Fraud Link Analysis Strategy & Operations

In the Technology division, we leverage innovation to build the connections and capabilities that power our Firm, enabling our clients and colleagues to redefine markets and shape the future of our communities. This is a Fraud Link Analysis Strategy & Operations position at the Director level, which is part of the job family responsible for identifying, assessing, and mitigating risks to ensure operational continuity and resilience in the face of potential threats or disruptions that could impact the organization, plus management of ongoing incidents.

Morgan Stanley is an industry leader in financial services, known for mobilizing capital to help governments, corporations, institutions, and individuals around the world achieve their financial goals.

Interested in joining a team that's eager to create, innovate and make an impact on the world? Read on.

This Director position will lead the operational execution and strategic development of fraud link analysis capabilities that leverage graph analytics and investigative tooling to identify, investigate, and mitigate complex fraud patterns. This role serves as a bridge between Fraud Operations, Fraud Technology, Analytics, and investigative teams by translating operational fraud needs into technical requirements, validating tool outputs, and ensuring graph-based insights are actionable for fraud review and remediation.

• Graph Analytics Tool Partnership: Collaborate with technology, data strategists, analytics, and linking operations teams to define requirements, prioritize enhancements, and support development of graph analytics tools used to detect and investigate fraud linkages.
• Data Integration and Readiness: Provide fraud operations subject matter expertise to guide the integration of account, party, transaction, device, payee, employee, known fraud, and other relevant data into graphing tools and investigative platforms.
• Output Testing and Validation: Test graph analytics outputs, validate query logic and business rules, assess data quality, identify false positives or gaps, and provide feedback to technology partners to improve tool accuracy and usability.
• Operational Strategy Development: Develop practical review strategies, workflow guidance, escalation thresholds, and handoff processes that enable operations teams to consistently review graph outputs and convert insights into fraud mitigation actions.
• Fraud Alert and Case Review: Perform hands-on review of potentially fraudulent activity based on graphing tool outputs. Based on review, document findings and recommend account-level or event-level actions.
• Cross-Functional Coordination: Partner with fraud investigations, alerting, event management, controls, analytics, technology, and leadership teams to align graph analytics capabilities with fraud typologies, operational needs, and risk reduction priorities.
• Procedure and Governance Support: Create and maintain operating procedures, review standards, quality control expectations, metrics, and documentation supporting the use of graph analytics in fraud operations.
• Emerging Fraud Response: Support the identification, investigation, escalation, and mitigation of emerging fraud events by using graph analytics to identify connected accounts, parties, counterparties, devices, or behavioral patterns.

• 5-8 years of experience in fraud risk, financial crimes, or a related investigative or operational role at a global financial institution
• Familiarity with Agile methodologies, as well as project management tools including JIRA
• Expertise with fraud case management, alerting systems, known fraud databases, or fraud analytics platforms
• Knowledge with onboarding tooling related to fraud case management, alerting systems, known fraud databases, or fraud analytics platforms
• Experience with the development of fraud strategies, enabling technology or managing large scale projects
• Experience working with technologists, documenting requirements and explaining business requirements
• BA or BS preferred, but not required

• Experience with graph database or graph visualization platforms such as Neo4j, Bloom, NeoDash, or similar tools.
• Knowledge of digital asset transactions (i.e. crypto)
• Familiarity with creation of AI agents and using AI technologies to create operational and strategic efficiencies
• Knowledge on SQL or Python for data analytics