Model required to identify set of customer as per business need.

Find out those customer who is going to escalate at upper level. Identify then and resolve their cases.

Design framework for Service data mart and develop the same using sql programming.

Developed a model which will identify those customers, who is going to raise complaints to RBI about the financial issues on their transactions and company support services. There are 140 Business Variable has used to create the model.

Exception exists everywhere, our task was to identify those, summaries them, store all kind of exception at one place into database and create their Impact report. Automate the report and send to respective teams with included insights and recommendation to improve the process.

Figure out top query raised by customers and possible way of solve those on Self-Service. I did analysis of data at click level and test the cross channel migration of customer. Report the same with insights and then Implementation at IVR level.

Work closely with self-service team of Experia Portal. Implementation of new features at portal, design new insta-services to customer to increase their experience at web portal.

This is the R-Model which predict the forecasted number of Service Request in next four month in Consumer, Emi Card, SME and Insurance business. Team Heads works on Capacity Planning at agent level with Help of these numbers.

There are a huge Service Request base at Branch, Written, Voice and Social etc level. I have designed process to pull data from Core table and create a Mart. This mart contains all Query related information at one place. It helps us into analysis of top queries of customer, Issues and Handling efficiency of agents.

This project belongs to Insurance Domain. So huge data involved in this project. To design data base model, Automate the daily and weekly report is the main role of this project. As every customer need to know about what kind of product they are buying and what will be the benefits to buy a particular. At the same time, Company is also maintaining a database from where we can calculate and answer query which is raised by customer and Business analytic team as well. So At back-end, we have a database where every records about policy holder and product level information available.

The dashboard is having all required information at one place. As this dash board is for policy related information, on daily basis there are changes required like number of calls, premium collected, next due date and current status of the policy etc., so daily basis refresh of dashboard is required. Initially it was truncate the all tables and push all data again from warehouse. But after this development it start effecting those column which have any changes.

As company deal with policy selling, so the agent is required to sell policies and company need to check their performance. So there is model requirement by which we can check whether agent is performing good or not. So it was agent level churning by data to identify more profitable agent as well fraud agent.

This is the education portal where student can see all information about colleges. It helps student to choose better college according to their requirement. The portal is designed such a way that user can filter data according to their requirement, like city, state, course wise filter. User can go with university as a filter as well.

Edforia is an ecommerce portal. Where user can by only curriculum book based on their class standard. In this portal user can find School Books, College Books, and Competitive Books.