AI and WealthTech: Intelligent Advisory & Personalization Training Course

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

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

• Understand the role of AI in financial automation and fraud detection.
• Build AI models to detect 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.

AI in Financial Services is transforming the way institutions manage risk, strategy, compliance, and customer experience.

This instructor-led, live training (online or onsite) is designed for intermediate-level financial and technology professionals who wish to understand how AI impacts strategy, ethics, and regulation in the financial sector.

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

• Understand the strategic applications of AI in financial services.
• Evaluate the ethical and regulatory implications of AI adoption.
• Develop frameworks for responsible AI governance and oversight.
• Align AI strategies with organisational goals and compliance requirements.

Format of the Course

• Interactive lecture and discussion.
• Case studies and group exercises.
• Practical analysis of real-world AI regulatory frameworks.

Course Customisation Options

• To request a customised training 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.

Applied AI brings new levels of efficiency and intelligence to the way finance professionals analyse and report on business performance.

This instructor-led, live training (online or onsite) is designed for intermediate-level finance professionals who wish to integrate AI tools into their financial statement workflows to improve accuracy, automate repetitive tasks, and gain forward-looking insights.

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

• Automate data extraction from financial documents using AI tools.
• Apply machine learning models to analyse trends and anomalies in financial statements.
• Use generative AI to assist with variance commentary, narrative reports, and scenario simulation.
• Interpret AI-generated outputs responsibly within the context of financial reporting and planning.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical practice.
• 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.

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.

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.

Machine Learning is a subset of Artificial Intelligence focused on creating systems that learn from data and make predictions or decisions without being explicitly programmed.

This instructor-led, live training (online or onsite) is aimed at intermediate-level finance professionals who wish to apply machine learning and AI techniques to real-world problems such as fraud detection, credit scoring, and risk modelling.

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

• Understand the core machine learning concepts relevant to finance.
• Apply supervised and unsupervised learning algorithms to financial datasets.
• Build and evaluate predictive models for credit risk, fraud detection, and market analysis.
• Use Python and scikit-learn to implement machine learning pipelines.

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.

This instructor-led, live training in New Zealand (online or on-site) is designed for intermediate-level finance professionals, data analysts, risk managers, and AI engineers who wish to harness multimodal AI for risk analysis and fraud detection.

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

• Understand how multimodal AI is applied in financial risk management.
• Analyse structured and unstructured financial data for fraud detection.
• Implement AI models to identify anomalies and suspicious activities.
• Leverage NLP and computer vision for financial document analysis.
• Deploy AI-driven fraud detection models in real-world financial systems.