Case study
Client onboarding and financial crime operations for a Schedule I bank
The challenge
Onboarding volumes were seasonal and unpredictable, but the financial crime team was fixed. In peak periods, onboarding times stretched well past the bank's commitment and abandonment at account opening rose measurably. In quiet periods the team was underutilised. Hiring to peak was uneconomic and hiring to average produced the peak problem. Separately, the screening configuration was generating a high false positive rate, and nobody had the data to prove it.
What Corpshore did
We built a dedicated financial crime operations team in Ontario with a contractually agreed capacity band, so the bank pays for a floor and flexes upward within a defined range without renegotiation each time volume moves. The team performs customer due diligence, enhanced due diligence on higher risk files, sanctions and PEP adjudication, and adverse media review, in four languages reflecting the bank's customer base.
Alongside the operational work, analysts logged the disposition reason for every false positive across the first ten weeks. That dataset gave the bank the evidence to retune thresholds its own team had long suspected were too tight but could not demonstrate. All adjudication remains in Canada. Non-adjudicative document handling is supported offshore under the same governance, with a documented cross-border transfer position disclosed in line with PIPEDA expectations.
Delivery model
Dedicated team, Ontario, with an offshore support layer, single governance framework across both.
Results
Median onboarding time for straight-through files reduced to within the bank's target window. Alert adjudication throughput per analyst improved 36 percent between month two and month seven as the retune took effect. Quality assurance pass rate on sampled files held above 98 percent across five internal audit cycles. A seasonal peak of roughly 2.6 times baseline was absorbed without service degradation and without permanent hiring.
Why it worked
The bank presented a staffing problem. Part of it was a configuration problem, and the operational partner was the only party generating the data to prove it. Documenting the pattern rather than simply clearing the queue is what changed the economics.
This client is anonymised on purpose. Several buyer types cannot be named without contractual permission, and public sector engagements frequently prohibit it. The metrics stated here are drawn from engagement data.
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