Maya
CORE PROFILE This role is responsible for developing, implementing, and continuously enhancing fraud risk management strategies across the customer lifecycle of Maya Bank’s lending products —from onboarding and application to account servicing and transaction monitoring. The role partners closely with Anti-Fraud, Data Science, Product, Operations, and Risk/Compliance teams to design and embed preventive, system-based controls that minimize fraud risk while enabling business growth and a seamless customer experience. This role focuses on fraud risk strategy, control design, and analytics for lending products, with emphasis on proactive risk mitigation and system-based controls. It is not an investigation or case-handling role. The role is also responsible for establishing a robust lending fraud risk framework, including detection strategies, monitoring mechanisms, and control optimization, as well as generating data-driven insights, reporting, and trend analyses to support strategic decision-making and strengthen overall fraud risk governance. NATURE OF WORK Fraud Risk Strategy \& Controls Lead the development and continuous enhancement of end-to-end fraud risk strategies for lending products, covering onboarding, account takeover, synthetic identity, and transaction fraud. Analyze fraud trends, performance metrics, and loss drivers to identify control gaps and recommend strategic improvements. Design and optimize fraud detection frameworks (rules, models, and control logic) in partnership with Data Science and Fraud Analytics teams. Collaborate with Credit Risk and Product teams to ensure fraud controls are aligned with customer experience and business growth objectives. Drive the implementation and optimization of fraud strategies within decision engines and fraud platforms. Provide strategic guidance to stakeholders on fraud risk metrics and control performance across lending products. Ensure fraud controls are proactively calibrated to address emerging risks, particularly within credit and lending portfolios. Fraud Risk Analytics \& Monitoring Develop and maintain risk-based monitoring frameworks to track fraud exposure, trends, and control effectiveness across lending products. Analyze multi-source data (e.g., onboarding, loan transactions, fraud platforms such as Sentinel) to identify vulnerabilities and emerging fraud risks. Produce regular, data-driven reports and insights to support management decision-making and risk governance. Define monitoring triggers, thresholds, and indicators to enable early detection of abnormal patterns and potential fraud risks. Establish dashboards and visualization tools to monitor fraud performance and highlight key risk drivers. Fraud Governance \& Continuous Improvement Review and enhance fraud control frameworks across products to ensure robustness, consistency, and regulatory compliance. Partner with stakeholders across Risk, Product, Technology, and Compliance to embed preventive, system-based controls into product and system design. Leverage advanced analytics and technologies (including AI/ML) to strengthen fraud prevention and detection capabilities. Generate insights on fraud patterns, authorization trends, and control performance, and provide structured updates to senior management. Drive continuous improvement initiatives using performance data to optimize fraud strategies, controls, and decisioning frameworks. DISPLAYED SKILL MASTERY Fraud Risk Strategy \& Control Design Fraud Risk Assessment (Lending \& Banking Products) Fraud Data Analytics \& Insight Generation Detection Frameworks (Rules, Models, and Anomaly Detection) Payment Wallet \& Banking Systems Architecture Lending Business \& Credit Risk Fundamentals Monitoring Frameworks, KPIs, and KRIs Technical Reporting \& Data Visualization (SQL, Power BI, Tableau, Python, etc.) Preventive \& System-Based Fraud Controls Trend Analysis \& Risk Identification Behavioral: Strategic Thinking \& Risk-Based Decision Making Strong Analytical and Problem-Solving Skills Effective Communication of Complex Risk Insights Cross-Functional Collaboration \& Stakeholder Management Business Acumen in Financial Services / Digital Banking Ability to Balance Business Growth and Risk Mitigation Data-Driven Decision Making and Cost-Benefit Analysis Innovation Mindset and Continuous Improvement Orientation Ability to Operate Under Ambiguity and Drive Outcomes Resilience and Sound Judgment Under Pressure EXPECTED RESULTS Partner with stakeholders to ensure fraud rules and controls are effectively calibrated to prevent emerging credit and lending fraud risks. Monitor authorization performance trends and ensure timely recalibration of fraud triggers, rules, and control thresholds. Research emerging fraud trends and assess relevance to Maya Bank, driving the development of proactive, risk-based control enhancements. Provide structured management reporting on key fraud risk indicators, control performance, and mitigation actions in collaboration with stakeholders. Utilize data tools (SQL, Power BI, Tableau, PowerPoint, etc.) to analyze performance, develop dashboards, and deliver actionable insights. Conduct risk-based post-event analyses to identify control gaps and recommend enhancements to fraud prevention frameworks. Track and evaluate key fraud performance metrics (e.g., fraud rates, false positives, chargebacks) to assess control effectiveness and optimize strategies. Ensure fraud risk strategies and controls are aligned with regulatory requirements and internal governance standards. Deliver regular fraud risk insights and strategic updates to senior leadership to support informed decision-making. REQUIRED QUALIFICATIONS MINIMUM EXPERIENCE Minimum 3 years of experience in fraud risk management, with focus on l ending fraud, identity fraud prevention, or fraud data analytics. Experience in digital banking and/or lending products is strongly preferred. Exposure to retail or business banking environments is an advantage. Demonstrated experience in fraud data analysis, monitoring, and control optimization, including rule tuning, trend analysis, and performance evaluation. Familiarity with fraud detection platforms, decision engines, or transaction monitoring systems is required. Proficiency in data analytics and reporting tools (e.g., SQL, Python, Power BI, Tableau, or similar) is required. Ability to translate data insights into actionable recommendations to support fraud risk strategies and control improvements. Strong collaboration skills, with experience working with cross-functional teams (e.g., Risk, Product, Analytics, Operations). Good communication skills to present insights and findings to stakeholders in a clear and structured manner. EDUCATIONAL BACKGROUND BS or equivalent degree in Mathematics, Statistics, CS, IT, IS, Data Science, or equivalent fields DESIRED WORK EXPERIENCE Hands-on experience in fraud data analytics, reporting, and lending fraud risk assessment, with exposure to identity fraud and transaction monitoring. Experience in analyzing fraud trends, control performance, and risk indicators to support fraud prevention and control optimization. Operational experience with the ability to act as a subject matter contributor in fraud risk management, providing insights and recommendations on fraud prevention and mitigation strategies.
Maya
