The Future of Financial Services: Data and AI Conference 2025 will convene over 200 industry leaders, innovators, and experts to navigate the transformative power of AI in financial services. Explore how AI is reshaping business models, enhancing operational efficiency, and driving customer-centric innovation through keynote presentations, engaging panel discussions, and other interactive formats.
Key Themes:
- The Economic Power of AI: Discover how generative AI is poised to add between $200 billion and $340 billion annually to the global banking sector by 2027, according to McKinsey Global Institute.
- AI-Powered Risk Management: Explore how AI is being used to create cutting-edge Next-Gen fraud detection capabilities in banking, building on the back of major Australian banks closing thousands of scam accounts.
- Hyper-Personalised Customer Experiences: Uncover new AI-driven avenues for personalising customer experiences.
- AI Governance in Finance: Explore the evolving regulatory frameworks around integrating AI and Machine Learning in Australian workplaces.
- The Future of Financial Data: As AI reshapes Australian finance, data is the key to resilience, innovation, and trust. Explore how advanced analytics, secure data sharing, and ethical monetisation are driving compliance, customer intelligence, and financial inclusion in an evolving regulatory and economic landscape
- Blueprint for Sustainable Data Centres: Discuss strategies for sustainable data centre growth in Australia’s rapidly expanding AI infrastructure market, balancing demand with responsible energy consumption
Gain insights from AI leaders across banking, insurance, wealth management, and fintech. Learn from early adopters who have launched AI-powered claims assistant tools, and identify the challenges and opportunities for responsible AI deployment, and explore the trends poised to reshape Australian businesses. Explore workforce evolution, responsible AI deployment, and actionable strategies for building a competitive edge in the data-driven future of finance.
- Architecting for AI: Balancing cloud-based innovation with regulatory compliance in modern data infrastructures
- Breaking Silos: Strategies for unified, high-quality data access across financial organisations
- Ethical AI Evolution: Mitigating bias, upholding standards, and preparing the workforce for AI-augmented finance
- Developing ethical frameworks for AI implementation in banking
- Strategies for managing emerging risks in the rapidly evolving technology landscape
- Fostering a culture of responsible innovation: Lessons from ANZ's AI Immersion Centre
- Harnessing generative AI to enhance operational efficiency and customer engagement in insurance
- Establishing ethical frameworks for AI use: Insights from QBE’s Data Ethics Advisory Panels
- Aligning data strategies with business priorities to deliver measurable outcomes across teams
- How larger datasets, new analytic techniques, and deeper technology integration are transforming overseas lenders—and what this means for Australia in the coming years
- Key steps banks and non-bank lenders can take now to prepare for the shift driven by AI and sophisticated modelling
- Emerging factors influencing credit risk that were previously undetectable, and what they mean for the future of lending
- How will generative AI’s projected $200–$340 billion impact reshape banking by 2027, and where should financial institutions invest now?
- As AI adoption accelerates, how can Australia’s financial sector scale sustainable data centres while managing energy demands?
- What are the key challenges in balancing AI-driven fraud detection, hyper-personalised customer experiences, and evolving regulatory frameworks?
- Learn where to start, how to pilot AI initiatives, and the steps to successfully integrate AI into existing ways of working while leveraging data.
- Explore the decision-making process behind prioritising AI initiatives, and how to articulate an AI value proposition.
- Discover how to craft a compelling message for the board and executives, focusing on measurable outcomes, scalability, and aligning AI adoption with strategic business goals.
Gold
Executive Roundtable
