Alexander Barnes is leading the search for a Fraud Investigations Lead for a global fintech operating across consumer and merchant payments.
This hire will own complex fraud investigations end-to-end and convert case intelligence into detection logic across products and systems.
Purpose of the role
Own high-complexity fraud investigations across the lifecycle.
From initial signal through to decisioning, escalation, and intelligence capture.
Translate investigative output into improved detection across:
* Consumer fraud
* Merchant fraud
* Account takeover and network activity
This is a deep investigative role. Not operations. Not process ownership.
Key responsibilities
* Complex case ownership:
Lead multi-layered fraud investigations. Build defensible case narratives from transaction data, behavioural signals, and external intelligence.
* Network and typology analysis:
Identify linked entities, shared infrastructure, and coordinated behaviour across accounts, devices, and payment flows.
* End-to-end decisioning:
Own case outcomes including escalation, SAR filing, offboarding, and law enforcement engagement.
* Signal and control development:
Translate case findings into detection inputs. New rules, signals, thresholds, and control logic embedded into product flows.
* Product and engineering collaboration:
Work directly with engineers and product teams to implement detection logic within onboarding, authentication, and transaction flows.
* Data and model challenge:
Partner with data science to validate model outputs, refine features, and improve precision and recall based on live fraud patterns.
* Fraud intelligence loop:
Continuously feed emerging typologies, attack vectors, and behavioural patterns back into detection systems.
Technical depth and standards:
* Set the bar for investigative quality. Structured thinking, clear documentation, and defensible decisions under uncertainty.
* Ideal candidates will bring
* Strong hands-on fraud investigation experience with full case ownership in fintech, banking, or payments.
* Background in financial crime from enforcement or legal settings (financial police, law enforcement, regulatory investigations).
* Experience working complex fraud typologies including mule networks, account takeover, and coordinated attacks across payment systems.
* Ability to analyse transaction flows, device and behavioural data, and link entities across fragmented datasets.
* Experience working with product, engineering, or data teams to implement fraud controls at system level.
* Strong understanding of how detection works in practice. Rules engines, signal design, and model limitations.
* Comfort operating with incomplete data and making high-confidence decisions.
* Clear bias toward hands-on investigation over operational management.