Join us for this research event focused on exploring how wealth management firms are tackling increasingly complex data environments.
📅 16 April, 16:00-18:00
🍸 Networking drinks until 20:00
📍 Eight Club, Dysart Street, City of London
We’ve partnered with The Wealth Mosaic to host a focused evening discussion exploring one of wealth management’s more pressing challenges – how poor data management is holding firms back from growth, efficiency, and innovation.
Designed specifically for wealth managers, the event offers the opportunity to explore how firms are tackling increasingly complex data environments while responding to regulatory demands, client expectations, and the growing impact of artificial intelligence (AI).
This evening event will place special emphasis on how:
• Firms are using data to enhance client understanding, segmentation, and reporting
• The role of data in meeting Consumer Duty and other regulatory requirements
• AI could be amplifying the risks associated with weak data foundations
Don’t miss this opportunity to connect with experts and gain valuable insight into new research that will support more robust and future-ready data strategies in wealth management. Register for free:
Event Background
Why data management matters more than ever
For many years, data issues in wealth management have existed quietly in the background. 79 percent of firms acknowledge that poor data quality is a pain point, and it is estimated to cost firms US$12.9 million every year on average. But although data management is broadly recognised as problematic, until now it has rarely been prioritised over more immediate operational or client-facing concerns. That dynamic is changing rapidly.
Across the industry, senior leadership teams are increasingly recognising that data quality is not simply a technology issue, but a core business capability that underpins growth, client service, and regulatory compliance.
Inconsistent or siloed data slows reporting, complicates compliance process, and limits the ability of firms to extract meaningful insights from their operations. At the same time, wealth managers are dealing with expanding volumes of data from multiple providers and internal systems – often delivered in different formats and requiring significant manual intervention to reconcile.
The emergence of AI has only heightened the urgency and created new threats stemming from poor data management practices. With the seductive power that AI offers to enhance efficiency and analytics, its dependence on a high-quality data foundation is often overlooked. Without those strong data foundations, firms risk amplifying inaccuracies, bias, and operational inefficiencies rather than solving them.
Transforming wealth management’s relationship with data
For wealth management leaders responsible for strategy, operations, technology, or client service, this event provides an opportunity to engage with peers facing similar challenges and gain practical insight into how firms are evolving their data capabilities.
Good data is no longer simply a matter of hygiene; it is fast becoming a key differentiator for wealth firms seeking to improve productivity, deepen client relationships, and unlock future growth opportunities. Conversely, firms that extensively adopt AI capabilities without first addressing their data management challenges risk exposing fundamental weaknesses that will sap client confidence.
This London gathering aims to move that conversation forward – helping wealth managers understand not just why data matters, but how firms can start turning it into a strategic advantage.
Introducing our new research
At the heart of the event will be a presentation of the key findings from our white paper, ‘Order from disorder: moving from fragmented data to competitive advantage’, based on interviews with wealth management firms conducted in early 2026.
The research reveals that most firms are now actively pursuing a ‘single source of truth’ for their data – typically through a centralised data lake or warehouse – yet the journey to achieving that goal remains complex. Implementation challenges range from legacy technology stacks and fragmented data sources to resource constraints and the need for organisation-wide cultural change.
