11th Investment Data & Technology Summit
25 August 2026
The Fullerton Hotel Sydney
Stream One – Investment Analytics
09.00-09.10 // Welcome and conference opening
09.10-09.50 // Next-generation risk analytics: modelling an interconnected world
Traditional risk frameworks are being challenged by a more interconnected and complicated market environment where geopolitical, macroeconomic, technological and supply chain shocks can transmit rapidly across asset classes.
This session explores how investors are evolving risk models from single-factor analysis to systemic scenario frameworks that can capture growing complexity and correlations:
- Incorporating geopolitical, policy and supply chain shocks into scenario design.
- Modelling cross-asset contagion, correlation breakdowns and second-order effects.
- Enhancing decision-making through forward-looking stress testing frameworks.
- Evaluating the role of AI in predictive modelling.
09.50-10.30 // Bouncing back: portfolio resilience in practice
In volatile markets, resilience is defined not only by drawdown management but by the ability to respond efficiently to dislocation. This session will examine how investment firms have combined analytics, governance and implementation readiness to recover faster from shocks experienced over the course of the past year:
- Integrating stress-testing, liquidity analytics and scenario planning into decision frameworks.
- Aligning asset allocation, liquidity pools and re-balancing processes under stress.
- Building governance structures that support rapid execution during dislocation.
10.30-11.00 // Refreshments and networking
11.00-11.30 // Total portfolio intelligence: achieving, measuring and demonstrating success
As investors adopt total portfolio management frameworks, evaluating decision quality at whole-of-fund level remains complex. This presentation will explore the data models, analytics and governance required to measure outcomes across an integrated portfolio:
- Moving beyond asset-class benchmarks to total portfolio objectives and risk budgets.
- Measuring interactions between exposures, liquidity and implementation decisions.
- Translating whole-of-fund analytics into clear committee-level reporting.
11.30-12.10 // Capital in motion: embedding liquidity intelligence into portfolio decision-making
This session explores how different investment managers are developing more granular real-time liquidity analytics systems to better understand and manage capital, funding resilience and portfolio flexibility across market regimes:
- Best practice liquidity, cash and treasury analytics.
- Integrating liquidity analytics into portfolio construction, risk budgeting and rebalancing decisions.
- Tools, models and dashboards.
12.10-12.30 // Audience roundtable discussion
12.30-13.30 // Lunch & networking
13.30-14.10 // Avoiding the herd: differentiating in an AI-driven world
As AI democratises access to analytics and public information, maintaining a competitive advantage increasingly depends on proprietary inputs and differentiated decision processes.
This session explores how investment teams can avoid consensus-positioning in an AI-enabled market:
- When commoditised AI models enhance value versus erode edge.
- Leveraging proprietary, alternative and behavioural data sources.
- Designing governance frameworks that convert AI outputs into differentiated decisions.
- Retaining IP in AI-augmented processes.
14.10-14.50 // Uplifting ‘below the line’ portfolio analytics
This presentation will explore how investment organisations are redefining the boundaries between independent performance functions and front office analytics as demand grows for faster, more flexible decision-support, alongside governed reporting frameworks:
- Defining responsibilities across performance, risk and front office functions.
- System selection: when are performance systems sufficient and when do front office teams require alternative analytical capabilities?
- Aligning system design and purpose across performance, analytics and portfolio decision-making functions.
- Managing consistency and duplication of analytical outputs across multiple platforms and tools.
- Front office AI use cases and impact on third-party services.
14.50-15.10 // Audience roundtable discussion
15.10-15.40 // Refreshments and networking
15.40-16.20 // Closing the execution gap: minimising slippage in portfolio completion and overlays
Completion portfolios and overlays are powerful tools for managing exposures, liquidity and portfolio alignment. However, weak execution can materially reduce intended benefits while – particularly in Australia and New Zealand – time-zone issues can also materially impact drift.
This presentation will discuss how investment firms can increase the efficiency of their portfolio completion and overlay strategies to optimise portfolio impact:
- Assessing hedge effectiveness, factor alignment and tracking error outcomes.
- Quantifying implementation slippage, including execution quality, timing delays, transaction costs and rebalancing inefficiencies.
- Whole-of-fund scenario analysis for overlay decisions.
- Closing the feedback loop between portfolio construction, execution and post-trade analytics.
16.20-16.50 // Hidden in plain sight: uncovering and managing portfolio concentration risk
Diversification is critical to efficient portfolio construction but must be considered across multiple dimensions. Focusing on any single lens – such as asset classes – can leave portfolios exposed to unintended concentrations.
This presentation outlines practical approaches to identify and manage concentration risk:
- Mapping exposures holistically: identifying direct and indirect exposures across asset classes and strategies to reveal hidden concentrations.
