The 2008 Financial Crisis which created a global financial market meltdown is mainly due to badly structured mortgage loans with poor or subpar credit quality and lack of proper tools to measure portfolio risks by the lenders. Even though several problems led to this crisis, we looked at this from a Big Data. Had the infrastructure and analytical analysis tools were present to the lenders, they would have found the various early warning signs on these mortgage loans and could have better prepared for the crisis. Aftermath of the crisis, all the big financial institutions took a fresh look and embarked onto build various tools and frameworks to address this Big Data in their portfolios with data driven analysis. The 3Vs (Velocity, Volume and Variety) of the Big Data in our Mortgage Loan Analysis System challenges our traditional approach in collecting, processing and presenting the individual and aggregated loan level data in a meaningful format to facilitate our portfolio managers in decision making. The traditional methods are implemented on a standalone on-premises SQL server. Our Framework creates the foundation of migrating from traditional standalone database architecture (on-premises) to Cloud Computing environment using “Script Based Implementation”. The methods we present are simple but effective and saves resources in terms of Hardware, Software and on-going maintenance costs. Big Data “Capture, Transform, Calculate and Visualize” (CTCV) implementation takes a phased approach rather than a big bang model. Our implementation helps the Big Data Management to be part of organizational tool kit. This saves hard dollars and brings us in line with the overall firm strategic vision of moving to Cloud Computing for Investment Management Services.
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