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Project Experience
Project 3
Project Title : Global risk Aggregation-GRA.
Client : American International Group-AIG.
Designation : Senior programmer analyst.
Duration : Apr 2013 to Jun 2013.
Environment : DataStage 8.5 and QualityStage 8.5, Oracle
11g, Unix
Project Summary:
The Risk Aggregation team within Enterprise Risk Management (ERM) performs scenario
analysis to understand AIG’s insurance/credit exposure to man-made disasters. Though
the process of querying AIG’s data is automated, the team is constrained by the manual
effort associated with external data collection, normalization and linkage to AIG data.
Responsibilities:
 Reduce manual intervention required
 Integration with external sources for fracking operator data
 Add new data sources (internal or external) with minimal development effort
 Conduct optimization and visualization analysis to inform business decisions
 Implemented end-to-end solution to perform fracking operations scenario
analysis and understand AIG insurance/credit exposure within the United States.
 Implemented quality stage stages like standardization, match frequency, match
specification and final load to DB to analyze the matching and non matching
operators.
 Linking external data with AIG policy data
 Demonstrate visualization of this data for analysis

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Project Experience3

  • 1. Project Experience Project 3 Project Title : Global risk Aggregation-GRA. Client : American International Group-AIG. Designation : Senior programmer analyst. Duration : Apr 2013 to Jun 2013. Environment : DataStage 8.5 and QualityStage 8.5, Oracle 11g, Unix Project Summary: The Risk Aggregation team within Enterprise Risk Management (ERM) performs scenario analysis to understand AIG’s insurance/credit exposure to man-made disasters. Though the process of querying AIG’s data is automated, the team is constrained by the manual effort associated with external data collection, normalization and linkage to AIG data. Responsibilities:  Reduce manual intervention required  Integration with external sources for fracking operator data  Add new data sources (internal or external) with minimal development effort  Conduct optimization and visualization analysis to inform business decisions  Implemented end-to-end solution to perform fracking operations scenario analysis and understand AIG insurance/credit exposure within the United States.  Implemented quality stage stages like standardization, match frequency, match specification and final load to DB to analyze the matching and non matching operators.  Linking external data with AIG policy data  Demonstrate visualization of this data for analysis