Job Description

Job Title: KYC Operator Location: Bangalore Note: Open to consider fresher candidates (Yes/No): NO Experience range: 3 - 5 years of KYC experience Project duration: 8 months, may extend based on performance & business. Shift timings: 11:30 AM to 8:30 PM Number of days work from office: 2 days each week Your skills and experience Strong end to end 3+ years of KYC operations experience, having worked on different entity types and geographies. Should have 4 eye / checker experience in the KYC process. Good written and verbal communication Analytical skills and attention to detail, with the ability to think laterally around issues, proposing solutions where required. Experience with investment banking clients and with preferably with risk and complex client entity structures Effective organisation, prioritisation, and interpersonal skills Ability to work to high standards and under strong time constraints. The ability to utilize your own area of expertise and knowledge to contribute to significant improvements in operational processes and policies. Combine subject matter expertise and able to transfer knowledge to colleagues. Your key responsibilities Operate as a KYC Quality Assurance SME with the global KYC QA function. Review KYC files on a sample basis by applying the QA methodology to deliver an objective review of client files. Perform accurate and consistent QA checks on KYC files across multiple locations, business areas and client types. Identify risks within the KYC documentation and confirm issues have been remediated and/or appropriately escalated through the escalation process. Partner with CLM & AFC QA teams to improve KYC standards. Support and contribute towards a continuous improvement program of work borne out of a QA testing results, assess root causes and thematic issues proposing steps to be taken to eliminate, evidencing improvements. Sustain to a culture of teamwork and collective achievement of departmental goals and objectives across QA & CLM teams. Contribute to forward looking strategy for QA including, AI, machine learning & process re-engineering.

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