisation Options

• To request a customised training session for this course, please contact us to make arrangements.

AI is transforming WealthTech by enabling highly personalised financial services, intelligent advisory platforms, and enhanced user experiences.

This instructor-led, live training (online or on-site) is aimed at intermediate-level finance and technology professionals who wish to design, evaluate, or implement AI-driven solutions for personalised wealth management and robo-advisory services.

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

• Understand how AI is applied in wealth management and digital advisory platforms.
• Design intelligent systems for personalised portfolio recommendations.
• Incorporate behavioural finance data and preferences into advisory algorithms.
• Evaluate ethical and regulatory concerns in automated investment advice.

Format of the Course

• Interactive lecture and discussion.
• Plenty of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customisation Options

• To request a customised training for this course, please contact us to arrange.

Applying AI brings enhanced efficiency and intelligence to how finance professionals assess and report on business performance.

Designed for intermediate-level finance professionals, this live instructor-led training (delivered either online or on-site) focuses on integrating AI tools into financial statement workflows. This approach aims to improve accuracy, automate routine tasks, and deliver forward-looking insights.

Upon completing this training, participants will be able to:

• Automate the extraction of data from financial documents using AI tools.
• Utilize machine learning models to identify trends and detect anomalies within financial statements.
• Leverage generative AI to support variance commentary, narrative reporting, and scenario simulations.
• Responsibly interpret AI-generated outputs within the context of financial reporting and planning.

Course Format

• Interactive lectures and facilitated discussions.
• Extensive exercises and practical practice.
• Hands-on implementation within a live-lab environment.

Customization Options

• To request a tailored training programme for this course, please contact us to make arrangements.

This instructor-led, live training in New Zealand (available online or on-site) is designed for finance professionals who wish to leverage ChatGPT to streamline their workflows and enhance their data analysis and reporting capabilities.

By the conclusion of this training, participants will be able to:

• Grasp the fundamentals of ChatGPT and its underlying mechanisms.
• Utilise ChatGPT to automate financial tasks such as data entry and report generation.
• Analyse financial data using ChatGPT to gain insights and support informed decision-making.
• Develop custom ChatGPT models tailored to specific financial use cases.

Copilot for Microsoft 365 is an AI-powered assistant that integrates with Microsoft Office applications to help finance and accounting professionals enhance productivity, streamline reporting, and support decision-making.

This instructor-led, live training (online or onsite) is aimed at finance and accounting professionals with limited experience with AI who wish to leverage Microsoft Copilot to improve accuracy, efficiency, and insight in financial tasks.

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

• Create financial reports quickly and accurately using Copilot.
• Automate repetitive accounting and data-entry tasks.
• Generate financial summaries and forecasts with AI assistance.
• Use natural language prompts to extract insights from large financial datasets.

Format of the Course

• Interactive lecture and discussion.
• Plenty of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customisation Options

• To request a customised training for this course, please contact us to arrange.

This intensive five-day programme is designed to give participants a thorough understanding of how artificial intelligence (AI) is transforming financial systems. By combining theoretical knowledge with practical application, participants will investigate state-of-the-art AI techniques specifically adapted for the finance industry. Upon completion of the course, attendees will possess the skills and insights required to effectively utilise AI technologies in key areas such as financial decision-making, risk management, fraud detection, algorithmic trading, and customer service within financial institutions. The objective is to empower professionals with the expertise necessary to navigate the shifting landscape of AI-driven finance and maintain a competitive edge in an increasingly demanding market.

Generative AI refers to a class of artificial intelligence techniques designed to generate new content or predictions from existing data, including Large Language Models (LLMs) and Generative Adversarial Networks (GANs).

This instructor-led, live training (available online or on-site) is tailored for beginner to intermediate-level finance professionals seeking to apply generative AI for forecasting, anomaly detection, and compliance within financial services.

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

• Grasp the foundational concepts underpinning generative AI models.
• Apply LLMs and GANs to practical use cases such as fraud detection and synthetic data generation.
• Craft effective prompts to support financial forecasting and reporting.
• Assess ethical and regulatory considerations specific to generative AI applications.

Course Format

• Interactive lectures and group discussions.
• Ample opportunities for exercises and hands-on practice.
• Real-time implementation in a live-lab environment.

Customisation Options

• To request a customised version of this course, please contact us to arrange a tailored session.

LangGraph is a framework for building stateful, multi-actor LLM applications as composable graphs with persistent state and control over execution.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level professionals who wish to design, implement, and operate LangGraph-based finance solutions with proper governance, observability, and compliance.

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

• Design finance-specific LangGraph workflows aligned to regulatory and audit requirements.
• Integrate financial data standards and ontologies into graph state and tooling.
• Implement reliability, safety, and human-in-the-loop controls for critical processes.
• Deploy, monitor, and optimise LangGraph systems for performance, cost, and SLAs.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customisation Options

• To request a customised training for this course, please contact us to arrange.