- Quantifying beyond traditional buckets: assessing concentration risk obscured by standard asset class groupings, without relying on a single risk lens.
- Implementing integrated oversight: establishing frameworks to monitor and manage exposures consistently across the total portfolio.
16.50-18.00 // Networking reception, drinks and canapés
Stream Two – Data Management & Technology
09.00-09.10 // Welcome and conference opening
09.10-09.50 // The edge of tomorrow: redesigning operating models for the future
As AI, automation and modern data architectures mature, investment firms are reassessing the sustainability of legacy operating models. This panel will examine how COOs are redesigning target operating models to be able to operate and compete in an AI-driven world:
- Which components of today’s operating model are structurally obsolete?
- Where should firms modernise incrementally versus re-platform entirely?
- What does a fit-for-purpose operating model look like by 2030?
- Where do traditional ‘data’ and ‘technology’ functions fit in and what new capabilities and skillsets are required to support more bespoke AI capabilities?
09.50-10.30 // Connecting the dots: semantic layers, knowledge graphs and context graphs
Semantic engineering is gaining traction as a means of bringing clarity and context to fragmented and unstructured data. This session explores the architectural, modelling and process foundations required to create successful semantic layers and knowledge graphs:
- Selecting and integrating relevant data sources, tools and systems.
- Designing semantic layers to organise and implement business logic across source systems.
- Using knowledge and context graphs to model relationships across entities, positions, research and documents.
Lenka Bednarikova
Head of AI & Advanced Analytics,
Australian Retirement Trust
10.30-11.00 // Refreshments and networking
11.00-11.30 // Building an internal LLM: architecture, governance and lessons learnt
This case study will feature an investment manager’s design and deployment of an internal LLM to enable secure AI-powered querying across proprietary research, documents and unstructured data sources:
- Architecture and model strategy: selecting the right model, infrastructure and deployment approach.
- Tooling and integration: connecting data sources, workflows and user interfaces.
- The end result: effective Q&A capabilities through a unified front-office experience.
11.30-12.10 // Agents at work: re-engineering investment management workflows
AI agents are beginning to automate repeatable workflows across investment operations, research support and control functions. This panel explores how firms are redesigning processes, controls and roles as agentic capabilities mature:
- Which workflows are most suitable for agent-led execution today?
- How should human oversight and exception management be structured?
- What are the implications for workforce design and operating leverage?
- Combating ‘cognitive decline’.
Gerard Miller
SVP – Head of Agentic Strategy,
FactSet
12.10-12.30 // Audience roundtable discussion
12.30-13.30 // Lunch & networking
13.30-14.10 // From fragmentation to intelligence: optimising master data management
As firms adopt AI and increasingly interconnected SaaS platforms, inconsistencies in foundational master data structures become more pronounced across analytics, risk and operational workflows.
This session will examine how investment firms are rethinking master data strategies to improve consistency and interpretability across systems:
- Defining and maintaining consistent representations of core entities.
- Balancing global standardisation with local flexibility.
- Managing version, lineage and entity control.
14.10-14.50 // Solving the private asset data conundrum: aspiration or emerging reality?
Despite years of technological innovation, achieving true multi-asset capabilities and accurate private asset security mastering remains a challenge for many market participants.
This session will discuss current capabilities in the market; how market participants are plugging any gaps and what might be in scope as realistic solutions.
Shaun Gordon
Independent,
(Former Head of Investment Ops, TelstraSuper)
James Goh
Executive Director – Data & Analytics,
JP Morgan
14.50-15.10 // Audience roundtable discussion
15.10-15.40 // Refreshments and networking
15.40-16.20 // Maximising ROI on AI tools: a market data deep dive
As AI implementation costs fall and capabilities accelerate, investment firms are re-thinking how they select tools, allocate technology spend and decide what to build internally versus buy from vendors.
This discussion will feature a couple of case studies and explores how investment managers are approaching AI tool selection, where the build-versus-buy equation is shifting and how firms are improving returns on their AI investments:
- Case study: unlocking value from market data.
- How is AI changing the build-versus-buy equation for investment technology, data and analytics teams and what are the considerations?
- Model and tool selection: What does effective AI tool selection look like, and when is a premium model genuinely worth the additional cost?
16.20-16.50 // Transforming portfolio analytics: a case study
This case study will demonstrate how one fund has upgraded its front office analytics support from the back office through to front office support, through an improved investment data architecture that provides a live view of the portfolio:
- Building a trusted near real-time view of exposures and positions.
- Standardising investment data definitions across teams.
- Enhancing portfolio decision-making through improved analytics delivery.
16.50-18.00 // Networking reception, drinks and canapés