Reconciliation and Discrepancy Resolution :
- Lead and execute complex data reconciliation processes to compare revenue and loss data across multiple clients.
- Compute & validate the losses & damage claimed by the customer. Conclude it with the customer by convincing them to withdraw the non genuine claims
- Investigate and resolve root causes of discrepancies, collaborating with various departments like finance, operations, security.
Loss and Revenue Analysis :
Utilize advanced analytical techniques to pinpoint trends, patterns, and drivers of revenue loss and gains.Develop predictive models and reports to forecast potential revenue leakage and identify opportunities for optimization.Process Improvement :
Drive initiatives to automate reconciliation processes using scripting languages (e.g., Python, SQL) and specialized reconciliation software. Design and implement new workflows, controls, and systems to enhance efficiency, scalability, and accuracy in data handling.
Team Leadership and Management : Supervise and mentor a team of data analysts, fostering their professional growth and ensuring the team meets its objectives. Manage project pipelines, allocate resources, and maintain high standards of data integrity and quality.Stakeholder Collaboration and Reporting :Act as a key business partner to senior leadership, finance, operations, sales, and IT teamsPrepare and present detailed reports and dashboards on financial performance, reconciliation status, and key insights related to loss and revenue.Translate complex data findings into clear, actionable business recommendations.Risk and Compliance :
Ensure all reconciliation activities and data handling practices comply with internal policies, accounting standards (e.g., GAAP), and external regulatory requirements.Support internal and external audits by providing accurate documentation and analysis.Skills Required
Scripting Languages, data reconciliation , Sql, Python, Analytical Techniques