Responsible for data governance and as part of this application have built control rule engine  to assess the quality of data that flow through various layers. And constructed an infrastructure to collect the data lineage and process and transformed the data in a meaningful format which aids business decision making. Data resides in hadoop database. So have used various technologies like Python Scripting for file processing and Exadata as rule engine with Spark-Scala to apply controls. 
 

This is a web portal like application. One stop shop for all the Wholesale Credit related data adjustments. It acts as a Feed Entry System as well as Manual Adjustment System. It enables users to adjust the changes in the current month trend of wholesale credit information with provision for reconciliation under proper workflow management to adjust the in the gap in the leger and digital data. This helps the user to capture the correct information which reduces risk. This a web application developed in Java, Spring MVC and hosted in tomcat server with Oracle as backend. 

This application is associated with Enterprise Capital Risk, mainly focus on retail customers. This will summarize the exposure that bank has around retail sector. This application helps to identify the risk involved under retail sector, that will allow the bank to lend further and set aside cushion. We application which displays a dashboard with metrics and calculated risk enables user to view and download aggregated and finely processed data. Web application built using Java / Spring and front end using Ext JS with hibernate as ORM.  User can get latest data by triggering the UI which runs the calculation in Hadoop job by automating via Autosys pooling job which waits for the trigger.
 

This is a web application serves as a tool to capture securitization related data in a structured format similar to the ledger. Using this tool the securitization assets and its associated pool and exposure details are captured and data passed to capital management team to calculate risk weighted assets. Every month user enters the data into the system and submitted for approval to the higher officials. On data submission, notification e­mail sent to authorized approvers from the system. Approver verifies data and approve/reject depending on the correctness. Approved records are exposed for credit risk calculation and during data fetch phase by upstream, data capture toll will be closed for data modification. Project developed using Spring MVC in the back end and DHTMLXGrid in the front end.
 

Front end application for structured transaction, is also a securitization data capture tool, a web application, for bank owned securitization assets. Project built from scratch using Spring MVC in the back end and Ext Js as the front end MVC. Works on the same way as SDC, with improved high performance in huge data display using buffered rendering and huge data persistence with Spring's thread pool executors.
 

This is a web application, serves as a dashboard for the SOA governance team. This application is designed around an IBM Product, Rational Asset Manager. IBM RAM is an
asset management tool. IBM Rational Asset Manager offers a definitive library to help organizations manage and govern the business and technical assets involved in software and systems delivery. Assets are published work products that are shared or referenced across the enterprise. We have been involved in loading data from various systems into RAM using RESTful Web services in a well defined as well as customized categorizations and display asset details in a dashboard using Spring Web MVC and using Maven as a build tool .