Core Profile
This role is responsible for developing, implementing, and optimizing fraud risk management strategies across the customer lifecycle for Maya Bank enterprise products from onboarding, application to account servicing and transaction monitoring. The role requires the employee to collaborate closely with antifraud teams, data science, products management, operations, bank operations, and risk/compliance teams to protect our customers and minimize fraud losses, while ensuring an optimal customer experience.
Establish a robust enterprise fraud risk management strategy ensuring effective fraud detection, monitoring, and investigation processes. Generate periodic reports and analyses on fraud risk and trends for reporting to key stakeholders.
Nature of Work
Fraud Risk Management Strategy
- Lead the development of end-to-end fraud strategies for enterprise products, including new account fraud, account takeover, synthetic identity, and transaction fraud.
- Analyze fraud trends, performance metrics, and loss data to identify areas of opportunity and recommend improvements to current strategies.
- Design and tune fraud detection models and rules in partnership with data science and fraud analytics teams.
- Work with credit risk and product teams to balance fraud controls with customer experience and business growth objectives.
- Oversee implementation of fraud rules and strategy changes in decision engines or fraud platforms
- Provide guidance to business stakeholders on fraud metrics related to lending products, but mainly on credit card transactions
- Work with appropriate stakeholders to ensure Fraud rules are effectively working towards prevention of emerging Credit fraud.
Fraud Review and Analytics
- Conducts overall fraud analytics related to enterprise bank onboarding and loan transactions from Sentinel and other fraud source data and collaborate with the Anti-fraud team to address potential risks that are not covered.
- Create standard monitoring reports in any visualization tool available for monitoring of fraud rates and checking of sudden changes in trends that may raise suspicions of possible fraud attacks
- Ensure robust and continuous fraud monitoring with appropriate triggers
- Generate daily management level reporting to report fraud risk related to enterprise products
- Review Standard fraud controls for all banking products and work with stakeholders (and Fraud compliance) to ensure compliance.
- Work closely with IT and data analytics teams to leverage advanced technologies such as AI and ML for real-time authorization and fraud detection.
- Design and implement robust fraud prevention and detection measures, leveraging data analytics and advanced technologies to identify and mitigate risks proactively.
- Analyzes data and generate insights on authorization trends, fraud patterns, and operational performance, providing regular reports and updates to senior management.
- Utilizes performance data to drive continuous improvement initiatives, optimizing processes and decision-making frameworks to achieve operational excellence
Displayed Skill Mastery
Technical
- Threat Analysis
- Payment Wallet/ Banking Architecture
- Fraud Risk assessment
- Lending Business
- Fraud Data Analytics
- Technical Reporting (via SQL, Power BI, Tableau, Python, etc)
- Fraud investigations
- Credit/Lending Fraud Assessment
- Anomaly Detection
Behavioral
- Critical Thinking
- Analytical Skills
- Strategic Communication
- Risk Balanced Decision Making
- Conflict Resolution
- Cross functional collaboration
- Business acumen for financial/Banking industry
- Cost Benefit Analysis (Business Vs Fraud/Security)
- Go above & beyond to innovate
- Pressure handling and efficient decision making
Required Qualifications
- Minimum 3 years experience in the field of Lending fraud assessment, Identity fraud prevention & Fraud Data Analytics.
- Digital Banking & Lending experience will be preferred.
- Business banking and retail banking experience will be preferred.
- Experience with fraud detection platforms, decision engines, and analytical tools (e.g., SQL, Python, SAS, R) is a must.
- Proven ability to lead cross-functional initiatives and communicate strategy to both technical and executive stakeholders.
EDUCATIONAL BACKGROUND
- BS or equivalent degree in Mathematics, Statistics, CS, IT, IS, Data Science, or equivalent fields
DESIRED WORK EXPERIENCE
- Hands on with Fraud Data analytics, Investigation ,Reporting and Lending Fraud.
- Operational work experience to act as SME to advise Fraud prevention, mitigation strategies.
