The firm relied on fragmented portfolio data across multiple custodians, leading to inconsistent information and limited visibility into client holdings. Advisors frequently spent significant time consolidating positions, transactions, and performance data before making investment decisions.

Manual portfolio rebalancing created additional operational overhead. Advisors had to identify portfolio deviations, determine appropriate trades, and coordinate execution across custodians, slowing down investment workflows and reducing time available for client engagement.

Risk assessment processes were also largely manual and depended on multiple data sources. The lack of centralized analytics made it difficult to identify portfolio risks quickly and apply consistent scoring across client accounts.

Regulatory reporting required extensive manual data preparation and validation, increasing turnaround times and operational effort. The firm needed a modern portfolio management solution that could unify investment data, automate repetitive workflows, and provide AI-driven insights for faster, data-informed decision-making.