In the fast-evolving world of institutional investing, staying ahead demands not just data but deep, actionable insights. This session will explore how Generative AI is redefining the investment process, drawing from AlphaSense's latest advancements - such as Generative Search - to illustrate the practical applications of AI-driven content analysis and provide a glimpse into the future of investment intelligence.

This session will explore new use cases and asset classes for alternative data beyond equities. How can fixed income and high yield investors leverage new data sources to gain a competitive advantage? Which data sets and signals are proving impactful for credit and industrial investors?

Investment managers are increasingly relying on market data to inform their investment decisions. How can different levels of data depth and granularity accommodate diverse trading strategies? How can analysts use historical data to identify long-term trends and market cycles?

With alpha spillage between assets and increasing demand for point-in-time quality data, cross-asset signals have proven to be a great solution to quantitative strategies for new information. This presentation will explore how quantitative investors can derive value from traditional and alternative data, linking assets and companies to create new ideas and datasets with deep point in time history.

Quantitative investment funds have been faced with notable changes to the data market in the last 5-10 years. This session will explore the current trends in alternative data usage. Which dataset types have grown in availability and popularity? What challenges do quantitative investors face in integrating new data? Does data supply meet demand?

Delve into the value of human intuition, creativity and strategic thinking, alongside the power of machine learning models. This panel will examine the potential and limitations of AI in quantitative investing, debating where human oversight remains essential and how both can work together to optimize investment strategies.

This session will highlight data innovation at global insurance and reinsurance business AXA XL, with a focus on how to extract more value from internal data, best practices for navigating risk through third party data and how to address some of the challenges with advocating for change to internal stakeholders.

The insurance industry has long relied on traditional data sources to assess risk, set premiums and manage customer relationships. Panelists will consider how new sources of third-party data can drive enhancements, with discussion of how insurance use cases for alternative data compare to investor use cases and considerations for upholding data security and privacy.

This session will delve into how satellite imagery and geolocation data can provide real-time insights into key macroeconomic trends and serve as powerful tools to uncover hidden opportunities across diverse asset classes. Discover how QuantCube’s approach transforms raw data into actionable intelligence, empowering investors to stay ahead in an ever-evolving landscape.

This session will explore how the climate crisis will personally impact ‘finance bros’ and discuss the investment strategies that can help mitigate these impacts and the damage caused to the global environment. We also highlight the alternative datasets that can add alpha for long and short-term climate investment strategies.

Ongoing climates of economic uncertainty and market volatility create opportunities for investors to benefit from macro strategies. Panelists explore the impact of recent macro and geo-political trends and consider the alternative data sources that can help track the global economy and drive sustainable investments.

This session will introduce data buyers to Neudata Ranger, a platform providing technical intelligence on market data sources. Find out more about the tools offered by Ranger to help buyers enter vendor conversations confidently, avoid trading disadvantages and keep abreast of the datasets offering best results relative to peers.

Alternative data is often defined as what it is not, but should the industry pay closer attention to the insights traditional data can offer? In this session, panelists will discuss the current challenges and opportunities in market and traditional data. How can complex data licensing and reporting be best managed? How is AI transforming data usage?

Across the credit industry, there exists both uncertainty and excitement around the impact of AI and advanced analytics on investing. As the market grows more digitalized how are investors defining their data and analytics innovation strategies? What are the main use cases for alternative data in credit investing?

Private equity and venture capital investors are copying our sisters in the hedge fund and mutual fund world: we’re trying to automate more of our job. This session will explore how investors and lenders in private companies are using AI and analytics to accelerate returns.

A growing number of private equity and venture capital firms are leveraging alternative data to identify and evaluate investment opportunities. How can new datasets better pinpoint undervalued assets and emerging market segments to support deal origination efforts?

This panel will explore how private equity firms can leverage non-traditional data to unlock a market edge. How can alternative approaches to data enhance the speed and accuracy of due diligence processes? What current and future trends should firms be aware of?