We are looking for experienced Business Analysts to support the implementation of fraud analytics for banking clients. The BAs will play a key functional role in the end-to-end implementation of a solution similar to Early Warning Systems (EWS), AML Transaction Monitoring, or Fraud Risk Management platforms.
Key Responsibilities:
• Lead the preparation of the Business Requirements Document (BRD) in collaboration with stakeholders.
• Conduct gap analysis, process mapping, and fraud risk scenario modeling.
• Ensure accurate data mapping from internal banking systems (e.g., CBS) and validate data quality.
• Collaborate with technical teams and data scientists to support model validation, risk scoring logic, and fraud detection workflows.
• Define and execute User Acceptance Testing (UAT) scenarios and test cases.
• Coordinate with vendors and internal teams to ensure seamless integration with external data sources (e.g., i4c, etc).
• Support development and validation of Machine Learning models for fraud, financial crimes, transaction and customer risk
Required Skills & Experience:
• 3-7 years of experience as a Business Analyst in the Banking or Financial Services domain.
• Proven experience in implementing systems such as:
• Enterprise Fraud Risk Management
• AML Transaction Monitoring
• Early Warning Systems (EWS)
• Robust understanding of banking data structures, credit risk, fund flow analysis, and fraud typologies.
• Familiarity with external data integration that may be required for generating market intelligence
• Experience in functional documentation, UAT coordination, and stakeholder management
• Knowledge of regulatory frameworks (RBI, SEBI, FIU-IND)
• Excellent communication, analytical, and problem-solving skills
• Experience in implementation of Anti Fraud machine learning models
Tools & Technologies (Preferred):
• Exposure to tools like SAS, Actimize, or similar.
• Experience with BI tools (Power BI, Tableau) and SQL / data querying tools is a plus.
📌 Assistant Manager (Gurugram)
🏢 KPMG India
📍 Gurugram
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