For pure-play e-commerce brands, fraud prevention is a year-round operational priority, but peak trading periods remain the ultimate stress test. Black Friday, seasonal launches and promotional surges can multiply transaction volumes overnight. The brands that manage fraud effectively during these spikes are those that have invested in orchestration, intelligent automation and scalable analyst workflows. The risk is if fraud systems are too loose, losses escalate. If controls are too aggressive, genuine customers are declined at the very moment revenue opportunity is highest…
Orchestration over point solutions
Many pure-play brands have layered fraud tools over time: payments risk scoring, device intelligence, behavioural analytics and manual review platforms. The challenge during peak periods is not the lack of data, but managing it coherently.
Leading e-commerce teams are adopting orchestration layers that route transactions dynamically based on risk level. Low-risk transactions pass through frictionlessly, while medium- or high-risk events trigger step-up verification or manual review.
This reduces unnecessary alerts and ensures analysts focus only on cases that genuinely require human judgement.
Workflow design for surge resilience
Workflow design is increasingly recognised as a competitive advantage. During high-volume events, manual queues can quickly become unmanageable if prioritisation is poor. Best practice includes:
- Risk-based queue segmentation (e.g. high-value, high-risk, repeat offender profiles)
- Automatic suppression of duplicate alerts
- Pre-defined escalation pathways
- Clear service-level targets aligned to peak trading expectation
Some brands now run “fraud war rooms” during major events, bringing together fraud, payments and customer service teams to ensure rapid resolution.
Alert prioritisation and analyst capacity
One of the biggest operational risks during peak periods is analyst fatigue. Overloaded teams can lead to slower reviews, inconsistent decisions and rising false positives.
Automation plays a critical role here. Machine learning models increasingly auto-approve or auto-decline a significant share of transactions, reserving manual review for borderline cases.
Capacity planning is also evolving. Data from previous trading peaks is used to forecast review volume, allowing brands to adjust staffing, shift patterns or outsource overflow review capacity in advance.
Automation with oversight
While automation reduces workload, governance remains essential. Continuous model monitoring is critical during peaks, when fraud patterns may shift rapidly. False positives can quietly increase if models are not tuned to seasonal behaviour changes.
Fraud prevention at scale is about balance: combining automation efficiency with human judgement, underpinned by strong data visibility.
Protecting revenue and reputation
For pure-play e-commerce brands, fraud prevention directly affects approval rates, customer trust and brand perception.
Those that invest in orchestration, intelligent workflow design and scalable analyst capacity will be best positioned to handle peak demand, protecting both margin and customer experience when it matters most.
Are you searching for Fraud Prevention solutions for your organisation? The Fraud Prevention Summit can help!
Photo by Anastassia Anufrieva on Unsplash
