BA - Fincrime
Domain and Business Knowledge and Data flows experience would be a differential
Domain & Business Knowledge
Strong background in Financial Crime domains, particularly:
Identity & Verification (ID&V)
KYC / CDD / EDD processes
Fraud and AML touchpoints across the customer lifecycle
Experience working with Netreveal (or similar FCC platforms), including understanding how rules, alerts, and decisions are driven by underlying data
Good appreciation of regulatory expectations (e.g. data lineage, auditability, explainability)
Data & Systems Understanding
Proven experience analysing data flows end‑to‑end, from source systems through to:
Decisioning engines
Downstream data platforms (e.g. CDM, data lakes, MI/reporting layers)
Ability to:
Define and document data requirements, mappings, and transformations
Understand upstream/downstream dependencies and impacts of change
Comfortable working with logical and physical data models, data dictionaries, and lineage views
BA Core Capabilities
Strong requirements engineering skills:
Eliciting, analysing, and documenting business and data requirements
Translating regulatory or policy needs into clear, consumable requirements
Experience producing:
Process maps (as‑is / to‑be)
Functional and non‑functional requirements
Data specifications and acceptance criteria
Confident challenging stakeholders on clarity, completeness, and value
Technology & Delivery Experience
Comfortable operating in Agile delivery models (Scrum / Kanban), including:
Backlog refinement
Supporting sprint delivery and testing
Stakeholder & Communication Skills
Ability to engage confidently with:
Financial crime SMEs
Secured Lending products
Product owners
Data and technology teams
Strong written and verbal communication, particularly when:
Explaining complex data or system behaviour
Producing clear documentation for audit or regulatory consumption
Nice to Have / Differentiators
Experience with customer onboarding journeys and digital ID&V tooling
Prior experience in regulated financial services environments
Understanding of MI, reporting, and downstream analytics use cases