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Clearing an Onboarding and AML Backlog Through Flexible Scaling

Client overview

Our client is a UK-based law firm operating in a regulated consumer legal services environment. The firm handles high volumes of client onboarding and is subject to strict AML and identity verification requirements as part of its regulatory obligations.

At the point of engagement, the firm was continuing to attract new instructions, but historic onboarding delays were creating operational risk and limiting its ability to progress cases.

Client Testimonial

We had built up a significant backlog of partially completed onboarding and AML cases which was creating operational pressure. Alpha helped us deal with that problem quickly by deploying a larger team to clear historic cases, and then flexing the resource down once the backlog was under control. The approach allowed us to stabilise onboarding without permanently increasing internal headcount. What stood out was the structure, flexibility and the teams understanding of how to execute our plan.

Alpha LPO at Durban Office

The Challenge

The backlog covered approximately four to five months of activity and presented several issues:

  • A growing compliance risk linked to incomplete AML and ID verification
  • Operational drag caused by teams repeatedly revisiting old cases
  • Limited internal capacity to clear historic work while managing new daily volume
  • A risk that valuable cases would never progress due to prolonged delays
  • Increasing pressure on UK teams already stretched by day-to-day onboarding

The firm recognised that clearing the backlog was critical, but doing so using a permanent UK headcount increase would create long-term inefficiency once the issue was resolved.

Alpha designed a flexible onboarding support model focused on clearing the historic backlog first, before transitioning into steady-state support.

The approach was deliberately phased.

Initially, a larger dedicated team was deployed to focus solely on backlog remediation. This included re-engaging clients, completing outstanding AML and ID checks, validating documentation and bringing files up to a position where they could progress or be formally closed.

Key elements of the solution included:

  • A rapidly deployed onboarding and AML support team
  • Clear segmentation between backlog cases and live daily onboarding
  • Structured workflows for ID and AML completion
  • Quality assurance aligned to regulatory standards
  • Daily reporting on clearance rates and remaining backlog

Once the historic cases were under control, the model was designed to flex.

Within a defined period, the historic backlog was substantially cleared, removing a significant operational and compliance risk from the business.

As intended, the team size was then reduced and reshaped to support ongoing daily onboarding activity rather than historic remediation.

Key outcomes included:

  • The successful clearance of four to five months of partially completed onboarding cases
  • Reduced compliance exposure related to incomplete AML and ID checks
  • A return to predictable onboarding timelines
  • The ability to flex resource levels in line with live demand
  • No long-term increase in fixed internal headcount

The firm was able to move from a reactive position to a controlled, steady-state operation.

Why it worked

The success of this engagement was driven by flexibility and sequencing rather than a one-size-fits-all solution.

Critical factors included:

  • The ability to deploy capacity quickly at the start
  • A clear distinction between backlog work and live onboarding
  • Dedicated teams focused on specific objectives
  • The ability to scale resource down once the initial problem was solved
  • A compliance-first approach to AML and identity verification

Rather than creating a permanent overhead, the model solved a specific problem and then adapted to ongoing needs.

The outcome

What began as a remediation exercise became a more resilient onboarding operation. The firm reduced compliance risk, cleared historic inefficiencies and implemented a flexible support model capable of adapting to future fluctuations in demand.

This case study demonstrates how legal process outsourcing can be used not just to scale up, but to scale intelligently, applying resource where it is needed most and removing it when it is not.