Shiva Shankari

Delivered data-driven insights on fraud trends and validated rule criteria to mitigate financial and operational risks across payment portfolios, building dashboards and using AI-assisted tools to improve analytical efficiency.

Defined risk management strategy and led a team of rules writers to improve internal and third-party rule engine accuracy across large transaction volumes, overseeing integration and end-to-end rule testing.

Strengthened fraud rules and reduced losses by leading data analysis and SQL-driven rule development, eliminating outdated rules to cut expenses by $6M and improving detection of first- and third-party fraud.

Developed fraud detection rules and Splunk alerts that saved $2M by analyzing orders and chargebacks, streamlining processing, and improving fraud operations efficiency.

Led and coached a fraud prevention operations team to reduce chargebacks and expedite high-risk case resolution while monitoring queues and managing escalations.

Reviewed and processed online orders to reduce fraudulent chargebacks by validating customer information and coordinating with banks and delivery teams to stop fraudulent shipments.

Led a team of test engineers to improve quality and stability of banking applications, increasing productivity through training on methodologies and tools.

Managed end-to-end testing for banking modules including EMV and online verification, setting up environments and resolving defects to ensure release quality.

Led test engineering and defect management for internet banking, implementing orthogonal arrays to achieve comprehensive coverage and improve testing efficiency.

Bachelor of Engineering from Anna University with coursework relevant to engineering principles and problem-solving.

Completed coursework on AI in Risk Management and Fraud Detection through LinkedIn Learning.

Obtained Loss Prevention Qualified (LPQ) certification focused on loss prevention best practices and investigations.