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    Job · 19185030

    KPMG logo

    Consultant Business Analysis (Banking Domain)

    KPMG · Gurugram · onsite · Posted 27d ago

    Undisclosed3–7 yrsfulltimeSourced fromNaukri

    About a minute. You'll make an account on the way through.

    About this role

    Role Overview:

    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)
    • Strong 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.

    Sourced from naukri

    Skills

    credit flowUATgap analysisFund Flow AnalysisEnterprise Risk ManagementFraud RiskEarly Warningtransaction monitoringBrdFRDAML Monitoring

    About KPMG India

    KPMG logo

    KPMG

    Management Consulting

    27.6k+

    employees

    1993

    33 years old

    Gurgaon / Gurugram, Haryana

    India

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