Head of Financial Crime Prevention Model Analytics

Overview

Connecting clients to markets – and talent to opportunity.With 5,400+ employees and over 80,000 institutional, commercial, and payments clients, we operate from more than 80 offices spread across six continents. As a Fortune 100, Nasdaq-listed provider, we connect clients to the global markets – focusing on innovation, human connection, and providing world-class products and services to all types of investors.Whether you want to forge a career connecting our retail clients to potential trading opportunities, or ingrain yourself in the world of institutional investing, StoneX Group is made up of four business segments that offer endless potential for progression and growth.

 

Business Segment Overview

 

Corporate: Engage in a deep variety of business-critical activities that keep our company running efficiently. From strategic marketing and financial management to human resources and operational oversight, you’ll have the opportunity to optimize processes and implement game-changing policies.

 

Role Purpose

 

StoneX is seeking a Head of Financial Crime Prevention (FCP) Model Analytics to establish and lead a first-line analytical centre of excellence for Transaction Monitoring, Customer Screening and Payment Screening.

The function will provide quantitative, technical and analytical expertise to optimize financial crime detection controls and related governance. It will ensure controls remain risk-sensitive, typology-led, data-driven and operationally efficient, while working with Technology and Data teams to obtain the evidence needed to validate completeness, accuracy and integrity.

The role will work closely with Transaction Monitoring, Customer Screening, Payment Screening, Technology and Data teams to improve risk coverage, detection performance and operational efficiency, with clear FCP Model Analytics ownership of calibration activities.

The role will partner with Technology, Data, Architecture and solution vendors to support the implementation, optimization and governance of financial crime solutions, using evidence on data lineage, completeness, accuracy and coverage to provide effective financial crime risk oversight.

Responsibilities

Key Responsibilities

 

Model Performance, Calibration & Optimisation

• Monitor Transaction Monitoring, Customer Screening and Payment Screening performance.
• Calibrate scenarios, rules, thresholds and matching logic.
• Use alert outcomes to improve detection performance and reduce false positives.
• Design and enhance scenarios, rules and detection logic for evolving typologies and emerging financial crime risks.
• Maintain analytical oversight of detection performance across products, legal entities, customer segments and jurisdictions.
• Own ongoing calibration and periodic recalibration of financial crime detection solutions, including Transaction Monitoring, Customer/Counterparty Screening, Payment Screening and related controls, ensuring they remain effective as typologies, volumes and risk parameters evolve.
• Partner with Technology, Data and solution vendors to support implementation, optimisation and performance monitoring of financial crime detection solutions.

Data Quality, Integrity & Governance

• Oversee data quality issues affecting financial crime systems.
• Validate, based on outputs provided by Technology and Data teams, the completeness, accuracy, consistency and timeliness of monitoring and screening data.
• Review data lineage, mapping logic, enrichment processes and transformations, based on documentation maintained by Technology and Data teams.
• Escalate material data quality issues affecting monitoring or screening controls.
• Develop data quality metrics, reporting and exception management for issues affecting monitoring or screening controls.
• Own the business assessment, challenge and sign-off of evidence provided by Technology and Data teams on data coverage, completeness, accuracy, timeliness and lineage, confirming that monitoring and screening data is fit for purpose and supports effective financial crime controls.

Screening & List Governance

• Oversee sanctions, PEP, adverse media and internal watchlist analytics.
• Oversee list onboarding, maintenance, testing, retirement and quality assurance.
• Validate list completeness, integrity and implementation accuracy using evidence from relevant system and data owners.
• Manage governance for list updates and configuration changes.
• Ensure screening configurations remain aligned to obligations, business requirements and risk appetite.
• Maintain lifecycle governance over financial crime solutions, screening lists, configurations and calibration records, including appropriate review, version control and change management.

Analytics, Insights & Management Information

• Produce management information on risk coverage, detection performance, control outcomes and operational efficiency.
• Provide clear insight and recommendations to management and governance forums.

Testing, Change & Implementation

• Design and execute analytical testing for new scenarios, rule enhancements, screening configuration changes, system upgrades and data changes, including above- and below-the-line testing where applicable.
• Define, support and evidence UAT, regression testing and implementation readiness for monitoring, screening, calibration, configuration and data-related changes.
• Work with Technology, Data and vendor teams to define business requirements, support implementation, validate solution changes and ensure controlled deployment of financial crime capabilities.

Governance & Regulatory Readiness

• Maintain inventories of detection models, monitoring scenarios, screening configurations, thresholds, assumptions, calibration activities and change history.
• Produce governance reporting for financial crime committees.
• Provide evidence and subject matter input to internal audit, assurance reviews and regulatory examinations.
• Maintain evidence supporting control outcomes, calibration decisions and model governance.
• Support governance and model validation for AI-enabled financial crime solutions, including use case inventory, explainability, performance monitoring, change control, appropriate human oversight and regulatory readiness.

Typology Development & Detection Enhancement

• Monitor emerging money laundering, sanctions and fraud typologies.
• Assess the impact of emerging typologies on existing detection controls.
• Drive appropriate use of advanced analytics, automation and AI-enabled detection techniques within defined governance standards.

Leadership & Team Development

• Build and lead a high-performing FCP Model Analytics function.
• Develop specialist capability across financial crime analytics, detection methodologies and optimisation.
• Establish methodologies, quality standards and operating procedures.
• Foster a culture of challenge, evidence-based decision making and continuous improvement.

Qualifications

Skills & Experience

 

Essential

• Significant experience in financial crime analytics.
• Strong understanding of financial crime typologies and detection methodologies.
• Strong analytical, statistical and data interpretation skills, with experience designing performance metrics, model governance and management information.
• Understanding of data quality, data governance, data lineage and AI model governance principles.
• Ability to translate complex analytical findings into practical, risk-based recommendations for senior stakeholders.
• Strong stakeholder management skills.
• Ability to work effectively with second-line Financial Crime Risk and Controls teams to demonstrate control suitability, effectiveness and alignment to risk appetite.

Desirable

• Experience operating within wholesale, institutional, brokerage, trading, payments or capital markets environments.
• Experience supporting model validation, regulatory reviews, audit examinations or financial crime technology programs.
• Knowledge of AI, machine learning, SQL, Python, data visualization or other advanced analytics techniques.
• Experience with financial crime technology and data providers such as NICE Actimize, CGI Hotscan360, Dow Jones Risk & Compliance, LSEG World-Check and WorkFusion.
• Relevant professional qualification, degree or equivalent experience in financial crime, data analytics, risk management, computer science, data science, statistics, mathematics, engineering, economics or another STEM-related discipline.

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