In wealth management, onboarding is the moment trust is earned, risk is controlled, and revenue starts moving. When that journey is slow or inconsistent, the cost is not only operational. It shows up as delayed funding, frustrated advisors, rework, and exposure businesses cannot afford.
Most financial institutions assume their onboarding problems are a people problem. Advisors aren't fast enough. Administrators need more training. The back-end system needs an upgrade. But the real culprit is rarely any one of those things — it's that no one has ever actually seen the process end to end.
When you can't see a process clearly, you can't fix it. You can only add workarounds. And every workaround becomes tribal knowledge that exits the building with the next person who leaves.
A large Canadian financial institution was struggling to convert clients efficiently through its wealth management onboarding process. The path from initial onboarding request to active account management touched multiple systems, advisor teams, and administrative layers,and no one had a complete picture of how those pieces fit together.
The challenges were compounding:
The result was unpredictable onboarding timelines, elevated error rates, and a process where bottlenecks were felt but never precisely located. Leaders knew something was wrong — they just couldn't point to where.
Ashling introduced process intelligence as the diagnostic foundation before any automation was considered.
By implementing process mining across the end-to-end wealth management onboarding workflow, the engagement created something the organization had never had before: a transparent, data-driven view of how work was actually moving — not how people assumed it was moving.
Dynamic dashboards allowed the team to filter by individual activities and human agents, surfacing exactly where delays were accumulating and where inconsistencies in execution were introducing risk. From that clarity came a prioritized roadmap:
The solution was layered deliberately: process mining first to understand, then targeted intelligent automation to improve, then ongoing monitoring to sustain.
Process mining gave the client a shared, objective baseline. It aligned operations, transformation teams, and leadership around the same facts, and it turned improvement conversations from opinion-driven to evidence-driven.
The organization moved from a process defined by individual judgment and institutional memory to one governed by data, monitored continuously, and optimized systematically
Wealth management is a trust business. Every delay in onboarding is a delay in revenue conversion. Every error is a risk event. And every process that lives inside someone's head rather than inside a system is a liability waiting to materialize.
For this client, the status quo wasn't stable. As advisor teams changed, as client volumes grew, and as regulatory expectations increased, a process that depended on tribal knowledge and individual prioritization was going to break more visibly over time.