Senior Analyst - Fraud Operations Strategy and Program Management

Senior Analyst - Fraud Operations Strategy and Program Management

At LPL, we are dedicated to safeguarding our clients and advisors through proactive fraud risk management. As Senior Analyst, Fraud Operations Strategy and Program Management, you will report to the Manager Fraud Operations Strategy and play a key role in developing, executing, and continuously improving fraud prevention and detection strategies across LPL’s platforms. This position involves collaboration with cross-functional teams to mitigate fraud risks, enhance program efficiency, and ensure compliance with industry standards and regulatory requirements.

You will assist in developing recurring metric dashboards, presentations, risk assessments, and the ongoing training and development of fraud communications and alerts and will assist the team or other business units on project work, partner with second line, technology, and information security groups, to review regulatory changes assessing impacts to LPL Financial as it relates to money movement and fraud.

• Responsible for end-to-end development of fraud data models, monitoring fraud trends, analyzing KPIs, and recommending improvements based on data insights.
• Develop and implement comprehensive fraud prevention and detection strategies aligned with organizational goals and lead cross-departmental initiatives to embed these capabilities into products and services.
• Monitor existing fraud detection models for performance, false positives, and risk exposure, suggesting iterative refinements as needed.
• Provide strategic insights and actionable recommendations to leadership by evaluating fraud metrics, customer behavior, and operational gaps, and track the impact of fraud strategy changes on business performance, measuring ROI and recommending adjustments.
• Build predictive models and develop logic for automation and scoring of high-risk behavior across multiple fraud typologies.
• Interface with Technology, Information Security, product teams, and other fraud-related groups to align model deployment and systematic fraud mitigation and engage with internal teams and external partners to align on fraud strategy objectives.
• Lead ad hoc analytics projects and drive innovation through dashboarding, segmentation, and data storytelling, preparing dashboards, reports, and presentations for stakeholders and executives.
• Identify necessary data sources and design robust pipelines and reporting layers for ongoing monitoring.
• Serve as a central point for cross-functional collaboration between Fraud Ops, Product, Technology, and Information Security on all data-related initiatives.
• Conduct periodic and ad hoc system testing of alert strategy and technology updates, and identify opportunities for process improvements and technological advancements in fraud detection.
• Manage project plans, timelines, and reporting to ensure timely achievement of milestones.
• Coordinate with product development teams to incorporate fraud risk considerations into new offerings.
• Lead meetings and communicate progress to senior leadership and external bodies.
• Ensure compliance with regulatory requirements and industry standards through policy development and audits.
• Stay informed on emerging fraud trends, tools, and technologies, and champion the adoption of advanced detection methodologies such as machine learning and behavioral analytics.

• 3+ years of experience in fraud prevention, detection, or program management within financial services (broker-dealer) or technology sectors.
• Deep understanding of various fraud types including account takeover, payment fraud (e.g. ACH fraud, wire fraud, credit/debit card fraud, check fraud), synthetic identity, and insider fraud and collusion.
• Strong understanding of fraud detection and prevention methodologies, including behavioral analytics and machine learning models.
• Experience in coordinating cross-functional teams and managing stakeholder expectations.

• Proficiency in data analytics tools such as SQL, Tableau, Power BI, or similar platforms.
• Experience with scripting languages like Python, R, or SAS for analytics and fraud…