Sr IT Business Analyst Fraud Technology at Citigroup in Shivaji Gardens

Job description

1. Role Overview & Objective The Senior IT Business Analyst – Fraud Prevention translates complex, high-level business and risk requirements into detailed, actionable technology deliverables. Serving as the primary bridge between Fraud Operations, Compliance, Risk Management, and Technology engineering teams, you will leverage modern analysis methodologies and enterprise AI capabilities to define, design, and implement advanced fraud detection and mitigation solutions. Your contributions will directly strengthen organizational resilience against emerging fraud threats while ensuring a frictionless customer journey. 2. Key Responsibilities Requirements Engineering & Business Analysis Leverage enterprise collaboration intelligence and AI-assisted elicitation tools to structure stakeholder workshops, extract business rules from discussions, and resolve requirement ambiguities and edge-case exceptions with Subject Matter Experts (SMEs). Elicit, analyze, and document comprehensive functional and non-functional requirements, producing industry-standard Business Requirement Documents (BRDs), Functional Requirement Documents (FRDs), and technical specifications. Utilize advanced analytical tools for requirement pattern discovery and dependency mapping across distributed systems. Design and maintain robust process artifacts—including use case models, activity diagrams, sequence diagrams, system context diagrams, and Business Process Model and Notation (BPMN 2.0) workflows—covering standard operating paths, fraud-positive scenarios, false-positive handling, timeouts, vendor outages, and dual-control approvals. Define detailed technical and integration requirements for in-house detection engines, third-party vendor platforms, and core payment rails (e.g., Card Authorization, ACH, Wire, Real-Time Payments [RTP]). Decompose business initiatives into structured Jira Epics and INVEST-compliant User Stories featuring testable Gherkin syntax (Given-When-Then) acceptance criteria across diverse personas Establish and maintain end-to-end Requirements Traceability Matrix (RTM) linking regulatory/policy mandates to BRDs, FRDs, user stories, test cases, and compliance audit evidence. Facilitate backlog grooming and sprint planning in Jira, ensuring user stories meet the Definition of Ready (DoR) and align with engineering sprint capacity. AI-Powered Fraud Solution Design Translate evolving fraud typologies—such as Account Takeover (ATO), Authorized Push Payment (APP) fraud, Synthetic Identity Theft, and mule account networks—into functional and technical specifications for machine learning models and real-time rule engines. Perform comprehensive impact assessments and root-cause analyses on fraud policy and rule updates, balancing fraud capture rate optimization against customer friction and False Positive Rates (FPR). System Integration & Testing Serve as the core technical liaison across core banking engines, fraud decisioning platforms, case management workflows, and identity verification/biometric APIs. Define data mapping specifications, schema definitions (JSON/XML), and API payloads for real-time transaction screening, event streaming (e.g., Kafka), and batch monitoring. Formulate and execute User Acceptance Testing (UAT) strategies, detailed test scripts, and defect triage workflows to validate fraud detection efficacy and system reliability prior to production releases. 3. Required Qualifications & Experience Education & Experience Education: Bachelor’s or Master’s degree in Computer Science, Management Information Systems (MIS), Finance, Business Analytics, or a related discipline. Experience: 10+ years of progressive experience as an IT Business Analyst, Systems Analyst, or Technical Product Owner, with at least 2–3 years dedicated to fraud detection, Anti-Money Laundering (AML), or payment risk within financial services or FinTech environments. Technical & Tool Competencies Methodologies: Deep expertise in Agile frameworks (Scrum, Kanba